ENH: Allow callable for on_bad_lines in read_csv when engine="python"

doc/source/user_guide/io.rst

@@ -1305,14 +1305,38 @@ You can elect to skip bad lines:
  0 1 2 3
  1 8 9 10
 
+Or pass a callable function to handle the bad line if ``engine="python"``.
+The bad line will be a list of strings that was split by the ``sep``:
+
+.. code-block:: ipython
+
+ In [29]: external_list = []
+
+ In [30]: def bad_lines_func(line):
+ ...: external_list.append(line)
+ ...: return line[-3:]
+
+ In [31]: pd.read_csv(StringIO(data), on_bad_lines=bad_lines_func, engine="python")
+ Out[31]:
+ a b c
+ 0 1 2 3
+ 1 5 6 7
+ 2 8 9 10
+
+ In [32]: external_list
+ Out[32]: [4, 5, 6, 7]
+
+ .. versionadded:: 1.4.0
+
+
 You can also use the ``usecols`` parameter to eliminate extraneous column
 data that appear in some lines but not others:
 
 .. code-block:: ipython
 
- In [30]: pd.read_csv(StringIO(data), usecols=[0, 1, 2])
+ In [33]: pd.read_csv(StringIO(data), usecols=[0, 1, 2])
 
- Out[30]:
+ Out[33]:
  a b c
  0 1 2 3
  1 4 5 6
@@ -1324,9 +1348,9 @@ fields are filled with ``NaN``.
 
 .. code-block:: ipython
 
- In [31]: pd.read_csv(StringIO(data), names=['a', 'b', 'c', 'd'])
+ In [34]: pd.read_csv(StringIO(data), names=['a', 'b', 'c', 'd'])
 
- Out[31]:
+ Out[34]:
  a b c d
  0 1 2 3 NaN
  1 4 5 6 7

doc/source/whatsnew/v1.4.0.rst

@@ -208,6 +208,7 @@ Other enhancements
 - :meth:`Series.str.split` now supports a ``regex`` argument that explicitly specifies whether the pattern is a regular expression. Default is ``None`` (:issue:`43563`, :issue:`32835`, :issue:`25549`)
 - :meth:`DataFrame.dropna` now accepts a single label as ``subset`` along with array-like (:issue:`41021`)
 - Added :meth:`DataFrameGroupBy.value_counts` (:issue:`43564`)
+- :func:`read_csv` now accepts a ``callable`` function in ``on_bad_lines`` when ``engine="python"`` for custom handling of bad lines (:issue:`5686`)
 - :class:`ExcelWriter` argument ``if_sheet_exists="overlay"`` option added (:issue:`40231`)
 - :meth:`read_excel` now accepts a ``decimal`` argument that allow the user to specify the decimal point when parsing string columns to numeric (:issue:`14403`)
 - :meth:`.GroupBy.mean`, :meth:`.GroupBy.std`, :meth:`.GroupBy.var`, :meth:`.GroupBy.sum` now supports `Numba <http://numba.pydata.org/>`_ execution with the ``engine`` keyword (:issue:`43731`, :issue:`44862`, :issue:`44939`)

pandas/io/parsers/python_parser.py

@@ -990,7 +990,11 @@ def _rows_to_cols(self, content: list[list[Scalar]]) -> list[np.ndarray]:
  actual_len = len(l)
 
  if actual_len > col_len:
- if (
+ if callable(self.on_bad_lines):
+ new_l = self.on_bad_lines(l)
+ if new_l is not None:
+ content.append(new_l)
+ elif (
  self.on_bad_lines == self.BadLineHandleMethod.ERROR
  or self.on_bad_lines == self.BadLineHandleMethod.WARN
  ):

pandas/io/parsers/readers.py

@@ -9,6 +9,7 @@
 from textwrap import fill
 from typing import (
  Any,
+ Callable,
  NamedTuple,
 )
 import warnings
@@ -354,7 +355,7 @@
  .. deprecated:: 1.3.0
  The ``on_bad_lines`` parameter should be used instead to specify behavior upon
  encountering a bad line instead.
-on_bad_lines : {{'error', 'warn', 'skip'}}, default 'error'
+on_bad_lines : {{'error', 'warn', 'skip'}} or callable, default 'error'
  Specifies what to do upon encountering a bad line (a line with too many fields).
  Allowed values are :
 
