TST: Fail on warning

.travis.yml

@@ -64,7 +64,7 @@ matrix:
     # In allow_failures
     - dist: trusty
       env:
-        - JOB="3.6, NumPy dev" ENV_FILE="ci/travis-36-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
+        - JOB="3.7, NumPy dev" ENV_FILE="ci/travis-37-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network -W error" PANDAS_TESTING_MODE="deprecate"
       addons:
         apt:
           packages:
@@ -79,7 +79,7 @@ matrix:
           - JOB="3.6, slow" ENV_FILE="ci/travis-36-slow.yaml" SLOW=true
       - dist: trusty
         env:
-          - JOB="3.6, NumPy dev" ENV_FILE="ci/travis-36-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network" PANDAS_TESTING_MODE="deprecate"
+          - JOB="3.7, NumPy dev" ENV_FILE="ci/travis-37-numpydev.yaml" TEST_ARGS="--skip-slow --skip-network -W error" PANDAS_TESTING_MODE="deprecate"
         addons:
           apt:
             packages:

ci/travis-36-numpydev.yaml → ci/travis-37-numpydev.yaml

@@ -2,7 +2,7 @@ name: pandas
 channels:
   - defaults
 dependencies:
-  - python=3.6*
+  - python=3.7*
   - pytz
   - Cython>=0.28.2
   # universal

doc/source/contributing.rst

@@ -859,6 +859,32 @@ preferred if the inputs or logic are simple, with Hypothesis tests reserved
 for cases with complex logic or where there are too many combinations of
 options or subtle interactions to test (or think of!) all of them.
 
+.. _warnings:
+
+Warnings
+~~~~~~~~
+
+By default, pandas test suite will fail if any unhandled warnings are emitted.
+
+If your change involves checking that a warning is actually emitted, use
+``tm.assert_produces_warning(ExpectedWarning)``. We prefer this to pytest's
+``pytest.warns`` context manager because ours checks that the warning's stacklevel
+is set correctly.
+
+If you have a test that would emit a warning, but you aren't actually testing the
+warning it self (say because it's going to be removed in the future, or because we're
+matching a 3rd-party library's behavior), then use ``pytest.mark.filterwarnings`` to
+ignore the error.
+
+```
+@pytest.mark.filterwarnings("ignore:msg:category")
+def test_thing(self):
+    ...
+```
+
+If the test generates a warning of class ``category`` whose message starts
+with ``msg``, the warning will be ignored and the test will pass.
+
 
 Running the test suite
 ----------------------

pandas/compat/__init__.py

@@ -38,6 +38,7 @@
 import struct
 import inspect
 from collections import namedtuple
+import collections
 
 PY2 = sys.version_info[0] == 2
 PY3 = sys.version_info[0] >= 3
@@ -135,6 +136,11 @@ def lfilter(*args, **kwargs):
 
     from importlib import reload
     reload = reload
+    Hashable = collections.abc.Hashable
+    Iterable = collections.abc.Iterable
+    Mapping = collections.abc.Mapping
+    Sequence = collections.abc.Sequence
+    Sized = collections.abc.Sized
 
 else:
     # Python 2
@@ -190,6 +196,12 @@ def get_range_parameters(data):
 
     reload = builtins.reload
 
+    Hashable = collections.Hashable
+    Iterable = collections.Iterable
+    Mapping = collections.Mapping
+    Sequence = collections.Sequence
+    Sized = collections.Sized
+
 if PY2:
     def iteritems(obj, **kw):
         return obj.iteritems(**kw)

pandas/compat/chainmap_impl.py

@@ -1,4 +1,11 @@
-from collections import MutableMapping
+import sys
+
+PY3 = sys.version_info[0] >= 3
+
+if PY3:
+    from collections.abc import MutableMapping
+else:
+    from collections import MutableMapping
 
 try:
     from thread import get_ident

pandas/conftest.py

@@ -31,6 +31,16 @@ def pytest_addoption(parser):
                      help="Fail if a test is skipped for missing data file.")
 
 
+def pytest_collection_modifyitems(items):
+    # Make unhandled ResourceWarnings fail early to track down
+    # https://github.com/pandas-dev/pandas/issues/22675
+    if PY3:
+        for item in items:
+            item.add_marker(
+                pytest.mark.filterwarnings("error::ResourceWarning")
+            )
+
+
 def pytest_runtest_setup(item):
     if 'slow' in item.keywords and item.config.getoption("--skip-slow"):
         pytest.skip("skipping due to --skip-slow")

pandas/core/algorithms.py

@@ -3,7 +3,7 @@
 intended for public consumption
 """
 from __future__ import division
-from warnings import warn, catch_warnings
+from warnings import warn, catch_warnings, simplefilter
 from textwrap import dedent
 
 import numpy as np
@@ -91,7 +91,8 @@ def _ensure_data(values, dtype=None):
 
