text:
Numba is not yet compatible with NumPy 1.18

xref: https://github.com/conda-forge/numba-feedstock/pull/44#issuecomment-624720581

Checklist

[ ] Used a fork of the feedstock to propose changes
[ ] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

Currently there are no numba versions that support 1.18. It's not clear (at least not to me) when that will change. So I don't think restricting is a good idea currently.
Sorry this is my first PR here. Can you please advise on what exactly you would like me to run?

It's not clear (at least not to me) when that will change. So I don't think restricting is a good idea currently.

Since the new versions being built have the correct numpy constraint added, you don't need to add it for new versions.

Sorry this is my first PR here. Can you please advise on what exactly you would like me to run?

See https://github.com/conda-forge/conda-forge-repodata-patches-feedstock/blob/master/recipe/show_diff.py

Sure, that makes sense. Have pushed that change.
Sorry I still have no idea what I should be doing with this. Could you please share what syntax you would like me to use to run it?

Just run the file. python recipe/show_diff.py

Thanks for clarifying 🙂
So I ran the script like so. Though it appears to only be downloading repodata from Linux (is that expected?). Appears the patch does include all OSes though.
$ python recipe/show_diff.py
Downloading: https://conda.anaconda.org/conda-forge/noarch/repodata_from_packages.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/noarch/repodata.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/linux-64/repodata_from_packages.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/linux-64/repodata.json.bz2
linux-64::numba-0.36.1-py35hdc42b47_0.tar.bz2

Here's the diff it showed:

-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.36.1"
+  "version": "0.36.1",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
linux-64::numba-0.36.1-py36hdc42b47_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.36.1"
+  "version": "0.36.1",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
linux-64::numba-0.36.2-py35_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy",
+    "numpy,<1.18.0",
-  "version": "0.36.2"
+  "version": "0.36.2",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
linux-64::numba-0.36.2-py36_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy",
+    "numpy,<1.18.0",
-  "version": "0.36.2"
+  "version": "0.36.2",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
linux-64::numba-0.38.0-py27_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27mu"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp27mu"
+  ]
linux-64::numba-0.38.0-py35_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
linux-64::numba-0.38.0-py36_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
linux-64::numba-0.38.1-py27_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27mu"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.1"
+  "version": "0.38.1",
+  "constrains": [
+    "python_abi * *_cp27mu"
+  ]
linux-64::numba-0.38.1-py35_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.1"
+  "version": "0.38.1",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
linux-64::numba-0.38.1-py36_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.1"
+  "version": "0.38.1",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
linux-64::numba-0.40.0-py27h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py27hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py35hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py36h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py36hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py37h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py37hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py27h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py27hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py36h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py36hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py37h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py27h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py27hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py36h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py36hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py37h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py37hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.42.1-py27hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.42.1-py36hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.42.1-py37hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.0-py27hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.0-py36hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.0-py37hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py27he1b5a44_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py27hf2d7682_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py36he1b5a44_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py36hf2d7682_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py37he1b5a44_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py37hf2d7682_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.44.1-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.44.1-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.44.1-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.0-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.0-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.0-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.1-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.1-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.1-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py27hb3f55d8_1.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py36hb3f55d8_1.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py37hb3f55d8_1.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.47.0-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.47.0-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.47.0-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.47.0-py38hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.48.0-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.48.0-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.48.0-py38hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
Downloading: https://conda.anaconda.org/conda-forge/linux-armv7l/repodata_from_packages.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/linux-armv7l/repodata.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/linux-aarch64/repodata_from_packages.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/linux-aarch64/repodata.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/linux-ppc64le/repodata_from_packages.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/linux-ppc64le/repodata.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/osx-64/repodata_from_packages.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/osx-64/repodata.json.bz2
osx-64::numba-0.36.1-py27hdc42b47_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.36.1"
+  "version": "0.36.1",
+  "constrains": [
+    "python_abi * *_cp27m"
+  ]
osx-64::numba-0.36.1-py35hdc42b47_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.36.1"
+  "version": "0.36.1",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
osx-64::numba-0.36.1-py36hdc42b47_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.36.1"
+  "version": "0.36.1",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
osx-64::numba-0.36.2-py27_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27m"
-  ],
-    "numpy",
+    "numpy,<1.18.0",
-  "version": "0.36.2"
+  "version": "0.36.2",
+  "constrains": [
+    "python_abi * *_cp27m"
+  ]
osx-64::numba-0.36.2-py35_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy",
+    "numpy,<1.18.0",
-  "version": "0.36.2"
+  "version": "0.36.2",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
osx-64::numba-0.36.2-py36_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy",
+    "numpy,<1.18.0",
-  "version": "0.36.2"
+  "version": "0.36.2",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
osx-64::numba-0.38.0-py27_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp27m"
+  ]
osx-64::numba-0.38.0-py35_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
osx-64::numba-0.38.0-py36_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
osx-64::numba-0.38.1-py27_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.1"
+  "version": "0.38.1",
+  "constrains": [
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+    "python_abi * *_cp37m"
+  ]
osx-64::numba-0.47.0-py38h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp38"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp38"
+  ]
osx-64::numba-0.48.0-py36h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
osx-64::numba-0.48.0-py37h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
osx-64::numba-0.48.0-py38h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp38"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp38"
+  ]
Downloading: https://conda.anaconda.org/conda-forge/win-32/repodata_from_packages.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/win-32/repodata.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/win-64/repodata_from_packages.json.bz2
Downloading: https://conda.anaconda.org/conda-forge/win-64/repodata.json.bz2
win-64::numba-0.46.0-py27h0e003f4_1.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp27m"
+  ]
win-64::numba-0.46.0-py36he350917_1.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
win-64::numba-0.46.0-py37he350917_1.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
win-64::numba-0.47.0-py36h67a5e14_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
win-64::numba-0.47.0-py37h67a5e14_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
win-64::numba-0.47.0-py38h67a5e14_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp38"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp38"
+  ]
win-64::numba-0.48.0-py36he350917_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
win-64::numba-0.48.0-py37he350917_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
win-64::numba-0.48.0-py38he350917_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp38"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp38"
+  ]

