1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
1217
1218
1219
1220
1221
1222
1223
1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
1260
1261
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
1282
1283
1284
1285
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
1301
1302
1303
1304
1305
1306
1307
1308
1309
1310
1311
1312
1313
1314
1315
1316
1317
1318
1319
1320
1321
1322
1323
1324
1325
1326
1327
1328
1329
1330
1331
1332
1333
1334
1335
1336
1337
1338
1339
1340
1341
1342
1343
1344
1345
1346
1347
1348
1349
1350
1351
1352
1353
1354
1355
1356
1357
1358
1359
1360
1361
1362
1363
1364
1365
1366
1367
1368
1369
1370
1371
1372
1373
1374
1375
1376
1377
1378
1379
1380
1381
1382
1383
1384
1385
1386
1387
1388
1389
1390
1391
1392
1393
1394
1395
1396
1397
1398
1399
1400
1401
1402
1403
1404
1405
1406
1407
1408
1409
1410
1411
1412
1413
1414
1415
1416
1417
1418
1419
1420
1421
1422
1423
1424
1425
1426
1427
1428
1429
1430
1431
1432
1433
1434
1435
1436
1437
1438
1439
1440
1441
1442
1443
1444
1445
1446
1447
1448
1449
1450
1451
1452
1453
1454
1455
1456
1457
1458
1459
1460
1461
1462
1463
1464
1465
1466
1467
1468
1469
1470
1471
1472
1473
1474
1475
1476
1477
1478
1479
1480
1481
1482
1483
1484
1485
1486
1487
1488
1489
1490
1491
1492
1493
1494
1495
1496
1497
1498
1499
1500
1501
1502
1503
1504
1505
1506
1507
1508
1509
1510
1511
1512
1513
1514
1515
1516
1517
1518
1519
1520
1521
1522
1523
1524
1525
1526
1527
1528
1529
1530
1531
1532
1533
1534
1535
1536
1537
1538
1539
1540
1541
1542
1543
1544
1545
1546
1547
1548
1549
1550
1551
1552
1553
1554
1555
1556
1557
1558
1559
1560
1561
1562
1563
1564
1565
1566
1567
1568
1569
1570
1571
1572
1573
1574
1575
1576
1577
1578
1579
1580
1581
1582
1583
1584
1585
1586
1587
1588
1589
1590
1591
1592
1593
1594
1595
1596
1597
1598
1599
1600
1601
1602
1603
1604
1605
1606
1607
1608
1609
1610
1611
1612
1613
1614
1615
1616
1617
1618
1619
1620
1621
1622
1623
1624
1625
1626
1627
1628
1629
1630
1631
1632
1633
1634
1635
1636
1637
1638
1639
1640
1641
1642
1643
1644
1645
1646
1647
1648
1649
1650
1651
1652
1653
1654
1655
1656
1657
1658
1659
1660
1661
1662
1663
1664
1665
1666
1667
1668
1669
1670
1671
1672
1673
1674
1675
1676
1677
1678
1679
1680
1681
1682
1683
1684
1685
1686
1687
1688
1689
1690
1691
1692
1693
1694
1695
1696
1697
1698
1699
1700
1701
1702
1703
1704
1705
1706
1707
1708
1709
1710
1711
1712
1713
1714
1715
1716
1717
1718
1719
1720
1721
1722
1723
1724
1725
1726
1727
1728
1729
1730
1731
1732
1733
1734
1735
1736
1737
1738
1739
1740
1741
1742
1743
1744
1745
1746
1747
1748
1749
1750
1751
1752
1753
1754
1755
1756
1757
1758
1759
1760
1761
1762
1763
1764
1765
1766
1767
1768
1769
1770
1771
1772
1773
1774
1775
1776
1777
1778
1779
1780
1781
1782
1783
1784
1785
1786
1787
1788
1789
1790
1791
1792
1793
1794
1795
1796
1797
1798
1799
1800
1801
1802
1803
1804
1805
1806
1807
1808
1809
1810
1811
1812
1813
1814
1815
1816
1817
1818
1819
1820
1821
1822
1823
1824
1825
1826
1827
1828
1829
1830
1831
1832
1833
1834
1835
1836
1837
1838
1839
1840
1841
1842
1843
1844
1845
1846
1847
1848
1849
1850
1851
1852
1853
1854
1855
1856
1857
1858
1859
1860
1861
1862
1863
1864
1865
1866
1867
1868
1869
1870
1871
1872
1873
1874
1875
1876
1877
1878
1879
1880
1881
1882
1883
1884
1885
1886
1887
1888
1889
1890
1891
1892
1893
1894
1895
1896
1897
1898
1899
1900
1901
1902
1903
1904
1905
1906
1907
1908
1909
1910
1911
1912
1913
1914
1915
1916
1917
1918
1919
1920
1921
1922
1923
1924
1925
1926
1927
1928
1929
1930
1931
1932
1933
1934
1935
1936
1937
1938
1939
1940
1941
1942
1943
1944
1945
1946
1947
1948
1949
1950
1951
1952
1953
1954
1955
1956
1957
1958
1959
1960
1961
1962
1963
1964
1965
1966
1967
1968
1969
1970
1971
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
2037
2038
2039
2040
2041
2042
2043
2044
2045
2046
2047
2048
2049
2050
2051
2052
2053
2054
2055
2056
2057
2058
2059
2060
2061
2062
2063
2064
2065
2066
2067
2068
2069
2070
2071
2072
2073
2074
2075
2076
2077
2078
2079
2080
2081
2082
2083
2084
2085
2086
2087
2088
2089
2090
2091
2092
2093
2094
2095
2096
2097
2098
2099
2100
2101
2102
2103
2104
2105
2106
2107
2108
2109
2110
2111
2112
2113
2114
2115
2116
2117
2118
2119
2120
2121
2122
2123
2124
2125
2126
2127
2128
2129
2130
2131
2132
2133
2134
2135
2136
2137
2138
2139
2140
2141
2142
2143
2144
2145
2146
2147
2148
2149
2150
2151
2152
2153
2154
2155
2156
2157
2158
2159
2160
2161
2162
2163
2164
2165
2166
2167
2168
2169
2170
2171
2172
2173
2174
2175
2176
2177
2178
2179
2180
2181
2182
2183
2184
2185
2186
2187
2188
2189
2190
2191
2192
2193
2194
2195
2196
2197
2198
2199
2200
2201
2202
2203
2204
2205
2206
2207
2208
2209
2210
2211
2212
2213
2214
2215
2216
2217
2218
2219
2220
2221
2222
2223
2224
2225
2226
2227
2228
2229
2230
2231
2232
2233
2234
2235
2236
2237
2238
2239
2240
2241
2242
2243
2244
2245
2246
2247
2248
2249
2250
2251
2252
2253
2254
2255
2256
2257
2258
2259
2260
2261
2262
2263
2264
2265
2266
2267
2268
2269
2270
2271
2272
2273
2274
2275
2276
2277
2278
2279
2280
2281
2282
2283
2284
2285
2286
2287
2288
2289
2290
2291
2292
2293
2294
2295
2296
2297
2298
2299
2300
2301
2302
2303
2304
2305
2306
2307
2308
2309
2310
2311
2312
2313
2314
2315
2316
2317
2318
2319
2320
2321
2322
2323
2324
2325
2326
2327
2328
2329
2330
2331
2332
2333
2334
2335
2336
2337
2338
2339
2340
2341
2342
2343
2344
2345
2346
2347
2348
2349
2350
2351
2352
2353
2354
2355
2356
2357
2358
2359
2360
2361
2362
2363
2364
2365
2366
2367
2368
2369
2370
2371
2372
2373
2374
2375
2376
2377
2378
2379
2380
2381
2382
2383
2384
2385
2386
2387
2388
2389
2390
2391
2392
2393
2394
2395
2396
2397
2398
2399
2400
2401
2402
2403
2404
2405
2406
2407
2408
2409
2410
2411
2412
2413
2414
2415
2416
2417
2418
2419
2420
2421
2422
2423
2424
2425
2426
2427
2428
2429
2430
2431
2432
2433
2434
2435
2436
2437
2438
2439
2440
2441
2442
2443
2444
2445
2446
2447
2448
2449
2450
2451
2452
2453
2454
2455
2456
2457
2458
2459
2460
2461
2462
2463
2464
2465
2466
2467
2468
2469
2470
2471
2472
2473
2474
2475
2476
2477
2478
2479
2480
2481
2482
2483
2484
2485
2486
2487
2488
2489
2490
2491
2492
2493
2494
2495
2496
2497
2498
2499
2500
2501
2502
2503
2504
2505
2506
2507
2508
2509
2510
2511
2512
2513
2514
2515
2516
2517
2518
2519
2520
2521
2522
2523
2524
2525
2526
2527
2528
2529
2530
2531
2532
2533
2534
2535
2536
2537
2538
2539
2540
2541
2542
2543
2544
2545
2546
2547
2548
2549
2550
2551
2552
2553
2554
2555
2556
2557
2558
2559
2560
2561
2562
2563
2564
2565
2566
2567
2568
2569
2570
2571
2572
2573
2574
2575
2576
2577
2578
2579
2580
2581
2582
2583
2584
2585
2586
2587
2588
2589
2590
2591
2592
2593
2594
2595
2596
2597
2598
2599
2600
2601
2602
2603
2604
2605
2606
2607
2608
2609
2610
2611
2612
2613
2614
2615
2616
2617
2618
2619
2620
2621
2622
2623
2624
2625
2626
2627
2628
2629
2630
2631
2632
2633
2634
2635
2636
2637
2638
2639
2640
2641
2642
2643
2644
2645
2646
2647
2648
2649
2650
2651
2652
2653
2654
2655
2656
2657
2658
2659
2660
2661
2662
2663
2664
2665
2666
2667
2668
2669
2670
2671
2672
2673
2674
2675
2676
2677
2678
2679
2680
2681
2682
2683
2684
2685
2686
2687
2688
2689
2690
2691
2692
2693
2694
2695
2696
2697
2698
2699
2700
2701
2702
2703
2704
2705
2706
2707
2708
2709
2710
2711
2712
2713
2714
2715
2716
2717
2718
2719
2720
2721
2722
2723
2724
2725
2726
2727
2728
2729
2730
2731
2732
2733
2734
2735
2736
2737
2738
2739
2740
2741
2742
2743
2744
2745
2746
2747
2748
2749
2750
2751
2752
2753
2754
2755
2756
2757
2758
2759
2760
2761
2762
2763
2764
2765
2766
2767
2768
2769
2770
2771
2772
2773
2774
2775
2776
2777
2778
2779
2780
2781
2782
2783
2784
2785
2786
2787
2788
2789
2790
2791
2792
2793
2794
2795
2796
2797
2798
2799
2800
2801
2802
2803
2804
2805
2806
2807
2808
2809
2810
2811
2812
2813
2814
2815
2816
2817
2818
2819
2820
2821
2822
2823
2824
2825
2826
2827
2828
2829
2830
2831
2832
2833
2834
2835
2836
2837
2838
2839
2840
2841
2842
2843
2844
2845
2846
2847
2848
2849
2850
2851
2852
2853
2854
2855
2856
2857
2858
2859
2860
2861
2862
2863
2864
2865
2866
2867
2868
2869
2870
2871
2872
2873
2874
2875
2876
2877
2878
2879
2880
2881
2882
2883
2884
2885
2886
2887
2888
2889
2890
2891
2892
2893
2894
2895
2896
2897
2898
2899
2900
2901
2902
2903
2904
2905
2906
2907
2908
2909
2910
2911
2912
2913
2914
2915
2916
2917
2918
2919
2920
2921
2922
2923
2924
2925
2926
2927
2928
2929
2930
2931
2932
2933
2934
2935
2936
2937
2938
2939
2940
2941
2942
2943
2944
2945
2946
2947
2948
2949
2950
2951
2952
2953
2954
2955
2956
2957
2958
2959
2960
2961
2962
2963
2964
2965
2966
2967
2968
2969
2970
2971
2972
2973
2974
2975
2976
2977
2978
2979
2980
2981
2982
2983
2984
2985
2986
2987
2988
2989
2990
2991
2992
2993
2994
2995
2996
2997
2998
2999
3000
3001
3002
3003
3004
3005
3006
3007
3008
3009
3010
3011
3012
3013
3014
3015
3016
3017
3018
3019
3020
3021
3022
3023
3024
3025
3026
3027
3028
3029
3030
3031
3032
3033
3034
3035
3036
3037
3038
3039
3040
3041
3042
3043
3044
3045
3046
3047
3048
3049
3050
3051
3052
3053
3054
3055
3056
3057
3058
3059
3060
3061
3062
3063
3064
3065
3066
3067
3068
3069
3070
3071
3072
3073
3074
3075
3076
3077
3078
3079
3080
3081
3082
3083
3084
3085
3086
3087
3088
3089
3090
3091
3092
3093
3094
3095
3096
3097
3098
3099
3100
3101
3102
3103
3104
3105
3106
3107
3108
3109
3110
3111
3112
3113
3114
3115
3116
3117
3118
3119
3120
3121
3122
3123
3124
3125
3126
3127
3128
3129
3130
3131
3132
3133
3134
3135
3136
3137
3138
3139
3140
3141
3142
3143
3144
3145
3146
3147
3148
3149
3150
3151
3152
3153
3154
3155
3156
3157
3158
3159
3160
3161
3162
3163
3164
3165
3166
3167
3168
3169
3170
3171
3172
3173
3174
3175
3176
3177
3178
3179
3180
3181
3182
3183
3184
3185
3186
3187
3188
3189
3190
3191
3192
3193
3194
3195
3196
3197
3198
3199
3200
3201
3202
3203
3204
3205
3206
3207
3208
3209
3210
3211
3212
3213
3214
3215
3216
3217
3218
3219
3220
3221
3222
3223
3224
3225
3226
3227
3228
3229
3230
3231
3232
3233
3234
3235
3236
3237
3238
3239
3240
3241
3242
3243
3244
3245
3246
3247
3248
3249
3250
3251
3252
3253
3254
3255
3256
3257
3258
3259
3260
3261
3262
3263
3264
3265
3266
3267
3268
3269
3270
3271
3272
3273
3274
3275
3276
3277
3278
3279
3280
3281
3282
3283
3284
3285
3286
3287
3288
3289
3290
3291
3292
3293
3294
3295
3296
3297
3298
3299
3300
3301
3302
3303
3304
3305
3306
3307
3308
3309
3310
3311
3312
3313
3314
3315
3316
3317
3318
3319
3320
3321
3322
3323
3324
3325
3326
3327
3328
3329
3330
3331
3332
3333
3334
3335
3336
3337
3338
3339
3340
3341
3342
3343
3344
3345
3346
3347
3348
3349
3350
3351
3352
3353
3354
3355
3356
3357
3358
3359
3360
3361
3362
3363
3364
3365
3366
3367
3368
3369
3370
3371
3372
3373
3374
3375
3376
3377
3378
3379
3380
3381
3382
3383
3384
3385
3386
3387
3388
3389
3390
3391
3392
3393
3394
3395
3396
3397
3398
3399
3400
3401
3402
3403
3404
3405
3406
3407
3408
3409
3410
3411
3412
3413
3414
3415
3416
3417
3418
3419
3420
3421
3422
3423
3424
3425
3426
3427
3428
3429
3430
3431
3432
3433
3434
3435
3436
3437
3438
3439
3440
3441
3442
3443
3444
3445
3446
3447
3448
3449
3450
3451
3452
3453
3454
3455
3456
3457
3458
3459
3460
3461
3462
3463
3464
3465
3466
3467
3468
3469
3470
3471
3472
3473
3474
3475
3476
3477
3478
3479
3480
3481
3482
3483
3484
3485
3486
3487
3488
3489
3490
3491
3492
3493
3494
3495
3496
3497
3498
3499
3500
3501
3502
3503
3504
3505
3506
3507
3508
3509
3510
3511
3512
3513
3514
3515
3516
3517
3518
3519
3520
3521
3522
3523
3524
3525
3526
3527
3528
3529
3530
3531
3532
3533
3534
3535
3536
3537
3538
3539
3540
3541
3542
3543
3544
3545
3546
3547
3548
3549
3550
3551
3552
3553
3554
3555
3556
3557
3558
3559
3560
3561
3562
3563
3564
3565
3566
3567
3568
3569
3570
3571
3572
3573
3574
3575
3576
3577
3578
3579
3580
3581
3582
3583
3584
3585
3586
3587
3588
3589
3590
3591
3592
3593
3594
3595
3596
3597
3598
3599
3600
3601
3602
3603
3604
3605
3606
3607
3608
3609
3610
3611
3612
3613
3614
3615
3616
3617
3618
3619
3620
3621
3622
3623
3624
3625
3626
3627
3628
3629
3630
3631
3632
3633
3634
3635
3636
3637
3638
3639
3640
3641
3642
3643
3644
3645
3646
3647
3648
3649
3650
3651
3652
3653
3654
3655
3656
3657
3658
3659
3660
3661
3662
3663
3664
3665
3666
3667
3668
3669
3670
3671
3672
3673
3674
3675
3676
3677
3678
3679
3680
3681
3682
3683
3684
3685
3686
3687
3688
3689
3690
3691
3692
3693
3694
3695
3696
3697
3698
3699
3700
3701
3702
3703
3704
3705
3706
3707
3708
3709
3710
3711
3712
3713
3714
3715
3716
3717
3718
3719
3720
3721
3722
3723
3724
3725
3726
3727
3728
3729
3730
3731
3732
3733
3734
3735
3736
3737
3738
3739
3740
3741
3742
3743
3744
3745
3746
3747
3748
3749
3750
3751
3752
3753
3754
3755
3756
3757
3758
3759
3760
3761
3762
3763
3764
3765
3766
3767
3768
3769
3770
3771
3772
3773
3774
3775
3776
3777
3778
3779
3780
3781
3782
3783
3784
3785
3786
3787
3788
3789
3790
3791
3792
3793
3794
3795
3796
3797
3798
3799
3800
3801
3802
3803
3804
3805
3806
3807
3808
3809
3810
3811
3812
3813
3814
3815
3816
3817
3818
3819
3820
3821
3822
3823
3824
3825
3826
3827
3828
3829
3830
3831
3832
3833
3834
3835
3836
3837
3838
3839
3840
3841
3842
3843
3844
3845
3846
3847
3848
3849
3850
3851
3852
3853
3854
3855
3856
3857
3858
3859
3860
3861
3862
3863
3864
3865
3866
3867
3868
3869
3870
3871
3872
3873
3874
3875
3876
3877
3878
3879
3880
3881
3882
3883
3884
3885
3886
3887
3888
3889
3890
3891
3892
3893
3894
3895
3896
3897
3898
3899
3900
3901
3902
3903
3904
3905
3906
3907
3908
3909
3910
3911
3912
3913
3914
3915
3916
3917
3918
3919
3920
3921
3922
3923
3924
3925
3926
3927
3928
3929
3930
3931
3932
3933
3934
3935
3936
3937
3938
3939
3940
3941
3942
3943
3944
3945
3946
3947
3948
3949
3950
3951
3952
3953
3954
3955
3956
3957
3958
3959
3960
3961
3962
3963
3964
3965
3966
3967
3968
3969
3970
3971
3972
3973
3974
3975
3976
3977
3978
3979
3980
3981
3982
3983
3984
3985
3986
3987
3988
3989
3990
3991
3992
3993
3994
3995
3996
3997
3998
3999
4000
4001
4002
4003
4004
4005
4006
4007
4008
4009
4010
4011
4012
4013
4014
4015
4016
4017
4018
4019
4020
4021
4022
4023
4024
4025
4026
4027
4028
4029
4030
4031
4032
4033
4034
4035
4036
4037
4038
4039
4040
4041
4042
4043
4044
4045
4046
4047
4048
4049
4050
4051
4052
4053
4054
4055
4056
4057
4058
4059
4060
4061
4062
4063
4064
4065
4066
4067
4068
4069
4070
4071
4072
4073
4074
4075
4076
4077
4078
4079
4080
4081
4082
4083
4084
4085
4086
4087
4088
4089
4090
4091
4092
4093
4094
4095
4096
4097
4098
4099
4100
4101
4102
4103
4104
4105
4106
4107
4108
4109
4110
4111
4112
4113
4114
4115
4116
4117
4118
4119
4120
4121
4122
4123
4124
4125
4126
4127
4128
4129
4130
4131
4132
4133
4134
4135
4136
4137
4138
4139
4140
4141
4142
4143
4144
4145
4146
4147
4148
4149
4150
4151
4152
4153
4154
4155
4156
4157
4158
4159
4160
4161
4162
4163
4164
4165
4166
4167
4168
4169
4170
4171
4172
4173
4174
4175
4176
4177
4178
4179
4180
4181
4182
4183
4184
4185
4186
4187
4188
4189
4190
4191
4192
4193
4194
4195
4196
4197
4198
4199
4200
4201
4202
4203
4204
4205
4206
4207
4208
4209
4210
4211
4212
4213
4214
4215
4216
4217
4218
4219
4220
4221
4222
4223
4224
4225
4226
4227
4228
4229
4230
4231
4232
4233
4234
4235
4236
4237
4238
4239
4240
4241
4242
4243
4244
4245
4246
4247
4248
4249
4250
4251
4252
4253
4254
4255
4256
4257
4258
4259
4260
4261
4262
4263
4264
4265
4266
4267
4268
4269
4270
4271
4272
4273
4274
4275
4276
4277
4278
4279
4280
4281
4282
4283
4284
4285
4286
4287
4288
4289
4290
4291
4292
4293
4294
4295
4296
4297
4298
4299
4300
4301
4302
4303
4304
4305
4306
4307
4308
4309
4310
4311
4312
4313
4314
4315
4316
4317
4318
4319
4320
4321
4322
4323
4324
4325
4326
4327
4328
4329
4330
4331
4332
4333
4334
4335
4336
4337
4338
4339
4340
4341
4342
4343
4344
4345
4346
4347
4348
4349
4350
4351
4352
4353
4354
4355
4356
4357
4358
4359
4360
4361
4362
4363
4364
4365
4366
4367
4368
4369
4370
4371
4372
4373
4374
4375
4376
4377
4378
4379
4380
4381
4382
4383
4384
4385
4386
4387
4388
4389
4390
4391
4392
4393
4394
4395
4396
4397
4398
4399
4400
4401
4402
4403
4404
4405
4406
4407
4408
4409
4410
4411
4412
4413
4414
4415
4416
4417
4418
4419
4420
4421
4422
4423
4424
4425
4426
4427
4428
4429
4430
4431
4432
4433
4434
4435
4436
4437
4438
4439
4440
4441
4442
4443
4444
4445
4446
4447
4448
4449
4450
4451
4452
4453
4454
4455
4456
4457
4458
4459
4460
4461
4462
4463
4464
4465
4466
4467
4468
4469
4470
4471
4472
4473
4474
4475
4476
4477
4478
4479
4480
4481
4482
4483
4484
4485
4486
4487
4488
4489
4490
4491
4492
4493
4494
4495
4496
4497
4498
4499
4500
4501
4502
4503
4504
4505
4506
4507
4508
4509
4510
4511
4512
4513
4514
4515
4516
4517
4518
4519
4520
4521
4522
4523
4524
4525
4526
4527
4528
4529
4530
4531
4532
4533
4534
4535
4536
4537
4538
4539
4540
4541
4542
4543
4544
4545
4546
4547
4548
4549
4550
4551
4552
4553
4554
4555
4556
4557
4558
4559
4560
4561
4562
4563
4564
4565
4566
4567
4568
4569
4570
4571
4572
4573
4574
4575
4576
4577
4578
4579
4580
4581
4582
4583
4584
4585
4586
4587
4588
4589
4590
4591
4592
4593
4594
4595
4596
4597
4598
4599
4600
4601
4602
4603
4604
4605
4606
4607
4608
4609
4610
4611
4612
4613
4614
4615
4616
4617
4618
4619
4620
4621
4622
4623
4624
4625
4626
4627
4628
4629
4630
4631
4632
4633
4634
4635
4636
4637
4638
4639
4640
4641
4642
4643
4644
4645
4646
4647
4648
4649
4650
4651
4652
4653
4654
4655
4656
4657
4658
4659
4660
4661
4662
4663
4664
4665
4666
4667
4668
4669
4670
4671
4672
4673
4674
4675
4676
4677
4678
4679
4680
4681
4682
4683
4684
4685
4686
4687
4688
4689
4690
4691
4692
4693
4694
4695
4696
4697
4698
4699
4700
4701
4702
4703
4704
4705
4706
4707
4708
4709
4710
4711
4712
4713
4714
4715
4716
4717
4718
4719
4720
4721
4722
4723
4724
4725
4726
4727
4728
4729
4730
4731
4732
4733
4734
4735
4736
4737
4738
4739
4740
4741
4742
4743
4744
4745
4746
4747
4748
4749
4750
4751
4752
4753
4754
4755
4756
4757
4758
4759
4760
4761
4762
4763
4764
4765
4766
4767
4768
4769
4770
4771
4772
4773
4774
4775
4776
4777
4778
4779
4780
4781
4782
4783
4784
4785
4786
4787
4788
4789
4790
4791
4792
4793
4794
4795
4796
4797
4798
4799
4800
4801
4802
4803
4804
4805
4806
4807
4808
4809
4810
4811
4812
4813
4814
4815
4816
4817
4818
4819
4820
4821
4822
4823
4824
4825
4826
4827
4828
4829
4830
4831
4832
4833
4834
4835
4836
4837
4838
4839
4840
4841
4842
4843
4844
4845
4846
4847
4848
4849
4850
4851
4852
4853
4854
4855
4856
4857
4858
4859
4860
4861
4862
4863
4864
4865
4866
4867
4868
4869
4870
4871
4872
4873
4874
4875
4876
4877
4878
4879
4880
4881
4882
4883
4884
4885
4886
4887
4888
4889
4890
4891
4892
4893
4894
4895
4896
4897
4898
4899
4900
4901
4902
4903
4904
4905
4906
4907
4908
4909
4910
4911
4912
4913
4914
4915
4916
4917
4918
4919
4920
4921
4922
4923
4924
4925
4926
4927
4928
4929
4930
4931
4932
4933
4934
4935
4936
4937
4938
4939
4940
4941
4942
4943
4944
4945
4946
4947
4948
4949
4950
4951
4952
4953
4954
4955
4956
4957
4958
4959
4960
4961
4962
4963
4964
4965
4966
4967
4968
4969
4970
4971
4972
4973
4974
4975
4976
4977
4978
4979
4980
4981
4982
4983
4984
4985
4986
4987
4988
4989
4990
4991
4992
4993
4994
4995
4996
4997
4998
4999
5000
5001
5002
5003
5004
5005
5006
5007
5008
5009
5010
5011
5012
5013
5014
5015
5016
5017
5018
5019
5020
5021
5022
5023
5024
5025
5026
5027
5028
5029
5030
5031
5032
5033
5034
5035
5036
5037
5038
5039
5040
5041
5042
5043
5044
5045
5046
5047
5048
5049
5050
5051
5052
5053
5054
5055
5056
5057
5058
5059
5060
5061
5062
5063
5064
5065
5066
5067
5068
5069
5070
5071
5072
5073
5074
5075
5076
5077
5078
5079
5080
5081
5082
5083
5084
5085
5086
5087
5088
5089
5090
5091
5092
5093
5094
5095
5096
5097
5098
5099
5100
5101
5102
5103
5104
5105
5106
5107
5108
5109
5110
5111
5112
5113
5114
5115
5116
5117
5118
5119
5120
5121
5122
5123
5124
5125
5126
5127
5128
5129
5130
5131
5132
5133
5134
5135
5136
5137
5138
5139
5140
5141
5142
5143
5144
5145
5146
5147
5148
5149
5150
5151
5152
5153
5154
5155
5156
5157
5158
5159
5160
5161
5162
5163
5164
5165
5166
5167
5168
5169
5170
5171
5172
5173
5174
5175
5176
5177
5178
5179
5180
5181
5182
5183
5184
5185
5186
5187
5188
5189
5190
5191
5192
5193
5194
5195
5196
5197
5198
5199
5200
5201
5202
5203
5204
5205
5206
5207
5208
5209
5210
5211
5212
5213
5214
5215
5216
5217
5218
5219
5220
5221
5222
5223
5224
5225
5226
5227
5228
5229
5230
5231
5232
5233
5234
5235
5236
5237
5238
5239
5240
5241
5242
5243
5244
5245
5246
5247
5248
5249
5250
5251
5252
5253
5254
5255
5256
5257
5258
5259
5260
5261
5262
5263
5264
5265
5266
5267
5268
5269
5270
5271
5272
5273
5274
5275
5276
5277
5278
5279
5280
5281
5282
5283
5284
5285
5286
5287
5288
5289
5290
5291
5292
5293
5294
5295
5296
5297
5298
5299
5300
5301
5302
5303
5304
5305
5306
5307
5308
5309
5310
5311
5312
5313
5314
5315
5316
5317
5318
5319
5320
5321
5322
5323
5324
5325
5326
5327
5328
5329
5330
5331
5332
5333
5334
5335
5336
5337
5338
5339
5340
5341
5342
5343
5344
5345
5346
5347
5348
5349
5350
5351
5352
5353
5354
5355
5356
5357
5358
5359
5360
5361
5362
5363
5364
5365
5366
5367
5368
5369
5370
5371
5372
5373
5374
5375
5376
5377
5378
5379
5380
5381
5382
5383
5384
5385
5386
5387
5388
5389
5390
5391
5392
5393
5394
5395
5396
5397
5398
5399
5400
5401
5402
5403
5404
5405
5406
5407
5408
5409
5410
5411
5412
5413
5414
5415
5416
5417
5418
5419
5420
5421
5422
5423
5424
5425
5426
5427
5428
5429
5430
5431
5432
5433
5434
5435
5436
5437
5438
5439
5440
5441
5442
5443
5444
5445
5446
5447
5448
5449
5450
5451
5452
5453
5454
5455
5456
5457
5458
5459
5460
5461
5462
5463
5464
5465
5466
5467
5468
5469
5470
5471
5472
5473
5474
5475
5476
5477
5478
5479
5480
5481
5482
5483
5484
5485
5486
5487
5488
5489
5490
5491
5492
5493
5494
5495
5496
5497
5498
5499
5500
5501
5502
5503
5504
5505
5506
5507
5508
5509
5510
5511
5512
5513
5514
5515
5516
5517
5518
5519
5520
5521
5522
5523
5524
5525
5526
5527
5528
5529
5530
5531
5532
5533
5534
5535
5536
5537
5538
5539
5540
5541
5542
5543
5544
5545
5546
5547
5548
5549
5550
5551
5552
5553
5554
5555
5556
5557
5558
5559
5560
5561
5562
5563
5564
5565
5566
5567
5568
5569
5570
5571
5572
5573
5574
5575
5576
5577
5578
5579
5580
5581
5582
5583
5584
5585
5586
5587
5588
5589
5590
5591
5592
5593
5594
5595
5596
5597
5598
5599
5600
5601
5602
5603
5604
5605
5606
5607
5608
5609
5610
5611
5612
5613
5614
5615
5616
5617
5618
5619
5620
5621
5622
5623
5624
5625
5626
5627
5628
5629
5630
5631
5632
5633
5634
5635
5636
5637
5638
5639
5640
5641
5642
5643
5644
5645
5646
5647
5648
5649
5650
5651
5652
5653
5654
5655
5656
5657
5658
5659
5660
5661
5662
5663
5664
5665
5666
5667
5668
5669
5670
5671
5672
5673
5674
5675
5676
5677
5678
5679
5680
5681
5682
5683
5684
5685
5686
5687
5688
5689
5690
5691
5692
5693
5694
5695
5696
5697
5698
5699
5700
5701
5702
5703
5704
5705
5706
5707
5708
5709
5710
5711
5712
5713
5714
5715
5716
5717
5718
5719
5720
5721
5722
5723
5724
5725
5726
5727
5728
5729
5730
5731
5732
5733
5734
5735
5736
5737
5738
5739
5740
5741
5742
5743
5744
5745
5746
5747
5748
5749
5750
5751
5752
5753
5754
5755
5756
5757
5758
5759
5760
5761
5762
5763
5764
5765
5766
5767
5768
5769
5770
5771
5772
5773
5774
5775
5776
5777
5778
5779
5780
5781
5782
5783
5784
5785
5786
5787
5788
5789
5790
5791
5792
5793
5794
5795
5796
5797
5798
5799
5800
5801
5802
5803
|
\documentclass{manual}
\usepackage[T1]{fontenc}
\usepackage{textcomp}
% Things to do:
% Should really move the Python startup file info to an appendix
\title{Python Tutorial}
\input{boilerplate}
\makeindex
\begin{document}
\maketitle
\ifhtml
\chapter*{Front Matter\label{front}}
\fi
\input{copyright}
\begin{abstract}
\noindent
Python is an easy to learn, powerful programming language. It has
efficient high-level data structures and a simple but effective
approach to object-oriented programming. Python's elegant syntax and
dynamic typing, together with its interpreted nature, make it an ideal
language for scripting and rapid application development in many areas
on most platforms.
