Add versioning release instructions, add boto3 version range #2829
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| * Ensure all dependencies have an upper cap, unless the reason is documented inline. | ||
| * Example of no upper cap: `scikit-learn>=1.0` |
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Discussion point: an Introduction of a overly aggressive upper cap would require binary releases every time we want to change the range. This significantly increase work for DLC patching (~1 wk becomes 3-4 weeks).
Pinning pros: repeatable builds
Pinning cons: require more frequent releases as the new CVEs coming.
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We already have aggressive upper caps on almost every dependency. We are planning to relax some of them this release (Numpy and SciPy)
| 2. Suppress the warning for the user + provide justification and appropriate TODOs. | ||
| 3. Avoid the range change and add an inline comment in setup.py that a warning occurred and why we didn't fix. | ||
| * Ensure CI passes, potentially benchmark to catch performance regressions / more complex bugs. | ||
| * Note: To truly catch potential errors, you will need to use the latest supported Python version, since some packages may only support the newer Python version in their latest releases. |
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We really need to test this on both sides of supported ranges: i.e. numpy at some point stopped 3.7 support; so 3.7 was stuck at <1.21, while 3.8/3.9 was 1.21+
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Yes, technically it is more complex to comprehensively test. We can add additional steps in future PRs.
| "statsmodels~=0.13.0", | ||
| "gluonts~=0.12.0", |
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This PR is not touching the version ranges to minimize potential merge conflicts with other PRs. A follow-up PR will be sent to clean up the ranges.
| "statsmodels~=0.13.0", | ||
| "gluonts~=0.12.0", | ||
| "torch>=1.9,<1.14", | ||
| "pytorch-lightning>=1.7.4,<1.9.0", | ||
| "networkx", | ||
| "networkx", # version range defined in `core/_setup_utils.py` | ||
| "statsforecast==1.4.0", |
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ditto; or if we pin, needs a comment
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Job PR-2829-cec3bbb is done. |
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Job PR-2829-c6de042 is done. |
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Description of changes:
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