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DEPS: Bump numpy to 1.13.3 #25554

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merged 25 commits into from Mar 28, 2019

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commented Mar 5, 2019

#25227 is trying to add pyproject.toml which is necessary for the whole pip-machinery to work smoothly post v.19.0. However, this seems to be running into problems with a numpy version bump, and mood there was to bump numpy requirement to 1.13.x.

The bare minimum for the bump is implemented in that PR, but a version bump requires getting rid of a bunch of compat code (and CI adjustments), otherwise the cruft just accumulates (it took me three PRs to clean out until 1.12).

Scipy is goint to bump to 1.13.3 with the next release (due to cython issues, I believe), so I thought I'll directly take it to 1.13.3 here.

I tried redistributing the CI jobs as best as I could. Here's the before/after:

EDIT: updated pins in #25554 (comment)

CI job: line number before this PR
ci/deps/azure-27-compat.yaml:10: numpy=1.12.0 numpy=1.13.3
ci/deps/azure-27-locale.yaml:10: numpy=1.12.0 numpy=1.14.*
ci/deps/azure-36-locale_slow.yaml:16: numpy numpy=1.15.*
ci/deps/azure-37-locale.yaml:15: numpy numpy
ci/deps/azure-37-numpydev.yaml:18: numpy numpy
ci/deps/azure-macos-35.yaml:14: numpy=1.12.0 numpy=1.13.3
ci/deps/azure-windows-27.yaml:15: numpy=1.12* numpy=1.13.3
ci/deps/azure-windows-36.yaml:12: numpy=1.14* numpy=1.15.*
ci/deps/travis-27.yaml:20: numpy=1.13* numpy=1.14.*
ci/deps/travis-36-doc.yaml:23: numpy=1.13* numpy
ci/deps/travis-36-locale.yaml:15: numpy numpy
ci/deps/travis-36-slow.yaml:12: numpy numpy
ci/deps/travis-36.yaml:17: numpy numpy=1.15.*
ci/deps/travis-37.yaml:10: numpy numpy

Matplotlib needs to be bumped as well (since current min 2.0.0 cannot be resolved by conda together with numpy 1.13.3), but it's only a tiny bump to 2.0.2 2.1.0 2.1.1 2.2.2. In any case, the version spread should probably start to reflect that there's a bunch of mpl 3.0.x about, and so I also changed the spread a bit here:

CI job: line number before this PR
ci/deps/azure-27-locale.yaml:9: matplotlib=2.0.0 matplotlib=2.2.2
ci/deps/azure-36-locale_slow.yaml:13: matplotlib matplotlib=3.0.*
ci/deps/azure-37-locale.yaml:12: matplotlib matplotlib
ci/deps/azure-macos-35.yaml:11: matplotlib=2.2.0 matplotlib=2.2.3
ci/deps/azure-windows-27.yaml:13: matplotlib=2.0.1 matplotlib=2.2.4
ci/deps/azure-windows-36.yaml:10: matplotlib matplotlib
ci/deps/travis-27.yaml:16: matplotlib=2.2.2 matplotlib=2.2.*
ci/deps/travis-36-doc.yaml:17: matplotlib matplotlib
ci/deps/travis-36-locale.yaml:12: matplotlib matplotlib=3.0.1
ci/deps/travis-36-slow.yaml:10: matplotlib matplotlib
ci/deps/travis-36.yaml:14: matplotlib matplotlib=3.0.0

It's probably wishful thinking that everything will pass straight away (especially when mpl versions change, see the code in pandas/tests/plotting/test_datetimelike.py), but oh well...

@h-vetinari h-vetinari referenced this pull request Mar 5, 2019

Closed

Specify build requirements in pyproject.toml (PEP 517) #25227

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commented Mar 5, 2019

Scipy is goint to bump to 1.13.3 with the next release (due to cython issues, I believe), so I thought I'll directly take it to 1.13.3 here.

Not due to Cython issues, just to reduce the maintenance burden. See https://mail.python.org/pipermail/scipy-dev/2018-November/023181.html for rationale.

+1 for going to 1.13.3 as well. Matplotlib is doing a similar thing (actually they want to be a bit more agressive), and wants to standardize a common Python/NumPy version support policy for core packages (see scipy/scipy#9610, we'll come back on that soon).

