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author | Raymond Hettinger <python@rcn.com> | 2003-11-18 17:50:34 (GMT) |
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committer | Raymond Hettinger <python@rcn.com> | 2003-11-18 17:50:34 (GMT) |
commit | 65674b80fc70b222a5a4bfc63b02691fba5aec9e (patch) | |
tree | 4ca3e5c638190e48ffb9a73abd6b115dfd9494ef /Doc | |
parent | 1b92fd5bcac0a179928a3a4d35e73e110ee10abd (diff) | |
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Documentation for set objects.
Diffstat (limited to 'Doc')
-rw-r--r-- | Doc/tut/tut.tex | 37 |
1 files changed, 37 insertions, 0 deletions
diff --git a/Doc/tut/tut.tex b/Doc/tut/tut.tex index 508a7ae..ce941f3 100644 --- a/Doc/tut/tut.tex +++ b/Doc/tut/tut.tex @@ -2053,6 +2053,43 @@ 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'] +>>> fruits = set(basket) # create a set without duplicates +>>> fruits +set(['orange', 'pear', 'apple', 'banana']) +>>> 'orange' in fruits # fast membership testing +True +>>> 'crabgrass' in fruits +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 |