Lines like +    "numpy,<1.18.0", are problematic.

That's weird because when I looked at the feedstock history it has always had some numpy constraint.

Ok have pushed a change that should fix this.

linux-64 diff
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.36.1"
+  "version": "0.36.1",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
linux-64::numba-0.36.1-py36hdc42b47_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.36.1"
+  "version": "0.36.1",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
linux-64::numba-0.36.2-py35_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy",
+    "numpy <1.18.0",
-  "version": "0.36.2"
+  "version": "0.36.2",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
linux-64::numba-0.36.2-py36_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy",
+    "numpy <1.18.0",
-  "version": "0.36.2"
+  "version": "0.36.2",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
linux-64::numba-0.38.0-py27_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27mu"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp27mu"
+  ]
linux-64::numba-0.38.0-py35_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
linux-64::numba-0.38.0-py36_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.0"
+  "version": "0.38.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
linux-64::numba-0.38.1-py27_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27mu"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.1"
+  "version": "0.38.1",
+  "constrains": [
+    "python_abi * *_cp27mu"
+  ]
linux-64::numba-0.38.1-py35_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp35m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.1"
+  "version": "0.38.1",
+  "constrains": [
+    "python_abi * *_cp35m"
+  ]
linux-64::numba-0.38.1-py36_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.11",
+    "numpy >=1.11,<1.18.0",
-  "version": "0.38.1"
+  "version": "0.38.1",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
linux-64::numba-0.40.0-py27h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py27hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py35hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py36h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py36hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py37h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.0-py37hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py27h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py27hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py36h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py36hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.40.1-py37h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py27h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py27hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py36h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py36hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py37h637b7d7_1000.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.41.0-py37hf8a1672_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.42.1-py27hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.42.1-py36hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.42.1-py37hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.0-py27hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.0-py36hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.0-py37hf484d3e_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py27he1b5a44_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py27hf2d7682_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py36he1b5a44_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py36hf2d7682_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py37he1b5a44_0.tar.bz2
-    "numpy 1.15.*",
-    "numpy >=1.15.4,<2.0a0",
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",
linux-64::numba-0.43.1-py37hf2d7682_0.tar.bz2
-    "numpy >=1.9.3,<2.0a0",
+    "numpy >=1.9.3,<2.0a0,<1.18.0",
linux-64::numba-0.44.1-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.44.1-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.44.1-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.0-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.0-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.0-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.1-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.1-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.45.1-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py27hb3f55d8_1.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py36hb3f55d8_1.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.46.0-py37hb3f55d8_1.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.47.0-py27hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.47.0-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.47.0-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.47.0-py38hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.48.0-py36hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.48.0-py37hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
linux-64::numba-0.48.0-py38hb3f55d8_0.tar.bz2
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",