The Python interpreter and the extensive standard library are freely
available in source or binary form for all major platforms from the
Python Web site, \url{http://www.python.org/}, and may be freely
distributed. The same site also contains distributions of and
pointers to many free third party Python modules, programs and tools,
and additional documentation.
The Python interpreter is easily extended with new functions and data
types implemented in C or \Cpp{} (or other languages callable from C).
Python is also suitable as an extension language for customizable
applications.
This tutorial introduces the reader informally to the basic concepts
and features of the Python language and system. It helps to have a
Python interpreter handy for hands-on experience, but all examples are
self-contained, so the tutorial can be read off-line as well.
For a description of standard objects and modules, see the
\citetitle[../lib/lib.html]{Python Library Reference} document. The
\citetitle[../ref/ref.html]{Python Reference Manual} gives a more
formal definition of the language. To write extensions in C or
\Cpp, read \citetitle[../ext/ext.html]{Extending and Embedding the
Python Interpreter} and \citetitle[../api/api.html]{Python/C API
Reference}. There are also several books covering Python in depth.
This tutorial does not attempt to be comprehensive and cover every
single feature, or even every commonly used feature. Instead, it
introduces many of Python's most noteworthy features, and will give
you a good idea of the language's flavor and style. After reading it,
you will be able to read and write Python modules and programs, and
you will be ready to learn more about the various Python library
modules described in the \citetitle[../lib/lib.html]{Python Library
Reference}.
\end{abstract}
\tableofcontents
\chapter{Whetting Your Appetite \label{intro}}
If you do much work on computers, eventually you find that there's
some task you'd like to automate. For example, you may wish to
perform a search-and-replace over a large number of text files, or
rename and rearrange a bunch of photo files in a complicated way.
Perhaps you'd like to write a small custom database, or a specialized
GUI application, or a simple game.
If you're a professional software developer, you may have to work with
several C/\Cpp/Java libraries but find the usual
write/compile/test/re-compile cycle is too slow. Perhaps you're
writing a test suite for such a library and find writing the testing
code a tedious task. Or maybe you've written a program that could use
an extension language, and you don't want to design and implement a
whole new language for your application.
Python is just the language for you.
You could write a {\UNIX} shell script or Windows batch files for some
of these tasks, but shell scripts are best at moving around files and
changing text data, not well-suited for GUI applications or games.
You could write a C/{\Cpp}/Java program, but it can take a lot of
development time to get even a first-draft program. Python is simpler
to use, available on Windows, MacOS X, and {\UNIX} operating systems,
and will help you get the job done more quickly.
Python is simple to use, but it is a real programming language,
offering much more structure and support for large programs than shell
scripts or batch files can offer. On the other hand, Python also
offers much more error checking than C, and, being a
\emph{very-high-level language}, it has high-level data types built
in, such as flexible arrays and dictionaries. Because of its more
general data types Python is applicable to a much larger problem
domain than Awk or even Perl, yet many things are at
least as easy in Python as in those languages.
Python allows you to split your program into modules that can be
reused in other Python programs. It comes with a large collection of
standard modules that you can use as the basis of your programs --- or
as examples to start learning to program in Python. Some of these
modules provide things like file I/O, system calls,
sockets, and even interfaces to graphical user interface toolkits like Tk.
Python is an interpreted language, which can save you considerable time
during program development because no compilation and linking is
necessary. The interpreter can be used interactively, which makes it
easy to experiment with features of the language, to write throw-away
programs, or to test functions during bottom-up program development.
It is also a handy desk calculator.
Python enables programs to be written compactly and readably. Programs
written in Python are typically much shorter than equivalent C,
\Cpp{}, or Java programs, for several reasons:
\begin{itemize}
\item
the high-level data types allow you to express complex operations in a
single statement;
\item
statement grouping is done by indentation instead of beginning and ending
brackets;
\item
no variable or argument declarations are necessary.
\end{itemize}
Python is \emph{extensible}: if you know how to program in C it is easy
to add a new built-in function or module to the interpreter, either to
perform critical operations at maximum speed, or to link Python
programs to libraries that may only be available in binary form (such
as a vendor-specific graphics library). Once you are really hooked,
you can link the Python interpreter into an application written in C
and use it as an extension or command language for that application.
By the way, the language is named after the BBC show ``Monty Python's
Flying Circus'' and has nothing to do with nasty reptiles. Making
references to Monty Python skits in documentation is not only allowed,
it is encouraged!
%\section{Where From Here \label{where}}
Now that you are all excited about Python, you'll want to examine it
in some more detail. Since the best way to learn a language is
to use it, the tutorial invites you to play with the Python interpreter
as you read.
In the next chapter, the mechanics of using the interpreter are
explained. This is rather mundane information, but essential for
trying out the examples shown later.
The rest of the tutorial introduces various features of the Python
language and system through examples, beginning with simple
expressions, statements and data types, through functions and modules,
and finally touching upon advanced concepts like exceptions
and user-defined classes.
\chapter{Using the Python Interpreter \label{using}}
\section{Invoking the Interpreter \label{invoking}}
The Python interpreter is usually installed as
\file{/usr/local/bin/python} on those machines where it is available;
putting \file{/usr/local/bin} in your \UNIX{} shell's search path
makes it possible to start it by typing the command
\begin{verbatim}
python
\end{verbatim}
to the shell. Since the choice of the directory where the interpreter
lives is an installation option, other places are possible; check with
your local Python guru or system administrator. (E.g.,
\file{/usr/local/python} is a popular alternative location.)
On Windows machines, the Python installation is usually placed in
\file{C:\e Python24}, though you can change this when you're running
the installer. To add this directory to your path,
you can type the following command into the command prompt in a DOS box:
\begin{verbatim}
set path=%path%;C:\python24
\end{verbatim}
Typing an end-of-file character (\kbd{Control-D} on \UNIX,
\kbd{Control-Z} on Windows) at the primary prompt causes the
interpreter to exit with a zero exit status. If that doesn't work,
you can exit the interpreter by typing the following commands:
\samp{import sys; sys.exit()}.
The interpreter's line-editing features usually aren't very
sophisticated. On \UNIX, whoever installed the interpreter may have
enabled support for the GNU readline library, which adds more
elaborate interactive editing and history features. Perhaps the
quickest check to see whether command line editing is supported is
typing Control-P to the first Python prompt you get. If it beeps, you
have command line editing; see Appendix \ref{interacting} for an
introduction to the keys. If nothing appears to happen, or if
\code{\^P} is echoed, command line editing isn't available; you'll
only be able to use backspace to remove characters from the current
line.
The interpreter operates somewhat like the \UNIX{} shell: when called
with standard input connected to a tty device, it reads and executes
commands interactively; when called with a file name argument or with
a file as standard input, it reads and executes a \emph{script} from
that file.
A second way of starting the interpreter is
\samp{\program{python} \programopt{-c} \var{command} [arg] ...}, which
executes the statement(s) in \var{command}, analogous to the shell's
\programopt{-c} option. Since Python statements often contain spaces
or other characters that are special to the shell, it is best to quote
\var{command} in its entirety with double quotes.
Some Python modules are also useful as scripts. These can be invoked using
\samp{\program{python} \programopt{-m} \var{module} [arg] ...}, which
executes the source file for \var{module} as if you had spelled out its
full name on the command line.
Note that there is a difference between \samp{python file} and
\samp{python <file}. In the latter case, input requests from the
program, such as calls to \function{input()} and \function{raw_input()}, are
satisfied from \emph{file}. Since this file has already been read
until the end by the parser before the program starts executing, the
program will encounter end-of-file immediately. In the former case
(which is usually what you want) they are satisfied from whatever file
or device is connected to standard input of the Python interpreter.
When a script file is used, it is sometimes useful to be able to run
the script and enter interactive mode afterwards. This can be done by
passing \programopt{-i} before the script. (This does not work if the
script is read from standard input, for the same reason as explained
in the previous paragraph.)
\subsection{Argument Passing \label{argPassing}}
When known to the interpreter, the script name and additional
arguments thereafter are passed to the script in the variable
\code{sys.argv}, which is a list of strings. Its length is at least
one; when no script and no arguments are given, \code{sys.argv[0]} is
an empty string. When the script name is given as \code{'-'} (meaning
standard input), \code{sys.argv[0]} is set to \code{'-'}. When
\programopt{-c} \var{command} is used, \code{sys.argv[0]} is set to
\code{'-c'}. When \programopt{-m} \var{module} is used, \code{sys.argv[0]}
is set to the full name of the located module. Options found after
\programopt{-c} \var{command} or \programopt{-m} \var{module} are not consumed
by the Python interpreter's option processing but left in \code{sys.argv} for
the command or module to handle.
\subsection{Interactive Mode \label{interactive}}
When commands are read from a tty, the interpreter is said to be in
\emph{interactive mode}. In this mode it prompts for the next command
with the \emph{primary prompt}, usually three greater-than signs
(\samp{>\code{>}>~}); for continuation lines it prompts with the
\emph{secondary prompt}, by default three dots (\samp{...~}).
The interpreter prints a welcome message stating its version number
and a copyright notice before printing the first prompt:
\begin{verbatim}
python
Python 1.5.2b2 (#1, Feb 28 1999, 00:02:06) [GCC 2.8.1] on sunos5
Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam
>>>
\end{verbatim}
Continuation lines are needed when entering a multi-line construct.
As an example, take a look at this \keyword{if} statement:
\begin{verbatim}
>>> the_world_is_flat = 1
>>> if the_world_is_flat:
... print "Be careful not to fall off!"
...
Be careful not to fall off!
\end{verbatim}
\section{The Interpreter and Its Environment \label{interp}}
\subsection{Error Handling \label{error}}
When an error occurs, the interpreter prints an error
message and a stack trace. In interactive mode, it then returns to
the primary prompt; when input came from a file, it exits with a
nonzero exit status after printing
the stack trace. (Exceptions handled by an \keyword{except} clause in a
\keyword{try} statement are not errors in this context.) Some errors are
unconditionally fatal and cause an exit with a nonzero exit; this
applies to internal inconsistencies and some cases of running out of
memory. All error messages are written to the standard error stream;
normal output from executed commands is written to standard
output.
Typing the interrupt character (usually Control-C or DEL) to the
primary or secondary prompt cancels the input and returns to the
primary prompt.\footnote{
A problem with the GNU Readline package may prevent this.
}
Typing an interrupt while a command is executing raises the
\exception{KeyboardInterrupt} exception, which may be handled by a
\keyword{try} statement.
\subsection{Executable Python Scripts \label{scripts}}
On BSD'ish \UNIX{} systems, Python scripts can be made directly
executable, like shell scripts, by putting the line
\begin{verbatim}
#! /usr/bin/env python
\end{verbatim}
(assuming that the interpreter is on the user's \envvar{PATH}) at the
beginning of the script and giving the file an executable mode. The
\samp{\#!} must be the first two characters of the file. On some
platforms, this first line must end with a \UNIX-style line ending
(\character{\e n}), not a Mac OS (\character{\e r}) or Windows
(\character{\e r\e n}) line ending. Note that
the hash, or pound, character, \character{\#}, is used to start a
comment in Python.
The script can be given an executable mode, or permission, using the
\program{chmod} command:
\begin{verbatim}
$ chmod +x myscript.py
\end{verbatim} % $ <-- bow to font-lock
\subsection{Source Code Encoding}
It is possible to use encodings different than \ASCII{} in Python source
files. The best way to do it is to put one more special comment line
right after the \code{\#!} line to define the source file encoding:
\begin{alltt}
# -*- coding: \var{encoding} -*-
\end{alltt}
With that declaration, all characters in the source file will be treated as
having the encoding \var{encoding}, and it will be
possible to directly write Unicode string literals in the selected
encoding. The list of possible encodings can be found in the
\citetitle[../lib/lib.html]{Python Library Reference}, in the section
on \ulink{\module{codecs}}{../lib/module-codecs.html}.
For example, to write Unicode literals including the Euro currency
symbol, the ISO-8859-15 encoding can be used, with the Euro symbol
having the ordinal value 164. This script will print the value 8364
(the Unicode codepoint corresponding to the Euro symbol) and then
exit:
\begin{alltt}
# -*- coding: iso-8859-15 -*-
currency = u"\texteuro"
print ord(currency)
\end{alltt}
If your editor supports saving files as \code{UTF-8} with a UTF-8
\emph{byte order mark} (aka BOM), you can use that instead of an
encoding declaration. IDLE supports this capability if
\code{Options/General/Default Source Encoding/UTF-8} is set. Notice
that this signature is not understood in older Python releases (2.2
and earlier), and also not understood by the operating system for
script files with \code{\#!} lines (only used on \UNIX{} systems).
By using UTF-8 (either through the signature or an encoding
declaration), characters of most languages in the world can be used
simultaneously in string literals and comments. Using non-\ASCII{}
characters in identifiers is not supported. To display all these
characters properly, your editor must recognize that the file is
UTF-8, and it must use a font that supports all the characters in the
file.
\subsection{The Interactive Startup File \label{startup}}
% XXX This should probably be dumped in an appendix, since most people
% don't use Python interactively in non-trivial ways.
When you use Python interactively, it is frequently handy to have some
standard commands executed every time the interpreter is started. You
can do this by setting an environment variable named
\envvar{PYTHONSTARTUP} to the name of a file containing your start-up
commands. This is similar to the \file{.profile} feature of the
\UNIX{} shells.
This file is only read in interactive sessions, not when Python reads
commands from a script, and not when \file{/dev/tty} is given as the
explicit source of commands (which otherwise behaves like an
interactive session). It is executed in the same namespace where
interactive commands are executed, so that objects that it defines or
imports can be used without qualification in the interactive session.
You can also change the prompts \code{sys.ps1} and \code{sys.ps2} in
this file.
If you want to read an additional start-up file from the current
directory, you can program this in the global start-up file using code
like \samp{if os.path.isfile('.pythonrc.py'):
execfile('.pythonrc.py')}. If you want to use the startup file in a
script, you must do this explicitly in the script:
\begin{verbatim}
import os
filename = os.environ.get('PYTHONSTARTUP')
if filename and os.path.isfile(filename):
execfile(filename)
\end{verbatim}
\chapter{An Informal Introduction to Python \label{informal}}
In the following examples, input and output are distinguished by the
presence or absence of prompts (\samp{>\code{>}>~} and \samp{...~}): to repeat
the example, you must type everything after the prompt, when the
prompt appears; lines that do not begin with a prompt are output from
the interpreter. %
%\footnote{
% I'd prefer to use different fonts to distinguish input
% from output, but the amount of LaTeX hacking that would require
% is currently beyond my ability.
%}
Note that a secondary prompt on a line by itself in an example means
you must type a blank line; this is used to end a multi-line command.
Many of the examples in this manual, even those entered at the
interactive prompt, include comments. Comments in Python start with
the hash character, \character{\#}, and extend to the end of the
physical line. A comment may appear at the start of a line or
following whitespace or code, but not within a string literal. A hash
character within a string literal is just a hash character.
Some examples:
\begin{verbatim}
# this is the first comment
SPAM = 1 # and this is the second comment
# ... and now a third!
STRING = "# This is not a comment."
\end{verbatim}
\section{Using Python as a Calculator \label{calculator}}
Let's try some simple Python commands. Start the interpreter and wait
for the primary prompt, \samp{>\code{>}>~}. (It shouldn't take long.)
\subsection{Numbers \label{numbers}}
The interpreter acts as a simple calculator: you can type an
expression at it and it will write the value. Expression syntax is
straightforward: the operators \code{+}, \code{-}, \code{*} and
\code{/} work just like in most other languages (for example, Pascal
or C); parentheses can be used for grouping. For example:
\begin{verbatim}
>>> 2+2
4
>>> # This is a comment
... 2+2
4
>>> 2+2 # and a comment on the same line as code
4
>>> (50-5*6)/4
5
>>> # Integer division returns the floor:
... 7/3
2
>>> 7/-3
-3
\end{verbatim}
The equal sign (\character{=}) is used to assign a value to a variable.
Afterwards, no result is displayed before the next interactive prompt:
\begin{verbatim}
>>> width = 20
>>> height = 5*9
>>> width * height
900
\end{verbatim}
A value can be assigned to several variables simultaneously:
\begin{verbatim}
>>> x = y = z = 0 # Zero x, y and z
>>> x
0
>>> y
0
>>> z
0
\end{verbatim}
There is full support for floating point; operators with mixed type
operands convert the integer operand to floating point:
\begin{verbatim}
>>> 3 * 3.75 / 1.5
7.5
>>> 7.0 / 2
3.5
\end{verbatim}
Complex numbers are also supported; imaginary numbers are written with
a suffix of \samp{j} or \samp{J}. Complex numbers with a nonzero
real component are written as \samp{(\var{real}+\var{imag}j)}, or can
be created with the \samp{complex(\var{real}, \var{imag})} function.
\begin{verbatim}
>>> 1j * 1J
(-1+0j)
>>> 1j * complex(0,1)
(-1+0j)
>>> 3+1j*3
(3+3j)
>>> (3+1j)*3
(9+3j)
>>> (1+2j)/(1+1j)
(1.5+0.5j)
\end{verbatim}
Complex numbers are always represented as two floating point numbers,
the real and imaginary part. To extract these parts from a complex
number \var{z}, use \code{\var{z}.real} and \code{\var{z}.imag}.
\begin{verbatim}
>>> a=1.5+0.5j
>>> a.real
1.5
>>> a.imag
0.5
\end{verbatim}
The conversion functions to floating point and integer
(\function{float()}, \function{int()} and \function{long()}) don't
work for complex numbers --- there is no one correct way to convert a
complex number to a real number. Use \code{abs(\var{z})} to get its
magnitude (as a float) or \code{z.real} to get its real part.
\begin{verbatim}
>>> a=3.0+4.0j
>>> float(a)
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: can't convert complex to float; use abs(z)
>>> a.real
3.0
>>> a.imag
4.0
>>> abs(a) # sqrt(a.real**2 + a.imag**2)
5.0
>>>
\end{verbatim}
In interactive mode, the last printed expression is assigned to the
variable \code{_}. This means that when you are using Python as a
desk calculator, it is somewhat easier to continue calculations, for
example:
\begin{verbatim}
>>> tax = 12.5 / 100
>>> price = 100.50
>>> price * tax
12.5625
>>> price + _
113.0625
>>> round(_, 2)
113.06
>>>
\end{verbatim}
This variable should be treated as read-only by the user. Don't
explicitly assign a value to it --- you would create an independent
local variable with the same name masking the built-in variable with
its magic behavior.
\subsection{Strings \label{strings}}
Besides numbers, Python can also manipulate strings, which can be
expressed in several ways. They can be enclosed in single quotes or
double quotes:
\begin{verbatim}
>>> 'spam eggs'
'spam eggs'
>>> 'doesn\'t'
"doesn't"
>>> "doesn't"
"doesn't"
>>> '"Yes," he said.'
'"Yes," he said.'
>>> "\"Yes,\" he said."
'"Yes," he said.'
>>> '"Isn\'t," she said.'
'"Isn\'t," she said.'
\end{verbatim}
String literals can span multiple lines in several ways. Continuation
lines can be used, with a backslash as the last character on the line
indicating that the next line is a logical continuation of the line:
\begin{verbatim}
hello = "This is a rather long string containing\n\
several lines of text just as you would do in C.\n\
Note that whitespace at the beginning of the line is\
significant."
print hello
\end{verbatim}
Note that newlines still need to be embedded in the string using
\code{\e n}; the newline following the trailing backslash is
discarded. This example would print the following:
\begin{verbatim}
This is a rather long string containing
several lines of text just as you would do in C.
Note that whitespace at the beginning of the line is significant.
\end{verbatim}
If we make the string literal a ``raw'' string, however, the
\code{\e n} sequences are not converted to newlines, but the backslash
at the end of the line, and the newline character in the source, are
both included in the string as data. Thus, the example:
\begin{verbatim}
hello = r"This is a rather long string containing\n\
several lines of text much as you would do in C."
print hello
\end{verbatim}
would print:
\begin{verbatim}
This is a rather long string containing\n\
several lines of text much as you would do in C.