@gfyoung gfyoung added the Dependencies label Mar 6, 2019

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commented Mar 6, 2019

install.rst also needs a small update:

* `NumPy <http://www.numpy.org>`__: 1.12.0 or higher

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commented Mar 6, 2019

Codecov Report

Merging #25554 into master will decrease coverage by 0.48%.
The diff coverage is 100%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master   #25554      +/-   ##
==========================================
- Coverage   91.75%   91.26%   -0.49%     
==========================================
  Files         173      173              
  Lines       52960    52961       +1     
==========================================
- Hits        48595    48337     -258     
- Misses       4365     4624     +259
Flag Coverage Δ
#multiple 89.83% <100%> (-0.51%) ⬇️
#single 41.73% <75%> (+0.01%) ⬆️
Impacted Files Coverage Δ
pandas/core/arrays/categorical.py 95.96% <ø> (ø) ⬆️
pandas/core/arrays/sparse.py 92.17% <ø> (ø) ⬆️
pandas/compat/numpy/__init__.py 93.1% <100%> (-0.23%) ⬇️
pandas/plotting/_compat.py 87.5% <100%> (ø) ⬆️
pandas/core/groupby/generic.py 86.98% <100%> (-0.02%) ⬇️
pandas/core/arrays/numpy_.py 94.49% <100%> (+0.83%) ⬆️
pandas/core/panel.py 38.56% <0%> (-33.19%) ⬇️
pandas/core/sparse/series.py 93.3% <0%> (-2.24%) ⬇️
pandas/core/indexing.py 90.88% <0%> (-1.41%) ⬇️
pandas/core/internals/managers.py 93.92% <0%> (-0.92%) ⬇️
... and 5 more

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commented Mar 6, 2019

Codecov Report

Merging #25554 into master will increase coverage by 0.02%.
The diff coverage is 100%.

Impacted file tree graph

@@            Coverage Diff             @@
##           master   #25554      +/-   ##
==========================================
+ Coverage   91.53%   91.55%   +0.02%     
==========================================
  Files         175      175              
  Lines       52808    52775      -33     
==========================================
- Hits        48338    48320      -18     
+ Misses       4470     4455      -15
Flag Coverage Δ
#multiple 90.12% <100%> (+0.02%) ⬆️
#single 41.82% <71.42%> (-0.01%) ⬇️
Impacted Files Coverage Δ
pandas/core/missing.py 93.96% <ø> (+1.39%) ⬆️
pandas/util/_test_decorators.py 93.22% <ø> (+0.57%) ⬆️
pandas/core/arrays/datetimes.py 97.79% <ø> (-0.01%) ⬇️
pandas/core/arrays/categorical.py 95.96% <ø> (ø) ⬆️
pandas/core/arrays/sparse.py 92.17% <ø> (ø) ⬆️
pandas/core/computation/check.py 92.3% <100%> (ø) ⬆️
pandas/core/nanops.py 93.84% <100%> (ø) ⬆️
pandas/core/arrays/numpy_.py 94.49% <100%> (+0.83%) ⬆️
pandas/compat/numpy/__init__.py 93.1% <100%> (-0.23%) ⬇️
pandas/core/groupby/generic.py 87.03% <100%> (-0.02%) ⬇️
... and 4 more

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@jreback
Regarding pins, please have a look at the OP. Bumping numpy is always a good time to look at the distribution in the CI.

For numpy, there's currently 3x 1.12, 2x 1.13, 1x 1.14, ZERO 1.15 and 7 unpinned.
I'm proposing to make this 3x 1.13, 2x 1.14, 2x 1.15 and 6 unpinned.

For matplotlib, there's currently 2.0.0, 2.0.1, 2.2.0, 2.2.2 and 7 unpinned.
I'm proposing to make this 2.0.2 (new min), 2.1.0, 2.2.0, 2.2.* (LTS!), 3.0.0, 3.0.1, 3.0.* and 4 unpinned.

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commented Mar 6, 2019

I like @h-vetinari's proposed pins in
#25554 (comment)

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commented Mar 8, 2019

@jreback @TomAugspurger
This should be done now. :)

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LGTM.

@h-vetinari if you're interested, I believe that this will let us delete the following on SparseArray / SparseSeries

  • __array_wrap__
  • __array_prepare__
  • __array_priority__

Those are disabled when the class defines __array_ufunc__, which was started in NumPy 1.13

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commented Mar 10, 2019

@TomAugspurger
That sounds like a separate PR?

@jreback
PTAL

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commented Mar 10, 2019

@TomAugspurger: @h-vetinari if you're interested [...]

@h-vetinari: @TomAugspurger That sounds like a separate PR?

I've got an initial draft prepared, but will wait until this one is merged.

