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id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at ▲ | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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1118113789 | PR_kwDOAMm_X84xxbjr | 6207 | Fix missing dependecy definition of 'packaging' | s-weigand 9513634 | closed | 0 | 19 | 2022-01-29T08:19:09Z | 2022-02-01T18:29:04Z | 2022-01-31T23:51:59Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/6207 | Hi there, we just wanted to upgrade
```console $ johnnydep xarray 2022-01-29 08:28:38 [info ] init johnnydist [johnnydep.lib] dist=xarray parent=None 2022-01-29 08:28:40 [info ] init johnnydist [johnnydep.lib] dist=numpy>=1.18 parent=xarray 2022-01-29 08:28:44 [info ] init johnnydist [johnnydep.lib] dist=pandas>=1.1 parent=xarray 2022-01-29 08:28:47 [info ] init johnnydist [johnnydep.lib] dist=numpy>=1.18.5 parent=pandas>=1.1 2022-01-29 08:28:51 [info ] init johnnydist [johnnydep.lib] dist=python-dateutil>=2.8.1 parent=pandas>=1.1 2022-01-29 08:28:53 [info ] init johnnydist [johnnydep.lib] dist=pytz>=2020.1 parent=pandas>=1.1 2022-01-29 08:28:56 [info ] init johnnydist [johnnydep.lib] dist=six>=1.5 parent=python-dateutil>=2.8.1 name summary xarray N-D labeled arrays and datasets in Python ├── numpy>=1.18 NumPy is the fundamental package for array computing with Python. └── pandas>=1.1 Powerful data structures for data analysis, time series, and statistics ├── numpy>=1.18.5 NumPy is the fundamental package for array computing with Python. ├── python-dateutil>=2.8.1 Extensions to the standard Python datetime module │ └── six>=1.5 Python 2 and 3 compatibility utilities └── pytz>=2020.1 World timezone definitions, modern and historical ``` The problem why your tests didn't catch this is that pytest pytest: simple powerful testing with Python ├── atomicwrites>=1.0 Atomic file writes. ├── attrs>=19.2.0 Classes Without Boilerplate ├── colorama Cross-platform colored terminal text. ├── iniconfig iniconfig: brain-dead simple config-ini parsing ├── packaging Core utilities for Python packages │ └── pyparsing!=3.0.5,>=2.0.2 Python parsing module ├── pluggy<2.0,>=0.12 plugin and hook calling mechanisms for python ├── py>=1.8.2 library with cross-python path, ini-parsing, io, code, log facilities └── toml Python Library for Tom's Obvious, Minimal Language ``` We also only saw our ASV workflow fail since ASV only installs the package and all direct runtime dependencies in the venv it runs the benchmark with. I prepared a dummy PR on my fork to demonstrate that this fixes the issue. Since the release is only 10h old maybe just do a quick post-release so most users won't even notice.
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xarray 13221727 | pull | |||||
1046614317 | PR_kwDOAMm_X84uL503 | 5948 | Fix plot.line crash for data of shape (1, N) in _title_for_slice on format_item | s-weigand 9513634 | closed | 0 | 2 | 2021-11-06T22:56:59Z | 2021-11-08T18:40:08Z | 2021-11-08T17:27:45Z | CONTRIBUTOR | 0 | pydata/xarray/pulls/5948 | Affected When dependabot recently made a PR to update We use The crash is caused because the following line allows arrays of shape But Before the check was https://github.com/pydata/xarray/blob/a78c1e0115d38cb4461fd1aba93334d440cff49c/xarray/core/formatting.py#L145-L146 Which didn't allow any arrays and caused the float formatting issue. Code showing the differences```python In [1]: import numpy as np In [2]: x = np.array(0.1) In [3]: x.shape Out[3]: () In [4]: np.issubdtype(type(x), np.floating) Out[4]: False In [5]: hasattr(x, "dtype") and np.issubdtype(x.dtype, np.floating) Out[5]: True In [6]: f"{x:.4}" Out[6]: '0.1' In [7]: f"{x.item():.4}" Out[7]: '0.1' In [8]: x = np.array([0.1]) In [9]: x.shape Out[9]: (1,) In [10]: np.issubdtype(type(x), np.floating) Out[10]: False In [11]: hasattr(x, "dtype") and np.issubdtype(x.dtype, np.floating) Out[11]: True In [12]: f"{x:.4}" --------------------------------------------------------------------------- TypeError Traceback (most recent call last) ~\AppData\Local\Temp/ipykernel_32644/2490801713.py in <module> ----> 1 f"{x:.4}" TypeError: unsupported format string passed to numpy.ndarray.__format__ In [13]: f"{x.item():.4}" Out[13]: '0.1' ```I hope
PS: Thanks for the awesome package ❤️ |
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xarray 13221727 | pull |
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