\end{verbatim}
Or, strings can be surrounded in a pair of matching triple-quotes:
\code{"""} or \code{'\code{'}'}. End of lines do not need to be escaped
when using triple-quotes, but they will be included in the string.
\begin{verbatim}
print """
Usage: thingy [OPTIONS]
-h Display this usage message
-H hostname Hostname to connect to
"""
\end{verbatim}
produces the following output:
\begin{verbatim}
Usage: thingy [OPTIONS]
-h Display this usage message
-H hostname Hostname to connect to
\end{verbatim}
The interpreter prints the result of string operations in the same way
as they are typed for input: inside quotes, and with quotes and other
funny characters escaped by backslashes, to show the precise
value. The string is enclosed in double quotes if the string contains
a single quote and no double quotes, else it's enclosed in single
quotes. (The \keyword{print} statement, described later, can be used
to write strings without quotes or escapes.)
Strings can be concatenated (glued together) with the
\code{+} operator, and repeated with \code{*}:
\begin{verbatim}
>>> word = 'Help' + 'A'
>>> word
'HelpA'
>>> '<' + word*5 + '>'
'<HelpAHelpAHelpAHelpAHelpA>'
\end{verbatim}
Two string literals next to each other are automatically concatenated;
the first line above could also have been written \samp{word = 'Help'
'A'}; this only works with two literals, not with arbitrary string
expressions:
\begin{verbatim}
>>> 'str' 'ing' # <- This is ok
'string'
>>> 'str'.strip() + 'ing' # <- This is ok
'string'
>>> 'str'.strip() 'ing' # <- This is invalid
File "<stdin>", line 1, in ?
'str'.strip() 'ing'
^
SyntaxError: invalid syntax
\end{verbatim}
Strings can be subscripted (indexed); like in C, the first character
of a string has subscript (index) 0. There is no separate character
type; a character is simply a string of size one. Like in Icon,
substrings can be specified with the \emph{slice notation}: two indices
separated by a colon.
\begin{verbatim}
>>> word[4]
'A'
>>> word[0:2]
'He'
>>> word[2:4]
'lp'
\end{verbatim}
Slice indices have useful defaults; an omitted first index defaults to
zero, an omitted second index defaults to the size of the string being
sliced.
\begin{verbatim}
>>> word[:2] # The first two characters
'He'
>>> word[2:] # Everything except the first two characters
'lpA'
\end{verbatim}
Unlike a C string, Python strings cannot be changed. Assigning to an
indexed position in the string results in an error:
\begin{verbatim}
>>> word[0] = 'x'
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: object doesn't support item assignment
>>> word[:1] = 'Splat'
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: object doesn't support slice assignment
\end{verbatim}
However, creating a new string with the combined content is easy and
efficient:
\begin{verbatim}
>>> 'x' + word[1:]
'xelpA'
>>> 'Splat' + word[4]
'SplatA'
\end{verbatim}
Here's a useful invariant of slice operations:
\code{s[:i] + s[i:]} equals \code{s}.
\begin{verbatim}
>>> word[:2] + word[2:]
'HelpA'
>>> word[:3] + word[3:]
'HelpA'
\end{verbatim}
Degenerate slice indices are handled gracefully: an index that is too
large is replaced by the string size, an upper bound smaller than the
lower bound returns an empty string.
\begin{verbatim}
>>> word[1:100]
'elpA'
>>> word[10:]
''
>>> word[2:1]
''
\end{verbatim}
Indices may be negative numbers, to start counting from the right.
For example:
\begin{verbatim}
>>> word[-1] # The last character
'A'
>>> word[-2] # The last-but-one character
'p'
>>> word[-2:] # The last two characters
'pA'
>>> word[:-2] # Everything except the last two characters
'Hel'
\end{verbatim}
But note that -0 is really the same as 0, so it does not count from
the right!
\begin{verbatim}
>>> word[-0] # (since -0 equals 0)
'H'
\end{verbatim}
Out-of-range negative slice indices are truncated, but don't try this
for single-element (non-slice) indices:
\begin{verbatim}
>>> word[-100:]
'HelpA'
>>> word[-10] # error
Traceback (most recent call last):
File "<stdin>", line 1, in ?
IndexError: string index out of range
\end{verbatim}
The best way to remember how slices work is to think of the indices as
pointing \emph{between} characters, with the left edge of the first
character numbered 0. Then the right edge of the last character of a
string of \var{n} characters has index \var{n}, for example:
\begin{verbatim}
+---+---+---+---+---+
| H | e | l | p | A |
+---+---+---+---+---+
0 1 2 3 4 5
-5 -4 -3 -2 -1
\end{verbatim}
The first row of numbers gives the position of the indices 0...5 in
the string; the second row gives the corresponding negative indices.
The slice from \var{i} to \var{j} consists of all characters between
the edges labeled \var{i} and \var{j}, respectively.
For non-negative indices, the length of a slice is the difference of
the indices, if both are within bounds. For example, the length of
\code{word[1:3]} is 2.
The built-in function \function{len()} returns the length of a string:
\begin{verbatim}
>>> s = 'supercalifragilisticexpialidocious'
>>> len(s)
34
\end{verbatim}
\begin{seealso}
\seetitle[../lib/typesseq.html]{Sequence Types}%
{Strings, and the Unicode strings described in the next
section, are examples of \emph{sequence types}, and
support the common operations supported by such types.}
\seetitle[../lib/string-methods.html]{String Methods}%
{Both strings and Unicode strings support a large number of
methods for basic transformations and searching.}
\seetitle[../lib/typesseq-strings.html]{String Formatting Operations}%
{The formatting operations invoked when strings and Unicode
strings are the left operand of the \code{\%} operator are
described in more detail here.}
\end{seealso}
\subsection{Unicode Strings \label{unicodeStrings}}
\sectionauthor{Marc-Andre Lemburg}{mal@lemburg.com}
Starting with Python 2.0 a new data type for storing text data is
available to the programmer: the Unicode object. It can be used to
store and manipulate Unicode data (see \url{http://www.unicode.org/})
and integrates well with the existing string objects, providing
auto-conversions where necessary.
Unicode has the advantage of providing one ordinal for every character
in every script used in modern and ancient texts. Previously, there
were only 256 possible ordinals for script characters. Texts were
typically bound to a code page which mapped the ordinals to script
characters. This lead to very much confusion especially with respect
to internationalization (usually written as \samp{i18n} ---
\character{i} + 18 characters + \character{n}) of software. Unicode
solves these problems by defining one code page for all scripts.
Creating Unicode strings in Python is just as simple as creating
normal strings:
\begin{verbatim}
>>> u'Hello World !'
u'Hello World !'
\end{verbatim}
The small \character{u} in front of the quote indicates that a
Unicode string is supposed to be created. If you want to include
special characters in the string, you can do so by using the Python
\emph{Unicode-Escape} encoding. The following example shows how:
\begin{verbatim}
>>> u'Hello\u0020World !'
u'Hello World !'
\end{verbatim}
The escape sequence \code{\e u0020} indicates to insert the Unicode
character with the ordinal value 0x0020 (the space character) at the
given position.
Other characters are interpreted by using their respective ordinal
values directly as Unicode ordinals. If you have literal strings
in the standard Latin-1 encoding that is used in many Western countries,
you will find it convenient that the lower 256 characters
of Unicode are the same as the 256 characters of Latin-1.
For experts, there is also a raw mode just like the one for normal
strings. You have to prefix the opening quote with 'ur' to have
Python use the \emph{Raw-Unicode-Escape} encoding. It will only apply
the above \code{\e uXXXX} conversion if there is an uneven number of
backslashes in front of the small 'u'.
\begin{verbatim}
>>> ur'Hello\u0020World !'
u'Hello World !'
>>> ur'Hello\\u0020World !'
u'Hello\\\\u0020World !'
\end{verbatim}
The raw mode is most useful when you have to enter lots of
backslashes, as can be necessary in regular expressions.
Apart from these standard encodings, Python provides a whole set of
other ways of creating Unicode strings on the basis of a known
encoding.
The built-in function \function{unicode()}\bifuncindex{unicode} provides
access to all registered Unicode codecs (COders and DECoders). Some of
the more well known encodings which these codecs can convert are
\emph{Latin-1}, \emph{ASCII}, \emph{UTF-8}, and \emph{UTF-16}.
The latter two are variable-length encodings that store each Unicode
character in one or more bytes. The default encoding is
normally set to \ASCII, which passes through characters in the range
0 to 127 and rejects any other characters with an error.
When a Unicode string is printed, written to a file, or converted
with \function{str()}, conversion takes place using this default encoding.
\begin{verbatim}
>>> u"abc"
u'abc'
>>> str(u"abc")
'abc'
>>> u"äöü"
u'\xe4\xf6\xfc'
>>> str(u"äöü")
Traceback (most recent call last):
File "<stdin>", line 1, in ?
UnicodeEncodeError: 'ascii' codec can't encode characters in position 0-2: ordinal not in range(128)
\end{verbatim}
To convert a Unicode string into an 8-bit string using a specific
encoding, Unicode objects provide an \function{encode()} method
that takes one argument, the name of the encoding. Lowercase names
for encodings are preferred.
\begin{verbatim}
>>> u"äöü".encode('utf-8')
'\xc3\xa4\xc3\xb6\xc3\xbc'
\end{verbatim}
If you have data in a specific encoding and want to produce a
corresponding Unicode string from it, you can use the
\function{unicode()} function with the encoding name as the second
argument.
\begin{verbatim}
>>> unicode('\xc3\xa4\xc3\xb6\xc3\xbc', 'utf-8')
u'\xe4\xf6\xfc'
\end{verbatim}
\subsection{Lists \label{lists}}
Python knows a number of \emph{compound} data types, used to group
together other values. The most versatile is the \emph{list}, which
can be written as a list of comma-separated values (items) between
square brackets. List items need not all have the same type.
\begin{verbatim}
>>> a = ['spam', 'eggs', 100, 1234]
>>> a
['spam', 'eggs', 100, 1234]
\end{verbatim}
Like string indices, list indices start at 0, and lists can be sliced,
concatenated and so on:
\begin{verbatim}
>>> a[0]
'spam'
>>> a[3]
1234
>>> a[-2]
100
>>> a[1:-1]
['eggs', 100]
>>> a[:2] + ['bacon', 2*2]
['spam', 'eggs', 'bacon', 4]
>>> 3*a[:3] + ['Boo!']
['spam', 'eggs', 100, 'spam', 'eggs', 100, 'spam', 'eggs', 100, 'Boo!']
\end{verbatim}
Unlike strings, which are \emph{immutable}, it is possible to change
individual elements of a list:
\begin{verbatim}
>>> a
['spam', 'eggs', 100, 1234]
>>> a[2] = a[2] + 23
>>> a
['spam', 'eggs', 123, 1234]
\end{verbatim}
Assignment to slices is also possible, and this can even change the size
of the list:
\begin{verbatim}
>>> # Replace some items:
... a[0:2] = [1, 12]
>>> a
[1, 12, 123, 1234]
>>> # Remove some:
... a[0:2] = []
>>> a
[123, 1234]
>>> # Insert some:
... a[1:1] = ['bletch', 'xyzzy']
>>> a
[123, 'bletch', 'xyzzy', 1234]
>>> a[:0] = a # Insert (a copy of) itself at the beginning
>>> a
[123, 'bletch', 'xyzzy', 1234, 123, 'bletch', 'xyzzy', 1234]
\end{verbatim}
The built-in function \function{len()} also applies to lists:
\begin{verbatim}
>>> len(a)
8
\end{verbatim}
It is possible to nest lists (create lists containing other lists),
for example:
\begin{verbatim}
>>> q = [2, 3]
>>> p = [1, q, 4]
>>> len(p)
3
>>> p[1]
[2, 3]
>>> p[1][0]
2
>>> p[1].append('xtra') # See section 5.1
>>> p
[1, [2, 3, 'xtra'], 4]
>>> q
[2, 3, 'xtra']
\end{verbatim}
Note that in the last example, \code{p[1]} and \code{q} really refer to
the same object! We'll come back to \emph{object semantics} later.
\section{First Steps Towards Programming \label{firstSteps}}
Of course, we can use Python for more complicated tasks than adding
two and two together. For instance, we can write an initial
sub-sequence of the \emph{Fibonacci} series as follows:
\begin{verbatim}
>>> # Fibonacci series:
... # the sum of two elements defines the next
... a, b = 0, 1
>>> while b < 10:
... print b
... a, b = b, a+b
...
1
1
2
3
5
8
\end{verbatim}
This example introduces several new features.
\begin{itemize}
\item
The first line contains a \emph{multiple assignment}: the variables
\code{a} and \code{b} simultaneously get the new values 0 and 1. On the
last line this is used again, demonstrating that the expressions on
the right-hand side are all evaluated first before any of the
assignments take place. The right-hand side expressions are evaluated
from the left to the right.
\item
The \keyword{while} loop executes as long as the condition (here:
\code{b < 10}) remains true. In Python, like in C, any non-zero
integer value is true; zero is false. The condition may also be a
string or list value, in fact any sequence; anything with a non-zero
length is true, empty sequences are false. The test used in the
example is a simple comparison. The standard comparison operators are
written the same as in C: \code{<} (less than), \code{>} (greater than),
\code{==} (equal to), \code{<=} (less than or equal to),
\code{>=} (greater than or equal to) and \code{!=} (not equal to).
\item
The \emph{body} of the loop is \emph{indented}: indentation is Python's
way of grouping statements. Python does not (yet!) provide an
intelligent input line editing facility, so you have to type a tab or
space(s) for each indented line. In practice you will prepare more
complicated input for Python with a text editor; most text editors have
an auto-indent facility. When a compound statement is entered
interactively, it must be followed by a blank line to indicate
completion (since the parser cannot guess when you have typed the last
line). Note that each line within a basic block must be indented by
the same amount.
\item
The \keyword{print} statement writes the value of the expression(s) it is
given. It differs from just writing the expression you want to write
(as we did earlier in the calculator examples) in the way it handles
multiple expressions and strings. Strings are printed without quotes,
and a space is inserted between items, so you can format things nicely,
like this:
\begin{verbatim}
>>> i = 256*256
>>> print 'The value of i is', i
The value of i is 65536
\end{verbatim}
A trailing comma avoids the newline after the output:
\begin{verbatim}
>>> a, b = 0, 1
>>> while b < 1000:
... print b,
... a, b = b, a+b
...
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
\end{verbatim}
Note that the interpreter inserts a newline before it prints the next
prompt if the last line was not completed.
\end{itemize}
\chapter{More Control Flow Tools \label{moreControl}}
Besides the \keyword{while} statement just introduced, Python knows
the usual control flow statements known from other languages, with
some twists.
\section{\keyword{if} Statements \label{if}}
Perhaps the most well-known statement type is the
\keyword{if} statement. For example:
\begin{verbatim}
>>> x = int(raw_input("Please enter an integer: "))
>>> if x < 0:
... x = 0
... print 'Negative changed to zero'
... elif x == 0:
... print 'Zero'
... elif x == 1:
... print 'Single'
... else:
... print 'More'
...
\end{verbatim}
There can be zero or more \keyword{elif} parts, and the
\keyword{else} part is optional. The keyword `\keyword{elif}' is
short for `else if', and is useful to avoid excessive indentation. An
\keyword{if} \ldots\ \keyword{elif} \ldots\ \keyword{elif} \ldots\ sequence
% Weird spacings happen here if the wrapping of the source text
% gets changed in the wrong way.
is a substitute for the \keyword{switch} or
\keyword{case} statements found in other languages.
\section{\keyword{for} Statements \label{for}}
The \keyword{for}\stindex{for} statement in Python differs a bit from
what you may be used to in C or Pascal. Rather than always
iterating over an arithmetic progression of numbers (like in Pascal),
or giving the user the ability to define both the iteration step and
halting condition (as C), Python's
\keyword{for}\stindex{for} statement iterates over the items of any
sequence (a list or a string), in the order that they appear in
the sequence. For example (no pun intended):
% One suggestion was to give a real C example here, but that may only
% serve to confuse non-C programmers.
\begin{verbatim}
>>> # Measure some strings:
... a = ['cat', 'window', 'defenestrate']
>>> for x in a:
... print x, len(x)
...
cat 3
window 6
defenestrate 12
\end{verbatim}
It is not safe to modify the sequence being iterated over in the loop
(this can only happen for mutable sequence types, such as lists). If
you need to modify the list you are iterating over (for example, to
duplicate selected items) you must iterate over a copy. The slice
notation makes this particularly convenient:
\begin{verbatim}
>>> for x in a[:]: # make a slice copy of the entire list
... if len(x) > 6: a.insert(0, x)
...
>>> a
['defenestrate', 'cat', 'window', 'defenestrate']
\end{verbatim}
\section{The \function{range()} Function \label{range}}
If you do need to iterate over a sequence of numbers, the built-in
function \function{range()} comes in handy. It generates lists
containing arithmetic progressions:
\begin{verbatim}
>>> range(10)
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
\end{verbatim}
The given end point is never part of the generated list;
\code{range(10)} generates a list of 10 values, the legal
indices for items of a sequence of length 10. It is possible to let
the range start at another number, or to specify a different increment
(even negative; sometimes this is called the `step'):
\begin{verbatim}
>>> range(5, 10)
[5, 6, 7, 8, 9]
>>> range(0, 10, 3)
[0, 3, 6, 9]
>>> range(-10, -100, -30)
[-10, -40, -70]
\end{verbatim}
To iterate over the indices of a sequence, combine
\function{range()} and \function{len()} as follows:
\begin{verbatim}
>>> a = ['Mary', 'had', 'a', 'little', 'lamb']
>>> for i in range(len(a)):
... print i, a[i]
...
0 Mary
1 had
2 a
3 little
4 lamb
\end{verbatim}
\section{\keyword{break} and \keyword{continue} Statements, and
\keyword{else} Clauses on Loops
\label{break}}
The \keyword{break} statement, like in C, breaks out of the smallest
enclosing \keyword{for} or \keyword{while} loop.
The \keyword{continue} statement, also borrowed from C, continues
with the next iteration of the loop.
Loop statements may have an \code{else} clause; it is executed when
the loop terminates through exhaustion of the list (with
\keyword{for}) or when the condition becomes false (with
\keyword{while}), but not when the loop is terminated by a
\keyword{break} statement. This is exemplified by the following loop,
which searches for prime numbers:
\begin{verbatim}
>>> for n in range(2, 10):
... for x in range(2, n):
... if n % x == 0:
... print n, 'equals', x, '*', n/x
... break
... else:
... # loop fell through without finding a factor
... print n, 'is a prime number'
...
2 is a prime number
3 is a prime number
4 equals 2 * 2
5 is a prime number
6 equals 2 * 3
7 is a prime number
8 equals 2 * 4
9 equals 3 * 3
\end{verbatim}
\section{\keyword{pass} Statements \label{pass}}
The \keyword{pass} statement does nothing.
It can be used when a statement is required syntactically but the
program requires no action.
For example:
\begin{verbatim}
>>> while True:
... pass # Busy-wait for keyboard interrupt
...
\end{verbatim}
\section{Defining Functions \label{functions}}
We can create a function that writes the Fibonacci series to an
arbitrary boundary:
\begin{verbatim}
>>> def fib(n): # write Fibonacci series up to n
... """Print a Fibonacci series up to n."""
... a, b = 0, 1
... while b < n:
... print b,
... a, b = b, a+b
...
>>> # Now call the function we just defined:
... fib(2000)
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597
\end{verbatim}
The keyword \keyword{def} introduces a function \emph{definition}. It
must be followed by the function name and the parenthesized list of
formal parameters. The statements that form the body of the function
start at the next line, and must be indented. The first statement of
the function body can optionally be a string literal; this string
literal is the function's \index{documentation strings}documentation
string, or \dfn{docstring}.\index{docstrings}\index{strings, documentation}
There are tools which use docstrings to automatically produce online
or printed documentation, or to let the user interactively browse
through code; it's good practice to include docstrings in code that
you write, so try to make a habit of it.
The \emph{execution} of a function introduces a new symbol table used
for the local variables of the function. More precisely, all variable
assignments in a function store the value in the local symbol table;
whereas variable references first look in the local symbol table, then
in the global symbol table, and then in the table of built-in names.
Thus, global variables cannot be directly assigned a value within a
function (unless named in a \keyword{global} statement), although
they may be referenced.
The actual parameters (arguments) to a function call are introduced in
the local symbol table of the called function when it is called; thus,
arguments are passed using \emph{call by value} (where the
\emph{value} is always an object \emph{reference}, not the value of
the object).\footnote{
Actually, \emph{call by object reference} would be a better
description, since if a mutable object is passed, the caller
will see any changes the callee makes to it (items
inserted into a list).
} When a function calls another function, a new local symbol table is
created for that call.
A function definition introduces the function name in the current
symbol table. The value of the function name
has a type that is recognized by the interpreter as a user-defined
function. This value can be assigned to another name which can then
also be used as a function. This serves as a general renaming
mechanism:
\begin{verbatim}
>>> fib
<function fib at 10042ed0>
>>> f = fib
>>> f(100)
1 1 2 3 5 8 13 21 34 55 89
\end{verbatim}
You might object that \code{fib} is not a function but a procedure. In
Python, like in C, procedures are just functions that don't return a
value. In fact, technically speaking, procedures do return a value,
albeit a rather boring one. This value is called \code{None} (it's a
built-in name). Writing the value \code{None} is normally suppressed by
the interpreter if it would be the only value written. You can see it
if you really want to:
\begin{verbatim}
>>> print fib(0)
None
\end{verbatim}
It is simple to write a function that returns a list of the numbers of
the Fibonacci series, instead of printing it:
\begin{verbatim}
>>> def fib2(n): # return Fibonacci series up to n
... """Return a list containing the Fibonacci series up to n."""
... result = []
... a, b = 0, 1
... while b < n:
... result.append(b) # see below
... a, b = b, a+b
... return result
...
>>> f100 = fib2(100) # call it
>>> f100 # write the result
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
\end{verbatim}
This example, as usual, demonstrates some new Python features:
\begin{itemize}
\item
The \keyword{return} statement returns with a value from a function.
\keyword{return} without an expression argument returns \code{None}.
Falling off the end of a procedure also returns \code{None}.
\item
The statement \code{result.append(b)} calls a \emph{method} of the list
object \code{result}. A method is a function that `belongs' to an
object and is named \code{obj.methodname}, where \code{obj} is some
object (this may be an expression), and \code{methodname} is the name
of a method that is defined by the object's type. Different types
define different methods. Methods of different types may have the
same name without causing ambiguity. (It is possible to define your
own object types and methods, using \emph{classes}, as discussed later
in this tutorial.)
The method \method{append()} shown in the example is defined for
list objects; it adds a new element at the end of the list. In this
example it is equivalent to \samp{result = result + [b]}, but more
efficient.
\end{itemize}
\section{More on Defining Functions \label{defining}}
It is also possible to define functions with a variable number of
arguments. There are three forms, which can be combined.
\subsection{Default Argument Values \label{defaultArgs}}
The most useful form is to specify a default value for one or more
arguments. This creates a function that can be called with fewer
arguments than it is defined to allow. For example:
\begin{verbatim}
def ask_ok(prompt, retries=4, complaint='Yes or no, please!'):
while True:
ok = raw_input(prompt)
if ok in ('y', 'ye', 'yes'): return True
if ok in ('n', 'no', 'nop', 'nope'): return False
retries = retries - 1
if retries < 0: raise IOError, 'refusenik user'
print complaint
\end{verbatim}
This function can be called either like this:
\code{ask_ok('Do you really want to quit?')} or like this:
\code{ask_ok('OK to overwrite the file?', 2)}.
This example also introduces the \keyword{in} keyword. This tests
whether or not a sequence contains a certain value.
The default values are evaluated at the point of function definition
in the \emph{defining} scope, so that
\begin{verbatim}
i = 5
def f(arg=i):
print arg
i = 6
f()
\end{verbatim}
will print \code{5}.
\strong{Important warning:} The default value is evaluated only once.
This makes a difference when the default is a mutable object such as a
list, dictionary, or instances of most classes. For example, the
following function accumulates the arguments passed to it on
subsequent calls:
\begin{verbatim}
def f(a, L=[]):
L.append(a)
return L
print f(1)
print f(2)
print f(3)
\end{verbatim}
This will print
\begin{verbatim}
[1]
[1, 2]
[1, 2, 3]
\end{verbatim}
If you don't want the default to be shared between subsequent calls,
you can write the function like this instead:
\begin{verbatim}
def f(a, L=None):
if L is None:
L = []
L.append(a)
return L
\end{verbatim}
\subsection{Keyword Arguments \label{keywordArgs}}
Functions can also be called using
keyword arguments of the form \samp{\var{keyword} = \var{value}}. For
instance, the following function:
\begin{verbatim}
def parrot(voltage, state='a stiff', action='voom', type='Norwegian Blue'):
print "-- This parrot wouldn't", action,
print "if you put", voltage, "volts through it."
print "-- Lovely plumage, the", type
print "-- It's", state, "!"
\end{verbatim}
could be called in any of the following ways:
\begin{verbatim}
parrot(1000)
parrot(action = 'VOOOOOM', voltage = 1000000)
parrot('a thousand', state = 'pushing up the daisies')
parrot('a million', 'bereft of life', 'jump')
\end{verbatim}
but the following calls would all be invalid:
\begin{verbatim}
parrot() # required argument missing
parrot(voltage=5.0, 'dead') # non-keyword argument following keyword
parrot(110, voltage=220) # duplicate value for argument
parrot(actor='John Cleese') # unknown keyword
\end{verbatim}
In general, an argument list must have any positional arguments
followed by any keyword arguments, where the keywords must be chosen
from the formal parameter names. It's not important whether a formal
parameter has a default value or not. No argument may receive a
value more than once --- formal parameter names corresponding to
positional arguments cannot be used as keywords in the same calls.
Here's an example that fails due to this restriction:
\begin{verbatim}
>>> def function(a):
... pass
...
>>> function(0, a=0)
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: function() got multiple values for keyword argument 'a'
\end{verbatim}
When a final formal parameter of the form \code{**\var{name}} is
present, it receives a \ulink{dictionary}{../lib/typesmapping.html}
containing all keyword arguments except for those corresponding to
a formal parameter. This may be
combined with a formal parameter of the form
\code{*\var{name}} (described in the next subsection) which receives a
tuple containing the positional arguments beyond the formal parameter
list. (\code{*\var{name}} must occur before \code{**\var{name}}.)
For example, if we define a function like this:
\begin{verbatim}
def cheeseshop(kind, *arguments, **keywords):
print "-- Do you have any", kind, '?'
print "-- I'm sorry, we're all out of", kind
for arg in arguments: print arg
print '-'*40
keys = keywords.keys()
keys.sort()
for kw in keys: print kw, ':', keywords[kw]
\end{verbatim}
It could be called like this:
\begin{verbatim}
cheeseshop('Limburger', "It's very runny, sir.",
"It's really very, VERY runny, sir.",
client='John Cleese',
shopkeeper='Michael Palin',
sketch='Cheese Shop Sketch')
\end{verbatim}
and of course it would print:
\begin{verbatim}
-- Do you have any Limburger ?
