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BUG: Fix for .str.replace with repl function #15056

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BUG: Fix for .str.replace with repl function #15056

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6ecc43d
BUG: Fix for .str.replace with repl function
Jan 4, 2017
91c883d
Update .str.replace docstring
Jan 4, 2017
4baa0a7
add tests for .str.replace with callable repl
Jan 4, 2017
30d4727
Bug fix in .str.replace type checking done wrong
Jan 5, 2017
067a7a8
Fix testing bug for .str.replace
Jan 6, 2017
ae04a3e
Add whatsnew for .str.replace with callable repl
Jan 6, 2017
27065a2
Reraise TypeError only with wrong number of args
Jan 6, 2017
14beb21
Add test for .str.replace with regex named groups
Jan 6, 2017
f15ee2a
improve test .str.replace with callable
Jan 22, 2017
40c0d97
improve .str.replace with callable
Jan 23, 2017
e15dcdf
fix bug catch TypeError with wrong number of args
Jan 23, 2017
c2cc13a
Update v0.20.0.txt
Jan 23, 2017
90779ce
fix linting issues
Jan 23, 2017
826730c
simplify .str.replace TypeError reraising and test
Jan 23, 2017
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11 changes: 6 additions & 5 deletions pandas/core/strings.py
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Original file line number Diff line number Diff line change
Expand Up @@ -303,8 +303,9 @@ def str_replace(arr, pat, repl, n=-1, case=True, flags=0):
----------
pat : string
Character sequence or regular expression
repl : string
Replacement sequence
repl : string or callable
Replacement string or a callable, it's passed the match object and
must return a replacement string to be used. See :func:`re.sub`.
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add the version (0.20.0) after callable

n : int, default -1 (all)
Number of replacements to make from start
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can you add some examples to the doc-string?

also would be nice to have an example in text.rst

case : boolean, default True
Expand All @@ -318,9 +319,9 @@ def str_replace(arr, pat, repl, n=-1, case=True, flags=0):
"""

# Check whether repl is valid (GH 13438)
if not is_string_like(repl):
raise TypeError("repl must be a string")
use_re = not case or len(pat) > 1 or flags
if not (is_string_like(repl) or callable(repl)):
raise TypeError("repl must be a string or function")
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function -> callable

use_re = not case or len(pat) > 1 or flags or callable(repl)

if use_re:
if not case:
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6 changes: 6 additions & 0 deletions pandas/tests/test_strings.py
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Expand Up @@ -435,6 +435,12 @@ def test_replace(self):
for data in (['a', 'b', None], ['a', 'b', 'c', 'ad']):
values = klass(data)
self.assertRaises(TypeError, values.str.replace, 'a', repl)

# GH 15055, callable repl
repl = lambda m: m.group(0).swapcase()
result = values.str.replace('[a-z][A-Z]{2}', repl, n=2)
exp = Series([u('foObaD__baRbaD'), NA])
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test where the callable has different than 1 arg (should be error)

test using named field in re (and callable works correctly)

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@hzpc-joostk hzpc-joostk Jan 5, 2017 •
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Thanks, @jreback . Named field/group is a good idea.

If the callable raises a TypeError because of a wrong number of arguments, this is caught in pandas.core.strings._map, returning a Series of NaNs.

We could overcome this by either inspecting the callable signature: inspect.signature or trying with a dummy Regex Match object. But this might have the side effect that the callable is called once before doing the replace on the array, confusing users with some kind of counter within the callable.

Sorry about the checks going wrong. It seems I am too careless with checking my commits. 😕

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With inspect I could do

n_empty_args = sum(1 for p in inspect.signature(repl).parameters.values() 
                   if p.kind in (p.POSITIONAL_ONLY, p.POSITIONAL_OR_KEYWORD, p.KEYWORD_ONLY) 
                   and p.default is p.empty)

# or better readable syntax

signature = inspect.signature(repl)
empty_args = [p for p in signature.parameters.values() 
              if p.kind in (p.POSITIONAL_ONLY, p.POSITIONAL_OR_KEYWORD, p.KEYWORD_ONLY) 
              and p.default is p.empty]
n_empty_args = len(empty_args)

# followed by

if n_empty_args > 1:
    raise TypeError("callable should have at most one positional without a default")

n_empty_args != 1 might work, unless the first arg has a default for some reason.

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this is too complicated, instead maybe you can introspect the actual error message in _map and if its a certain class of errors, just re-raise the TypeError

tm.assert_series_equal(result, exp)

def test_repeat(self):
values = Series(['a', 'b', NA, 'c', NA, 'd'])
Expand Down