Restore CI after PY2 drop

ci/azure/posix.yml

@@ -15,6 +15,18 @@ jobs:
           PATTERN: "not slow and not network"
 
       ${{ if eq(parameters.name, 'Linux') }}:
+        py35_compat:
+          ENV_FILE: ci/deps/azure-35-compat.yaml
+          CONDA_PY: "35"
+          PATTERN: "not slow and not network"
+
+        py36_locale_slow_old_np:
+          ENV_FILE: ci/deps/azure-36-locale.yaml
+          CONDA_PY: "36"
+          PATTERN: "slow"
+          LOCALE_OVERRIDE: "zh_CN.UTF-8"
+          EXTRA_APT: "language-pack-zh-hans"
+
         py36_locale_slow:
           ENV_FILE: ci/deps/azure-36-locale_slow.yaml
           CONDA_PY: "36"

ci/azure/windows.yml

@@ -12,6 +12,10 @@ jobs:
         ENV_FILE: ci/deps/azure-windows-36.yaml
         CONDA_PY: "36"
 
+      py37_np141:
+        ENV_FILE: ci/deps/azure-windows-37.yaml
+        CONDA_PY: "37"
+
   steps:
     - task: CondaEnvironment@1
       inputs:

ci/deps/azure-35-compat.yaml

@@ -0,0 +1,29 @@
+name: pandas-dev
+channels:
+  - defaults
+  - conda-forge
+dependencies:
+  - beautifulsoup4==4.4.1
+  - bottleneck=1.2.0
+  - cython=0.28.2
+  - hypothesis>=3.58.0
+  - jinja2=2.8
+  - numexpr=2.6.1
+  - numpy=1.12.0
+  - openpyxl=2.4.0
+  - pytables=3.4.2
+  - python-dateutil=2.5.0
+  - python=3.5*
+  - pytz=2015.4
+  - scipy=0.18.1
+  - xlrd=1.0.0
+  - xlsxwriter=0.7.7
+  - xlwt=1.0.0
+  # universal
+  - pytest-xdist
+  - pytest-mock
+  - isort
+  - pip:
+    # for python 3.5, pytest>=4.0.2 is not available in conda
+    - pytest>=4.0.2
+    - html5lib==1.0b2

ci/deps/azure-36-locale.yaml

@@ -0,0 +1,29 @@
+name: pandas-dev
+channels:
+  - defaults
+  - conda-forge
+dependencies:
+  - beautifulsoup4==4.5.1
+  - bottleneck=1.2.0
+  - cython=0.28.2
+  - lxml
+  - matplotlib=2.0.0
+  - numpy=1.12.0
+  - openpyxl=2.4.0
+  - python-dateutil
+  - python-blosc
+  - python=3.6
+  - pytz=2016.10
+  - scipy
+  - sqlalchemy=1.1.4
+  - xlrd=1.0.0
+  - xlsxwriter=0.9.4
+  - xlwt=1.2.0
+  # universal
+  - pytest>=4.0.2
+  - pytest-xdist
+  - pytest-mock
+  - hypothesis>=3.58.0
+  - isort
+  - pip:
+    - html5lib==1.0b2

ci/deps/azure-macos-35.yaml

@@ -12,7 +12,7 @@ dependencies:
   - nomkl
   - numexpr
   - numpy=1.12.0
-  - openpyxl=2.5.5
+  - openpyxl
   - pyarrow
   - pytables
   - python=3.5*

ci/deps/azure-windows-37.yaml

@@ -0,0 +1,33 @@
+name: pandas-dev
+channels:
+  - defaults
+  - conda-forge
+dependencies:
+  - beautifulsoup4
+  - bottleneck
+  - gcsfs
+  - html5lib
+  - jinja2
+  - lxml
+  - matplotlib=3.0.1
+  - numexpr
+  - numpy=1.14.*
+  - openpyxl
+  - pytables
+  - python=3.7.*
+  - python-dateutil
+  - pytz
+  - s3fs
+  - scipy
+  - sqlalchemy
+  - xlrd
+  - xlsxwriter
+  - xlwt
+  # universal
+  - cython>=0.28.2
+  - pytest>=4.0.2
+  - pytest-xdist
+  - pytest-mock
+  - moto
+  - hypothesis>=3.58.0
+  - isort

ci/deps/travis-36-locale.yaml

@@ -15,7 +15,7 @@ dependencies:
   - numpy
   - openpyxl
   - psycopg2
-  - pymysql
+  - pymysql=0.7.9
   - pytables
   - python-dateutil
   - python=3.6*