-- I'm sorry, we're all out of Limburger
It's very runny, sir.
It's really very, VERY runny, sir.
----------------------------------------
client : John Cleese
shopkeeper : Michael Palin
sketch : Cheese Shop Sketch
\end{verbatim}
Note that the \method{sort()} method of the list of keyword argument
names is called before printing the contents of the \code{keywords}
dictionary; if this is not done, the order in which the arguments are
printed is undefined.
\subsection{Arbitrary Argument Lists \label{arbitraryArgs}}
Finally, the least frequently used option is to specify that a
function can be called with an arbitrary number of arguments. These
arguments will be wrapped up in a tuple. Before the variable number
of arguments, zero or more normal arguments may occur.
\begin{verbatim}
def fprintf(file, format, *args):
file.write(format % args)
\end{verbatim}
\subsection{Unpacking Argument Lists \label{unpacking-arguments}}
The reverse situation occurs when the arguments are already in a list
or tuple but need to be unpacked for a function call requiring separate
positional arguments. For instance, the built-in \function{range()}
function expects separate \var{start} and \var{stop} arguments. If they
are not available separately, write the function call with the
\code{*}-operator to unpack the arguments out of a list or tuple:
\begin{verbatim}
>>> range(3, 6) # normal call with separate arguments
[3, 4, 5]
>>> args = [3, 6]
>>> range(*args) # call with arguments unpacked from a list
[3, 4, 5]
\end{verbatim}
In the same fashion, dictionaries can deliver keyword arguments with the
\code{**}-operator:
\begin{verbatim}
>>> def parrot(voltage, state='a stiff', action='voom'):
... print "-- This parrot wouldn't", action,
... print "if you put", voltage, "volts through it.",
... print "E's", state, "!"
...
>>> d = {"voltage": "four million", "state": "bleedin' demised", "action": "VOOM"}
>>> parrot(**d)
-- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised !
\end{verbatim}
\subsection{Lambda Forms \label{lambda}}
By popular demand, a few features commonly found in functional
programming languages like Lisp have been added to Python. With the
\keyword{lambda} keyword, small anonymous functions can be created.
Here's a function that returns the sum of its two arguments:
\samp{lambda a, b: a+b}. Lambda forms can be used wherever function
objects are required. They are syntactically restricted to a single
expression. Semantically, they are just syntactic sugar for a normal
function definition. Like nested function definitions, lambda forms
can reference variables from the containing scope:
\begin{verbatim}
>>> def make_incrementor(n):
... return lambda x: x + n
...
>>> f = make_incrementor(42)
>>> f(0)
42
>>> f(1)
43
\end{verbatim}
\subsection{Documentation Strings \label{docstrings}}
There are emerging conventions about the content and formatting of
documentation strings.
\index{docstrings}\index{documentation strings}
\index{strings, documentation}
The first line should always be a short, concise summary of the
object's purpose. For brevity, it should not explicitly state the
object's name or type, since these are available by other means
(except if the name happens to be a verb describing a function's
operation). This line should begin with a capital letter and end with
a period.
If there are more lines in the documentation string, the second line
should be blank, visually separating the summary from the rest of the
description. The following lines should be one or more paragraphs
describing the object's calling conventions, its side effects, etc.
The Python parser does not strip indentation from multi-line string
literals in Python, so tools that process documentation have to strip
indentation if desired. This is done using the following convention.
The first non-blank line \emph{after} the first line of the string
determines the amount of indentation for the entire documentation
string. (We can't use the first line since it is generally adjacent
to the string's opening quotes so its indentation is not apparent in
the string literal.) Whitespace ``equivalent'' to this indentation is
then stripped from the start of all lines of the string. Lines that
are indented less should not occur, but if they occur all their
leading whitespace should be stripped. Equivalence of whitespace
should be tested after expansion of tabs (to 8 spaces, normally).
Here is an example of a multi-line docstring:
\begin{verbatim}
>>> def my_function():
... """Do nothing, but document it.
...
... No, really, it doesn't do anything.
... """
... pass
...
>>> print my_function.__doc__
Do nothing, but document it.
No, really, it doesn't do anything.
\end{verbatim}
\chapter{Data Structures \label{structures}}
This chapter describes some things you've learned about already in
more detail, and adds some new things as well.
\section{More on Lists \label{moreLists}}
The list data type has some more methods. Here are all of the methods
of list objects:
\begin{methoddesc}[list]{append}{x}
Add an item to the end of the list;
equivalent to \code{a[len(a):] = [\var{x}]}.
\end{methoddesc}
\begin{methoddesc}[list]{extend}{L}
Extend the list by appending all the items in the given list;
equivalent to \code{a[len(a):] = \var{L}}.
\end{methoddesc}
\begin{methoddesc}[list]{insert}{i, x}
Insert an item at a given position. The first argument is the index
of the element before which to insert, so \code{a.insert(0, \var{x})}
inserts at the front of the list, and \code{a.insert(len(a), \var{x})}
is equivalent to \code{a.append(\var{x})}.
\end{methoddesc}
\begin{methoddesc}[list]{remove}{x}
Remove the first item from the list whose value is \var{x}.
It is an error if there is no such item.
\end{methoddesc}
\begin{methoddesc}[list]{pop}{\optional{i}}
Remove the item at the given position in the list, and return it. If
no index is specified, \code{a.pop()} removes and returns the last item
in the list. (The square brackets
around the \var{i} in the method signature denote that the parameter
is optional, not that you should type square brackets at that
position. You will see this notation frequently in the
\citetitle[../lib/lib.html]{Python Library Reference}.)
\end{methoddesc}
\begin{methoddesc}[list]{index}{x}
Return the index in the list of the first item whose value is \var{x}.
It is an error if there is no such item.
\end{methoddesc}
\begin{methoddesc}[list]{count}{x}
Return the number of times \var{x} appears in the list.
\end{methoddesc}
\begin{methoddesc}[list]{sort}{}
Sort the items of the list, in place.
\end{methoddesc}
\begin{methoddesc}[list]{reverse}{}
Reverse the elements of the list, in place.
\end{methoddesc}
An example that uses most of the list methods:
\begin{verbatim}
>>> a = [66.25, 333, 333, 1, 1234.5]
>>> print a.count(333), a.count(66.25), a.count('x')
2 1 0
>>> a.insert(2, -1)
>>> a.append(333)
>>> a
[66.25, 333, -1, 333, 1, 1234.5, 333]
>>> a.index(333)
1
>>> a.remove(333)
>>> a
[66.25, -1, 333, 1, 1234.5, 333]
>>> a.reverse()
>>> a
[333, 1234.5, 1, 333, -1, 66.25]
>>> a.sort()
>>> a
[-1, 1, 66.25, 333, 333, 1234.5]
\end{verbatim}
\subsection{Using Lists as Stacks \label{lists-as-stacks}}
\sectionauthor{Ka-Ping Yee}{ping@lfw.org}
The list methods make it very easy to use a list as a stack, where the
last element added is the first element retrieved (``last-in,
first-out''). To add an item to the top of the stack, use
\method{append()}. To retrieve an item from the top of the stack, use
\method{pop()} without an explicit index. For example:
\begin{verbatim}
>>> stack = [3, 4, 5]
>>> stack.append(6)
>>> stack.append(7)
>>> stack
[3, 4, 5, 6, 7]
>>> stack.pop()
7
>>> stack
[3, 4, 5, 6]
>>> stack.pop()
6
>>> stack.pop()
5
>>> stack
[3, 4]
\end{verbatim}
\subsection{Using Lists as Queues \label{lists-as-queues}}
\sectionauthor{Ka-Ping Yee}{ping@lfw.org}
You can also use a list conveniently as a queue, where the first
element added is the first element retrieved (``first-in,
first-out''). To add an item to the back of the queue, use
\method{append()}. To retrieve an item from the front of the queue,
use \method{pop()} with \code{0} as the index. For example:
\begin{verbatim}
>>> queue = ["Eric", "John", "Michael"]
>>> queue.append("Terry") # Terry arrives
>>> queue.append("Graham") # Graham arrives
>>> queue.pop(0)
'Eric'
>>> queue.pop(0)
'John'
>>> queue
['Michael', 'Terry', 'Graham']
\end{verbatim}
\subsection{Functional Programming Tools \label{functional}}
There are three built-in functions that are very useful when used with
lists: \function{filter()}, \function{map()}, and \function{reduce()}.
\samp{filter(\var{function}, \var{sequence})} returns a sequence
consisting of those items from the
sequence for which \code{\var{function}(\var{item})} is true.
If \var{sequence} is a \class{string} or \class{tuple}, the result will
be of the same type; otherwise, it is always a \class{list}.
For example, to compute some primes:
\begin{verbatim}
>>> def f(x): return x % 2 != 0 and x % 3 != 0
...
>>> filter(f, range(2, 25))
[5, 7, 11, 13, 17, 19, 23]
\end{verbatim}
\samp{map(\var{function}, \var{sequence})} calls
\code{\var{function}(\var{item})} for each of the sequence's items and
returns a list of the return values. For example, to compute some
cubes:
\begin{verbatim}
>>> def cube(x): return x*x*x
...
>>> map(cube, range(1, 11))
[1, 8, 27, 64, 125, 216, 343, 512, 729, 1000]
\end{verbatim}
More than one sequence may be passed; the function must then have as
many arguments as there are sequences and is called with the
corresponding item from each sequence (or \code{None} if some sequence
is shorter than another). For example:
\begin{verbatim}
>>> seq = range(8)
>>> def add(x, y): return x+y
...
>>> map(add, seq, seq)
[0, 2, 4, 6, 8, 10, 12, 14]
\end{verbatim}
\samp{reduce(\var{function}, \var{sequence})} returns a single value
constructed by calling the binary function \var{function} on the first two
items of the sequence, then on the result and the next item, and so
on. For example, to compute the sum of the numbers 1 through 10:
\begin{verbatim}
>>> def add(x,y): return x+y
...
>>> reduce(add, range(1, 11))
55
\end{verbatim}
If there's only one item in the sequence, its value is returned; if
the sequence is empty, an exception is raised.
A third argument can be passed to indicate the starting value. In this
case the starting value is returned for an empty sequence, and the
function is first applied to the starting value and the first sequence
item, then to the result and the next item, and so on. For example,
\begin{verbatim}
>>> def sum(seq):
... def add(x,y): return x+y
... return reduce(add, seq, 0)
...
>>> sum(range(1, 11))
55
>>> sum([])
0
\end{verbatim}
Don't use this example's definition of \function{sum()}: since summing
numbers is such a common need, a built-in function
\code{sum(\var{sequence})} is already provided, and works exactly like
this.
\versionadded{2.3}
\subsection{List Comprehensions}
List comprehensions provide a concise way to create lists without resorting
to use of \function{map()}, \function{filter()} and/or \keyword{lambda}.
The resulting list definition tends often to be clearer than lists built
using those constructs. Each list comprehension consists of an expression
followed by a \keyword{for} clause, then zero or more \keyword{for} or
\keyword{if} clauses. The result will be a list resulting from evaluating
the expression in the context of the \keyword{for} and \keyword{if} clauses
which follow it. If the expression would evaluate to a tuple, it must be
parenthesized.
\begin{verbatim}
>>> freshfruit = [' banana', ' loganberry ', 'passion fruit ']
>>> [weapon.strip() for weapon in freshfruit]
['banana', 'loganberry', 'passion fruit']
>>> vec = [2, 4, 6]
>>> [3*x for x in vec]
[6, 12, 18]
>>> [3*x for x in vec if x > 3]
[12, 18]
>>> [3*x for x in vec if x < 2]
[]
>>> [[x,x**2] for x in vec]
[[2, 4], [4, 16], [6, 36]]
>>> [x, x**2 for x in vec] # error - parens required for tuples
File "<stdin>", line 1, in ?
[x, x**2 for x in vec]
^
SyntaxError: invalid syntax
>>> [(x, x**2) for x in vec]
[(2, 4), (4, 16), (6, 36)]
>>> vec1 = [2, 4, 6]
>>> vec2 = [4, 3, -9]
>>> [x*y for x in vec1 for y in vec2]
[8, 6, -18, 16, 12, -36, 24, 18, -54]
>>> [x+y for x in vec1 for y in vec2]
[6, 5, -7, 8, 7, -5, 10, 9, -3]
>>> [vec1[i]*vec2[i] for i in range(len(vec1))]
[8, 12, -54]
\end{verbatim}
List comprehensions are much more flexible than \function{map()} and can be
applied to complex expressions and nested functions:
\begin{verbatim}
>>> [str(round(355/113.0, i)) for i in range(1,6)]
['3.1', '3.14', '3.142', '3.1416', '3.14159']
\end{verbatim}
\section{The \keyword{del} statement \label{del}}
There is a way to remove an item from a list given its index instead
of its value: the \keyword{del} statement. This differs from the
\method{pop()}) method which returns a value. The \keyword{del}
statement can also be used to
remove slices from a list (which we did earlier by assignment of an
empty list to the slice). For example:
\begin{verbatim}
>>> a = [-1, 1, 66.25, 333, 333, 1234.5]
>>> del a[0]
>>> a
[1, 66.25, 333, 333, 1234.5]
>>> del a[2:4]
>>> a
[1, 66.25, 1234.5]
\end{verbatim}
\keyword{del} can also be used to delete entire variables:
\begin{verbatim}
>>> del a
\end{verbatim}
Referencing the name \code{a} hereafter is an error (at least until
another value is assigned to it). We'll find other uses for
\keyword{del} later.
\section{Tuples and Sequences \label{tuples}}
We saw that lists and strings have many common properties, such as
indexing and slicing operations. They are two examples of
\ulink{\emph{sequence} data types}{../lib/typesseq.html}. Since
Python is an evolving language, other sequence data types may be
added. There is also another standard sequence data type: the
\emph{tuple}.
A tuple consists of a number of values separated by commas, for
instance:
\begin{verbatim}
>>> t = 12345, 54321, 'hello!'
>>> t[0]
12345
>>> t
(12345, 54321, 'hello!')
>>> # Tuples may be nested:
... u = t, (1, 2, 3, 4, 5)
>>> u
((12345, 54321, 'hello!'), (1, 2, 3, 4, 5))
\end{verbatim}
As you see, on output tuples are always enclosed in parentheses, so
that nested tuples are interpreted correctly; they may be input with
or without surrounding parentheses, although often parentheses are
necessary anyway (if the tuple is part of a larger expression).
Tuples have many uses. For example: (x, y) coordinate pairs, employee
records from a database, etc. Tuples, like strings, are immutable: it
is not possible to assign to the individual items of a tuple (you can
simulate much of the same effect with slicing and concatenation,
though). It is also possible to create tuples which contain mutable
objects, such as lists.
A special problem is the construction of tuples containing 0 or 1
items: the syntax has some extra quirks to accommodate these. Empty
tuples are constructed by an empty pair of parentheses; a tuple with
one item is constructed by following a value with a comma
(it is not sufficient to enclose a single value in parentheses).
Ugly, but effective. For example:
\begin{verbatim}
>>> empty = ()
>>> singleton = 'hello', # <-- note trailing comma
>>> len(empty)
0
>>> len(singleton)
1
>>> singleton
('hello',)
\end{verbatim}
The statement \code{t = 12345, 54321, 'hello!'} is an example of
\emph{tuple packing}: the values \code{12345}, \code{54321} and
\code{'hello!'} are packed together in a tuple. The reverse operation
is also possible:
\begin{verbatim}
>>> x, y, z = t
\end{verbatim}
This is called, appropriately enough, \emph{sequence unpacking}.
Sequence unpacking requires the list of variables on the left to
have the same number of elements as the length of the sequence. Note
that multiple assignment is really just a combination of tuple packing
and sequence unpacking!
There is a small bit of asymmetry here: packing multiple values
always creates a tuple, and unpacking works for any sequence.
% XXX Add a bit on the difference between tuples and lists.
\section{Sets \label{sets}}
Python also includes a data type for \emph{sets}. A set is an unordered
collection with no duplicate elements. Basic uses include membership
testing and eliminating duplicate entries. Set objects also support
mathematical operations like union, intersection, difference, and
symmetric difference.
Here is a brief demonstration:
\begin{verbatim}
>>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
>>> fruit = set(basket) # create a set without duplicates
>>> fruit
set(['orange', 'pear', 'apple', 'banana'])
>>> 'orange' in fruit # fast membership testing
True
>>> 'crabgrass' in fruit
False
>>> # Demonstrate set operations on unique letters from two words
...
>>> a = set('abracadabra')
>>> b = set('alacazam')
>>> a # unique letters in a
set(['a', 'r', 'b', 'c', 'd'])
>>> a - b # letters in a but not in b
set(['r', 'd', 'b'])
>>> a | b # letters in either a or b
set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l'])
>>> a & b # letters in both a and b
set(['a', 'c'])
>>> a ^ b # letters in a or b but not both
set(['r', 'd', 'b', 'm', 'z', 'l'])
\end{verbatim}
\section{Dictionaries \label{dictionaries}}
Another useful data type built into Python is the
\ulink{\emph{dictionary}}{../lib/typesmapping.html}.
Dictionaries are sometimes found in other languages as ``associative
memories'' or ``associative arrays''. Unlike sequences, which are
indexed by a range of numbers, dictionaries are indexed by \emph{keys},
which can be any immutable type; strings and numbers can always be
keys. Tuples can be used as keys if they contain only strings,
numbers, or tuples; if a tuple contains any mutable object either
directly or indirectly, it cannot be used as a key. You can't use
lists as keys, since lists can be modified in place using
index assignments, slice assignments, or methods like
\method{append()} and \method{extend()}.
It is best to think of a dictionary as an unordered set of
\emph{key: value} pairs, with the requirement that the keys are unique
(within one dictionary).
A pair of braces creates an empty dictionary: \code{\{\}}.
Placing a comma-separated list of key:value pairs within the
braces adds initial key:value pairs to the dictionary; this is also the
way dictionaries are written on output.
The main operations on a dictionary are storing a value with some key
and extracting the value given the key. It is also possible to delete
a key:value pair
with \code{del}.
If you store using a key that is already in use, the old value
associated with that key is forgotten. It is an error to extract a
value using a non-existent key.
The \method{keys()} method of a dictionary object returns a list of all
the keys used in the dictionary, in arbitrary order (if you want it
sorted, just apply the \method{sort()} method to the list of keys). To
check whether a single key is in the dictionary, either use the dictionary's
\method{has_key()} method or the \keyword{in} keyword.
Here is a small example using a dictionary:
\begin{verbatim}
>>> tel = {'jack': 4098, 'sape': 4139}
>>> tel['guido'] = 4127
>>> tel
{'sape': 4139, 'guido': 4127, 'jack': 4098}
>>> tel['jack']
4098
>>> del tel['sape']
>>> tel['irv'] = 4127
>>> tel
{'guido': 4127, 'irv': 4127, 'jack': 4098}
>>> tel.keys()
['guido', 'irv', 'jack']
>>> tel.has_key('guido')
True
>>> 'guido' in tel
True
\end{verbatim}
The \function{dict()} constructor builds dictionaries directly from
lists of key-value pairs stored as tuples. When the pairs form a
pattern, list comprehensions can compactly specify the key-value list.
\begin{verbatim}
>>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)])
{'sape': 4139, 'jack': 4098, 'guido': 4127}
>>> dict([(x, x**2) for x in (2, 4, 6)]) # use a list comprehension
{2: 4, 4: 16, 6: 36}
\end{verbatim}
Later in the tutorial, we will learn about Generator Expressions
which are even better suited for the task of supplying key-values pairs to
the \function{dict()} constructor.
When the keys are simple strings, it is sometimes easier to specify
pairs using keyword arguments:
\begin{verbatim}
>>> dict(sape=4139, guido=4127, jack=4098)
{'sape': 4139, 'jack': 4098, 'guido': 4127}
\end{verbatim}
\section{Looping Techniques \label{loopidioms}}
When looping through dictionaries, the key and corresponding value can
be retrieved at the same time using the \method{iteritems()} method.
\begin{verbatim}
>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
>>> for k, v in knights.iteritems():
... print k, v
...
gallahad the pure
robin the brave
\end{verbatim}
When looping through a sequence, the position index and corresponding
value can be retrieved at the same time using the
\function{enumerate()} function.
\begin{verbatim}
>>> for i, v in enumerate(['tic', 'tac', 'toe']):
... print i, v
...
0 tic
1 tac
2 toe
\end{verbatim}
To loop over two or more sequences at the same time, the entries
can be paired with the \function{zip()} function.
\begin{verbatim}
>>> questions = ['name', 'quest', 'favorite color']
>>> answers = ['lancelot', 'the holy grail', 'blue']
>>> for q, a in zip(questions, answers):
... print 'What is your %s? It is %s.' % (q, a)
...
What is your name? It is lancelot.
What is your quest? It is the holy grail.
What is your favorite color? It is blue.
\end{verbatim}
To loop over a sequence in reverse, first specify the sequence
in a forward direction and then call the \function{reversed()}
function.
\begin{verbatim}
>>> for i in reversed(xrange(1,10,2)):
... print i
...
9
7
5
3
1
\end{verbatim}
To loop over a sequence in sorted order, use the \function{sorted()}
function which returns a new sorted list while leaving the source
unaltered.
\begin{verbatim}
>>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana']
>>> for f in sorted(set(basket)):
... print f
...
apple
banana
orange
pear
\end{verbatim}
\section{More on Conditions \label{conditions}}
The conditions used in \code{while} and \code{if} statements can
contain any operators, not just comparisons.
The comparison operators \code{in} and \code{not in} check whether a value
occurs (does not occur) in a sequence. The operators \code{is} and
\code{is not} compare whether two objects are really the same object; this
only matters for mutable objects like lists. All comparison operators
have the same priority, which is lower than that of all numerical
operators.
Comparisons can be chained. For example, \code{a < b == c} tests
whether \code{a} is less than \code{b} and moreover \code{b} equals
\code{c}.
Comparisons may be combined using the Boolean operators \code{and} and
\code{or}, and the outcome of a comparison (or of any other Boolean
expression) may be negated with \code{not}. These have lower
priorities than comparison operators; between them, \code{not} has
the highest priority and \code{or} the lowest, so that
\code{A and not B or C} is equivalent to \code{(A and (not B)) or C}.
As always, parentheses can be used to express the desired composition.
The Boolean operators \code{and} and \code{or} are so-called
\emph{short-circuit} operators: their arguments are evaluated from
left to right, and evaluation stops as soon as the outcome is
determined. For example, if \code{A} and \code{C} are true but
\code{B} is false, \code{A and B and C} does not evaluate the
expression \code{C}. When used as a general value and not as a
Boolean, the return value of a short-circuit operator is the last
evaluated argument.
It is possible to assign the result of a comparison or other Boolean
expression to a variable. For example,
\begin{verbatim}
>>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance'
>>> non_null = string1 or string2 or string3
>>> non_null
'Trondheim'
\end{verbatim}
Note that in Python, unlike C, assignment cannot occur inside expressions.
C programmers may grumble about this, but it avoids a common class of
problems encountered in C programs: typing \code{=} in an expression when
\code{==} was intended.
\section{Comparing Sequences and Other Types \label{comparing}}
Sequence objects may be compared to other objects with the same
sequence type. The comparison uses \emph{lexicographical} ordering:
first the first two items are compared, and if they differ this
determines the outcome of the comparison; if they are equal, the next
two items are compared, and so on, until either sequence is exhausted.
If two items to be compared are themselves sequences of the same type,
the lexicographical comparison is carried out recursively. If all
items of two sequences compare equal, the sequences are considered
equal. If one sequence is an initial sub-sequence of the other, the
shorter sequence is the smaller (lesser) one. Lexicographical
ordering for strings uses the \ASCII{} ordering for individual
characters. Some examples of comparisons between sequences of the
same type:
\begin{verbatim}
(1, 2, 3) < (1, 2, 4)
[1, 2, 3] < [1, 2, 4]
'ABC' < 'C' < 'Pascal' < 'Python'
(1, 2, 3, 4) < (1, 2, 4)
(1, 2) < (1, 2, -1)
(1, 2, 3) == (1.0, 2.0, 3.0)
(1, 2, ('aa', 'ab')) < (1, 2, ('abc', 'a'), 4)
\end{verbatim}
Note that comparing objects of different types is legal. The outcome
is deterministic but arbitrary: the types are ordered by their name.
Thus, a list is always smaller than a string, a string is always
smaller than a tuple, etc. \footnote{
The rules for comparing objects of different types should
not be relied upon; they may change in a future version of
the language.
} Mixed numeric types are compared according to their numeric value, so
0 equals 0.0, etc.
\chapter{Modules \label{modules}}
If you quit from the Python interpreter and enter it again, the
definitions you have made (functions and variables) are lost.
Therefore, if you want to write a somewhat longer program, you are
better off using a text editor to prepare the input for the interpreter
and running it with that file as input instead. This is known as creating a
\emph{script}. As your program gets longer, you may want to split it
into several files for easier maintenance. You may also want to use a
handy function that you've written in several programs without copying
its definition into each program.
To support this, Python has a way to put definitions in a file and use
them in a script or in an interactive instance of the interpreter.
Such a file is called a \emph{module}; definitions from a module can be
\emph{imported} into other modules or into the \emph{main} module (the
collection of variables that you have access to in a script
executed at the top level
and in calculator mode).
A module is a file containing Python definitions and statements. The
file name is the module name with the suffix \file{.py} appended. Within
a module, the module's name (as a string) is available as the value of
the global variable \code{__name__}. For instance, use your favorite text
editor to create a file called \file{fibo.py} in the current directory
with the following contents:
\begin{verbatim}
# Fibonacci numbers module
def fib(n): # write Fibonacci series up to n
a, b = 0, 1
while b < n:
print b,
a, b = b, a+b
def fib2(n): # return Fibonacci series up to n
result = []
a, b = 0, 1
while b < n:
result.append(b)
a, b = b, a+b
return result
\end{verbatim}
Now enter the Python interpreter and import this module with the
following command:
\begin{verbatim}
>>> import fibo
\end{verbatim}
This does not enter the names of the functions defined in \code{fibo}
directly in the current symbol table; it only enters the module name
\code{fibo} there.
Using the module name you can access the functions:
\begin{verbatim}
>>> fibo.fib(1000)
1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
>>> fibo.fib2(100)
[1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89]
>>> fibo.__name__
'fibo'
\end{verbatim}
If you intend to use a function often you can assign it to a local name:
\begin{verbatim}
>>> fib = fibo.fib
>>> fib(500)
1 1 2 3 5 8 13 21 34 55 89 144 233 377
\end{verbatim}
\section{More on Modules \label{moreModules}}
A module can contain executable statements as well as function
definitions.
