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authorRaymond Hettinger <python@rcn.com>2009-02-23 21:23:04 (GMT)
committerRaymond Hettinger <python@rcn.com>2009-02-23 21:23:04 (GMT)
commitd187d520850833c46944f0096362270f6f09b8ab (patch)
tree5e17665a95c28e1d0008935255c610f6a04d2c24
parentfc9a6659b49b510e30318f1cf79bf9f19a2c057a (diff)
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Sync-up itertools docs with Py3.1 version.
* Merge 69715: rewrite introduction and add summary table * Merge 69739: generalize tee() recipe * Merge 69141: Fix tab alignment on recipes to match other recipes * Merge 68942: Update powerset() recipe
-rw-r--r--Doc/library/itertools.rst126
1 files changed, 77 insertions, 49 deletions
diff --git a/Doc/library/itertools.rst b/Doc/library/itertools.rst
index 1f4d5b5..8bdf625 100644
--- a/Doc/library/itertools.rst
+++ b/Doc/library/itertools.rst
@@ -14,40 +14,63 @@
.. versionadded:: 2.3
-This module implements a number of :term:`iterator` building blocks inspired by
-constructs from the Haskell and SML programming languages. Each has been recast
-in a form suitable for Python.
+This module implements a number of :term:`iterator` building blocks inspired
+by constructs from APL, Haskell, and SML. Each has been recast in a form
+suitable for Python.
The module standardizes a core set of fast, memory efficient tools that are
-useful by themselves or in combination. Standardization helps avoid the
-readability and reliability problems which arise when many different individuals
-create their own slightly varying implementations, each with their own quirks
-and naming conventions.
-
-The tools are designed to combine readily with one another. This makes it easy
-to construct more specialized tools succinctly and efficiently in pure Python.
+useful by themselves or in combination. Together, they form an "iterator
+algebra" making it possible to construct specialized tools succinctly and
+efficiently in pure Python.
For instance, SML provides a tabulation tool: ``tabulate(f)`` which produces a
sequence ``f(0), f(1), ...``. This toolbox provides :func:`imap` and
-:func:`count` which can be combined to form ``imap(f, count())`` and produce an
+:func:`count` which can be combined to form ``imap(f, count())`` to produce an
equivalent result.
-Likewise, the functional tools are designed to work well with the high-speed
-functions provided by the :mod:`operator` module.
-
-Whether cast in pure python form or compiled code, tools that use iterators are
-more memory efficient (and often faster) than their list based counterparts. Adopting
-the principles of just-in-time manufacturing, they create data when and where
-needed instead of consuming memory with the computer equivalent of "inventory".
-
-
-.. seealso::
-
- The Standard ML Basis Library, `The Standard ML Basis Library
- <http://www.standardml.org/Basis/>`_.
-
- Haskell, A Purely Functional Language, `Definition of Haskell and the Standard
- Libraries <http://www.haskell.org/definition/>`_.
+The tools also work well with the high-speed functions in the :mod:`operator`
+module. For example, the plus-operator can be mapped across two vectors to
+form an efficient dot-product: ``sum(imap(operator.add, vector1, vector2))``.
+
+
+**Infinite Iterators:**
+
+ ================== ================= =================================================
+ Iterator Arguments Results
+ ================== ================= =================================================
+ :func:`count` start start, start+1, start+2, ...
+ :func:`cycle` p p0, p1, ... plast, p0, p1, ...
+ :func:`repeat` elem [,n] elem, elem, elem, ... endlessly or up to n times
+ ================== ================= =================================================
+
+**Iterators terminating on the shortest input sequence:**
+
+ ==================== ============================ =================================================
+ Iterator Arguments Results
+ ==================== ============================ =================================================
+ :func:`chain` p, q, ... p0, p1, ... plast, q0, q1, ...
+ :func:`dropwhile` pred, seq seq[n], seq[n+1], starting when pred fails
+ :func:`groupby` iterable[, keyfunc] sub-iterators grouped by value of keyfunc(v)
+ :func:`ifilter` pred, seq elements of seq where pred(elem) is True
+ :func:`ifilterfalse` pred, seq elements of seq where pred(elem) is False
+ :func:`islice` seq, [start,] stop [, step] elements from seq[start:stop:step]
+ :func:`imap` func, p, q, ... func(p0, q0), fun(p1, q1), ...
+ :func:`starmap` func, seq func(\*seq[0]), fun(\*seq[1]), ...
+ :func:`tee` it, n it1, it2 , ... itn splits one iterator into n
+ :func:`takewhile` pred, seq seq[0], seq[1], until pred fails
+ :func:`izip` p, q, ... (p[0], q[0]), (p[1], q[1]), ...
+ :func:`izip_longest` p, q, ... (p[0], q[0]), (p[1], q[1]), ...
+ ==================== ============================ =================================================
+
+**Combinatoric generators:**
+
+ ===================================== ==================== =================================================
+ Iterator Arguments Results
+ ===================================== ==================== =================================================
+ :func:`product` p, q, ... [repeat=1] cartesian product
+ :func:`permutations` p[, r] r-length permutations (without repeated elements)
+ :func:`combinations` p[, r] r-length combinations (sorted and no repeats)
+ ===================================== ==================== =================================================
.. _itertools-functions:
@@ -697,26 +720,31 @@ which incur interpreter overhead.
indices[i:] = [indices[i] + 1] * (r - i)
yield tuple(pool[i] for i in indices)
- def unique_everseen(iterable, key=None):
- "List unique elements, preserving order. Remember all elements ever seen."
- # unique_everseen('AAAABBBCCDAABBB') --> A B C D
- # unique_everseen('ABBCcAD', str.lower) --> A B C D
- seen = set()
- seen_add = seen.add
- if key is None:
- for element in iterable:
- if element not in seen:
- seen_add(element)
- yield element
- else:
- for element in iterable:
- k = key(element)
- if k not in seen:
- seen_add(k)
- yield element
+ def powerset(iterable):
+ "powerset([1,2,3]) --> () (1,) (2,) (3,) (1,2) (1,3) (2,3) (1,2,3)"
+ s = list(iterable)
+ return chain.from_iterable(combinations(s, r) for r in range(len(s)+1))
- def unique_justseen(iterable, key=None):
- "List unique elements, preserving order. Remember only the element just seen."
- # unique_justseen('AAAABBBCCDAABBB') --> A B C D A B
- # unique_justseen('ABBCcAD', str.lower) --> A B C A D
- return imap(next, imap(itemgetter(1), groupby(iterable, key)))
+ def unique_everseen(iterable, key=None):
+ "List unique elements, preserving order. Remember all elements ever seen."
+ # unique_everseen('AAAABBBCCDAABBB') --> A B C D
+ # unique_everseen('ABBCcAD', str.lower) --> A B C D
+ seen = set()
+ seen_add = seen.add
+ if key is None:
+ for element in iterable:
+ if element not in seen:
+ seen_add(element)
+ yield element
+ else:
+ for element in iterable:
+ k = key(element)
+ if k not in seen:
+ seen_add(k)
+ yield element
+
+ def unique_justseen(iterable, key=None):
+ "List unique elements, preserving order. Remember only the element just seen."
+ # unique_justseen('AAAABBBCCDAABBB') --> A B C D A B
+ # unique_justseen('ABBCcAD', str.lower) --> A B C A D
+ return imap(next, imap(itemgetter(1), groupby(iterable, key)))