osx-64 diff
-  "constrains": [
-    "python_abi * *_cp27m"
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+    "python_abi * *_cp27m"
+  ]
osx-64::numba-0.46.0-py27h4f17bb1_1.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp27m"
+  ]
osx-64::numba-0.46.0-py36h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
osx-64::numba-0.46.0-py36h4f17bb1_1.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
osx-64::numba-0.46.0-py37h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
osx-64::numba-0.46.0-py37h4f17bb1_1.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
osx-64::numba-0.47.0-py27h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp27m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp27m"
+  ]
osx-64::numba-0.47.0-py36h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
osx-64::numba-0.47.0-py37h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
osx-64::numba-0.47.0-py38h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp38"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp38"
+  ]
osx-64::numba-0.48.0-py36h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
osx-64::numba-0.48.0-py37h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
osx-64::numba-0.48.0-py38h4f17bb1_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp38"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp38"
+  ]

win-64 diff
-  "constrains": [
-    "python_abi * *_cp27m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp27m"
+  ]
win-64::numba-0.46.0-py36he350917_1.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
win-64::numba-0.46.0-py37he350917_1.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.46.0"
+  "version": "0.46.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
win-64::numba-0.47.0-py36h67a5e14_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
win-64::numba-0.47.0-py37h67a5e14_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
win-64::numba-0.47.0-py38h67a5e14_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp38"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.47.0"
+  "version": "0.47.0",
+  "constrains": [
+    "python_abi * *_cp38"
+  ]
win-64::numba-0.48.0-py36he350917_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp36m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp36m"
+  ]
win-64::numba-0.48.0-py37he350917_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp37m"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp37m"
+  ]
win-64::numba-0.48.0-py38he350917_0.tar.bz2
-  "constrains": [
-    "python_abi * *_cp38"
-  ],
-    "numpy >=1.14.6,<2.0a0",
+    "numpy >=1.14.6,<2.0a0,<1.18.0",
-  "version": "0.48.0"
+  "version": "0.48.0",
+  "constrains": [
+    "python_abi * *_cp38"
+  ]

My understanding was that although some of the numba test suite fails when run with NumPy 1.18 there was no need to exclude that version for installation into a users environment.
@stuartarchibald could you provide guidance here?  Should the current numba conda packages be adjusted to restrict the version of numpy installed to exclude versions equal to or greater than 1.18?

For reference, I restricted the numpy version to be less than 1.18 in the test section of the numba recipe in AnacondaRecipes while leaving the run requirement on numpy un-constrained.

I thought about that. However it sounds like there hasn't been testing/development with NumPy 1.18. So constraining it seemed safer.
Happy to defer to Stuart 🙂

Numba has been tested against 1.18, it fails :) IIRC it's a few bits of datetime that cause the problem as NumPy changed behaviour. I guess strictly 1.18 shouldn't be declared supported, however >99.99% of the compiler works "just fine" with it. Am going to propose we just fix up 0.50RC (which is due soon) to work with 1.18.

Any more thoughts here @jjhelmus @isuruf?

My inclination is to merge this tomorrow if I don't hear anything. Currently this is causing end users problems and I would like to fix that soon.

@stuartarchibald, it's not clear to me from your comment whether you are okay with marking all builds <=0.49 as incompatible with numpy 1.18 or not. Can you clarify?

cc @conda-forge/numba

Friendly nudge 😉

This was discussed at some length at the Numba developer's meeting. Conclusions were:

An upper bound on NumPy support should not be applied from Numba's side, this is fairly consistent with other projects where there's no immediate ABI concern.
Specifically, NumPy 1.18 works with Numba well enough for us to not feel the need to place restrictions on support (only visible change to existing supported code is likely to be isnan or NaT related, both due to changes in NumPy).
Numba 0.50 will be out soon which replicates the couple of things that NumPy changed for 1.18 so "official" support would be achieved.
If needs be a 0.49.x could be released with an "upper bound" on NumPy applied.

So we have already done 4. The issue is the solver will try to grab the latest numpy anyways often meaning it will downgrade numba. The repodata patch fixes that by making this numpy version constraint consistent for older versions; so, the solver doesn't try to get out of that constraint.

cc @conda-forge/core

IIUC (based on Stuart's item 4) we are ok to merge.

Item 1 and 2 says otherwise.

The way I understand @stuartarchibald's comment:
Numba 0.49 is close enough to supporting NumPy 1.18 that it should be allowed for now. Once 0.50 is out, we can limit 0.49.x to < 1.18.
Is that a correct summary?