These statements are intended to initialize the module.
They are executed only the
\emph{first} time the module is imported somewhere.\footnote{
In fact function definitions are also `statements' that are
`executed'; the execution enters the function name in the
module's global symbol table.
}
Each module has its own private symbol table, which is used as the
global symbol table by all functions defined in the module.
Thus, the author of a module can use global variables in the module
without worrying about accidental clashes with a user's global
variables.
On the other hand, if you know what you are doing you can touch a
module's global variables with the same notation used to refer to its
functions,
\code{modname.itemname}.
Modules can import other modules. It is customary but not required to
place all \keyword{import} statements at the beginning of a module (or
script, for that matter). The imported module names are placed in the
importing module's global symbol table.
There is a variant of the \keyword{import} statement that imports
names from a module directly into the importing module's symbol
table. For example:
\begin{verbatim}
>>> from fibo import fib, fib2
>>> fib(500)
1 1 2 3 5 8 13 21 34 55 89 144 233 377
\end{verbatim}
This does not introduce the module name from which the imports are taken
in the local symbol table (so in the example, \code{fibo} is not
defined).
There is even a variant to import all names that a module defines:
\begin{verbatim}
>>> from fibo import *
>>> fib(500)
1 1 2 3 5 8 13 21 34 55 89 144 233 377
\end{verbatim}
This imports all names except those beginning with an underscore
(\code{_}).
\subsection{The Module Search Path \label{searchPath}}
\indexiii{module}{search}{path}
When a module named \module{spam} is imported, the interpreter searches
for a file named \file{spam.py} in the current directory,
and then in the list of directories specified by
the environment variable \envvar{PYTHONPATH}. This has the same syntax as
the shell variable \envvar{PATH}, that is, a list of
directory names. When \envvar{PYTHONPATH} is not set, or when the file
is not found there, the search continues in an installation-dependent
default path; on \UNIX, this is usually \file{.:/usr/local/lib/python}.
Actually, modules are searched in the list of directories given by the
variable \code{sys.path} which is initialized from the directory
containing the input script (or the current directory),
\envvar{PYTHONPATH} and the installation-dependent default. This allows
Python programs that know what they're doing to modify or replace the
module search path. Note that because the directory containing the
script being run is on the search path, it is important that the
script not have the same name as a standard module, or Python will
attempt to load the script as a module when that module is imported.
This will generally be an error. See section~\ref{standardModules},
``Standard Modules,'' for more information.
\subsection{``Compiled'' Python files}
As an important speed-up of the start-up time for short programs that
use a lot of standard modules, if a file called \file{spam.pyc} exists
in the directory where \file{spam.py} is found, this is assumed to
contain an already-``byte-compiled'' version of the module \module{spam}.
The modification time of the version of \file{spam.py} used to create
\file{spam.pyc} is recorded in \file{spam.pyc}, and the
\file{.pyc} file is ignored if these don't match.
Normally, you don't need to do anything to create the
\file{spam.pyc} file. Whenever \file{spam.py} is successfully
compiled, an attempt is made to write the compiled version to
\file{spam.pyc}. It is not an error if this attempt fails; if for any
reason the file is not written completely, the resulting
\file{spam.pyc} file will be recognized as invalid and thus ignored
later. The contents of the \file{spam.pyc} file are platform
independent, so a Python module directory can be shared by machines of
different architectures.
Some tips for experts:
\begin{itemize}
\item
When the Python interpreter is invoked with the \programopt{-O} flag,
optimized code is generated and stored in \file{.pyo} files. The
optimizer currently doesn't help much; it only removes
\keyword{assert} statements. When \programopt{-O} is used, \emph{all}
bytecode is optimized; \code{.pyc} files are ignored and \code{.py}
files are compiled to optimized bytecode.
\item
Passing two \programopt{-O} flags to the Python interpreter
(\programopt{-OO}) will cause the bytecode compiler to perform
optimizations that could in some rare cases result in malfunctioning
programs. Currently only \code{__doc__} strings are removed from the
bytecode, resulting in more compact \file{.pyo} files. Since some
programs may rely on having these available, you should only use this
option if you know what you're doing.
\item
A program doesn't run any faster when it is read from a \file{.pyc} or
\file{.pyo} file than when it is read from a \file{.py} file; the only
thing that's faster about \file{.pyc} or \file{.pyo} files is the
speed with which they are loaded.
\item
When a script is run by giving its name on the command line, the
bytecode for the script is never written to a \file{.pyc} or
\file{.pyo} file. Thus, the startup time of a script may be reduced
by moving most of its code to a module and having a small bootstrap
script that imports that module. It is also possible to name a
\file{.pyc} or \file{.pyo} file directly on the command line.
\item
It is possible to have a file called \file{spam.pyc} (or
\file{spam.pyo} when \programopt{-O} is used) without a file
\file{spam.py} for the same module. This can be used to distribute a
library of Python code in a form that is moderately hard to reverse
engineer.
\item
The module \ulink{\module{compileall}}{../lib/module-compileall.html}%
{} \refstmodindex{compileall} can create \file{.pyc} files (or
\file{.pyo} files when \programopt{-O} is used) for all modules in a
directory.
\end{itemize}
\section{Standard Modules \label{standardModules}}
Python comes with a library of standard modules, described in a separate
document, the \citetitle[../lib/lib.html]{Python Library Reference}
(``Library Reference'' hereafter). Some modules are built into the
interpreter; these provide access to operations that are not part of
the core of the language but are nevertheless built in, either for
efficiency or to provide access to operating system primitives such as
system calls. The set of such modules is a configuration option which
also depends on the underlying platform For example,
the \module{amoeba} module is only provided on systems that somehow
support Amoeba primitives. One particular module deserves some
attention: \ulink{\module{sys}}{../lib/module-sys.html}%
\refstmodindex{sys}, which is built into every
Python interpreter. The variables \code{sys.ps1} and
\code{sys.ps2} define the strings used as primary and secondary
prompts:
\begin{verbatim}
>>> import sys
>>> sys.ps1
'>>> '
>>> sys.ps2
'... '
>>> sys.ps1 = 'C> '
C> print 'Yuck!'
Yuck!
C>
\end{verbatim}
These two variables are only defined if the interpreter is in
interactive mode.
The variable \code{sys.path} is a list of strings that determines the
interpreter's search path for modules. It is initialized to a default
path taken from the environment variable \envvar{PYTHONPATH}, or from
a built-in default if \envvar{PYTHONPATH} is not set. You can modify
it using standard list operations:
\begin{verbatim}
>>> import sys
>>> sys.path.append('/ufs/guido/lib/python')
\end{verbatim}
\section{The \function{dir()} Function \label{dir}}
The built-in function \function{dir()} is used to find out which names
a module defines. It returns a sorted list of strings:
\begin{verbatim}
>>> import fibo, sys
>>> dir(fibo)
['__name__', 'fib', 'fib2']
>>> dir(sys)
['__displayhook__', '__doc__', '__excepthook__', '__name__', '__stderr__',
'__stdin__', '__stdout__', '_getframe', 'api_version', 'argv',
'builtin_module_names', 'byteorder', 'callstats', 'copyright',
'displayhook', 'exc_clear', 'exc_info', 'exc_type', 'excepthook',
'exec_prefix', 'executable', 'exit', 'getdefaultencoding', 'getdlopenflags',
'getrecursionlimit', 'getrefcount', 'hexversion', 'maxint', 'maxunicode',
'meta_path', 'modules', 'path', 'path_hooks', 'path_importer_cache',
'platform', 'prefix', 'ps1', 'ps2', 'setcheckinterval', 'setdlopenflags',
'setprofile', 'setrecursionlimit', 'settrace', 'stderr', 'stdin', 'stdout',
'version', 'version_info', 'warnoptions']
\end{verbatim}
Without arguments, \function{dir()} lists the names you have defined
currently:
\begin{verbatim}
>>> a = [1, 2, 3, 4, 5]
>>> import fibo
>>> fib = fibo.fib
>>> dir()
['__builtins__', '__doc__', '__file__', '__name__', 'a', 'fib', 'fibo', 'sys']
\end{verbatim}
Note that it lists all types of names: variables, modules, functions, etc.
\function{dir()} does not list the names of built-in functions and
variables. If you want a list of those, they are defined in the
standard module \module{__builtin__}\refbimodindex{__builtin__}:
\begin{verbatim}
>>> import __builtin__
>>> dir(__builtin__)
['ArithmeticError', 'AssertionError', 'AttributeError', 'DeprecationWarning',
'EOFError', 'Ellipsis', 'EnvironmentError', 'Exception', 'False',
'FloatingPointError', 'FutureWarning', 'IOError', 'ImportError',
'IndentationError', 'IndexError', 'KeyError', 'KeyboardInterrupt',
'LookupError', 'MemoryError', 'NameError', 'None', 'NotImplemented',
'NotImplementedError', 'OSError', 'OverflowError', 'OverflowWarning',
'PendingDeprecationWarning', 'ReferenceError', 'RuntimeError',
'RuntimeWarning', 'StandardError', 'StopIteration', 'SyntaxError',
'SyntaxWarning', 'SystemError', 'SystemExit', 'TabError', 'True',
'TypeError', 'UnboundLocalError', 'UnicodeDecodeError',
'UnicodeEncodeError', 'UnicodeError', 'UnicodeTranslateError',
'UserWarning', 'ValueError', 'Warning', 'WindowsError',
'ZeroDivisionError', '_', '__debug__', '__doc__', '__import__',
'__name__', 'abs', 'apply', 'basestring', 'bool', 'buffer',
'callable', 'chr', 'classmethod', 'cmp', 'coerce', 'compile',
'complex', 'copyright', 'credits', 'delattr', 'dict', 'dir', 'divmod',
'enumerate', 'eval', 'execfile', 'exit', 'file', 'filter', 'float',
'frozenset', 'getattr', 'globals', 'hasattr', 'hash', 'help', 'hex',
'id', 'input', 'int', 'intern', 'isinstance', 'issubclass', 'iter',
'len', 'license', 'list', 'locals', 'long', 'map', 'max', 'min',
'object', 'oct', 'open', 'ord', 'pow', 'property', 'quit', 'range',
'raw_input', 'reduce', 'reload', 'repr', 'reversed', 'round', 'set',
'setattr', 'slice', 'sorted', 'staticmethod', 'str', 'sum', 'super',
'tuple', 'type', 'unichr', 'unicode', 'vars', 'xrange', 'zip']
\end{verbatim}
\section{Packages \label{packages}}
Packages are a way of structuring Python's module namespace
by using ``dotted module names''. For example, the module name
\module{A.B} designates a submodule named \samp{B} in a package named
\samp{A}. Just like the use of modules saves the authors of different
modules from having to worry about each other's global variable names,
the use of dotted module names saves the authors of multi-module
packages like NumPy or the Python Imaging Library from having to worry
about each other's module names.
Suppose you want to design a collection of modules (a ``package'') for
the uniform handling of sound files and sound data. There are many
different sound file formats (usually recognized by their extension,
for example: \file{.wav}, \file{.aiff}, \file{.au}), so you may need
to create and maintain a growing collection of modules for the
conversion between the various file formats. There are also many
different operations you might want to perform on sound data (such as
mixing, adding echo, applying an equalizer function, creating an
artificial stereo effect), so in addition you will be writing a
never-ending stream of modules to perform these operations. Here's a
possible structure for your package (expressed in terms of a
hierarchical filesystem):
\begin{verbatim}
Sound/ Top-level package
__init__.py Initialize the sound package
Formats/ Subpackage for file format conversions
__init__.py
wavread.py
wavwrite.py
aiffread.py
aiffwrite.py
auread.py
auwrite.py
...
Effects/ Subpackage for sound effects
__init__.py
echo.py
surround.py
reverse.py
...
Filters/ Subpackage for filters
__init__.py
equalizer.py
vocoder.py
karaoke.py
...
\end{verbatim}
When importing the package, Python searches through the directories
on \code{sys.path} looking for the package subdirectory.
The \file{__init__.py} files are required to make Python treat the
directories as containing packages; this is done to prevent
directories with a common name, such as \samp{string}, from
unintentionally hiding valid modules that occur later on the module
search path. In the simplest case, \file{__init__.py} can just be an
empty file, but it can also execute initialization code for the
package or set the \code{__all__} variable, described later.
Users of the package can import individual modules from the
package, for example:
\begin{verbatim}
import Sound.Effects.echo
\end{verbatim}
This loads the submodule \module{Sound.Effects.echo}. It must be referenced
with its full name.
\begin{verbatim}
Sound.Effects.echo.echofilter(input, output, delay=0.7, atten=4)
\end{verbatim}
An alternative way of importing the submodule is:
\begin{verbatim}
from Sound.Effects import echo
\end{verbatim}
This also loads the submodule \module{echo}, and makes it available without
its package prefix, so it can be used as follows:
\begin{verbatim}
echo.echofilter(input, output, delay=0.7, atten=4)
\end{verbatim}
Yet another variation is to import the desired function or variable directly:
\begin{verbatim}
from Sound.Effects.echo import echofilter
\end{verbatim}
Again, this loads the submodule \module{echo}, but this makes its function
\function{echofilter()} directly available:
\begin{verbatim}
echofilter(input, output, delay=0.7, atten=4)
\end{verbatim}
Note that when using \code{from \var{package} import \var{item}}, the
item can be either a submodule (or subpackage) of the package, or some
other name defined in the package, like a function, class or
variable. The \code{import} statement first tests whether the item is
defined in the package; if not, it assumes it is a module and attempts
to load it. If it fails to find it, an
\exception{ImportError} exception is raised.
Contrarily, when using syntax like \code{import
\var{item.subitem.subsubitem}}, each item except for the last must be
a package; the last item can be a module or a package but can't be a
class or function or variable defined in the previous item.
\subsection{Importing * From a Package \label{pkg-import-star}}
%The \code{__all__} Attribute
\ttindex{__all__}
Now what happens when the user writes \code{from Sound.Effects import
*}? Ideally, one would hope that this somehow goes out to the
filesystem, finds which submodules are present in the package, and
imports them all. Unfortunately, this operation does not work very
well on Mac and Windows platforms, where the filesystem does not
always have accurate information about the case of a filename! On
these platforms, there is no guaranteed way to know whether a file
\file{ECHO.PY} should be imported as a module \module{echo},
\module{Echo} or \module{ECHO}. (For example, Windows 95 has the
annoying practice of showing all file names with a capitalized first
letter.) The DOS 8+3 filename restriction adds another interesting
problem for long module names.
The only solution is for the package author to provide an explicit
index of the package. The import statement uses the following
convention: if a package's \file{__init__.py} code defines a list
named \code{__all__}, it is taken to be the list of module names that
should be imported when \code{from \var{package} import *} is
encountered. It is up to the package author to keep this list
up-to-date when a new version of the package is released. Package
authors may also decide not to support it, if they don't see a use for
importing * from their package. For example, the file
\file{Sounds/Effects/__init__.py} could contain the following code:
\begin{verbatim}
__all__ = ["echo", "surround", "reverse"]
\end{verbatim}
This would mean that \code{from Sound.Effects import *} would
import the three named submodules of the \module{Sound} package.
If \code{__all__} is not defined, the statement \code{from Sound.Effects
import *} does \emph{not} import all submodules from the package
\module{Sound.Effects} into the current namespace; it only ensures that the
package \module{Sound.Effects} has been imported (possibly running any
initialization code in \file{__init__.py}) and then imports whatever names are
defined in the package. This includes any names defined (and
submodules explicitly loaded) by \file{__init__.py}. It also includes any
submodules of the package that were explicitly loaded by previous
import statements. Consider this code:
\begin{verbatim}
import Sound.Effects.echo
import Sound.Effects.surround
from Sound.Effects import *
\end{verbatim}
In this example, the echo and surround modules are imported in the
current namespace because they are defined in the
\module{Sound.Effects} package when the \code{from...import} statement
is executed. (This also works when \code{__all__} is defined.)
Note that in general the practice of importing \code{*} from a module or
package is frowned upon, since it often causes poorly readable code.
However, it is okay to use it to save typing in interactive sessions,
and certain modules are designed to export only names that follow
certain patterns.
Remember, there is nothing wrong with using \code{from Package
import specific_submodule}! In fact, this is the
recommended notation unless the importing module needs to use
submodules with the same name from different packages.
\subsection{Intra-package References}
The submodules often need to refer to each other. For example, the
\module{surround} module might use the \module{echo} module. In fact,
such references
are so common that the \keyword{import} statement first looks in the
containing package before looking in the standard module search path.
Thus, the surround module can simply use \code{import echo} or
\code{from echo import echofilter}. If the imported module is not
found in the current package (the package of which the current module
is a submodule), the \keyword{import} statement looks for a top-level
module with the given name.
When packages are structured into subpackages (as with the
\module{Sound} package in the example), there's no shortcut to refer
to submodules of sibling packages - the full name of the subpackage
must be used. For example, if the module
\module{Sound.Filters.vocoder} needs to use the \module{echo} module
in the \module{Sound.Effects} package, it can use \code{from
Sound.Effects import echo}.
\subsection{Packages in Multiple Directories}
Packages support one more special attribute, \member{__path__}. This
is initialized to be a list containing the name of the directory
holding the package's \file{__init__.py} before the code in that file
is executed. This variable can be modified; doing so affects future
searches for modules and subpackages contained in the package.
While this feature is not often needed, it can be used to extend the
set of modules found in a package.
\chapter{Input and Output \label{io}}
There are several ways to present the output of a program; data can be
printed in a human-readable form, or written to a file for future use.
This chapter will discuss some of the possibilities.
\section{Fancier Output Formatting \label{formatting}}
So far we've encountered two ways of writing values: \emph{expression
statements} and the \keyword{print} statement. (A third way is using
the \method{write()} method of file objects; the standard output file
can be referenced as \code{sys.stdout}. See the Library Reference for
more information on this.)
Often you'll want more control over the formatting of your output than
simply printing space-separated values. There are two ways to format
your output; the first way is to do all the string handling yourself;
using string slicing and concatenation operations you can create any
layout you can imagine. The standard module
\module{string}\refstmodindex{string} contains some useful operations
for padding strings to a given column width; these will be discussed
shortly. The second way is to use the \code{\%} operator with a
string as the left argument. The \code{\%} operator interprets the
left argument much like a \cfunction{sprintf()}-style format
string to be applied to the right argument, and returns the string
resulting from this formatting operation.
One question remains, of course: how do you convert values to strings?
Luckily, Python has ways to convert any value to a string: pass it to
the \function{repr()} or \function{str()} functions. Reverse quotes
(\code{``}) are equivalent to \function{repr()}, but they are no
longer used in modern Python code and will likely not be in future
versions of the language.
The \function{str()} function is meant to return representations of
values which are fairly human-readable, while \function{repr()} is
meant to generate representations which can be read by the interpreter
(or will force a \exception{SyntaxError} if there is not equivalent
syntax). For objects which don't have a particular representation for
human consumption, \function{str()} will return the same value as
\function{repr()}. Many values, such as numbers or structures like
lists and dictionaries, have the same representation using either
function. Strings and floating point numbers, in particular, have two
distinct representations.
Some examples:
\begin{verbatim}
>>> s = 'Hello, world.'
>>> str(s)
'Hello, world.'
>>> repr(s)
"'Hello, world.'"
>>> str(0.1)
'0.1'
>>> repr(0.1)
'0.10000000000000001'
>>> x = 10 * 3.25
>>> y = 200 * 200
>>> s = 'The value of x is ' + repr(x) + ', and y is ' + repr(y) + '...'
>>> print s
The value of x is 32.5, and y is 40000...
>>> # The repr() of a string adds string quotes and backslashes:
... hello = 'hello, world\n'
>>> hellos = repr(hello)
>>> print hellos
'hello, world\n'
>>> # The argument to repr() may be any Python object:
... repr((x, y, ('spam', 'eggs')))
"(32.5, 40000, ('spam', 'eggs'))"
>>> # reverse quotes are convenient in interactive sessions:
... `x, y, ('spam', 'eggs')`
"(32.5, 40000, ('spam', 'eggs'))"
\end{verbatim}
Here are two ways to write a table of squares and cubes:
\begin{verbatim}
>>> for x in range(1, 11):
... print repr(x).rjust(2), repr(x*x).rjust(3),
... # Note trailing comma on previous line
... print repr(x*x*x).rjust(4)
...
1 1 1
2 4 8
3 9 27
4 16 64
5 25 125
6 36 216
7 49 343
8 64 512
9 81 729
10 100 1000
>>> for x in range(1,11):
... print '%2d %3d %4d' % (x, x*x, x*x*x)
...
1 1 1
2 4 8
3 9 27
4 16 64
5 25 125
6 36 216
7 49 343
8 64 512
9 81 729
10 100 1000
\end{verbatim}
(Note that one space between each column was added by the way
\keyword{print} works: it always adds spaces between its arguments.)
This example demonstrates the \method{rjust()} method of string objects,
which right-justifies a string in a field of a given width by padding
it with spaces on the left. There are similar methods
\method{ljust()} and \method{center()}. These
methods do not write anything, they just return a new string. If
the input string is too long, they don't truncate it, but return it
unchanged; this will mess up your column lay-out but that's usually
better than the alternative, which would be lying about a value. (If
you really want truncation you can always add a slice operation, as in
\samp{x.ljust(n)[:n]}.)
There is another method, \method{zfill()}, which pads a
numeric string on the left with zeros. It understands about plus and
minus signs:
\begin{verbatim}
>>> '12'.zfill(5)
'00012'
>>> '-3.14'.zfill(7)
'-003.14'
>>> '3.14159265359'.zfill(5)
'3.14159265359'
\end{verbatim}
Using the \code{\%} operator looks like this:
\begin{verbatim}
>>> import math
>>> print 'The value of PI is approximately %5.3f.' % math.pi
The value of PI is approximately 3.142.
\end{verbatim}
If there is more than one format in the string, you need to pass a
tuple as right operand, as in this example:
\begin{verbatim}
>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 7678}
>>> for name, phone in table.items():
... print '%-10s ==> %10d' % (name, phone)
...
Jack ==> 4098
Dcab ==> 7678
Sjoerd ==> 4127
\end{verbatim}
Most formats work exactly as in C and require that you pass the proper
type; however, if you don't you get an exception, not a core dump.
The \code{\%s} format is more relaxed: if the corresponding argument is
not a string object, it is converted to string using the
\function{str()} built-in function. Using \code{*} to pass the width
or precision in as a separate (integer) argument is supported. The
C formats \code{\%n} and \code{\%p} are not supported.
If you have a really long format string that you don't want to split
up, it would be nice if you could reference the variables to be
formatted by name instead of by position. This can be done by using
form \code{\%(name)format}, as shown here:
\begin{verbatim}
>>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678}
>>> print 'Jack: %(Jack)d; Sjoerd: %(Sjoerd)d; Dcab: %(Dcab)d' % table
Jack: 4098; Sjoerd: 4127; Dcab: 8637678
\end{verbatim}
This is particularly useful in combination with the new built-in
\function{vars()} function, which returns a dictionary containing all
local variables.
\section{Reading and Writing Files \label{files}}
% Opening files
\function{open()}\bifuncindex{open} returns a file
object\obindex{file}, and is most commonly used with two arguments:
\samp{open(\var{filename}, \var{mode})}.
\begin{verbatim}
>>> f=open('/tmp/workfile', 'w')
>>> print f
<open file '/tmp/workfile', mode 'w' at 80a0960>
\end{verbatim}
The first argument is a string containing the filename. The second
argument is another string containing a few characters describing the
way in which the file will be used. \var{mode} can be \code{'r'} when
the file will only be read, \code{'w'} for only writing (an existing
file with the same name will be erased), and \code{'a'} opens the file
for appending; any data written to the file is automatically added to
the end. \code{'r+'} opens the file for both reading and writing.
The \var{mode} argument is optional; \code{'r'} will be assumed if
it's omitted.
On Windows and the Macintosh, \code{'b'} appended to the
mode opens the file in binary mode, so there are also modes like
\code{'rb'}, \code{'wb'}, and \code{'r+b'}. Windows makes a
distinction between text and binary files; the end-of-line characters
in text files are automatically altered slightly when data is read or
written. This behind-the-scenes modification to file data is fine for
\ASCII{} text files, but it'll corrupt binary data like that in \file{JPEG} or
\file{EXE} files. Be very careful to use binary mode when reading and
writing such files.
\subsection{Methods of File Objects \label{fileMethods}}
The rest of the examples in this section will assume that a file
object called \code{f} has already been created.
To read a file's contents, call \code{f.read(\var{size})}, which reads
some quantity of data and returns it as a string. \var{size} is an
optional numeric argument. When \var{size} is omitted or negative,
the entire contents of the file will be read and returned; it's your
problem if the file is twice as large as your machine's memory.
Otherwise, at most \var{size} bytes are read and returned. If the end
of the file has been reached, \code{f.read()} will return an empty
string (\code {""}).
\begin{verbatim}
>>> f.read()
'This is the entire file.\n'
>>> f.read()
''
\end{verbatim}
\code{f.readline()} reads a single line from the file; a newline
character (\code{\e n}) is left at the end of the string, and is only
omitted on the last line of the file if the file doesn't end in a
newline. This makes the return value unambiguous; if
\code{f.readline()} returns an empty string, the end of the file has
been reached, while a blank line is represented by \code{'\e n'}, a
string containing only a single newline.
\begin{verbatim}
>>> f.readline()
'This is the first line of the file.\n'
>>> f.readline()
'Second line of the file\n'
>>> f.readline()
''
\end{verbatim}
\code{f.readlines()} returns a list containing all the lines of data
in the file. If given an optional parameter \var{sizehint}, it reads
that many bytes from the file and enough more to complete a line, and
returns the lines from that. This is often used to allow efficient
reading of a large file by lines, but without having to load the
entire file in memory. Only complete lines will be returned.
\begin{verbatim}
>>> f.readlines()
['This is the first line of the file.\n', 'Second line of the file\n']
\end{verbatim}
An alternate approach to reading lines is to loop over the file object.
This is memory efficient, fast, and leads to simpler code:
\begin{verbatim}
>>> for line in f:
print line,
This is the first line of the file.
Second line of the file
\end{verbatim}
The alternative approach is simpler but does not provide as fine-grained
control. Since the two approaches manage line buffering differently,
they should not be mixed.
