Comments (2)
I agree, though I find tag management to be not obvious to me. Can you provide your own workflow, or a workflow you have seen?
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If you are using no tool for this purpose I think the default way is in order to make a new release is:
- Update the
version
to the new version number in setup.py, let's call the version X.Y.Z - Also update
__version___
in__init__.py
to X.Y.Z what most tools provide, check numpy, scipy etc.
import numpy as np; print(np.__version__)
- Update your readme and changelog files to reflect the new version
- Run all your unit tests again and check that they work
- Commit this and call it "Version bump"
- Create a git tag X.Y.Z
- Build and submit the package to PyPI, i.e.
python setup.py bdist_wheel upload
My personal recommendation is to just use PyScaffold which will provide an automised version scheme during development. When you want to release it's only:
- Update Readme and Changelog
- Commit everything
- Create a git tag
- Build and submit your package
PyScaffold will handle the rest like setting the version number everywhere.
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Related Issues (20)
- Sometimes a test fails (test_uniform)
- tdigest.__version__ returns wrong version
- tdigest fails to serialize in spark
- Horribly slow on PyPy HOT 2
- Negative trimmed mean
- difference between java implementation and python HOT 8
- Updates to algorithm in latest paper [help needed] HOT 3
- wheel incorrectly contains `.pyc` files HOT 3
- Not able to install python package HOT 1
- CDF benchmark HOT 1
- well done HOT 1
- Is the code still maintained? HOT 1
- python2.7 ypeError: unbound method _cython_3_0_0a9.cython_function_or_method object must be called with RBTree instance as first argument (got AccumulationTree instance instead)
- pyspark example misses import
- Corner case where values are identical? HOT 1
- Best way to serialize and load HOT 1
- Scale function
- Tag request for git project: tdigest 0.5.2.2 HOT 1
- Conda Distribution
- Alternative faster t-digest implementation HOT 1
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