BUG: Don't warn if default conflicts with dialect

xref pandas-devgh-23761.

doc/source/whatsnew/v0.24.0.rst

@@ -1383,6 +1383,7 @@ Notice how we now instead output ``np.nan`` itself instead of a stringified form
 - Bug in :meth:`HDFStore.append` when appending a :class:`DataFrame` with an empty string column and ``min_itemsize`` < 8 (:issue:`12242`)
 - Bug in :func:`read_csv()` in which incorrect error messages were being raised when ``skipfooter`` was passed in along with ``nrows``, ``iterator``, or ``chunksize`` (:issue:`23711`)
 - Bug in :meth:`read_csv()` in which :class:`MultiIndex` index names were being improperly handled in the cases when they were not provided (:issue:`23484`)
+- Bug in :meth:`read_csv()` in which unnecessary warnings were being raised when the dialect's values conflicted with the default arguments (:issue:`23761`)
 - Bug in :meth:`read_html()` in which the error message was not displaying the valid flavors when an invalid one was provided (:issue:`23549`)
 - Bug in :meth:`read_excel()` in which extraneous header names were extracted, even though none were specified (:issue:`11733`)
 - Bug in :meth:`read_excel()` in which ``index_col=None`` was not being respected and parsing index columns anyway (:issue:`20480`)

pandas/io/parsers.py

@@ -632,6 +632,24 @@ def parser_f(filepath_or_buffer,
             if sep is False:
                 sep = default_sep
 
+        # gh-23761
+        #
+        # When a dialect is passed, it overrides any of the overlapping
+        # parameters passed in directly. We don't want to warn if the
+        # default parameters were passed in (since it probably means
+        # that the user didn't pass them in explicitly in the first place).
+        #
+        # "delimiter" is the annoying corner case because we alias it to
+        # "sep" before doing comparison to the dialect values later on.
+        # Thus, we need a flag to indicate that we need to "override"
+        # the comparison to dialect values by checking if default values
+        # for BOTH "delimiter" and "sep" were provided.
+        if dialect is not None:
+            sep_override = delimiter is None and sep == default_sep
+            kwds = dict(sep_override=sep_override)
+        else:
+            kwds = dict()
+
         # Alias sep -> delimiter.
         if delimiter is None:
             delimiter = sep
@@ -647,7 +665,7 @@ def parser_f(filepath_or_buffer,
             engine = 'c'
             engine_specified = False
 
-        kwds = dict(delimiter=delimiter,
+        kwds.update(delimiter=delimiter,
                     engine=engine,
                     dialect=dialect,
                     compression=compression,
@@ -769,18 +787,27 @@ def __init__(self, f, engine=None, **kwds):
                 except AttributeError:
                     raise ValueError("Invalid dialect '{dialect}' provided"
                                      .format(dialect=kwds['dialect']))
-                provided = kwds.get(param, _parser_defaults[param])
+                parser_default = _parser_defaults[param]
+                provided = kwds.get(param, parser_default)
 
-                # Messages for conflicting values between the dialect instance
-                # and the actual parameters provided.
+                # Messages for conflicting values between the dialect
+                # instance and the actual parameters provided.
                 conflict_msgs = []
 
-                if dialect_val != provided:
-                    conflict_msgs.append((
-                        "Conflicting values for '{param}': '{val}' was "
-                        "provided, but the dialect specifies '{diaval}'. "
-                        "Using the dialect-specified value.".format(
-                            param=param, val=provided, diaval=dialect_val)))
+                # Don't warn if the default parameter was passed in,
+                # even if it conflicts with the dialect (gh-23761).
+                if provided != parser_default and provided != dialect_val:
+                    msg = ("Conflicting values for '{param}': '{val}' was "
+                           "provided, but the dialect specifies '{diaval}'. "
+                           "Using the dialect-specified value.".format(
+                               param=param, val=provided, diaval=dialect_val))
+
+                    # Annoying corner case for not warning about
+                    # conflicts between dialect and delimiter parameter.
+                    # Refer to the outer "_read_" function for more info.
+                    if not (param == "delimiter" and
+                            kwds.pop("sep_override", False)):
+                        conflict_msgs.append(msg)
 
                 if conflict_msgs:
                     warnings.warn('\n\n'.join(conflict_msgs), ParserWarning,

pandas/tests/io/parser/test_dialect.py

@@ -16,6 +16,14 @@
 import pandas.util.testing as tm
 
 
+@pytest.fixture
+def custom_dialect():
+    dialect_name = "weird"
+    dialect_kwargs = dict(doublequote=False, escapechar="~", delimiter=":",
+                          skipinitialspace=False, quotechar="~", quoting=3)
+    return dialect_name, dialect_kwargs
+
+
 def test_dialect(all_parsers):
     parser = all_parsers
     data = """\
@@ -26,10 +34,7 @@ def test_dialect(all_parsers):
 
     dia = csv.excel()
     dia.quoting = csv.QUOTE_NONE
-
-    # Conflicting dialect quoting.
-    with tm.assert_produces_warning(ParserWarning):
-        df = parser.read_csv(StringIO(data), dialect=dia)
+    df = parser.read_csv(StringIO(data), dialect=dia)
 
     data = """\
 label1,label2,label3
@@ -53,14 +58,10 @@ def test_dialect_str(all_parsers):
         "fruit": ["apple", "pear"],
         "vegetable": ["broccoli", "tomato"]
     })
-    csv.register_dialect(dialect_name, delimiter=":")
 