The way I understand @stuartarchibald's comment:
Numba 0.49 is close enough to supporting NumPy 1.18 that it should be allowed for now. Once 0.50 is out, we can limit 0.49.x to < 1.18.

Correct.

The action item would be: This cannot be merged until 0.50 is out and in conda-forge, and then it can be.
Is that a correct summary?

I think yes.
I also wonder about e.g. someone with NumPy 1.17, they could technically install a Numba version without support for it? same goes for any Numba with any previous NumPy? Is this issue unique to Numba, I'd assume not, for example NumPy's changes to e.g. np.datetime64 NaT handling in 1.18 could hit other Python packages, what are they doing? Does the policy actually need to be "maximum version of supported dependencies are those from the time when the package shipped", unless there's some sort of backport policy?

I also wonder about e.g. someone with NumPy 1.17, they could technically install a Numba version without support for it? same goes for any Numba with any previous NumPy? Is this issue unique to Numba, I'd assume not, for example NumPy's changes to e.g. np.datetime64 NaT handling in 1.18 could hit other Python packages, what are they doing? Does the policy actually need to be "maximum version of supported dependencies are those from the time when the package shipped", unless there's some sort of backport policy?

I'd advocate for a case-by-case basis discussion with the package maintainers as we are doing here. A struct maximum version based on when a package was shipped will create all sorts of weirdness and excessive rebuilds.

also hi @stuartarchibald! thanks for all of the help with the numba cuda stuff on gitter!

also hi @stuartarchibald! thanks for all of the help with the numba cuda stuff on gitter!

@beckermr hi :), no problem!

I also wonder about e.g. someone with NumPy 1.17, they could technically install a Numba version without support for it? same goes for any Numba with any previous NumPy? Is this issue unique to Numba, I'd assume not, for example NumPy's changes to e.g. np.datetime64 NaT handling in 1.18 could hit other Python packages, what are they doing? Does the policy actually need to be "maximum version of supported dependencies are those from the time when the package shipped", unless there's some sort of backport policy?

I'd advocate for a case-by-case basis discussion with the package maintainers as we are doing here. A strict maximum version based on when a package was shipped will create all sorts of weirdness and excessive rebuilds.

It just seems a bit strange in this case to fix up this particular package, but not historical releases? Perhaps this "fix" creates a new precedent for noting maximum supported NumPy for future Numba releases. I think that could be ok, but it also causes minor problems in cases like that present with 0.49.1, where NumPy 1.18 works apart from a couple of small things, and doing the restriction might be a bit too disruptive to anywhere relying on Numba, given the magnitude of the "incompatibility" and there being no solution otherwise?
As a side note: When discussing this at the Numba developers meeting @sklam suggested it'd be useful to have a way of expressing "This package was tested against ...", doesn't meant it won't work with other things, but the tested versions are specified, I like this idea.

This is fixing historical releases though. Currently only 0.49.* packages are fixed without this change. So this extends the fix to the long tail.
Though the issue is the solver won't respect the numpy requirement.
Usually we add constraints like this when we have identified a problem (as we did here).

My main point though is that a generic policy won't work. I'll leave the specifics of this instance to those already here.

This is fixing historical releases though. Currently only 0.49.* packages are fixed without this change. So this extends the fix to the long tail.

Does this fix the tail against more than just NumPy 1.18 or have I misunderstood this?!

It adds an upper bound of numpy <1.18 to any numba release <0.49.0. The diffs in the repo data are above in the comments, though they are hard to parse to the uninitiated for sure!

BTW @isuruf @jakirkham are these lines ok?
+    "numpy 1.15.*,<1.18.0",
+    "numpy >=1.15.4,<2.0a0,<1.18.0",

In particular, the top one is pretty non-sensical and I wonder if it is going to make the solver barf.

It adds an upper bound of numpy <1.18 to any numba release <0.49.0. The diffs in the repo data are above in the comments, though they are hard to parse to the uninitiated for sure!

Thanks for confirming. I think for the purposes of this PR the solution proposed here https://github.com/conda-forge/conda-forge-repodata-patches-feedstock/pull/51#issuecomment-639604635 is good. I also think that the point about matching up restrictions to releases, a concrete example of which is Numba 0.42 would not "work" with NumPy 1.16, is also valid but not something to address in this PR.
Thanks to everyone for helping resolve this!