\code{f.write(\var{string})} writes the contents of \var{string} to
the file, returning \code{None}.
\begin{verbatim}
>>> f.write('This is a test\n')
\end{verbatim}
To write something other than a string, it needs to be converted to a
string first:
\begin{verbatim}
>>> value = ('the answer', 42)
>>> s = str(value)
>>> f.write(s)
\end{verbatim}
\code{f.tell()} returns an integer giving the file object's current
position in the file, measured in bytes from the beginning of the
file. To change the file object's position, use
\samp{f.seek(\var{offset}, \var{from_what})}. The position is
computed from adding \var{offset} to a reference point; the reference
point is selected by the \var{from_what} argument. A
\var{from_what} value of 0 measures from the beginning of the file, 1
uses the current file position, and 2 uses the end of the file as the
reference point. \var{from_what} can be omitted and defaults to 0,
using the beginning of the file as the reference point.
\begin{verbatim}
>>> f = open('/tmp/workfile', 'r+')
>>> f.write('0123456789abcdef')
>>> f.seek(5) # Go to the 6th byte in the file
>>> f.read(1)
'5'
>>> f.seek(-3, 2) # Go to the 3rd byte before the end
>>> f.read(1)
'd'
\end{verbatim}
When you're done with a file, call \code{f.close()} to close it and
free up any system resources taken up by the open file. After calling
\code{f.close()}, attempts to use the file object will automatically fail.
\begin{verbatim}
>>> f.close()
>>> f.read()
Traceback (most recent call last):
File "<stdin>", line 1, in ?
ValueError: I/O operation on closed file
\end{verbatim}
File objects have some additional methods, such as
\method{isatty()} and \method{truncate()} which are less frequently
used; consult the Library Reference for a complete guide to file
objects.
\subsection{The \module{pickle} Module \label{pickle}}
\refstmodindex{pickle}
Strings can easily be written to and read from a file. Numbers take a
bit more effort, since the \method{read()} method only returns
strings, which will have to be passed to a function like
\function{int()}, which takes a string like \code{'123'} and
returns its numeric value 123. However, when you want to save more
complex data types like lists, dictionaries, or class instances,
things get a lot more complicated.
Rather than have users be constantly writing and debugging code to
save complicated data types, Python provides a standard module called
\ulink{\module{pickle}}{../lib/module-pickle.html}. This is an
amazing module that can take almost
any Python object (even some forms of Python code!), and convert it to
a string representation; this process is called \dfn{pickling}.
Reconstructing the object from the string representation is called
\dfn{unpickling}. Between pickling and unpickling, the string
representing the object may have been stored in a file or data, or
sent over a network connection to some distant machine.
If you have an object \code{x}, and a file object \code{f} that's been
opened for writing, the simplest way to pickle the object takes only
one line of code:
\begin{verbatim}
pickle.dump(x, f)
\end{verbatim}
To unpickle the object again, if \code{f} is a file object which has
been opened for reading:
\begin{verbatim}
x = pickle.load(f)
\end{verbatim}
(There are other variants of this, used when pickling many objects or
when you don't want to write the pickled data to a file; consult the
complete documentation for
\ulink{\module{pickle}}{../lib/module-pickle.html} in the
\citetitle[../lib/]{Python Library Reference}.)
\ulink{\module{pickle}}{../lib/module-pickle.html} is the standard way
to make Python objects which can be stored and reused by other
programs or by a future invocation of the same program; the technical
term for this is a \dfn{persistent} object. Because
\ulink{\module{pickle}}{../lib/module-pickle.html} is so widely used,
many authors who write Python extensions take care to ensure that new
data types such as matrices can be properly pickled and unpickled.
\chapter{Errors and Exceptions \label{errors}}
Until now error messages haven't been more than mentioned, but if you
have tried out the examples you have probably seen some. There are
(at least) two distinguishable kinds of errors:
\emph{syntax errors} and \emph{exceptions}.
\section{Syntax Errors \label{syntaxErrors}}
Syntax errors, also known as parsing errors, are perhaps the most common
kind of complaint you get while you are still learning Python:
\begin{verbatim}
>>> while True print 'Hello world'
File "<stdin>", line 1, in ?
while True print 'Hello world'
^
SyntaxError: invalid syntax
\end{verbatim}
The parser repeats the offending line and displays a little `arrow'
pointing at the earliest point in the line where the error was
detected. The error is caused by (or at least detected at) the token
\emph{preceding} the arrow: in the example, the error is detected at
the keyword \keyword{print}, since a colon (\character{:}) is missing
before it. File name and line number are printed so you know where to
look in case the input came from a script.
\section{Exceptions \label{exceptions}}
Even if a statement or expression is syntactically correct, it may
cause an error when an attempt is made to execute it.
Errors detected during execution are called \emph{exceptions} and are
not unconditionally fatal: you will soon learn how to handle them in
Python programs. Most exceptions are not handled by programs,
however, and result in error messages as shown here:
\begin{verbatim}
>>> 10 * (1/0)
Traceback (most recent call last):
File "<stdin>", line 1, in ?
ZeroDivisionError: integer division or modulo by zero
>>> 4 + spam*3
Traceback (most recent call last):
File "<stdin>", line 1, in ?
NameError: name 'spam' is not defined
>>> '2' + 2
Traceback (most recent call last):
File "<stdin>", line 1, in ?
TypeError: cannot concatenate 'str' and 'int' objects
\end{verbatim}
The last line of the error message indicates what happened.
Exceptions come in different types, and the type is printed as part of
the message: the types in the example are
\exception{ZeroDivisionError}, \exception{NameError} and
\exception{TypeError}.
The string printed as the exception type is the name of the built-in
exception that occurred. This is true for all built-in
exceptions, but need not be true for user-defined exceptions (although
it is a useful convention).
Standard exception names are built-in identifiers (not reserved
keywords).
The rest of the line provides detail based on the type of exception
and what caused it.
The preceding part of the error message shows the context where the
exception happened, in the form of a stack traceback.
In general it contains a stack traceback listing source lines; however,
it will not display lines read from standard input.
The \citetitle[../lib/module-exceptions.html]{Python Library
Reference} lists the built-in exceptions and their meanings.
\section{Handling Exceptions \label{handling}}
It is possible to write programs that handle selected exceptions.
Look at the following example, which asks the user for input until a
valid integer has been entered, but allows the user to interrupt the
program (using \kbd{Control-C} or whatever the operating system
supports); note that a user-generated interruption is signalled by
raising the \exception{KeyboardInterrupt} exception.
\begin{verbatim}
>>> while True:
... try:
... x = int(raw_input("Please enter a number: "))
... break
... except ValueError:
... print "Oops! That was no valid number. Try again..."
...
\end{verbatim}
The \keyword{try} statement works as follows.
\begin{itemize}
\item
First, the \emph{try clause} (the statement(s) between the
\keyword{try} and \keyword{except} keywords) is executed.
\item
If no exception occurs, the \emph{except\ clause} is skipped and
execution of the \keyword{try} statement is finished.
\item
If an exception occurs during execution of the try clause, the rest of
the clause is skipped. Then if its type matches the exception named
after the \keyword{except} keyword, the except clause is executed, and
then execution continues after the \keyword{try} statement.
\item
If an exception occurs which does not match the exception named in the
except clause, it is passed on to outer \keyword{try} statements; if
no handler is found, it is an \emph{unhandled exception} and execution
stops with a message as shown above.
\end{itemize}
A \keyword{try} statement may have more than one except clause, to
specify handlers for different exceptions. At most one handler will
be executed. Handlers only handle exceptions that occur in the
corresponding try clause, not in other handlers of the same
\keyword{try} statement. An except clause may name multiple exceptions
as a parenthesized tuple, for example:
\begin{verbatim}
... except (RuntimeError, TypeError, NameError):
... pass
\end{verbatim}
The last except clause may omit the exception name(s), to serve as a
wildcard. Use this with extreme caution, since it is easy to mask a
real programming error in this way! It can also be used to print an
error message and then re-raise the exception (allowing a caller to
handle the exception as well):
\begin{verbatim}
import sys
try:
f = open('myfile.txt')
s = f.readline()
i = int(s.strip())
except IOError, (errno, strerror):
print "I/O error(%s): %s" % (errno, strerror)
except ValueError:
print "Could not convert data to an integer."
except:
print "Unexpected error:", sys.exc_info()[0]
raise
\end{verbatim}
The \keyword{try} \ldots\ \keyword{except} statement has an optional
\emph{else clause}, which, when present, must follow all except
clauses. It is useful for code that must be executed if the try
clause does not raise an exception. For example:
\begin{verbatim}
for arg in sys.argv[1:]:
try:
f = open(arg, 'r')
except IOError:
print 'cannot open', arg
else:
print arg, 'has', len(f.readlines()), 'lines'
f.close()
\end{verbatim}
The use of the \keyword{else} clause is better than adding additional
code to the \keyword{try} clause because it avoids accidentally
catching an exception that wasn't raised by the code being protected
by the \keyword{try} \ldots\ \keyword{except} statement.
When an exception occurs, it may have an associated value, also known as
the exception's \emph{argument}.
The presence and type of the argument depend on the exception type.
The except clause may specify a variable after the exception name (or tuple).
The variable is bound to an exception instance with the arguments stored
in \code{instance.args}. For convenience, the exception instance
defines \method{__getitem__} and \method{__str__} so the arguments can
be accessed or printed directly without having to reference \code{.args}.
\begin{verbatim}
>>> try:
... raise Exception('spam', 'eggs')
... except Exception, inst:
... print type(inst) # the exception instance
... print inst.args # arguments stored in .args
... print inst # __str__ allows args to printed directly
... x, y = inst # __getitem__ allows args to be unpacked directly
... print 'x =', x
... print 'y =', y
...
<type 'instance'>
('spam', 'eggs')
('spam', 'eggs')
x = spam
y = eggs
\end{verbatim}
If an exception has an argument, it is printed as the last part
(`detail') of the message for unhandled exceptions.
Exception handlers don't just handle exceptions if they occur
immediately in the try clause, but also if they occur inside functions
that are called (even indirectly) in the try clause.
For example:
\begin{verbatim}
>>> def this_fails():
... x = 1/0
...
>>> try:
... this_fails()
... except ZeroDivisionError, detail:
... print 'Handling run-time error:', detail
...
Handling run-time error: integer division or modulo by zero
\end{verbatim}
\section{Raising Exceptions \label{raising}}
The \keyword{raise} statement allows the programmer to force a
specified exception to occur.
For example:
\begin{verbatim}
>>> raise NameError, 'HiThere'
Traceback (most recent call last):
File "<stdin>", line 1, in ?
NameError: HiThere
\end{verbatim}
The first argument to \keyword{raise} names the exception to be
raised. The optional second argument specifies the exception's
argument. Alternatively, the above could be written as
\code{raise NameError('HiThere')}. Either form works fine, but there
seems to be a growing stylistic preference for the latter.
If you need to determine whether an exception was raised but don't
intend to handle it, a simpler form of the \keyword{raise} statement
allows you to re-raise the exception:
\begin{verbatim}
>>> try:
... raise NameError, 'HiThere'
... except NameError:
... print 'An exception flew by!'
... raise
...
An exception flew by!
Traceback (most recent call last):
File "<stdin>", line 2, in ?
NameError: HiThere
\end{verbatim}
\section{User-defined Exceptions \label{userExceptions}}
Programs may name their own exceptions by creating a new exception
class. Exceptions should typically be derived from the
\exception{Exception} class, either directly or indirectly. For
example:
\begin{verbatim}
>>> class MyError(Exception):
... def __init__(self, value):
... self.value = value
... def __str__(self):
... return repr(self.value)
...
>>> try:
... raise MyError(2*2)
... except MyError, e:
... print 'My exception occurred, value:', e.value
...
My exception occurred, value: 4
>>> raise MyError, 'oops!'
Traceback (most recent call last):
File "<stdin>", line 1, in ?
__main__.MyError: 'oops!'
\end{verbatim}
In this example, the default \method{__init__} of \class{Exception}
has been overridden. The new behavior simply creates the \var{value}
attribute. This replaces the default behavior of creating the
\var{args} attribute.
Exception classes can be defined which do anything any other class can
do, but are usually kept simple, often only offering a number of
attributes that allow information about the error to be extracted by
handlers for the exception. When creating a module that can raise
several distinct errors, a common practice is to create a base class
for exceptions defined by that module, and subclass that to create
specific exception classes for different error conditions:
\begin{verbatim}
class Error(Exception):
"""Base class for exceptions in this module."""
pass
class InputError(Error):
"""Exception raised for errors in the input.
Attributes:
expression -- input expression in which the error occurred
message -- explanation of the error
"""
def __init__(self, expression, message):
self.expression = expression
self.message = message
class TransitionError(Error):
"""Raised when an operation attempts a state transition that's not
allowed.
Attributes:
previous -- state at beginning of transition
next -- attempted new state
message -- explanation of why the specific transition is not allowed
"""
def __init__(self, previous, next, message):
self.previous = previous
self.next = next
self.message = message
\end{verbatim}
Most exceptions are defined with names that end in ``Error,'' similar
to the naming of the standard exceptions.
Many standard modules define their own exceptions to report errors
that may occur in functions they define. More information on classes
is presented in chapter \ref{classes}, ``Classes.''
\section{Defining Clean-up Actions \label{cleanup}}
The \keyword{try} statement has another optional clause which is
intended to define clean-up actions that must be executed under all
circumstances. For example:
\begin{verbatim}
>>> try:
... raise KeyboardInterrupt
... finally:
... print 'Goodbye, world!'
...
Goodbye, world!
Traceback (most recent call last):
File "<stdin>", line 2, in ?
KeyboardInterrupt
\end{verbatim}
A \emph{finally clause} is executed whether or not an exception has
occurred in the try clause. When an exception has occurred, it is
re-raised after the finally clause is executed. The finally clause is
also executed ``on the way out'' when the \keyword{try} statement is
left via a \keyword{break} or \keyword{return} statement.
The code in the finally clause is useful for releasing external
resources (such as files or network connections), regardless of
whether the use of the resource was successful.
A \keyword{try} statement must either have one or more except clauses
or one finally clause, but not both (because it would be unclear which
clause should be executed first).
\chapter{Classes \label{classes}}
Python's class mechanism adds classes to the language with a minimum
of new syntax and semantics. It is a mixture of the class mechanisms
found in \Cpp{} and Modula-3. As is true for modules, classes in Python
do not put an absolute barrier between definition and user, but rather
rely on the politeness of the user not to ``break into the
definition.'' The most important features of classes are retained
with full power, however: the class inheritance mechanism allows
multiple base classes, a derived class can override any methods of its
base class or classes, and a method can call the method of a base class with the
same name. Objects can contain an arbitrary amount of private data.
In \Cpp{} terminology, all class members (including the data members) are
\emph{public}, and all member functions are \emph{virtual}. There are
no special constructors or destructors. As in Modula-3, there are no
shorthands for referencing the object's members from its methods: the
method function is declared with an explicit first argument
representing the object, which is provided implicitly by the call. As
in Smalltalk, classes themselves are objects, albeit in the wider
sense of the word: in Python, all data types are objects. This
provides semantics for importing and renaming. Unlike
\Cpp{} and Modula-3, built-in types can be used as base classes for
extension by the user. Also, like in \Cpp{} but unlike in Modula-3, most
built-in operators with special syntax (arithmetic operators,
subscripting etc.) can be redefined for class instances.
\section{A Word About Terminology \label{terminology}}
Lacking universally accepted terminology to talk about classes, I will
make occasional use of Smalltalk and \Cpp{} terms. (I would use Modula-3
terms, since its object-oriented semantics are closer to those of
Python than \Cpp, but I expect that few readers have heard of it.)
Objects have individuality, and multiple names (in multiple scopes)
can be bound to the same object. This is known as aliasing in other
languages. This is usually not appreciated on a first glance at
Python, and can be safely ignored when dealing with immutable basic
types (numbers, strings, tuples). However, aliasing has an
(intended!) effect on the semantics of Python code involving mutable
objects such as lists, dictionaries, and most types representing
entities outside the program (files, windows, etc.). This is usually
used to the benefit of the program, since aliases behave like pointers
in some respects. For example, passing an object is cheap since only
a pointer is passed by the implementation; and if a function modifies
an object passed as an argument, the caller will see the change --- this
eliminates the need for two different argument passing mechanisms as in
Pascal.
\section{Python Scopes and Name Spaces \label{scopes}}
Before introducing classes, I first have to tell you something about
Python's scope rules. Class definitions play some neat tricks with
namespaces, and you need to know how scopes and namespaces work to
fully understand what's going on. Incidentally, knowledge about this
subject is useful for any advanced Python programmer.
Let's begin with some definitions.
A \emph{namespace} is a mapping from names to objects. Most
namespaces are currently implemented as Python dictionaries, but
that's normally not noticeable in any way (except for performance),
and it may change in the future. Examples of namespaces are: the set
of built-in names (functions such as \function{abs()}, and built-in
exception names); the global names in a module; and the local names in
a function invocation. In a sense the set of attributes of an object
also form a namespace. The important thing to know about namespaces
is that there is absolutely no relation between names in different
namespaces; for instance, two different modules may both define a
function ``maximize'' without confusion --- users of the modules must
prefix it with the module name.
By the way, I use the word \emph{attribute} for any name following a
dot --- for example, in the expression \code{z.real}, \code{real} is
an attribute of the object \code{z}. Strictly speaking, references to
names in modules are attribute references: in the expression
\code{modname.funcname}, \code{modname} is a module object and
\code{funcname} is an attribute of it. In this case there happens to
be a straightforward mapping between the module's attributes and the
global names defined in the module: they share the same namespace!
\footnote{
Except for one thing. Module objects have a secret read-only
attribute called \member{__dict__} which returns the dictionary
used to implement the module's namespace; the name
\member{__dict__} is an attribute but not a global name.
Obviously, using this violates the abstraction of namespace
implementation, and should be restricted to things like
post-mortem debuggers.
}
Attributes may be read-only or writable. In the latter case,
assignment to attributes is possible. Module attributes are writable:
you can write \samp{modname.the_answer = 42}. Writable attributes may
also be deleted with the \keyword{del} statement. For example,
\samp{del modname.the_answer} will remove the attribute
\member{the_answer} from the object named by \code{modname}.
Name spaces are created at different moments and have different
lifetimes. The namespace containing the built-in names is created
when the Python interpreter starts up, and is never deleted. The
global namespace for a module is created when the module definition
is read in; normally, module namespaces also last until the
interpreter quits. The statements executed by the top-level
invocation of the interpreter, either read from a script file or
interactively, are considered part of a module called
\module{__main__}, so they have their own global namespace. (The
built-in names actually also live in a module; this is called
\module{__builtin__}.)
The local namespace for a function is created when the function is
called, and deleted when the function returns or raises an exception
that is not handled within the function. (Actually, forgetting would
be a better way to describe what actually happens.) Of course,
recursive invocations each have their own local namespace.
A \emph{scope} is a textual region of a Python program where a
namespace is directly accessible. ``Directly accessible'' here means
that an unqualified reference to a name attempts to find the name in
the namespace.
Although scopes are determined statically, they are used dynamically.
At any time during execution, there are at least three nested scopes whose
namespaces are directly accessible: the innermost scope, which is searched
first, contains the local names; the namespaces of any enclosing
functions, which are searched starting with the nearest enclosing scope;
the middle scope, searched next, contains the current module's global names;
and the outermost scope (searched last) is the namespace containing built-in
names.
If a name is declared global, then all references and assignments go
directly to the middle scope containing the module's global names.
Otherwise, all variables found outside of the innermost scope are read-only
(an attempt to write to such a variable will simply create a \emph{new}
local variable in the innermost scope, leaving the identically named
outer variable unchanged).
Usually, the local scope references the local names of the (textually)
current function. Outside functions, the local scope references
the same namespace as the global scope: the module's namespace.
Class definitions place yet another namespace in the local scope.
It is important to realize that scopes are determined textually: the
global scope of a function defined in a module is that module's
namespace, no matter from where or by what alias the function is
called. On the other hand, the actual search for names is done
dynamically, at run time --- however, the language definition is
evolving towards static name resolution, at ``compile'' time, so don't
rely on dynamic name resolution! (In fact, local variables are
already determined statically.)
A special quirk of Python is that assignments always go into the
innermost scope. Assignments do not copy data --- they just
bind names to objects. The same is true for deletions: the statement
\samp{del x} removes the binding of \code{x} from the namespace
referenced by the local scope. In fact, all operations that introduce
new names use the local scope: in particular, import statements and
function definitions bind the module or function name in the local
scope. (The \keyword{global} statement can be used to indicate that
particular variables live in the global scope.)
\section{A First Look at Classes \label{firstClasses}}
Classes introduce a little bit of new syntax, three new object types,
and some new semantics.
\subsection{Class Definition Syntax \label{classDefinition}}
The simplest form of class definition looks like this:
\begin{verbatim}
class ClassName:
<statement-1>
.
.
.
<statement-N>
\end{verbatim}
Class definitions, like function definitions
(\keyword{def} statements) must be executed before they have any
effect. (You could conceivably place a class definition in a branch
of an \keyword{if} statement, or inside a function.)
In practice, the statements inside a class definition will usually be
function definitions, but other statements are allowed, and sometimes
useful --- we'll come back to this later. The function definitions
inside a class normally have a peculiar form of argument list,
dictated by the calling conventions for methods --- again, this is
explained later.
When a class definition is entered, a new namespace is created, and
used as the local scope --- thus, all assignments to local variables
go into this new namespace. In particular, function definitions bind
the name of the new function here.
When a class definition is left normally (via the end), a \emph{class
object} is created. This is basically a wrapper around the contents
of the namespace created by the class definition; we'll learn more
about class objects in the next section. The original local scope
(the one in effect just before the class definition was entered) is
reinstated, and the class object is bound here to the class name given
in the class definition header (\class{ClassName} in the example).
\subsection{Class Objects \label{classObjects}}
Class objects support two kinds of operations: attribute references
and instantiation.
\emph{Attribute references} use the standard syntax used for all
attribute references in Python: \code{obj.name}. Valid attribute
names are all the names that were in the class's namespace when the
class object was created. So, if the class definition looked like
this:
\begin{verbatim}
class MyClass:
"A simple example class"
i = 12345
def f(self):
return 'hello world'
\end{verbatim}
then \code{MyClass.i} and \code{MyClass.f} are valid attribute
references, returning an integer and a function object, respectively.
Class attributes can also be assigned to, so you can change the value
of \code{MyClass.i} by assignment. \member{__doc__} is also a valid
attribute, returning the docstring belonging to the class: \code{"A
simple example class"}.
Class \emph{instantiation} uses function notation. Just pretend that
the class object is a parameterless function that returns a new
instance of the class. For example (assuming the above class):
\begin{verbatim}
x = MyClass()
\end{verbatim}
creates a new \emph{instance} of the class and assigns this object to
the local variable \code{x}.
The instantiation operation (``calling'' a class object) creates an
empty object. Many classes like to create objects with instances
customized to a specific initial state.
Therefore a class may define a special method named
\method{__init__()}, like this:
\begin{verbatim}
def __init__(self):
self.data = []
\end{verbatim}
When a class defines an \method{__init__()} method, class
instantiation automatically invokes \method{__init__()} for the
newly-created class instance. So in this example, a new, initialized
instance can be obtained by:
\begin{verbatim}
x = MyClass()
\end{verbatim}
Of course, the \method{__init__()} method may have arguments for
greater flexibility. In that case, arguments given to the class
instantiation operator are passed on to \method{__init__()}. For
example,
\begin{verbatim}
>>> class Complex:
... def __init__(self, realpart, imagpart):
... self.r = realpart
... self.i = imagpart
...
>>> x = Complex(3.0, -4.5)
>>> x.r, x.i
(3.0, -4.5)
\end{verbatim}
\subsection{Instance Objects \label{instanceObjects}}
Now what can we do with instance objects? The only operations
understood by instance objects are attribute references. There are
two kinds of valid attribute names, data attributes and methods.
\emph{data attributes} correspond to
``instance variables'' in Smalltalk, and to ``data members'' in
\Cpp. Data attributes need not be declared; like local variables,
they spring into existence when they are first assigned to. For
example, if \code{x} is the instance of \class{MyClass} created above,
the following piece of code will print the value \code{16}, without
leaving a trace:
\begin{verbatim}
x.counter = 1
while x.counter < 10:
x.counter = x.counter * 2
print x.counter
del x.counter
\end{verbatim}
The other kind of instance attribute reference is a \emph{method}.
A method is a function that ``belongs to'' an
object. (In Python, the term method is not unique to class instances:
other object types can have methods as well. For example, list objects have
methods called append, insert, remove, sort, and so on. However,
in the following discussion, we'll use the term method exclusively to mean
methods of class instance objects, unless explicitly stated otherwise.)
Valid method names of an instance object depend on its class. By
definition, all attributes of a class that are function
objects define corresponding methods of its instances. So in our
example, \code{x.f} is a valid method reference, since
\code{MyClass.f} is a function, but \code{x.i} is not, since
\code{MyClass.i} is not. But \code{x.f} is not the same thing as
\code{MyClass.f} --- it is a \obindex{method}\emph{method object}, not
a function object.
\subsection{Method Objects \label{methodObjects}}
Usually, a method is called right after it is bound:
\begin{verbatim}
x.f()
\end{verbatim}
In the \class{MyClass} example, this will return the string \code{'hello world'}.
However, it is not necessary to call a method right away:
\code{x.f} is a method object, and can be stored away and called at a
later time. For example:
\begin{verbatim}
xf = x.f
while True:
print xf()
\end{verbatim}
will continue to print \samp{hello world} until the end of time.
What exactly happens when a method is called? You may have noticed
that \code{x.f()} was called without an argument above, even though
the function definition for \method{f} specified an argument. What
happened to the argument? Surely Python raises an exception when a
function that requires an argument is called without any --- even if
the argument isn't actually used...
Actually, you may have guessed the answer: the special thing about
methods is that the object is passed as the first argument of the
function. In our example, the call \code{x.f()} is exactly equivalent
to \code{MyClass.f(x)}. In general, calling a method with a list of
\var{n} arguments is equivalent to calling the corresponding function
with an argument list that is created by inserting the method's object
before the first argument.
If you still don't understand how methods work, a look at the
implementation can perhaps clarify matters. When an instance
attribute is referenced that isn't a data attribute, its class is
searched. If the name denotes a valid class attribute that is a
function object, a method object is created by packing (pointers to)
the instance object and the function object just found together in an
abstract object: this is the method object. When the method object is
called with an argument list, it is unpacked again, a new argument
list is constructed from the instance object and the original argument
list, and the function object is called with this new argument list.
\section{Random Remarks \label{remarks}}
% [These should perhaps be placed more carefully...]
Data attributes override method attributes with the same name; to
avoid accidental name conflicts, which may cause hard-to-find bugs in
large programs, it is wise to use some kind of convention that
minimizes the chance of conflicts. Possible conventions include
capitalizing method names, prefixing data attribute names with a small
unique string (perhaps just an underscore), or using verbs for methods
and nouns for data attributes.