@@ -364,6 +365,16 @@
 
  .. versionadded:: 1.3.0
 
+ - callable, function with signature
+ ``(bad_line: list[str]) -> list[str] | None`` that will process a single
+ bad line. ``bad_line`` is a list of strings split by the ``sep``.
+ If the function returns ``None`, the bad line will be ignored.
+ If the function returns a new list of strings with more elements than
+ expected, a ``ParserWarning`` will be emitted while dropping extra elements.
+ Only supported when ``engine="python"``
+
+ .. versionadded:: 1.4.0
+
 delim_whitespace : bool, default False
  Specifies whether or not whitespace (e.g. ``' '`` or ``'\t'``) will be
  used as the sep. Equivalent to setting ``sep='\\s+'``. If this option
@@ -1367,7 +1378,7 @@ def _refine_defaults_read(
  sep: str | object,
  error_bad_lines: bool | None,
  warn_bad_lines: bool | None,
- on_bad_lines: str | None,
+ on_bad_lines: str | Callable | None,
  names: ArrayLike | None | object,
  prefix: str | None | object,
  defaults: dict[str, Any],
@@ -1399,7 +1410,7 @@ def _refine_defaults_read(
  Whether to error on a bad line or not.
  warn_bad_lines : str or None
  Whether to warn on a bad line or not.
- on_bad_lines : str or None
+ on_bad_lines : str, callable or None
  An option for handling bad lines or a sentinel value(None).
  names : array-like, optional
  List of column names to use. If the file contains a header row,
@@ -1503,6 +1514,12 @@ def _refine_defaults_read(
  kwds["on_bad_lines"] = ParserBase.BadLineHandleMethod.WARN
  elif on_bad_lines == "skip":
  kwds["on_bad_lines"] = ParserBase.BadLineHandleMethod.SKIP
+ elif callable(on_bad_lines):
+ if engine != "python":
+ raise ValueError(
+ "on_bad_line can only be a callable function if engine='python'"
+ )
+ kwds["on_bad_lines"] = on_bad_lines
  else:
  raise ValueError(f"Argument {on_bad_lines} is invalid for on_bad_lines")
  else:

pandas/tests/io/parser/test_python_parser_only.py

@@ -4,6 +4,7 @@
 these tests out of this module as soon as the C parser can accept further
 arguments when parsing.
 """
+from __future__ import annotations
 
 import csv
 from io import (
@@ -13,7 +14,10 @@
 
 import pytest
 
-from pandas.errors import ParserError
+from pandas.errors import (
+ ParserError,
+ ParserWarning,
+)
 
 from pandas import (
  DataFrame,
@@ -329,3 +333,128 @@ def readline(self):
  return self.data
 