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commented Mar 10, 2019

this needs to wait until 0.24.2 is done and needs review

@@ -11,10 +11,10 @@ dependencies:
- gcsfs
- geopandas
- html5lib
- matplotlib
- matplotlib=3.0.0

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is there a reason this is pinned exactly to 3.0.0, which was superseded immedately by 3.0.1?

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There were almost three months between 3.0.0 and 3.0.1, see https://github.com/matplotlib/matplotlib/releases.

I just tried to spread some pins throughout the 3.x Series, see OP.

@@ -53,8 +53,10 @@ def setup_method(self, method):
import matplotlib as mpl
mpl.rcdefaults()

self.mpl_ge_2_0_1 = plotting._compat._mpl_ge_2_0_1()
self.mpl_eq_2_0_2 = plotting._compat._mpl_eq_2_0_2()

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I would just bump mpl to 2.1 min to avoid all of these extra things

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ok, will do, but the special casing for 2.2.0 will still be necessary, unless we bump to 2.2.2

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cc @tacaswell any thoughts here?

@jreback jreback added this to the 0.25.0 milestone Mar 10, 2019

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@jreback For pins, please check OP. Happy to change however you want. Will bump matplotlib pending further input from you (already to 2.2.2?)

@@ -11,10 +11,10 @@ dependencies:
- gcsfs
- geopandas
- html5lib
- matplotlib
- matplotlib=3.0.0

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There were almost three months between 3.0.0 and 3.0.1, see https://github.com/matplotlib/matplotlib/releases.

I just tried to spread some pins throughout the 3.x Series, see OP.

@@ -53,8 +53,10 @@ def setup_method(self, method):
import matplotlib as mpl
mpl.rcdefaults()

self.mpl_ge_2_0_1 = plotting._compat._mpl_ge_2_0_1()
self.mpl_eq_2_0_2 = plotting._compat._mpl_eq_2_0_2()

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ok, will do, but the special casing for 2.2.0 will still be necessary, unless we bump to 2.2.2

@jreback jreback referenced this pull request Mar 10, 2019

Merged

Remove py27 CI jobs #24942

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commented Mar 10, 2019

@jreback
Checked the MPL releases, and 2.2.2 is barely a year old. Therefore, I bumped only to 2.1.0.

@h-vetinari h-vetinari force-pushed the h-vetinari:bump_numpy branch from b25d597 to 3550ed4 Mar 11, 2019

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commented Mar 11, 2019

@jreback
OK, nevermind, I went to matplotlib 2.2.2 after all. By the time pandas 0.24.2 hits, this will be over a year old, and there's just too much variability in the MPL point releases for 2.1.x so that any starting point in 2.0.1 | 2.0.2 | 2.1.0 | 2.1.1 | 2.1.2 (and to a degree 2.2.0) would lead to lots of compat code (along the lines of what you didn't like above). And since 2.2.2 was only released 10 days after 2.2.0, I went to 2.2.2 right away.

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commented Mar 11, 2019

Sorry for the Matplotlib API thrashing.

2.2.x is the LTS version so it is a good choice!

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commented Mar 13, 2019

@jreback
I keep running into a weird cython error on the azure-windows-27 job:

running build_ext
pandas._libs.algos: -> [['pandas\\_libs/algos.c']]
Traceback (most recent call last):
  File "setup.py", line 751, in <module>
    **setuptools_kwargs)
  File "C:\Miniconda\lib\site-packages\setuptools\__init__.py", line 143, in setup
    return distutils.core.setup(**attrs)
  File "C:\Miniconda\lib\distutils\core.py", line 148, in setup
    dist.run_commands()
  File "C:\Miniconda\lib\distutils\dist.py", line 966, in run_commands
    self.run_command(cmd)
  File "C:\Miniconda\lib\distutils\dist.py", line 985, in run_command
    cmd_obj.run()
  File "C:\Miniconda\lib\distutils\command\build_ext.py", line 339, in run
    self.build_extensions()
  File "setup.py", line 372, in build_extensions
    self.check_cython_extensions(self.extensions)
  File "setup.py", line 369, in check_cython_extensions
    """.format(src=src))
Exception: Cython-generated file 'pandas\_libs/algos.c' not found.
                Cython is required to compile pandas from a development branch.
                Please install Cython or download a release package of pandas.

Bumping cython didn't help (resp. then the 3.5 jobs can't satisfy min). How about we drop the PY2 CI (#24942) first before bumping numpy?

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CLN: remove PY2 #25725

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commented Mar 19, 2019

@h-vetinari can you merge master on this now that Py2 CI jobs are out?