Data attributes may be referenced by methods as well as by ordinary
users (``clients'') of an object. In other words, classes are not
usable to implement pure abstract data types. In fact, nothing in
Python makes it possible to enforce data hiding --- it is all based
upon convention. (On the other hand, the Python implementation,
written in C, can completely hide implementation details and control
access to an object if necessary; this can be used by extensions to
Python written in C.)
Clients should use data attributes with care --- clients may mess up
invariants maintained by the methods by stamping on their data
attributes. Note that clients may add data attributes of their own to
an instance object without affecting the validity of the methods, as
long as name conflicts are avoided --- again, a naming convention can
save a lot of headaches here.
There is no shorthand for referencing data attributes (or other
methods!) from within methods. I find that this actually increases
the readability of methods: there is no chance of confusing local
variables and instance variables when glancing through a method.
Often, the first argument of a method is called
\code{self}. This is nothing more than a convention: the name
\code{self} has absolutely no special meaning to Python. (Note,
however, that by not following the convention your code may be less
readable to other Python programmers, and it is also conceivable that
a \emph{class browser} program might be written that relies upon such a
convention.)
Any function object that is a class attribute defines a method for
instances of that class. It is not necessary that the function
definition is textually enclosed in the class definition: assigning a
function object to a local variable in the class is also ok. For
example:
\begin{verbatim}
# Function defined outside the class
def f1(self, x, y):
return min(x, x+y)
class C:
f = f1
def g(self):
return 'hello world'
h = g
\end{verbatim}
Now \code{f}, \code{g} and \code{h} are all attributes of class
\class{C} that refer to function objects, and consequently they are all
methods of instances of \class{C} --- \code{h} being exactly equivalent
to \code{g}. Note that this practice usually only serves to confuse
the reader of a program.
Methods may call other methods by using method attributes of the
\code{self} argument:
\begin{verbatim}
class Bag:
def __init__(self):
self.data = []
def add(self, x):
self.data.append(x)
def addtwice(self, x):
self.add(x)
self.add(x)
\end{verbatim}
Methods may reference global names in the same way as ordinary
functions. The global scope associated with a method is the module
containing the class definition. (The class itself is never used as a
global scope!) While one rarely encounters a good reason for using
global data in a method, there are many legitimate uses of the global
scope: for one thing, functions and modules imported into the global
scope can be used by methods, as well as functions and classes defined
in it. Usually, the class containing the method is itself defined in
this global scope, and in the next section we'll find some good
reasons why a method would want to reference its own class!
\section{Inheritance \label{inheritance}}
Of course, a language feature would not be worthy of the name ``class''
without supporting inheritance. The syntax for a derived class
definition looks like this:
\begin{verbatim}
class DerivedClassName(BaseClassName):
<statement-1>
.
.
.
<statement-N>
\end{verbatim}
The name \class{BaseClassName} must be defined in a scope containing
the derived class definition. In place of a base class name, other
arbitrary expressions are also allowed. This can be useful, for
example, when the base class is defined in another module:
\begin{verbatim}
class DerivedClassName(modname.BaseClassName):
\end{verbatim}
Execution of a derived class definition proceeds the same as for a
base class. When the class object is constructed, the base class is
remembered. This is used for resolving attribute references: if a
requested attribute is not found in the class, the search proceeds to look in the
base class. This rule is applied recursively if the base class itself
is derived from some other class.
There's nothing special about instantiation of derived classes:
\code{DerivedClassName()} creates a new instance of the class. Method
references are resolved as follows: the corresponding class attribute
is searched, descending down the chain of base classes if necessary,
and the method reference is valid if this yields a function object.
Derived classes may override methods of their base classes. Because
methods have no special privileges when calling other methods of the
same object, a method of a base class that calls another method
defined in the same base class may end up calling a method of
a derived class that overrides it. (For \Cpp{} programmers: all methods
in Python are effectively \keyword{virtual}.)
An overriding method in a derived class may in fact want to extend
rather than simply replace the base class method of the same name.
There is a simple way to call the base class method directly: just
call \samp{BaseClassName.methodname(self, arguments)}. This is
occasionally useful to clients as well. (Note that this only works if
the base class is defined or imported directly in the global scope.)
\subsection{Multiple Inheritance \label{multiple}}
Python supports a limited form of multiple inheritance as well. A
class definition with multiple base classes looks like this:
\begin{verbatim}
class DerivedClassName(Base1, Base2, Base3):
<statement-1>
.
.
.
<statement-N>
\end{verbatim}
The only rule necessary to explain the semantics is the resolution
rule used for class attribute references. This is depth-first,
left-to-right. Thus, if an attribute is not found in
\class{DerivedClassName}, it is searched in \class{Base1}, then
(recursively) in the base classes of \class{Base1}, and only if it is
not found there, it is searched in \class{Base2}, and so on.
(To some people breadth first --- searching \class{Base2} and
\class{Base3} before the base classes of \class{Base1} --- looks more
natural. However, this would require you to know whether a particular
attribute of \class{Base1} is actually defined in \class{Base1} or in
one of its base classes before you can figure out the consequences of
a name conflict with an attribute of \class{Base2}. The depth-first
rule makes no differences between direct and inherited attributes of
\class{Base1}.)
It is clear that indiscriminate use of multiple inheritance is a
maintenance nightmare, given the reliance in Python on conventions to
avoid accidental name conflicts. A well-known problem with multiple
inheritance is a class derived from two classes that happen to have a
common base class. While it is easy enough to figure out what happens
in this case (the instance will have a single copy of ``instance
variables'' or data attributes used by the common base class), it is
not clear that these semantics are in any way useful.
%% XXX Add rules for new-style MRO?
\section{Private Variables \label{private}}
There is limited support for class-private
identifiers. Any identifier of the form \code{__spam} (at least two
leading underscores, at most one trailing underscore) is textually
replaced with \code{_classname__spam}, where \code{classname} is the
current class name with leading underscore(s) stripped. This mangling
is done without regard to the syntactic position of the identifier, so
it can be used to define class-private instance and class variables,
methods, variables stored in globals, and even variables stored in instances.
private to this class on instances of \emph{other} classes. Truncation
may occur when the mangled name would be longer than 255 characters.
Outside classes, or when the class name consists of only underscores,
no mangling occurs.
Name mangling is intended to give classes an easy way to define
``private'' instance variables and methods, without having to worry
about instance variables defined by derived classes, or mucking with
instance variables by code outside the class. Note that the mangling
rules are designed mostly to avoid accidents; it still is possible for
a determined soul to access or modify a variable that is considered
private. This can even be useful in special circumstances, such as in
the debugger, and that's one reason why this loophole is not closed.
(Buglet: derivation of a class with the same name as the base class
makes use of private variables of the base class possible.)
Notice that code passed to \code{exec}, \code{eval()} or
\code{evalfile()} does not consider the classname of the invoking
class to be the current class; this is similar to the effect of the
\code{global} statement, the effect of which is likewise restricted to
code that is byte-compiled together. The same restriction applies to
\code{getattr()}, \code{setattr()} and \code{delattr()}, as well as
when referencing \code{__dict__} directly.
\section{Odds and Ends \label{odds}}
Sometimes it is useful to have a data type similar to the Pascal
``record'' or C ``struct'', bundling together a few named data
items. An empty class definition will do nicely:
\begin{verbatim}
class Employee:
pass
john = Employee() # Create an empty employee record
# Fill the fields of the record
john.name = 'John Doe'
john.dept = 'computer lab'
john.salary = 1000
\end{verbatim}
A piece of Python code that expects a particular abstract data type
can often be passed a class that emulates the methods of that data
type instead. For instance, if you have a function that formats some
data from a file object, you can define a class with methods
\method{read()} and \method{readline()} that get the data from a string
buffer instead, and pass it as an argument.% (Unfortunately, this
%technique has its limitations: a class can't define operations that
%are accessed by special syntax such as sequence subscripting or
%arithmetic operators, and assigning such a ``pseudo-file'' to
%\code{sys.stdin} will not cause the interpreter to read further input
%from it.)
Instance method objects have attributes, too: \code{m.im_self} is the
instance object with the method \method{m}, and \code{m.im_func} is the
function object corresponding to the method.
\section{Exceptions Are Classes Too\label{exceptionClasses}}
User-defined exceptions are identified by classes as well. Using this
mechanism it is possible to create extensible hierarchies of exceptions.
There are two new valid (semantic) forms for the raise statement:
\begin{verbatim}
raise Class, instance
raise instance
\end{verbatim}
In the first form, \code{instance} must be an instance of
\class{Class} or of a class derived from it. The second form is a
shorthand for:
\begin{verbatim}
raise instance.__class__, instance
\end{verbatim}
A class in an except clause is compatible with an exception if it is the same
class or a base class thereof (but not the other way around --- an
except clause listing a derived class is not compatible with a base
class). For example, the following code will print B, C, D in that
order:
\begin{verbatim}
class B:
pass
class C(B):
pass
class D(C):
pass
for c in [B, C, D]:
try:
raise c()
except D:
print "D"
except C:
print "C"
except B:
print "B"
\end{verbatim}
Note that if the except clauses were reversed (with
\samp{except B} first), it would have printed B, B, B --- the first
matching except clause is triggered.
When an error message is printed for an unhandled exception, the
exception's class name is printed, then a colon and a space, and
finally the instance converted to a string using the built-in function
\function{str()}.
\section{Iterators\label{iterators}}
By now you have probably noticed that most container objects can be looped
over using a \keyword{for} statement:
\begin{verbatim}
for element in [1, 2, 3]:
print element
for element in (1, 2, 3):
print element
for key in {'one':1, 'two':2}:
print key
for char in "123":
print char
for line in open("myfile.txt"):
print line
\end{verbatim}
This style of access is clear, concise, and convenient. The use of iterators
pervades and unifies Python. Behind the scenes, the \keyword{for}
statement calls \function{iter()} on the container object. The
function returns an iterator object that defines the method
\method{next()} which accesses elements in the container one at a
time. When there are no more elements, \method{next()} raises a
\exception{StopIteration} exception which tells the \keyword{for} loop
to terminate. This example shows how it all works:
\begin{verbatim}
>>> s = 'abc'
>>> it = iter(s)
>>> it
<iterator object at 0x00A1DB50>
>>> it.next()
'a'
>>> it.next()
'b'
>>> it.next()
'c'
>>> it.next()
Traceback (most recent call last):
File "<stdin>", line 1, in ?
it.next()
StopIteration
\end{verbatim}
Having seen the mechanics behind the iterator protocol, it is easy to add
iterator behavior to your classes. Define a \method{__iter__()} method
which returns an object with a \method{next()} method. If the class defines
\method{next()}, then \method{__iter__()} can just return \code{self}:
\begin{verbatim}
class Reverse:
"Iterator for looping over a sequence backwards"
def __init__(self, data):
self.data = data
self.index = len(data)
def __iter__(self):
return self
def next(self):
if self.index == 0:
raise StopIteration
self.index = self.index - 1
return self.data[self.index]
>>> for char in Reverse('spam'):
... print char
...
m
a
p
s
\end{verbatim}
\section{Generators\label{generators}}
Generators are a simple and powerful tool for creating iterators. They are
written like regular functions but use the \keyword{yield} statement whenever
they want to return data. Each time \method{next()} is called, the
generator resumes where it left-off (it remembers all the data values and
which statement was last executed). An example shows that generators can
be trivially easy to create:
\begin{verbatim}
def reverse(data):
for index in range(len(data)-1, -1, -1):
yield data[index]
>>> for char in reverse('golf'):
... print char
...
f
l
o
g
\end{verbatim}
Anything that can be done with generators can also be done with class based
iterators as described in the previous section. What makes generators so
compact is that the \method{__iter__()} and \method{next()} methods are
created automatically.
Another key feature is that the local variables and execution state
are automatically saved between calls. This made the function easier to write
and much more clear than an approach using instance variables like
\code{self.index} and \code{self.data}.
In addition to automatic method creation and saving program state, when
generators terminate, they automatically raise \exception{StopIteration}.
In combination, these features make it easy to create iterators with no
more effort than writing a regular function.
\section{Generator Expressions\label{genexps}}
Some simple generators can be coded succinctly as expressions using a syntax
similar to list comprehensions but with parentheses instead of brackets. These
expressions are designed for situations where the generator is used right
away by an enclosing function. Generator expressions are more compact but
less versatile than full generator definitions and tend to be more memory
friendly than equivalent list comprehensions.
Examples:
\begin{verbatim}
>>> sum(i*i for i in range(10)) # sum of squares
285
>>> xvec = [10, 20, 30]
>>> yvec = [7, 5, 3]
>>> sum(x*y for x,y in zip(xvec, yvec)) # dot product
260
>>> from math import pi, sin
>>> sine_table = dict((x, sin(x*pi/180)) for x in range(0, 91))
>>> unique_words = set(word for line in page for word in line.split())
>>> valedictorian = max((student.gpa, student.name) for student in graduates)
>>> data = 'golf'
>>> list(data[i] for i in range(len(data)-1,-1,-1))
['f', 'l', 'o', 'g']
\end{verbatim}
\chapter{Brief Tour of the Standard Library \label{briefTour}}
\section{Operating System Interface\label{os-interface}}
The \ulink{\module{os}}{../lib/module-os.html}
module provides dozens of functions for interacting with the
operating system:
\begin{verbatim}
>>> import os
>>> os.system('time 0:02')
0
>>> os.getcwd() # Return the current working directory
'C:\\Python24'
>>> os.chdir('/server/accesslogs')
\end{verbatim}
Be sure to use the \samp{import os} style instead of
\samp{from os import *}. This will keep \function{os.open()} from
shadowing the builtin \function{open()} function which operates much
differently.
\bifuncindex{help}
The builtin \function{dir()} and \function{help()} functions are useful
as interactive aids for working with large modules like \module{os}:
\begin{verbatim}
>>> import os
>>> dir(os)
<returns a list of all module functions>
>>> help(os)
<returns an extensive manual page created from the module's docstrings>
\end{verbatim}
For daily file and directory management tasks, the
\ulink{\module{shutil}}{../lib/module-shutil.html}
module provides a higher level interface that is easier to use:
\begin{verbatim}
>>> import shutil
>>> shutil.copyfile('data.db', 'archive.db')
>>> shutil.move('/build/executables', 'installdir')
\end{verbatim}
\section{File Wildcards\label{file-wildcards}}
The \ulink{\module{glob}}{../lib/module-glob.html}
module provides a function for making file lists from directory
wildcard searches:
\begin{verbatim}
>>> import glob
>>> glob.glob('*.py')
['primes.py', 'random.py', 'quote.py']
\end{verbatim}
\section{Command Line Arguments\label{command-line-arguments}}
Common utility scripts often need to process command line arguments.
These arguments are stored in the
\ulink{\module{sys}}{../lib/module-sys.html}\ module's \var{argv}
attribute as a list. For instance the following output results from
running \samp{python demo.py one two three} at the command line:
\begin{verbatim}
>>> import sys
>>> print sys.argv
['demo.py', 'one', 'two', 'three']
\end{verbatim}
The \ulink{\module{getopt}}{../lib/module-getopt.html}
module processes \var{sys.argv} using the conventions of the \UNIX{}
\function{getopt()} function. More powerful and flexible command line
processing is provided by the
\ulink{\module{optparse}}{../lib/module-optparse.html} module.
\section{Error Output Redirection and Program Termination\label{stderr}}
The \ulink{\module{sys}}{../lib/module-sys.html}
module also has attributes for \var{stdin}, \var{stdout}, and
\var{stderr}. The latter is useful for emitting warnings and error
messages to make them visible even when \var{stdout} has been redirected:
\begin{verbatim}
>>> sys.stderr.write('Warning, log file not found starting a new one\n')
Warning, log file not found starting a new one
\end{verbatim}
The most direct way to terminate a script is to use \samp{sys.exit()}.
\section{String Pattern Matching\label{string-pattern-matching}}
The \ulink{\module{re}}{../lib/module-re.html}
module provides regular expression tools for advanced string processing.
For complex matching and manipulation, regular expressions offer succinct,
optimized solutions:
\begin{verbatim}
>>> import re
>>> re.findall(r'\bf[a-z]*', 'which foot or hand fell fastest')
['foot', 'fell', 'fastest']
>>> re.sub(r'(\b[a-z]+) \1', r'\1', 'cat in the the hat')
'cat in the hat'
\end{verbatim}
When only simple capabilities are needed, string methods are preferred
because they are easier to read and debug:
\begin{verbatim}
>>> 'tea for too'.replace('too', 'two')
'tea for two'
\end{verbatim}
\section{Mathematics\label{mathematics}}
The \ulink{\module{math}}{../lib/module-math.html} module gives
access to the underlying C library functions for floating point math:
\begin{verbatim}
>>> import math
>>> math.cos(math.pi / 4.0)
0.70710678118654757
>>> math.log(1024, 2)
10.0
\end{verbatim}
The \ulink{\module{random}}{../lib/module-random.html}
module provides tools for making random selections:
\begin{verbatim}
>>> import random
>>> random.choice(['apple', 'pear', 'banana'])
'apple'
>>> random.sample(xrange(100), 10) # sampling without replacement
[30, 83, 16, 4, 8, 81, 41, 50, 18, 33]
>>> random.random() # random float
0.17970987693706186
>>> random.randrange(6) # random integer chosen from range(6)
4
\end{verbatim}
\section{Internet Access\label{internet-access}}
There are a number of modules for accessing the internet and processing
internet protocols. Two of the simplest are
\ulink{\module{urllib2}}{../lib/module-urllib2.html}
for retrieving data from urls and
\ulink{\module{smtplib}}{../lib/module-smtplib.html}
for sending mail:
\begin{verbatim}
>>> import urllib2
>>> for line in urllib2.urlopen('http://tycho.usno.navy.mil/cgi-bin/timer.pl'):
... if 'EST' in line: # look for Eastern Standard Time
... print line
<BR>Nov. 25, 09:43:32 PM EST
>>> import smtplib
>>> server = smtplib.SMTP('localhost')
>>> server.sendmail('soothsayer@example.org', 'jcaesar@example.org',
"""To: jcaesar@example.org
From: soothsayer@example.org
Beware the Ides of March.
""")
>>> server.quit()
\end{verbatim}
\section{Dates and Times\label{dates-and-times}}
The \ulink{\module{datetime}}{../lib/module-datetime.html} module
supplies classes for manipulating dates and times in both simple
and complex ways. While date and time arithmetic is supported, the
focus of the implementation is on efficient member extraction for
output formatting and manipulation. The module also supports objects
that are timezone aware.
\begin{verbatim}
# dates are easily constructed and formatted
>>> from datetime import date
>>> now = date.today()
>>> now
datetime.date(2003, 12, 2)
>>> now.strftime("%m-%d-%y. %d %b %Y is a %A on the %d day of %B.")
'12-02-03. 02 Dec 2003 is a Tuesday on the 02 day of December.'
# dates support calendar arithmetic
>>> birthday = date(1964, 7, 31)
>>> age = now - birthday
>>> age.days
14368
\end{verbatim}
\section{Data Compression\label{data-compression}}
Common data archiving and compression formats are directly supported
by modules including:
\ulink{\module{zlib}}{../lib/module-zlib.html},
\ulink{\module{gzip}}{../lib/module-gzip.html},
\ulink{\module{bz2}}{../lib/module-bz2.html},
\ulink{\module{zipfile}}{../lib/module-zipfile.html}, and
\ulink{\module{tarfile}}{../lib/module-tarfile.html}.
\begin{verbatim}
>>> import zlib
>>> s = 'witch which has which witches wrist watch'
>>> len(s)
41
>>> t = zlib.compress(s)
>>> len(t)
37
>>> zlib.decompress(t)
'witch which has which witches wrist watch'
>>> zlib.crc32(s)
226805979
\end{verbatim}
\section{Performance Measurement\label{performance-measurement}}
Some Python users develop a deep interest in knowing the relative
performance of different approaches to the same problem.
Python provides a measurement tool that answers those questions
immediately.
For example, it may be tempting to use the tuple packing and unpacking
feature instead of the traditional approach to swapping arguments.
The \ulink{\module{timeit}}{../lib/module-timeit.html} module
quickly demonstrates a modest performance advantage:
\begin{verbatim}
>>> from timeit import Timer
>>> Timer('t=a; a=b; b=t', 'a=1; b=2').timeit()
0.57535828626024577
>>> Timer('a,b = b,a', 'a=1; b=2').timeit()
0.54962537085770791
\end{verbatim}
In contrast to \module{timeit}'s fine level of granularity, the
\ulink{\module{profile}}{../lib/module-profile.html} and \module{pstats}
modules provide tools for identifying time critical sections in larger blocks
of code.
\section{Quality Control\label{quality-control}}
One approach for developing high quality software is to write tests for
each function as it is developed and to run those tests frequently during
the development process.
The \ulink{\module{doctest}}{../lib/module-doctest.html} module provides
a tool for scanning a module and validating tests embedded in a program's
docstrings. Test construction is as simple as cutting-and-pasting a
typical call along with its results into the docstring. This improves
the documentation by providing the user with an example and it allows the
doctest module to make sure the code remains true to the documentation:
\begin{verbatim}
def average(values):
"""Computes the arithmetic mean of a list of numbers.
>>> print average([20, 30, 70])
40.0
"""
return sum(values, 0.0) / len(values)
import doctest
doctest.testmod() # automatically validate the embedded tests
\end{verbatim}
The \ulink{\module{unittest}}{../lib/module-unittest.html} module is not
as effortless as the \module{doctest} module, but it allows a more
comprehensive set of tests to be maintained in a separate file:
\begin{verbatim}
import unittest
class TestStatisticalFunctions(unittest.TestCase):
def test_average(self):
self.assertEqual(average([20, 30, 70]), 40.0)
self.assertEqual(round(average([1, 5, 7]), 1), 4.3)
self.assertRaises(ZeroDivisionError, average, [])
self.assertRaises(TypeError, average, 20, 30, 70)
unittest.main() # Calling from the command line invokes all tests
\end{verbatim}
\section{Batteries Included\label{batteries-included}}
Python has a ``batteries included'' philosophy. This is best seen
through the sophisticated and robust capabilities of its larger
packages. For example:
\begin{itemize}
\item The \ulink{\module{xmlrpclib}}{../lib/module-xmlrpclib.html} and
\ulink{\module{SimpleXMLRPCServer}}{../lib/module-SimpleXMLRPCServer.html}
modules make implementing remote procedure calls into an almost trivial task.
Despite the modules names, no direct knowledge or handling of XML is needed.
\item The \ulink{\module{email}}{../lib/module-email.html} package is a library
for managing email messages, including MIME and other RFC 2822-based message
documents. Unlike \module{smtplib} and \module{poplib} which actually send
and receive messages, the email package has a complete toolset for building
or decoding complex message structures (including attachments) and for
implementing internet encoding and header protocols.
\item The \ulink{\module{xml.dom}}{../lib/module-xml.dom.html} and
\ulink{\module{xml.sax}}{../lib/module-xml.sax.html} packages provide robust
support for parsing this popular data interchange format. Likewise, the
\ulink{\module{csv}}{../lib/module-csv.html} module supports direct reads and
writes in a common database format. Together, these modules and packages
greatly simplify data interchange between python applications and other
tools.
\item Internationalization is supported by a number of modules including
\ulink{\module{gettext}}{../lib/module-gettext.html},
\ulink{\module{locale}}{../lib/module-locale.html}, and the
\ulink{\module{codecs}}{../lib/module-codecs.html} package.
\end{itemize}
\chapter{Brief Tour of the Standard Library -- Part II\label{briefTourTwo}}
This second tour covers more advanced modules that support professional
programming needs. These modules rarely occur in small scripts.
\section{Output Formatting\label{output-formatting}}
The \ulink{\module{repr}}{../lib/module-repr.html} module provides a
version of \function{repr()} customized for abbreviated displays of large
or deeply nested containers:
\begin{verbatim}
>>> import repr
>>> repr.repr(set('supercalifragilisticexpialidocious'))
"set(['a', 'c', 'd', 'e', 'f', 'g', ...])"
\end{verbatim}
The \ulink{\module{pprint}}{../lib/module-pprint.html} module offers
more sophisticated control over printing both built-in and user defined
objects in a way that is readable by the interpreter. When the result
is longer than one line, the ``pretty printer'' adds line breaks and
indentation to more clearly reveal data structure:
\begin{verbatim}
>>> import pprint
>>> t = [[[['black', 'cyan'], 'white', ['green', 'red']], [['magenta',
... 'yellow'], 'blue']]]
...
>>> pprint.pprint(t, width=30)
[[[['black', 'cyan'],
'white',
['green', 'red']],
[['magenta', 'yellow'],
'blue']]]
\end{verbatim}
The \ulink{\module{textwrap}}{../lib/module-textwrap.html} module
formats paragraphs of text to fit a given screen width:
\begin{verbatim}
>>> import textwrap
>>> doc = """The wrap() method is just like fill() except that it returns
... a list of strings instead of one big string with newlines to separate
... the wrapped lines."""
...
>>> print textwrap.fill(doc, width=40)
The wrap() method is just like fill()
except that it returns a list of strings
instead of one big string with newlines
to separate the wrapped lines.
\end{verbatim}
The \ulink{\module{locale}}{../lib/module-locale.html} module accesses
a database of culture specific data formats. The grouping attribute
of locale's format function provides a direct way of formatting numbers
with group separators:
\begin{verbatim}
>>> import locale
>>> locale.setlocale(locale.LC_ALL, 'English_United States.1252')
'English_United States.1252'
>>> conv = locale.localeconv() # get a mapping of conventions
>>> x = 1234567.8
>>> locale.format("%d", x, grouping=True)
'1,234,567'
>>> locale.format("%s%.*f", (conv['currency_symbol'],
... conv['frac_digits'], x), grouping=True)
'$1,234,567.80'
\end{verbatim}
\section{Templating\label{templating}}
The \ulink{\module{string}}{../lib/module-string.html} module includes a
versatile \class{Template} class with a simplified syntax suitable for
editing by end-users. This allows users to customize their applications
without having to alter the application.
The format uses placeholder names formed by \samp{\$} with valid Python
identifiers (alphanumeric characters and underscores). Surrounding the
placeholder with braces allows it to be followed by more alphanumeric letters
with no intervening spaces. Writing \samp{\$\$} creates a single escaped
\samp{\$}:
\begin{verbatim}
>>> from string import Template
>>> t = Template('${village}folk send $$10 to $cause.')
>>> t.substitute(village='Nottingham', cause='the ditch fund')
'Nottinghamfolk send $10 to the ditch fund.'
\end{verbatim}
The \method{substitute} method raises a \exception{KeyError} when a
placeholder is not supplied in a dictionary or a keyword argument. For
mail-merge style applications, user supplied data may be incomplete and the
\method{safe_substitute} method may be more appropriate --- it will leave
placeholders unchanged if data is missing:
\begin{verbatim}
>>> t = Template('Return the $item to $owner.')
