Merge pull request #19 from jmenglund/develop

Develop

CHANGELOG.md

@@ -4,6 +4,19 @@ Tracking changes in pandas-validation between versions.
 See also https://github.com/jmenglund/pandas-validation/releases.
 
 
+## 0.4.0 ##
+
+This is a minor release with the following changes:
+
+* Non-NumPy numeric dtypes should now be supported.
+* The ValidationWarning is now issued att stack level 2. This makes it possible to
+  trace the line of code that called the function that raised the warning.
+
+Released: 2019-05-27
+
+[View commits](https://github.com/jmenglund/pandas-validation/compare/v0.3.2...v0.4.0)
+
+
 ## 0.3.2 ##
 
 This is a patch release that fixes an issue with validating numbers with `min_value=0`

docs/source/pandas-validation/quickstart.rst

@@ -17,11 +17,11 @@ know more, I suggest that you have a look at the :ref:`API reference<api>`.
 
 The code examples below assume that you first do the following imports:
 
-.. code-block:: python
+.. code-block:: pycon
 
-    import numpy as np
-    import pandas as pd
-    import pandasvalidation as pv
+    >>> import numpy as np
+    >>> import pandas as pd
+    >>> import pandasvalidation as pv
 
 
 .. _validate-dates:
@@ -36,18 +36,19 @@ user that some values are invalid. If `return_type` is set to ``values``, a
 pandas Series will be returned with only the valid datetime values.
 
 
-.. code-block:: python
+.. code-block:: pycon
 
-    s1 = pd.Series(
+    >>> s1 = pd.Series(
         ['2014', '2014-01-07', '2014-02-28', np.nan],
         name='My dates')
-    pv.validate_datetime(
+    >>> pv.validate_datetime(
         s1,
         nullable=False,
         unique=True,
         min_datetime='2014-01-05',
         max_datetime='2014-02-15',
         return_type=None)
+    ValidationWarning: 'My dates': NaT value(s); date(s) too early; date(s) too late.
 
 
 .. _validate-numbers:
@@ -60,20 +61,20 @@ Like in the example above, warnings will indicate invalid values to the user.
 If `return_type` is set to ``values``, a pandas Series will be returned with
 only the valid numeric values.
 
-.. code-block:: python
+.. code-block:: pycon
 
-    s2 = pd.Series(
+    >>> s2 = pd.Series(
         [1, '1', '2.3', np.nan],
         name='My numeric values')
-    pv.validate_numeric(
+    >>> pv.validate_numeric(
         s2,
         nullable=False,
         unique=True,
         integer=True,
         min_value=2,
         max_value=2,
         return_type=None)
-
+    ValidationWarning: 'My numeric values': NaN value(s); duplicates; non-integer(s); value(s) too low; values(s) too high.
 
 .. _validate-strings:
 
@@ -86,12 +87,12 @@ warnings then issued if there are invalid values. If `return_type` is
 set to ``values``, a pandas Series will be returned with only the valid
 strings.
 
-.. code-block:: python
+.. code-block:: pycon
 
-    s3 = pd.Series(
+    >>> s3 = pd.Series(
         [1, 1, 'ab\n', 'a b', 'Ab', 'AB', np.nan],
         name='My strings')
-    pv.validate_string(
+    >>> pv.validate_string(
         s3,
         nullable=False,
         unique=True,
@@ -102,3 +103,4 @@ strings.
         trailing_whitespace=False,
         whitespace=False,
         return_type=None)
+    ValidationWarning: 'My strings': NaN value(s); duplicates; string(s) too short; string(s) too long; wrong case letter(s); newline character(s); trailing whitespace; whitespace.

pandasvalidation.py

@@ -13,7 +13,7 @@
 
 __author__ = 'Markus Englund'
 __license__ = 'MIT'
-__version__ = '0.3.2'
+__version__ = '0.4.0'
 
 
 class ValidationWarning(Warning):
@@ -157,11 +157,11 @@ def to_datetime(
         if isinstance(arg, pandas.Series):
             warnings.warn(
                 '{}: value(s) not converted to datetime set as NaT'
-                .format(repr(arg.name)), ValidationWarning)
+                .format(repr(arg.name)), ValidationWarning, stacklevel=2)
         else:  # pragma: no cover
             warnings.warn(
                 'Value(s) not converted to datetime set as NaT',
-                ValidationWarning)
+                ValidationWarning, stacklevel=2)
     return converted
 
 
@@ -180,11 +180,11 @@ def to_numeric(arg):
         if isinstance(arg, pandas.Series):
             warnings.warn(
                 '{}: value(s) not converted to numeric set as NaN'
-                .format(repr(arg.name)), ValidationWarning)
+                .format(repr(arg.name)), ValidationWarning, stacklevel=2)
         else:  # pragma: no cover
             warnings.warn(
                 'Value(s) not converted to numeric set as NaN',
-                ValidationWarning)
+                ValidationWarning, stacklevel=2)
     return converted
 
 
@@ -261,7 +261,7 @@ def validate_datetime(
 
     if len(msg_list) > 0:
         msg = repr(series.name) + ': ' + '; '.join(msg_list) + '.'
-        warnings.warn(msg, ValidationWarning)
+        warnings.warn(msg, ValidationWarning, stacklevel=2)
 
     if return_type is not None:
         return _get_return_object(masks, converted, return_type)
@@ -299,7 +299,7 @@ def validate_numeric(
         'too_low': 'value(s) too low',
         'too_high': 'values(s) too high'}
 
-    if not numpy.issubdtype(series.dtype, numpy.number):
+    if not pandas.api.types.is_numeric_dtype(series.dtype):
         converted = pandas.to_numeric(series, errors='coerce')
     else:
         converted = series.copy()
@@ -323,7 +323,7 @@ def validate_numeric(
 
     if len(msg_list) > 0:
         msg = repr(series.name) + ': ' + '; '.join(msg_list) + '.'
-        warnings.warn(msg, ValidationWarning)
+        warnings.warn(msg, ValidationWarning, stacklevel=2)
 
     if return_type is not None:
         return _get_return_object(masks, converted, return_type)
@@ -436,7 +436,7 @@ def validate_string(
 
     if len(msg_list) > 0:
         msg = repr(series.name) + ': ' + '; '.join(msg_list) + '.'
-        warnings.warn(msg, ValidationWarning)
+        warnings.warn(msg, ValidationWarning, stacklevel=2)
 
     if return_type is not None:
         return _get_return_object(masks, converted, return_type)

release-checklist.rst

@@ -36,7 +36,7 @@ Things to remember when making a new release of pandas-validation.
 #.  Create pull request(s) with changes for the new release.
 
 #.  Create distributions and upload the files to
-    `PyPI <https://pypi.python.org/pypi>`_ with
+    `PyPI <https://pypi.org>`_ with
     `twine <https://github.com/pypa/twine>`_.
 
     .. code-block:: none

setup.py

@@ -4,7 +4,7 @@
 
 setup(
     name='pandas-validation',
-    version='0.3.2',
+    version='0.4.0',
     description=(
         'A Python package for validating data with pandas'),
     long_description=open(