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commented Mar 19, 2019

@WillAyd: @h-vetinari can you merge master on this now that Py2 CI jobs are out?

Since #24942 was split up, this PR here still depends on #25752. It would be helpful if you could give the latter one a look. :)

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commented Mar 23, 2019

Currently rebasing on top of #25752. This is the current set of pins for python/numpy/matplotlib. Comments welcome.

CI job: line number OS python numpy mpl
azure-35-compat.yaml:10: posix python=3.5.* numpy=1.13.3 -
azure-36-locale.yaml:10: posix python=3.6.* numpy=1.14.* matplotlib=2.2.2
azure-36-locale_slow.yaml:16: posix python=3.6.* numpy=1.15.* matplotlib=3.0.*
azure-37-locale.yaml:15: posix python=3.7.* numpy matplotlib
azure-37-numpydev.yaml:18: posix python=3.7.* numpy -
azure-macos-35.yaml:14: macos python=3.5.* numpy=1.13.3 matplotlib=2.2.3
azure-windows-36.yaml:15: win python=3.6.* numpy=1.15.* matplotlib=3.0.2
azure-windows-37.yaml:12: win python=3.7.* numpy=1.14.* matplotlib=2.2.*
travis-36-cov.yaml:17: posix python=3.6.* numpy=1.15.* matplotlib
travis-36-doc.yaml:23: posix python=3.6.* numpy matplotlib
travis-36-locale.yaml:15: posix python=3.6.* numpy matplotlib=3.0.0
travis-36-slow.yaml:12: posix python=3.6.* numpy matplotlib
travis-37.yaml:10: posix python=3.7.* numpy -

PS. Note that matplotlib 3.0.1 was superseded by 3.0.2 within a day.

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commented Mar 23, 2019

see if we can remove 1 or more jobs keeping the same coverage (reasonably) of deps (can be a follow up)
i don’t think it’s a big deal if we only test oldest numpy and then newest
1.14/1.15 or pretty much compat with 1.16

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commented Mar 23, 2019

Well, I didn't design the CI jobs - there's OSes, numpies, locales, DB tests. Not sure we should reduce much more, but from the table above, I'd get rid of travis-3.6-locale.

Maybe @TomAugspurger @jorisvandenbossche want to opine?

Also, we still need to actually merge #25752.

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ok looks good. don't make any more changes, except for chopping the whatsnew as indicated. ping on green.

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Below is an overview of the minimal versions, as required resp. recommended. Optional libraries below the lowest tested version may still work, but are not considered supported.

+-----------------+-----------------+-----------------------+
| Package | Minimum Version | Comment |

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this is too verbose. pls separate into 2 tables, the basic deps (numpy, pytz, bottleneck, numexpr); make the table like we had it exactly

you can make a table for other things, but i am going to limit that list.

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I kept pytest due to #23519.

I kept the structure of the table because the distinction between the kind of requirement (hard requirement vs. requirement if installed) is clearer like this, and fits with the other table.

+-----------------+-----------------+-----------------------+
| numexpr | 2.6.2 | Required if installed |
+-----------------+-----------------+-----------------------+
| beautifulsoup4 | 4.4.1 | Lowest tested version |

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remove beautifulsoup, blosc, gcfs, junja2, lxml, psycopg2, pymsql, s3fs, cython and pytest

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h-vetinari Mar 26, 2019

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pytest was explicitly added to this table by #23519.

I added all the libraries from https://pandas-docs.github.io/pandas-docs-travis/install.html#dependencies. I think this is a worthwhile overview to have somewhere (maybe not the whatsnew). Thoughts, @datapythonista?

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Will follow up later today, no time right now.

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+-----------------+-----------------+-----------------------+
| numexpr | 2.6.2 | Required if installed |
+-----------------+-----------------+-----------------------+
| beautifulsoup4 | 4.4.1 | Lowest tested version |

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h-vetinari Mar 26, 2019

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pytest was explicitly added to this table by #23519.

I added all the libraries from https://pandas-docs.github.io/pandas-docs-travis/install.html#dependencies. I think this is a worthwhile overview to have somewhere (maybe not the whatsnew). Thoughts, @datapythonista?

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PTAL

Below is an overview of the minimal versions, as required resp. recommended. Optional libraries below the lowest tested version may still work, but are not considered supported.

+-----------------+-----------------+-----------------------+
| Package | Minimum Version | Comment |

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I kept pytest due to #23519.