doc/source/install.rst

@@ -259,7 +259,7 @@ Optional Dependencies
 * `PyTables <http://www.pytables.org>`__: necessary for HDF5-based storage, Version 3.4.2 or higher
 * `pyarrow <http://arrow.apache.org/docs/python/>`__ (>= 0.9.0): necessary for feather-based storage.
 * `Apache Parquet <https://parquet.apache.org/>`__, either `pyarrow <http://arrow.apache.org/docs/python/>`__ (>= 0.7.0) or `fastparquet <https://fastparquet.readthedocs.io/en/latest>`__ (>= 0.2.1) for parquet-based storage. The `snappy <https://pypi.org/project/python-snappy>`__ and `brotli <https://pypi.org/project/brotlipy>`__ are available for compression support.
-* `SQLAlchemy <http://www.sqlalchemy.org>`__: for SQL database support. Version 1.0.8 or higher recommended. Besides SQLAlchemy, you also need a database specific driver. You can find an overview of supported drivers for each SQL dialect in the `SQLAlchemy docs <http://docs.sqlalchemy.org/en/latest/dialects/index.html>`__. Some common drivers are:
+* `SQLAlchemy <http://www.sqlalchemy.org>`__: for SQL database support. Version 1.1.4 or higher recommended. Besides SQLAlchemy, you also need a database specific driver. You can find an overview of supported drivers for each SQL dialect in the `SQLAlchemy docs <http://docs.sqlalchemy.org/en/latest/dialects/index.html>`__. Some common drivers are:
 
     * `psycopg2 <http://initd.org/psycopg/>`__: for PostgreSQL
     * `pymysql <https://github.com/PyMySQL/PyMySQL>`__: for MySQL.

doc/source/whatsnew/v0.25.0.rst

@@ -123,13 +123,13 @@ If installed, we now require:
 +=================+=================+==========+
 | beautifulsoup4  | 4.4.1           |          |
 +-----------------+-----------------+----------+
-| openpyxl        | 2.2.6           |          |
+| openpyxl        | 2.4.0           |          |
 +-----------------+-----------------+----------+
-| pymysql         | 0.6.6           |          |
+| pymysql         | 0.7.9           |          |
 +-----------------+-----------------+----------+
 | pytz            | 2015.4          |          |
 +-----------------+-----------------+----------+
-| sqlalchemy      | 1.0.8           |          |
+| sqlalchemy      | 1.1.4           |          |
 +-----------------+-----------------+----------+
 | xlsxwriter      | 0.7.7           |          |
 +-----------------+-----------------+----------+

pandas/tests/test_algos.py

@@ -20,7 +20,7 @@
 import pandas as pd
 from pandas import (
     Categorical, CategoricalIndex, DatetimeIndex, Index, IntervalIndex, Series,
-    Timestamp, compat)
+    Timestamp, _np_version_under1p14, compat)
 import pandas.core.algorithms as algos
 from pandas.core.arrays import DatetimeArray
 import pandas.core.common as com
@@ -228,9 +228,11 @@ def test_complex_sorting(self):
         # gh 12666 - check no segfault
         x17 = np.array([complex(i) for i in range(17)], dtype=object)
 
-        msg = (r"'(<|>)' not supported between instances of 'complex' and"
-               r" 'complex'|"
-               r"unorderable types: complex\(\) > complex\(\)")
+        msg = (r"unorderable types: {0} [<>] {0}".format(r"complex\(\)")
+               if _np_version_under1p14 else
+               r"'[<>]' not supported between instances of {0} and {0}".format(
+                   "'complex'")
+               )
         with pytest.raises(TypeError, match=msg):
             algos.factorize(x17[::-1], sort=True)
 

pandas/tests/test_sorting.py

@@ -7,7 +7,8 @@
 import pytest
 
 from pandas import (
-    DataFrame, MultiIndex, Series, compat, concat, merge, to_datetime)
+    DataFrame, MultiIndex, Series, _np_version_under1p14, compat, concat,
+    merge, to_datetime)
 from pandas.core import common as com
 from pandas.core.sorting import (
     decons_group_index, get_group_index, is_int64_overflow_possible,
@@ -413,10 +414,13 @@ def test_mixed_integer_from_list(self):
     def test_unsortable(self):
         # GH 13714
         arr = np.array([1, 2, datetime.now(), 0, 3], dtype=object)
-        msg = (r"'(<|>)' not supported between instances of ('"
-               r"datetime\.datetime' and 'int'|'int' and 'datetime\.datetime"
-               r"')|"
-               r"unorderable types: int\(\) > datetime\.datetime\(\)")
+        msg = (r"unorderable types: ({0} [<>] {1}|{1} [<>] {0})".format(
+                   r"int\(\)", r"datetime\.datetime\(\)")  # noqa: E126
+               if _np_version_under1p14 else
+               (r"'[<>]' not supported between instances of "
+                r"({0} and {1}|{1} and {0})").format(
+                    "'int'", r"'datetime\.datetime'")
+               )
         with pytest.raises(TypeError, match=msg):
             safe_sort(arr)