-    # Conflicting dialect delimiter.
-    with tm.assert_produces_warning(ParserWarning):
+    with tm.with_csv_dialect(dialect_name, delimiter=":"):
         df = parser.read_csv(StringIO(data), dialect=dialect_name)
-
-    tm.assert_frame_equal(df, exp)
-    csv.unregister_dialect(dialect_name)
+        tm.assert_frame_equal(df, exp)
 
 
 def test_invalid_dialect(all_parsers):
@@ -75,17 +76,60 @@ class InvalidDialect(object):
         parser.read_csv(StringIO(data), dialect=InvalidDialect)
 
 
-@pytest.mark.parametrize("delimiter", [",", "."])
-def test_dialect_conflict(all_parsers, delimiter):
-    data = "a,b\n1,2"
-    dialect = "excel"
+@pytest.mark.parametrize("arg", [None, "doublequote", "escapechar",
+                                 "skipinitialspace", "quotechar", "quoting"])
+@pytest.mark.parametrize("value", ["dialect", "default", "other"])
+def test_dialect_conflict_except_delimiter(all_parsers, custom_dialect,
+                                           arg, value):
+    # see gh-23761.
+    dialect_name, dialect_kwargs = custom_dialect
+    parser = all_parsers
+
+    expected = DataFrame({"a": [1], "b": [2]})
+    data = "a:b\n1:2"
+
+    warning_klass = None
+    kwds = dict()
+
+    # arg=None tests when we pass in the dialect without any other arguments.
+    if arg is not None:
+        if "value" == "dialect":  # No conflict --> no warning.
+            kwds[arg] = dialect_kwargs[arg]
+        elif "value" == "default":  # Default --> no warning.
+            from pandas.io.parsers import _parser_defaults
+            kwds[arg] = _parser_defaults[arg]
+        else:  # Non-default + conflict with dialect --> warning.
+            warning_klass = ParserWarning
+            kwds[arg] = "blah"
+
+    with tm.with_csv_dialect(dialect_name, **dialect_kwargs):
+        with tm.assert_produces_warning(warning_klass):
+            result = parser.read_csv(StringIO(data),
+                                     dialect=dialect_name, **kwds)
+            tm.assert_frame_equal(result, expected)
+
+
+@pytest.mark.parametrize("kwargs,warning_klass", [
+    (dict(sep=","), None),           # sep is default --> sep_override=True
+    (dict(sep="."), ParserWarning),  # sep isn't default --> sep_override=False
+    (dict(delimiter=":"), None),     # No conflict
+    (dict(delimiter=None), None),    # Default arguments --> sep_override=True
+    (dict(delimiter=","), ParserWarning),  # Conflict
+    (dict(delimiter="."), ParserWarning),  # Conflict
+], ids=["sep-override-true", "sep-override-false",
+        "delimiter-no-conflict", "delimiter-default-arg",
+        "delimiter-conflict", "delimiter-conflict2"])
+def test_dialect_conflict_delimiter(all_parsers, custom_dialect,
+                                    kwargs, warning_klass):
+    # see gh-23761.
+    dialect_name, dialect_kwargs = custom_dialect
     parser = all_parsers
 
     expected = DataFrame({"a": [1], "b": [2]})
-    warning_klass = None if delimiter == "," else ParserWarning
+    data = "a:b\n1:2"
 
-    with tm.assert_produces_warning(warning_klass):
-        result = parser.read_csv(StringIO(data),
-                                 delimiter=delimiter,
-                                 dialect=dialect)
-        tm.assert_frame_equal(result, expected)
+    with tm.with_csv_dialect(dialect_name, **dialect_kwargs):
+        with tm.assert_produces_warning(warning_klass):
+            result = parser.read_csv(StringIO(data),
+                                     dialect=dialect_name, **kwargs)
+            tm.assert_frame_equal(result, expected)

pandas/util/testing.py

@@ -2835,6 +2835,37 @@ def __exit__(self, exc_type, exc_value, traceback):
         np.random.set_state(self.start_state)
 
 
+@contextmanager
+def with_csv_dialect(name, **kwargs):
+    """
+    Context manager to temporarily register a CSV dialect for parsing CSV.
+
+    Parameters
+    ----------
+    name : str
+        The name of the dialect.
+    kwargs : mapping
+        The parameters for the dialect.
+
+    Raises
+    ------
+    ValueError : the name of the dialect conflicts with a builtin one.
+
+    See Also
+    --------
+    csv : Python's CSV library.
+    """
+    import csv
+    _BUILTIN_DIALECTS = {"excel", "excel-tab", "unix"}
+
+    if name in _BUILTIN_DIALECTS:
+        raise ValueError("Cannot override builtin dialect.")
+
+    csv.register_dialect(name, **kwargs)
+    yield
+    csv.unregister_dialect(name)
+
+
 @contextmanager
 def use_numexpr(use, min_elements=None):
     from pandas.core.computation import expressions as expr