I kept the structure of the table because the distinction between the kind of requirement (hard requirement vs. requirement if installed) is clearer like this, and fits with the other table.

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commented Mar 27, 2019

@jreback
Argh, now we're right back to the errors I had fixed with the regex stuff that you reverted against my request. #25874

r"')|"
r"unorderable types: int\(\) > datetime\.datetime\(\)")
msg = ("unorderable types: ({0} [<>] {1}|{1} [<>] {0})".format(
r"int\(\)", r"datetime\.datetime\(\)") # noqa: E126

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this fails the wheel building CI. pls don't revert this, I don't want to debug this problem. Just make this MUCH simpler so it will pretty much always pass.

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It will not fail the wheel building CI. I actually checked the wheel builder failures from #25867 before giving my review in #25874.

In case you don't have time to read the review, the original code in #25752 has an if _np_version_under1p14 else-switch that turned out to be wrong, while the regex here only uses a |-conjunction.

[...] I don't want to debug this problem.

Neither did I, but I've had to for a passing CI. Please have a look at the actual regexes. What I've written is a proper superset of the current regexes (again, now that the switch has been turned into "|").

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Just make this MUCH simpler so it will pretty much always pass.

Done.

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pls just make the changes I indicated. otherwise this iteration cycle will continue to extend.

+-----------------+-----------------+-----------------------+
| numexpr | 2.6.2 | Required if installed |
+-----------------+-----------------+-----------------------+
| pytest | 4.0.2 | Development-only req. |

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this is a misleading comment for pytest. its required if you run tests

Require if installed is very misleading, remove it

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I reverted it. That being said, pytest is not necessary to run pandas, so it is "as required" as, say openpyxl to write excel files.

The following table lists the lowest version per library that is currently being tested throughout the development of pandas.
Optional libraries below the lowest tested version may still work, but are not considered supported.

+-----------------+-----------------+-----------------------+

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remove the comment column.

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Done.

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Updated. Please take the time to read my comment about the regex.

+-----------------+-----------------+-----------------------+
| numexpr | 2.6.2 | Required if installed |
+-----------------+-----------------+-----------------------+
| pytest | 4.0.2 | Development-only req. |

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I reverted it. That being said, pytest is not necessary to run pandas, so it is "as required" as, say openpyxl to write excel files.

The following table lists the lowest version per library that is currently being tested throughout the development of pandas.
Optional libraries below the lowest tested version may still work, but are not considered supported.

+-----------------+-----------------+-----------------------+

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h-vetinari Mar 27, 2019

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Done.

r"')|"
r"unorderable types: int\(\) > datetime\.datetime\(\)")
msg = ("unorderable types: ({0} [<>] {1}|{1} [<>] {0})".format(
r"int\(\)", r"datetime\.datetime\(\)") # noqa: E126

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h-vetinari Mar 27, 2019

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It will not fail the wheel building CI. I actually checked the wheel builder failures from #25867 before giving my review in #25874.

In case you don't have time to read the review, the original code in #25752 has an if _np_version_under1p14 else-switch that turned out to be wrong, while the regex here only uses a |-conjunction.

[...] I don't want to debug this problem.

Neither did I, but I've had to for a passing CI. Please have a look at the actual regexes. What I've written is a proper superset of the current regexes (again, now that the switch has been turned into "|").

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commented Mar 28, 2019

It will not fail the wheel building CI. I actually checked the wheel builder failures from #25867 before giving my review in #25874.

not sure what you are talking about. it DID fail. The reverted does not. If you fixed it great. I want to avoid having broken CI's endlessly.

@jreback jreback merged commit 68dd979 into pandas-dev:master Mar 28, 2019

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commented Mar 28, 2019

thanks

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commented Mar 28, 2019

@h-vetinari looks like this broke the gbq tests; these are pretty funky and I don't think are tested on actual branches (thoguh they used to be AFAIR): see https://travis-ci.org/pandas-dev/pandas/jobs/512494733

so pls do a PR to disable for now.

@h-vetinari h-vetinari referenced this pull request Mar 28, 2019

Merged

Fix pandas-gbq deps #25912

@h-vetinari h-vetinari deleted the h-vetinari:bump_numpy branch Mar 28, 2019

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commented Mar 28, 2019

@jreback: not sure what you are talking about. it DID fail. The reverted does not. If you fixed it great. I want to avoid having broken CI's endlessly.

I did fail, and I had fixed it (not by reverting exactly, but then I've tried to explain that already twice). Now it's more simplified anyway, which is IMO anyway a better approach for matching these error messages.

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