Drop Python 3.9 and bump NumPy versions in conda-package workflow #229
conda-package.yml
on: pull_request
Matrix: build_linux
Matrix: build_windows
Matrix: test_linux
Matrix: test_windows
Annotations
8 warnings
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build_windows (3.12)
WARNING conda.cli.main_config:_set_key(451): Key auto_activate_base is an alias of auto_activate; setting value with latter
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build_windows (3.10)
WARNING conda.cli.main_config:_set_key(451): Key auto_activate_base is an alias of auto_activate; setting value with latter
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build_windows (3.13)
WARNING conda.cli.main_config:_set_key(451): Key auto_activate_base is an alias of auto_activate; setting value with latter
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build_windows (3.11)
WARNING conda.cli.main_config:_set_key(451): Key auto_activate_base is an alias of auto_activate; setting value with latter
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test_windows (3.13, 2.3)
WARNING conda.cli.main_config:_set_key(451): Key auto_activate_base is an alias of auto_activate; setting value with latter
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test_windows (3.12, 2.3)
WARNING conda.cli.main_config:_set_key(451): Key auto_activate_base is an alias of auto_activate; setting value with latter
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test_windows (3.10, 2.2)
WARNING conda.cli.main_config:_set_key(451): Key auto_activate_base is an alias of auto_activate; setting value with latter
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test_windows (3.11, 2.3)
WARNING conda.cli.main_config:_set_key(451): Key auto_activate_base is an alias of auto_activate; setting value with latter
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Artifacts
Produced during runtime
| Name | Size | Digest | |
|---|---|---|---|
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mkl_random Linux Python 3.10
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305 KB |
sha256:c21402bfa1f1d57e42fe1618e42b58299931d7fa0e9fe04a35150e9cc9e05ea7
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mkl_random Linux Python 3.11
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320 KB |
sha256:bc0ff906be2b73bf4c11d96a87312fce819868b15a04a08ebdfa2c3c889ee14f
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mkl_random Linux Python 3.12
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318 KB |
sha256:3e3c7a0fa350d95e556f5c1122d734bffd1c861c89f671c78df6970460d52691
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mkl_random Linux Python 3.13
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319 KB |
sha256:309cb2eabc7493fe806c3024f726536d7626613a945a4a41517c25972b908e79
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mkl_random Windows Python 3.10
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245 KB |
sha256:346050735c1399e21db67168d21edbd4b18978952bd5dc7b921ce0abc1e118fb
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mkl_random Windows Python 3.11
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250 KB |
sha256:c1dcb8f061e5893cdc06cecb271f84304aa850e27dc85ccdf0c7021483d34fce
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mkl_random Windows Python 3.12
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239 KB |
sha256:3fa13576b6e4f142ce4b10ae0f66c93ca4da438f9d7d3b9817ac706b0e3f7f6c
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mkl_random Windows Python 3.13
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243 KB |
sha256:01392fd172b68fc82c6914724baf213163f3c8d77deec2d3a915fa405a150ce8
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