>>> d = dict(item='unladen swallow')
>>> t.substitute(d)
Traceback (most recent call last):
. . .
KeyError: 'owner'
>>> t.safe_substitute(d)
'Return the unladen swallow to $owner.'
\end{verbatim}
Template subclasses can specify a custom delimiter. For example, a batch
renaming utility for a photo browser may elect to use percent signs for
placeholders such as the current date, image sequence number, or file format:
\begin{verbatim}
>>> import time, os.path
>>> photofiles = ['img_1074.jpg', 'img_1076.jpg', 'img_1077.jpg']
>>> class BatchRename(Template):
... delimiter = '%'
>>> fmt = raw_input('Enter rename style (%d-date %n-seqnum %f-format): ')
Enter rename style (%d-date %n-seqnum %f-format): Ashley_%n%f
>>> t = BatchRename(fmt)
>>> date = time.strftime('%d%b%y')
>>> for i, filename in enumerate(photofiles):
... base, ext = os.path.splitext(filename)
... newname = t.substitute(d=date, n=i, f=ext)
... print '%s --> %s' % (filename, newname)
img_1074.jpg --> Ashley_0.jpg
img_1076.jpg --> Ashley_1.jpg
img_1077.jpg --> Ashley_2.jpg
\end{verbatim}
Another application for templating is separating program logic from the
details of multiple output formats. This makes it possible to substitute
custom templates for XML files, plain text reports, and HTML web reports.
\section{Working with Binary Data Record Layouts\label{binary-formats}}
The \ulink{\module{struct}}{../lib/module-struct.html} module provides
\function{pack()} and \function{unpack()} functions for working with
variable length binary record formats. The following example shows how
to loop through header information in a ZIP file (with pack codes
\code{"H"} and \code{"L"} representing two and four byte unsigned
numbers respectively):
\begin{verbatim}
import struct
data = open('myfile.zip', 'rb').read()
start = 0
for i in range(3): # show the first 3 file headers
start += 14
fields = struct.unpack('LLLHH', data[start:start+16])
crc32, comp_size, uncomp_size, filenamesize, extra_size = fields
start += 16
filename = data[start:start+filenamesize]
start += filenamesize
extra = data[start:start+extra_size]
print filename, hex(crc32), comp_size, uncomp_size
start += extra_size + comp_size # skip to the next header
\end{verbatim}
\section{Multi-threading\label{multi-threading}}
Threading is a technique for decoupling tasks which are not sequentially
dependent. Threads can be used to improve the responsiveness of
applications that accept user input while other tasks run in the
background. A related use case is running I/O in parallel with
computations in another thread.
The following code shows how the high level
\ulink{\module{threading}}{../lib/module-threading.html} module can run
tasks in background while the main program continues to run:
\begin{verbatim}
import threading, zipfile
class AsyncZip(threading.Thread):
def __init__(self, infile, outfile):
threading.Thread.__init__(self)
self.infile = infile
self.outfile = outfile
def run(self):
f = zipfile.ZipFile(self.outfile, 'w', zipfile.ZIP_DEFLATED)
f.write(self.infile)
f.close()
print 'Finished background zip of: ', self.infile
background = AsyncZip('mydata.txt', 'myarchive.zip')
background.start()
print 'The main program continues to run in foreground.'
background.join() # Wait for the background task to finish
print 'Main program waited until background was done.'
\end{verbatim}
The principal challenge of multi-threaded applications is coordinating
threads that share data or other resources. To that end, the threading
module provides a number of synchronization primitives including locks,
events, condition variables, and semaphores.
While those tools are powerful, minor design errors can result in
problems that are difficult to reproduce. So, the preferred approach
to task coordination is to concentrate all access to a resource
in a single thread and then use the
\ulink{\module{Queue}}{../lib/module-Queue.html} module to feed that
thread with requests from other threads. Applications using
\class{Queue} objects for inter-thread communication and coordination
are easier to design, more readable, and more reliable.
\section{Logging\label{logging}}
The \ulink{\module{logging}}{../lib/module-logging.html} module offers
a full featured and flexible logging system. At its simplest, log
messages are sent to a file or to \code{sys.stderr}:
\begin{verbatim}
import logging
logging.debug('Debugging information')
logging.info('Informational message')
logging.warning('Warning:config file %s not found', 'server.conf')
logging.error('Error occurred')
logging.critical('Critical error -- shutting down')
\end{verbatim}
This produces the following output:
\begin{verbatim}
WARNING:root:Warning:config file server.conf not found
ERROR:root:Error occurred
CRITICAL:root:Critical error -- shutting down
\end{verbatim}
By default, informational and debugging messages are suppressed and the
output is sent to standard error. Other output options include routing
messages through email, datagrams, sockets, or to an HTTP Server. New
filters can select different routing based on message priority:
\constant{DEBUG}, \constant{INFO}, \constant{WARNING}, \constant{ERROR},
and \constant{CRITICAL}.
The logging system can be configured directly from Python or can be
loaded from a user editable configuration file for customized logging
without altering the application.
\section{Weak References\label{weak-references}}
Python does automatic memory management (reference counting for most
objects and garbage collection to eliminate cycles). The memory is
freed shortly after the last reference to it has been eliminated.
This approach works fine for most applications but occasionally there
is a need to track objects only as long as they are being used by
something else. Unfortunately, just tracking them creates a reference
that makes them permanent. The
\ulink{\module{weakref}}{../lib/module-weakref.html} module provides
tools for tracking objects without creating a reference. When the
object is no longer needed, it is automatically removed from a weakref
table and a callback is triggered for weakref objects. Typical
applications include caching objects that are expensive to create:
\begin{verbatim}
>>> import weakref, gc
>>> class A:
... def __init__(self, value):
... self.value = value
... def __repr__(self):
... return str(self.value)
...
>>> a = A(10) # create a reference
>>> d = weakref.WeakValueDictionary()
>>> d['primary'] = a # does not create a reference
>>> d['primary'] # fetch the object if it is still alive
10
>>> del a # remove the one reference
>>> gc.collect() # run garbage collection right away
0
>>> d['primary'] # entry was automatically removed
Traceback (most recent call last):
File "<pyshell#108>", line 1, in -toplevel-
d['primary'] # entry was automatically removed
File "C:/PY24/lib/weakref.py", line 46, in __getitem__
o = self.data[key]()
KeyError: 'primary'
\end{verbatim}
\section{Tools for Working with Lists\label{list-tools}}
Many data structure needs can be met with the built-in list type.
However, sometimes there is a need for alternative implementations
with different performance trade-offs.
The \ulink{\module{array}}{../lib/module-array.html} module provides an
\class{array()} object that is like a list that stores only homogenous
data and stores it more compactly. The following example shows an array
of numbers stored as two byte unsigned binary numbers (typecode
\code{"H"}) rather than the usual 16 bytes per entry for regular lists
of python int objects:
\begin{verbatim}
>>> from array import array
>>> a = array('H', [4000, 10, 700, 22222])
>>> sum(a)
26932
>>> a[1:3]
array('H', [10, 700])
\end{verbatim}
The \ulink{\module{collections}}{../lib/module-collections.html} module
provides a \class{deque()} object that is like a list with faster
appends and pops from the left side but slower lookups in the middle.
These objects are well suited for implementing queues and breadth first
tree searches:
\begin{verbatim}
>>> from collections import deque
>>> d = deque(["task1", "task2", "task3"])
>>> d.append("task4")
>>> print "Handling", d.popleft()
Handling task1
unsearched = deque([starting_node])
def breadth_first_search(unsearched):
node = unsearched.popleft()
for m in gen_moves(node):
if is_goal(m):
return m
unsearched.append(m)
\end{verbatim}
In addition to alternative list implementations, the library also offers
other tools such as the \ulink{\module{bisect}}{../lib/module-bisect.html}
module with functions for manipulating sorted lists:
\begin{verbatim}
>>> import bisect
>>> scores = [(100, 'perl'), (200, 'tcl'), (400, 'lua'), (500, 'python')]
>>> bisect.insort(scores, (300, 'ruby'))
>>> scores
[(100, 'perl'), (200, 'tcl'), (300, 'ruby'), (400, 'lua'), (500, 'python')]
\end{verbatim}
The \ulink{\module{heapq}}{../lib/module-heapq.html} module provides
functions for implementing heaps based on regular lists. The lowest
valued entry is always kept at position zero. This is useful for
applications which repeatedly access the smallest element but do not
want to run a full list sort:
\begin{verbatim}
>>> from heapq import heapify, heappop, heappush
>>> data = [1, 3, 5, 7, 9, 2, 4, 6, 8, 0]
>>> heapify(data) # rearrange the list into heap order
>>> heappush(data, -5) # add a new entry
>>> [heappop(data) for i in range(3)] # fetch the three smallest entries
[-5, 0, 1]
\end{verbatim}
\section{Decimal Floating Point Arithmetic\label{decimal-fp}}
The \ulink{\module{decimal}}{../lib/module-decimal.html} module offers a
\class{Decimal} datatype for decimal floating point arithmetic. Compared to
the built-in \class{float} implementation of binary floating point, the new
class is especially helpful for financial applications and other uses which
require exact decimal representation, control over precision, control over
rounding to meet legal or regulatory requirements, tracking of significant
decimal places, or for applications where the user expects the results to
match calculations done by hand.
For example, calculating a 5\%{} tax on a 70 cent phone charge gives
different results in decimal floating point and binary floating point.
The difference becomes significant if the results are rounded to the
nearest cent:
\begin{verbatim}
>>> from decimal import *
>>> Decimal('0.70') * Decimal('1.05')
Decimal("0.7350")
>>> .70 * 1.05
0.73499999999999999
\end{verbatim}
The \class{Decimal} result keeps a trailing zero, automatically inferring four
place significance from multiplicands with two place significance. Decimal reproduces
mathematics as done by hand and avoids issues that can arise when binary
floating point cannot exactly represent decimal quantities.
Exact representation enables the \class{Decimal} class to perform
modulo calculations and equality tests that are unsuitable for binary
floating point:
\begin{verbatim}
>>> Decimal('1.00') % Decimal('.10')
Decimal("0.00")
>>> 1.00 % 0.10
0.09999999999999995
>>> sum([Decimal('0.1')]*10) == Decimal('1.0')
True
>>> sum([0.1]*10) == 1.0
False
\end{verbatim}
The \module{decimal} module provides arithmetic with as much precision as
needed:
\begin{verbatim}
>>> getcontext().prec = 36
>>> Decimal(1) / Decimal(7)
Decimal("0.142857142857142857142857142857142857")
\end{verbatim}
\chapter{What Now? \label{whatNow}}
Reading this tutorial has probably reinforced your interest in using
Python --- you should be eager to apply Python to solving your
real-world problems. Where should you go to learn more?
This tutorial is part of Python's documentation set.
Some other documents in the set are:
\begin{itemize}
\item \citetitle[../lib/lib.html]{Python Library Reference}:
You should browse through this manual, which gives complete (though
terse) reference material about types, functions, and the modules in
the standard library. The standard Python distribution includes a
\emph{lot} of additional code. There are modules to read \UNIX{}
mailboxes, retrieve documents via HTTP, generate random numbers, parse
command-line options, write CGI programs, compress data, and many other tasks.
Skimming through the Library Reference will give you an idea of
what's available.
\item \citetitle[../inst/inst.html]{Installing Python Modules}
explains how to install external modules written by other Python
users.
\item \citetitle[../ref/ref.html]{Language Reference}: A detailed
explanation of Python's syntax and semantics. It's heavy reading,
but is useful as a
\end{itemize}
More Python resources:
\begin{itemize}
\item \url{http://www.python.org}: The major Python Web site. It contains
code, documentation, and pointers to Python-related pages around the
Web. This Web site is mirrored in various places around the
world, such as Europe, Japan, and Australia; a mirror may be faster
than the main site, depending on your geographical location.
\item \url{http://docs.python.org}: Fast access to Python's
documentation.
\item \url{http://cheeseshop.python.org}:
The Python Package Index, nicknamed the Cheese Shop,
is an index of user-created Python modules that are available for
download. Once you begin releasing code, you can register it
here so that others can find it.
\item \url{http://aspn.activestate.com/ASPN/Python/Cookbook/}: The
Python Cookbook is a sizable collection of code examples, larger
modules, and useful scripts. Particularly notable contributions are
collected in a book also titled \citetitle{Python Cookbook} (O'Reilly
\& Associates, ISBN 0-596-00797-3.)
\end{itemize}
For Python-related questions and problem reports, you can post to the
newsgroup \newsgroup{comp.lang.python}, or send them to the mailing
list at \email{python-list@python.org}. The newsgroup and mailing list
are gatewayed, so messages posted to one will automatically be
forwarded to the other. There are around 120 postings a day (with peaks
up to several hundred),
% Postings figure based on average of last six months activity as
% reported by www.egroups.com; Jan. 2000 - June 2000: 21272 msgs / 182
% days = 116.9 msgs / day and steadily increasing.
asking (and answering) questions, suggesting new features, and
announcing new modules. Before posting, be sure to check the list of
\ulink{Frequently Asked Questions}{http://www.python.org/doc/faq/} (also called the FAQ), or look for it in the
\file{Misc/} directory of the Python source distribution. Mailing
list archives are available at \url{http://mail.python.org/pipermail/}.
The FAQ answers many of the questions that come up again and again,
and may already contain the solution for your problem.
\appendix
\chapter{Interactive Input Editing and History Substitution\label{interacting}}
Some versions of the Python interpreter support editing of the current
input line and history substitution, similar to facilities found in
the Korn shell and the GNU Bash shell. This is implemented using the
\emph{GNU Readline} library, which supports Emacs-style and vi-style
editing. This library has its own documentation which I won't
duplicate here; however, the basics are easily explained. The
interactive editing and history described here are optionally
available in the \UNIX{} and Cygwin versions of the interpreter.
This chapter does \emph{not} document the editing facilities of Mark
Hammond's PythonWin package or the Tk-based environment, IDLE,
distributed with Python. The command line history recall which
operates within DOS boxes on NT and some other DOS and Windows flavors
is yet another beast.
\section{Line Editing \label{lineEditing}}
If supported, input line editing is active whenever the interpreter
prints a primary or secondary prompt. The current line can be edited
using the conventional Emacs control characters. The most important
of these are: \kbd{C-A} (Control-A) moves the cursor to the beginning
of the line, \kbd{C-E} to the end, \kbd{C-B} moves it one position to
the left, \kbd{C-F} to the right. Backspace erases the character to
the left of the cursor, \kbd{C-D} the character to its right.
\kbd{C-K} kills (erases) the rest of the line to the right of the
cursor, \kbd{C-Y} yanks back the last killed string.
\kbd{C-underscore} undoes the last change you made; it can be repeated
for cumulative effect.
\section{History Substitution \label{history}}
History substitution works as follows. All non-empty input lines
issued are saved in a history buffer, and when a new prompt is given
you are positioned on a new line at the bottom of this buffer.
\kbd{C-P} moves one line up (back) in the history buffer,
\kbd{C-N} moves one down. Any line in the history buffer can be
edited; an asterisk appears in front of the prompt to mark a line as
modified. Pressing the \kbd{Return} key passes the current line to
the interpreter. \kbd{C-R} starts an incremental reverse search;
\kbd{C-S} starts a forward search.
\section{Key Bindings \label{keyBindings}}
The key bindings and some other parameters of the Readline library can
be customized by placing commands in an initialization file called
\file{\~{}/.inputrc}. Key bindings have the form
\begin{verbatim}
key-name: function-name
\end{verbatim}
or
\begin{verbatim}
"string": function-name
\end{verbatim}
and options can be set with
\begin{verbatim}
set option-name value
\end{verbatim}
For example:
\begin{verbatim}
# I prefer vi-style editing:
set editing-mode vi
# Edit using a single line:
set horizontal-scroll-mode On
# Rebind some keys:
Meta-h: backward-kill-word
"\C-u": universal-argument
"\C-x\C-r": re-read-init-file
\end{verbatim}
Note that the default binding for \kbd{Tab} in Python is to insert a
\kbd{Tab} character instead of Readline's default filename completion
function. If you insist, you can override this by putting
\begin{verbatim}
Tab: complete
\end{verbatim}
in your \file{\~{}/.inputrc}. (Of course, this makes it harder to
type indented continuation lines if you're accustomed to using
\kbd{Tab} for that purpose.)
Automatic completion of variable and module names is optionally
available. To enable it in the interpreter's interactive mode, add
the following to your startup file:\footnote{
Python will execute the contents of a file identified by the
\envvar{PYTHONSTARTUP} environment variable when you start an
interactive interpreter.}
\refstmodindex{rlcompleter}\refbimodindex{readline}
\begin{verbatim}
import rlcompleter, readline
readline.parse_and_bind('tab: complete')
\end{verbatim}
This binds the \kbd{Tab} key to the completion function, so hitting
the \kbd{Tab} key twice suggests completions; it looks at Python
statement names, the current local variables, and the available module
names. For dotted expressions such as \code{string.a}, it will
evaluate the expression up to the final \character{.} and then
suggest completions from the attributes of the resulting object. Note
that this may execute application-defined code if an object with a
\method{__getattr__()} method is part of the expression.
A more capable startup file might look like this example. Note that
this deletes the names it creates once they are no longer needed; this
is done since the startup file is executed in the same namespace as
the interactive commands, and removing the names avoids creating side
effects in the interactive environment. You may find it convenient
to keep some of the imported modules, such as
\ulink{\module{os}}{../lib/module-os.html}, which turn
out to be needed in most sessions with the interpreter.
\begin{verbatim}
# Add auto-completion and a stored history file of commands to your Python
# interactive interpreter. Requires Python 2.0+, readline. Autocomplete is
# bound to the Esc key by default (you can change it - see readline docs).
#
# Store the file in ~/.pystartup, and set an environment variable to point
# to it: "export PYTHONSTARTUP=/max/home/itamar/.pystartup" in bash.
#
# Note that PYTHONSTARTUP does *not* expand "~", so you have to put in the
# full path to your home directory.
import atexit
import os
import readline
import rlcompleter
historyPath = os.path.expanduser("~/.pyhistory")
def save_history(historyPath=historyPath):
import readline
readline.write_history_file(historyPath)
if os.path.exists(historyPath):
readline.read_history_file(historyPath)
atexit.register(save_history)
del os, atexit, readline, rlcompleter, save_history, historyPath
\end{verbatim}
\section{Commentary \label{commentary}}
This facility is an enormous step forward compared to earlier versions
of the interpreter; however, some wishes are left: It would be nice if
the proper indentation were suggested on continuation lines (the
parser knows if an indent token is required next). The completion
mechanism might use the interpreter's symbol table. A command to
check (or even suggest) matching parentheses, quotes, etc., would also
be useful.
\chapter{Floating Point Arithmetic: Issues and Limitations\label{fp-issues}}
\sectionauthor{Tim Peters}{tim_one@users.sourceforge.net}
Floating-point numbers are represented in computer hardware as
base 2 (binary) fractions. For example, the decimal fraction
\begin{verbatim}
0.125
\end{verbatim}
has value 1/10 + 2/100 + 5/1000, and in the same way the binary fraction
\begin{verbatim}
0.001
\end{verbatim}
has value 0/2 + 0/4 + 1/8. These two fractions have identical values,
the only real difference being that the first is written in base 10
fractional notation, and the second in base 2.
Unfortunately, most decimal fractions cannot be represented exactly as
binary fractions. A consequence is that, in general, the decimal
floating-point numbers you enter are only approximated by the binary
floating-point numbers actually stored in the machine.
The problem is easier to understand at first in base 10. Consider the
fraction 1/3. You can approximate that as a base 10 fraction:
\begin{verbatim}
0.3
\end{verbatim}
or, better,
\begin{verbatim}
0.33
\end{verbatim}
or, better,
\begin{verbatim}
0.333
\end{verbatim}
and so on. No matter how many digits you're willing to write down, the
result will never be exactly 1/3, but will be an increasingly better
approximation of 1/3.
In the same way, no matter how many base 2 digits you're willing to
use, the decimal value 0.1 cannot be represented exactly as a base 2
fraction. In base 2, 1/10 is the infinitely repeating fraction
\begin{verbatim}
0.0001100110011001100110011001100110011001100110011...
\end{verbatim}
Stop at any finite number of bits, and you get an approximation. This
is why you see things like:
\begin{verbatim}
>>> 0.1
0.10000000000000001
\end{verbatim}
On most machines today, that is what you'll see if you enter 0.1 at
a Python prompt. You may not, though, because the number of bits
used by the hardware to store floating-point values can vary across
machines, and Python only prints a decimal approximation to the true
decimal value of the binary approximation stored by the machine. On
most machines, if Python were to print the true decimal value of
the binary approximation stored for 0.1, it would have to display
\begin{verbatim}
>>> 0.1
0.1000000000000000055511151231257827021181583404541015625
\end{verbatim}
instead! The Python prompt uses the builtin
\function{repr()} function to obtain a string version of everything it
displays. For floats, \code{repr(\var{float})} rounds the true
decimal value to 17 significant digits, giving
\begin{verbatim}
0.10000000000000001
\end{verbatim}
\code{repr(\var{float})} produces 17 significant digits because it
turns out that's enough (on most machines) so that
\code{eval(repr(\var{x})) == \var{x}} exactly for all finite floats
\var{x}, but rounding to 16 digits is not enough to make that true.
Note that this is in the very nature of binary floating-point: this is
not a bug in Python, and it is not a bug in your code either. You'll
see the same kind of thing in all languages that support your
hardware's floating-point arithmetic (although some languages may
not \emph{display} the difference by default, or in all output modes).
Python's builtin \function{str()} function produces only 12
significant digits, and you may wish to use that instead. It's
unusual for \code{eval(str(\var{x}))} to reproduce \var{x}, but the
output may be more pleasant to look at:
\begin{verbatim}
>>> print str(0.1)
0.1
\end{verbatim}
It's important to realize that this is, in a real sense, an illusion:
the value in the machine is not exactly 1/10, you're simply rounding
the \emph{display} of the true machine value.
Other surprises follow from this one. For example, after seeing
\begin{verbatim}
>>> 0.1
0.10000000000000001
\end{verbatim}
you may be tempted to use the \function{round()} function to chop it
back to the single digit you expect. But that makes no difference:
\begin{verbatim}
>>> round(0.1, 1)
0.10000000000000001
\end{verbatim}
The problem is that the binary floating-point value stored for "0.1"
was already the best possible binary approximation to 1/10, so trying
to round it again can't make it better: it was already as good as it
gets.
Another consequence is that since 0.1 is not exactly 1/10,
summing ten values of 0.1 may not yield exactly 1.0, either:
\begin{verbatim}
>>> sum = 0.0
>>> for i in range(10):
... sum += 0.1
...
>>> sum
0.99999999999999989
\end{verbatim}
Binary floating-point arithmetic holds many surprises like this. The
problem with "0.1" is explained in precise detail below, in the
"Representation Error" section. See
\citetitle[http://www.lahey.com/float.htm]{The Perils of Floating
Point} for a more complete account of other common surprises.
As that says near the end, ``there are no easy answers.'' Still,
don't be unduly wary of floating-point! The errors in Python float
operations are inherited from the floating-point hardware, and on most
machines are on the order of no more than 1 part in 2**53 per
operation. That's more than adequate for most tasks, but you do need
to keep in mind that it's not decimal arithmetic, and that every float
operation can suffer a new rounding error.
While pathological cases do exist, for most casual use of
floating-point arithmetic you'll see the result you expect in the end
if you simply round the display of your final results to the number of
decimal digits you expect. \function{str()} usually suffices, and for
finer control see the discussion of Python's \code{\%} format
operator: the \code{\%g}, \code{\%f} and \code{\%e} format codes
supply flexible and easy ways to round float results for display.
\section{Representation Error
\label{fp-error}}
This section explains the ``0.1'' example in detail, and shows how
you can perform an exact analysis of cases like this yourself. Basic
familiarity with binary floating-point representation is assumed.
\dfn{Representation error} refers to the fact that some (most, actually)
decimal fractions cannot be represented exactly as binary (base 2)
fractions. This is the chief reason why Python (or Perl, C, \Cpp,
Java, Fortran, and many others) often won't display the exact decimal
number you expect:
\begin{verbatim}
>>> 0.1
0.10000000000000001
\end{verbatim}
Why is that? 1/10 is not exactly representable as a binary fraction.
Almost all machines today (November 2000) use IEEE-754 floating point
arithmetic, and almost all platforms map Python floats to IEEE-754
"double precision". 754 doubles contain 53 bits of precision, so on
input the computer strives to convert 0.1 to the closest fraction it can
of the form \var{J}/2**\var{N} where \var{J} is an integer containing
exactly 53 bits. Rewriting
\begin{verbatim}
1 / 10 ~= J / (2**N)
\end{verbatim}
as
\begin{verbatim}
J ~= 2**N / 10
\end{verbatim}
and recalling that \var{J} has exactly 53 bits (is \code{>= 2**52} but
\code{< 2**53}), the best value for \var{N} is 56:
\begin{verbatim}
>>> 2**52
4503599627370496L
>>> 2**53
9007199254740992L
>>> 2**56/10
7205759403792793L
\end{verbatim}
That is, 56 is the only value for \var{N} that leaves \var{J} with
exactly 53 bits. The best possible value for \var{J} is then that
quotient rounded:
\begin{verbatim}
>>> q, r = divmod(2**56, 10)
>>> r
6L
\end{verbatim}
Since the remainder is more than half of 10, the best approximation is
obtained by rounding up:
\begin{verbatim}
>>> q+1
7205759403792794L
\end{verbatim}
Therefore the best possible approximation to 1/10 in 754 double
precision is that over 2**56, or
\begin{verbatim}
7205759403792794 / 72057594037927936
\end{verbatim}
Note that since we rounded up, this is actually a little bit larger than
1/10; if we had not rounded up, the quotient would have been a little
bit smaller than 1/10. But in no case can it be \emph{exactly} 1/10!
So the computer never ``sees'' 1/10: what it sees is the exact
fraction given above, the best 754 double approximation it can get:
\begin{verbatim}
>>> .1 * 2**56
7205759403792794.0
\end{verbatim}
If we multiply that fraction by 10**30, we can see the (truncated)
value of its 30 most significant decimal digits:
\begin{verbatim}
>>> 7205759403792794 * 10**30 / 2**56
100000000000000005551115123125L
\end{verbatim}
meaning that the exact number stored in the computer is approximately
equal to the decimal value 0.100000000000000005551115123125. Rounding
that to 17 significant digits gives the 0.10000000000000001 that Python
displays (well, will display on any 754-conforming platform that does
best-possible input and output conversions in its C library --- yours may
not!).
\chapter{History and License}
\input{license}
\input{glossary}
\input{tut.ind}
\end{document}
|