             # ignore the fact that we are casting to float
             # which discards complex parts
-            with catch_warnings(record=True):
+            with catch_warnings():
+                simplefilter("ignore", np.ComplexWarning)
                 values = ensure_float64(values)
             return values, 'float64', 'float64'
 

pandas/core/arrays/datetimelike.py

@@ -59,6 +59,7 @@ def cmp_method(self, other):
         # numpy will show a DeprecationWarning on invalid elementwise
         # comparisons, this will raise in the future
         with warnings.catch_warnings(record=True):
+            warnings.filterwarnings("ignore", "elementwise", FutureWarning)
             with np.errstate(all='ignore'):
                 result = op(self.values, np.asarray(other))
 

pandas/core/arrays/integer.py

@@ -5,7 +5,7 @@
 
 from pandas._libs.lib import infer_dtype
 from pandas.util._decorators import cache_readonly
-from pandas.compat import u, range
+from pandas.compat import u, range, string_types
 from pandas.compat import set_function_name
 
 from pandas.core.dtypes.cast import astype_nansafe
@@ -147,6 +147,11 @@ def coerce_to_array(values, dtype, mask=None, copy=False):
             dtype = values.dtype
 
     if dtype is not None:
+        if (isinstance(dtype, string_types) and
+                (dtype.startswith("Int") or dtype.startswith("UInt"))):
+            # Avoid DeprecationWarning from NumPy about np.dtype("Int64")
+            # https://github.com/numpy/numpy/pull/7476
+            dtype = dtype.lower()
         if not issubclass(type(dtype), _IntegerDtype):
             try:
                 dtype = _dtypes[str(np.dtype(dtype))]
@@ -508,6 +513,7 @@ def cmp_method(self, other):
             # numpy will show a DeprecationWarning on invalid elementwise
             # comparisons, this will raise in the future
             with warnings.catch_warnings(record=True):
+                warnings.filterwarnings("ignore", "elementwise", FutureWarning)
                 with np.errstate(all='ignore'):
                     result = op(self._data, other)
 

pandas/core/common.py

@@ -356,7 +356,7 @@ def standardize_mapping(into):
             return partial(
                 collections.defaultdict, into.default_factory)
         into = type(into)
-    if not issubclass(into, collections.Mapping):
+    if not issubclass(into, compat.Mapping):
         raise TypeError('unsupported type: {into}'.format(into=into))
     elif into == collections.defaultdict:
         raise TypeError(

pandas/core/computation/eval.py

@@ -323,6 +323,7 @@ def eval(expr, parser='pandas', engine=None, truediv=True,
             # to use a non-numeric indexer
             try:
                 with warnings.catch_warnings(record=True):
+                    # TODO: Filter the warnings we actually care about here.
                     target[assigner] = ret
             except (TypeError, IndexError):
                 raise ValueError("Cannot assign expression output to target")

pandas/core/dtypes/inference.py

@@ -1,10 +1,9 @@
 """ basic inference routines """
 
-import collections
 import re
 import numpy as np
-from collections import Iterable
 from numbers import Number
+from pandas import compat
 from pandas.compat import (PY2, string_types, text_type,
                            string_and_binary_types, re_type)
 from pandas._libs import lib
@@ -112,7 +111,7 @@ def _iterable_not_string(obj):
     False
     """
 
-    return (isinstance(obj, collections.Iterable) and
+    return (isinstance(obj, compat.Iterable) and
             not isinstance(obj, string_types))
 
 
@@ -284,7 +283,7 @@ def is_list_like(obj):
     False
     """
 
-    return (isinstance(obj, Iterable) and
+    return (isinstance(obj, compat.Iterable) and
             # we do not count strings/unicode/bytes as list-like
             not isinstance(obj, string_and_binary_types) and
             # exclude zero-dimensional numpy arrays, effectively scalars

pandas/core/frame.py

@@ -418,9 +418,9 @@ def __init__(self, data=None, index=None, columns=None, dtype=None,
                                          copy=copy)
 
         # For data is list-like, or Iterable (will consume into list)
-        elif (isinstance(data, collections.Iterable)
+        elif (isinstance(data, compat.Iterable)
               and not isinstance(data, string_and_binary_types)):
-            if not isinstance(data, collections.Sequence):
+            if not isinstance(data, compat.Sequence):
                 data = list(data)
             if len(data) > 0:
                 if is_list_like(data[0]) and getattr(data[0], 'ndim', 1) == 1:
@@ -7655,7 +7655,7 @@ def _to_arrays(data, columns, coerce_float=False, dtype=None):
     if isinstance(data[0], (list, tuple)):
         return _list_to_arrays(data, columns, coerce_float=coerce_float,
                                dtype=dtype)
-    elif isinstance(data[0], collections.Mapping):
+    elif isinstance(data[0], compat.Mapping):
         return _list_of_dict_to_arrays(data, columns,
                                        coerce_float=coerce_float, dtype=dtype)
     elif isinstance(data[0], Series):

pandas/core/groupby/generic.py

@@ -758,7 +758,7 @@ def aggregate(self, func_or_funcs, *args, **kwargs):
         if isinstance(func_or_funcs, compat.string_types):
             return getattr(self, func_or_funcs)(*args, **kwargs)
 