  parser.read_csv(NoNextBuffer("a\n1"))
+
+
+@pytest.mark.parametrize("bad_line_func", [lambda x: ["2", "3"], lambda x: x[:2]])
+def test_on_bad_lines_callable(python_parser_only, bad_line_func):
+ # GH 5686
+ parser = python_parser_only
+ data = """a,b
+1,2
+2,3,4,5,6
+3,4
+"""
+ bad_sio = StringIO(data)
+ result = parser.read_csv(bad_sio, on_bad_lines=bad_line_func)
+ expected = DataFrame({"a": [1, 2, 3], "b": [2, 3, 4]})
+ tm.assert_frame_equal(result, expected)
+
+
+def test_on_bad_lines_callable_write_to_external_list(python_parser_only):
+ # GH 5686
+ parser = python_parser_only
+ data = """a,b
+1,2
+2,3,4,5,6
+3,4
+"""
+ bad_sio = StringIO(data)
+ lst = []
+
+ def bad_line_func(bad_line: list[str]) -> list[str]:
+ lst.append(bad_line)
+ return ["2", "3"]
+
+ result = parser.read_csv(bad_sio, on_bad_lines=bad_line_func)
+ expected = DataFrame({"a": [1, 2, 3], "b": [2, 3, 4]})
+ tm.assert_frame_equal(result, expected)
+ assert lst == [["2", "3", "4", "5", "6"]]
+
+
+@pytest.mark.parametrize("bad_line_func", [lambda x: ["foo", "bar"], lambda x: x[:2]])
+@pytest.mark.parametrize("sep", [",", "111"])
+def test_on_bad_lines_callable_iterator_true(python_parser_only, bad_line_func, sep):
+ # GH 5686
+ # iterator=True has a separate code path than iterator=False
+ parser = python_parser_only
+ data = f"""
+0{sep}1
+hi{sep}there
+foo{sep}bar{sep}baz
+good{sep}bye
+"""
+ bad_sio = StringIO(data)
+ result_iter = parser.read_csv(
+ bad_sio, on_bad_lines=bad_line_func, chunksize=1, iterator=True, sep=sep
+ )
+ expecteds = [
+ {"0": "hi", "1": "there"},
+ {"0": "foo", "1": "bar"},
+ {"0": "good", "1": "bye"},
+ ]
+ for i, (result, expected) in enumerate(zip(result_iter, expecteds)):
+ expected = DataFrame(expected, index=range(i, i + 1))
+ tm.assert_frame_equal(result, expected)
+
+
+def test_on_bad_lines_callable_dont_swallow_errors(python_parser_only):
+ # GH 5686
+ parser = python_parser_only
+ data = """a,b
+1,2
+2,3,4,5,6
+3,4
+"""
+ bad_sio = StringIO(data)
+ msg = "This function is buggy."
+
+ def bad_line_func(bad_line):
+ raise ValueError(msg)
+
+ with pytest.raises(ValueError, match=msg):
+ parser.read_csv(bad_sio, on_bad_lines=bad_line_func)
+
+
+def test_on_bad_lines_callable_not_expected_length(python_parser_only):
+ # GH 5686
+ parser = python_parser_only
+ data = """a,b
+1,2
+2,3,4,5,6
+3,4
+"""
+ bad_sio = StringIO(data)
+
+ with tm.assert_produces_warning(ParserWarning, match="Length of header or names"):
+ result = parser.read_csv(bad_sio, on_bad_lines=lambda x: x)
+ expected = DataFrame({"a": [1, 2, 3], "b": [2, 3, 4]})
+ tm.assert_frame_equal(result, expected)
+
+
+def test_on_bad_lines_callable_returns_none(python_parser_only):
+ # GH 5686
+ parser = python_parser_only
+ data = """a,b
+1,2
+2,3,4,5,6
+3,4
+"""
+ bad_sio = StringIO(data)
+
+ result = parser.read_csv(bad_sio, on_bad_lines=lambda x: None)
+ expected = DataFrame({"a": [1, 3], "b": [2, 4]})
+ tm.assert_frame_equal(result, expected)
+
+
+def test_on_bad_lines_index_col_inferred(python_parser_only):
+ # GH 5686
+ parser = python_parser_only
+ data = """a,b
+1,2,3
+4,5,6
+"""
+ bad_sio = StringIO(data)
+
+ result = parser.read_csv(bad_sio, on_bad_lines=lambda x: ["99", "99"])
+ expected = DataFrame({"a": [2, 5], "b": [3, 6]}, index=[1, 4])
+ tm.assert_frame_equal(result, expected)

pandas/tests/io/parser/test_unsupported.py

@@ -149,3 +149,15 @@ def test_pyarrow_engine(self):
  kwargs[default] = "warn"
  with pytest.raises(ValueError, match=msg):
  read_csv(StringIO(data), engine="pyarrow", **kwargs)
+
+ def test_on_bad_lines_callable_python_only(self, all_parsers):
+ # GH 5686
+ sio = StringIO("a,b\n1,2")
+ bad_lines_func = lambda x: x
+ parser = all_parsers
+ if all_parsers.engine != "python":
+ msg = "on_bad_line can only be a callable function if engine='python'"
+ with pytest.raises(ValueError, match=msg):
+ parser.read_csv(sio, on_bad_lines=bad_lines_func)
+ else:
+ parser.read_csv(sio, on_bad_lines=bad_lines_func)