remove cruft from Schwarzian transform section

This commit is contained in:
Benjamin Peterson 2016-05-26 22:55:49 -07:00
parent 6d3ad2f64d
commit 047ada4ef3
1 changed files with 1 additions and 30 deletions

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@ -1312,40 +1312,11 @@ I want to do a complicated sort: can you do a Schwartzian Transform in Python?
The technique, attributed to Randal Schwartz of the Perl community, sorts the
elements of a list by a metric which maps each element to its "sort value". In
Python, just use the ``key`` argument for the ``sort()`` method::
Python, use the ``key`` argument for the :func:`sort()` function::
Isorted = L[:]
Isorted.sort(key=lambda s: int(s[10:15]))
The ``key`` argument is new in Python 2.4, for older versions this kind of
sorting is quite simple to do with list comprehensions. To sort a list of
strings by their uppercase values::
tmp1 = [(x.upper(), x) for x in L] # Schwartzian transform
tmp1.sort()
Usorted = [x[1] for x in tmp1]
To sort by the integer value of a subfield extending from positions 10-15 in
each string::
tmp2 = [(int(s[10:15]), s) for s in L] # Schwartzian transform
tmp2.sort()
Isorted = [x[1] for x in tmp2]
For versions prior to 3.0, Isorted may also be computed by ::
def intfield(s):
return int(s[10:15])
def Icmp(s1, s2):
return cmp(intfield(s1), intfield(s2))
Isorted = L[:]
Isorted.sort(Icmp)
but since this method calls ``intfield()`` many times for each element of L, it
is slower than the Schwartzian Transform.
How can I sort one list by values from another list?
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