-        if isinstance(func_or_funcs, collections.Iterable):
+        if isinstance(func_or_funcs, compat.Iterable):
             # Catch instances of lists / tuples
             # but not the class list / tuple itself.
             ret = self._aggregate_multiple_funcs(func_or_funcs,

pandas/core/indexes/base.py

@@ -98,6 +98,7 @@ def cmp_method(self, other):
             # numpy will show a DeprecationWarning on invalid elementwise
             # comparisons, this will raise in the future
             with warnings.catch_warnings(record=True):
+                warnings.filterwarnings("ignore", "elementwise", FutureWarning)
                 with np.errstate(all='ignore'):
                     result = op(self.values, np.asarray(other))
 

pandas/core/internals/blocks.py

@@ -3490,6 +3490,7 @@ def _putmask_smart(v, m, n):
 
         # we ignore ComplexWarning here
         with warnings.catch_warnings(record=True):
+            warnings.simplefilter("ignore", np.ComplexWarning)
             nn_at = nn.astype(v.dtype)
 
         # avoid invalid dtype comparisons

pandas/core/series.py

@@ -6,7 +6,6 @@
 # pylint: disable=E1101,E1103
 # pylint: disable=W0703,W0622,W0613,W0201
 
-import collections
 import warnings
 from textwrap import dedent
 
@@ -242,8 +241,8 @@ def __init__(self, data=None, index=None, dtype=None, name=None,
                 raise TypeError("{0!r} type is unordered"
                                 "".format(data.__class__.__name__))
             # If data is Iterable but not list-like, consume into list.
-            elif (isinstance(data, collections.Iterable)
-                  and not isinstance(data, collections.Sized)):
+            elif (isinstance(data, compat.Iterable)
+                  and not isinstance(data, compat.Sized)):
                 data = list(data)
             else:
 

pandas/core/window.py

@@ -2387,11 +2387,13 @@ def dataframe_from_int_dict(data, frame_template):
                     if not arg2.columns.is_unique:
                         raise ValueError("'arg2' columns are not unique")
                     with warnings.catch_warnings(record=True):
+                        warnings.simplefilter("ignore", RuntimeWarning)
                         X, Y = arg1.align(arg2, join='outer')
                     X = X + 0 * Y
                     Y = Y + 0 * X
 
                     with warnings.catch_warnings(record=True):
+                        warnings.simplefilter("ignore", RuntimeWarning)
                         res_columns = arg1.columns.union(arg2.columns)
                     for col in res_columns:
                         if col in X and col in Y:

pandas/io/html.py

@@ -6,14 +6,14 @@
 import os
 import re
 import numbers
-import collections
 
 from distutils.version import LooseVersion
 
 from pandas.core.dtypes.common import is_list_like
 from pandas.errors import EmptyDataError
 from pandas.io.common import _is_url, urlopen, _validate_header_arg
 from pandas.io.parsers import TextParser
+from pandas import compat
 from pandas.compat import (lrange, lmap, u, string_types, iteritems,
                            raise_with_traceback, binary_type)
 from pandas import Series
@@ -859,7 +859,7 @@ def _validate_flavor(flavor):
         flavor = 'lxml', 'bs4'
     elif isinstance(flavor, string_types):
         flavor = flavor,
-    elif isinstance(flavor, collections.Iterable):
+    elif isinstance(flavor, compat.Iterable):
         if not all(isinstance(flav, string_types) for flav in flavor):
             raise TypeError('Object of type {typ!r} is not an iterable of '
                             'strings'

pandas/io/pickle.py

@@ -160,7 +160,8 @@ def try_read(path, encoding=None):
         # GH 6899
         try:
             with warnings.catch_warnings(record=True):
-                # We want to silencce any warnings about, e.g. moved modules.
+                # We want to silence any warnings about, e.g. moved modules.
+                warnings.simplefilter("ignore", Warning)
                 return read_wrapper(lambda f: pkl.load(f))
         except Exception:
             # reg/patched pickle

pandas/tests/api/test_api.py

@@ -1,6 +1,5 @@
 # -*- coding: utf-8 -*-
 import sys
-from warnings import catch_warnings
 
 import pytest
 import pandas as pd
@@ -175,30 +174,30 @@ def test_get_store(self):
 
 class TestJson(object):
 
+    @pytest.mark.filterwarnings("ignore")
     def test_deprecation_access_func(self):
-        with catch_warnings(record=True):
-            pd.json.dumps([])
+        pd.json.dumps([])
 
 
 class TestParser(object):
 
+    @pytest.mark.filterwarnings("ignore")
     def test_deprecation_access_func(self):
-        with catch_warnings(record=True):
-            pd.parser.na_values
+        pd.parser.na_values
 
 
 class TestLib(object):
 
+    @pytest.mark.filterwarnings("ignore")
     def test_deprecation_access_func(self):
-        with catch_warnings(record=True):
-            pd.lib.infer_dtype('foo')
+        pd.lib.infer_dtype('foo')
 
 
 class TestTSLib(object):
 
+    @pytest.mark.filterwarnings("ignore")
     def test_deprecation_access_func(self):
-        with catch_warnings(record=True):
-            pd.tslib.Timestamp('20160101')
+        pd.tslib.Timestamp('20160101')
 
 
 class TestTypes(object):