I've added PR ( https://github.com/conda-forge/numba-feedstock/pull/47 ) to relax the numpy version constraint.

authors: beckermr conda-forge-linter henryiii isuruf jakirkham jjhelmus stuartarchibald


text:
Update cptec-model

Checklist

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[x] Bumped the build number (if the version is unchanged)
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@conda-forge-admin please rerender

source: gharchive/pull-request

repo: conda-forge/cptec-model-feedstock

license_type: permissive

license_source: github-api


text:
Update version to 11.2

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Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.
I do have some suggestions for making it better though...
For recipe:

License is not an SPDX identifier (or a custom LicenseRef) nor an SPDX license expression.

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@AgrawalAmey @xmnlab Would you mind also merging the two newer versions 11.1 and 11.2?

@Hoeze there seems to be an issue with this build where it is can only be installed in python 3.9. I was planning to merge the other PRs once we have a resolution for this problem.

Alright, thanks for the note :+1:

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@xmnlab we can merge this right after #31

@AgrawalAmey #31 is merged
this PR now will need a rebase/update, thanks!

@xmnlab oh sorry, resolved the conflict. Thank you!

@xmnlab merging this now. Thank you!

authors: AgrawalAmey Hoeze conda-forge-linter xmnlab

repo: conda-forge/cudatoolkit-dev-feedstock


text:
update v0.1.11

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repo: conda-forge/dash-extensions-feedstock


text:
y

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repo: conda-forge/ddtrace-feedstock


text:
Release 0.6.3

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authors: conda-forge-linter theroggy

repo: conda-forge/geofileops-feedstock


text:
No libgcc

This package does not link to libgomp so we don't need libgcc as a run requirement.

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text:
Update to 0.6.1

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authors: conda-forge-linter jtpio


text:
Fixed dependencies for v0.2.1.

Fixes dependencies submitted in #24

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repo: conda-forge/langchain-aws-feedstock


text:
Graphviz dependency pinning is ignored

Issue:
In the recipe, graphviz >=2.38.0 is pinned so as to allow Windows to find a working version. However, when I download the bz2 from Conda, I see graphviz >=2.40.1,<3.0a0. I am unable to get this recipe to download on Windows and am wondering if this is the issue.

Environment (conda list):

$ conda list

Details about  conda and system ( conda info ):

$ conda info

Curious if this is still an issue given graphviz builds on Windows as of ~1yr ago ( https://github.com/conda-forge/graphviz-feedstock/pull/59 )

source: gharchive/issue

authors: Benjamin-Lee jakirkham

repo: conda-forge/mechwolf-feedstock


text:
Try building with Rust

It would be great to be able to use Rust to build Mercurial on conda-forge.
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Perhaps @alphare can take a look

Mhh I'm not 100% sure what the layers involved might transform, but the way to trigger a Rust build through Mercurial's setup.py is with PURE=--rust. One day I'll send a patch to rename PURE to SETUPOPTS or something more in line with what it actually does.

authors: Alphare conda-forge-linter ngoldbaum paugier

repo: conda-forge/mercurial-feedstock


text:
To 7.1.3 conda patches

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repo: conda-forge/ndcctools-feedstock


text:
pywin32 dependency

Solution to issue cannot be found in the documentation.

[X] I checked the documentation.

Issue
Trying to test the installation of omero-py using this new feedstock and https://github.com/conda-forge/zeroc-ice-feedstock/pull/21 on a M1
(base) sbesson@Sebastiens-MacBook-Pro ~ % cat environment.yml
---
name: omero_py
channels:
  - conda-forge
  - defaults
dependencies:
  - omero-py
(base) sbesson@Sebastiens-MacBook-Pro ~ % conda env create -f environment.yml
Collecting package metadata (repodata.json): done
Solving environment: |
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes.  Press CTRL-C to abort.
failed

UnsatisfiableError: The following specifications were found to be incompatible with your system:

  - feature:/osx-arm64::__unix==0=0
  - omero-py -> pywin32-on-windows -> __unix

Your installed version is: 0

This had already been flagged in https://github.com/ome/conda-omero-py/issues/13 and and fixed in the package  shipped in the ome conda channel by removing the noarch - see https://github.com/ome/conda-omero-py/pull/1
Installed packages
(base) sbesson@Sebastiens-MacBook-Pro ~ % conda list
# packages in environment at /Users/sbesson/miniconda3:
#
# Name                    Version                   Build  Channel
brotlipy                  0.7.0           py38h1a28f6b_1002
ca-certificates           2021.10.26           hca03da5_2
certifi                   2021.10.8        py38hca03da5_2
cffi                      1.15.0           py38h22df2f2_1
charset-normalizer        2.0.4              pyhd3eb1b0_0
conda                     4.11.0           py38hca03da5_0
conda-package-handling    1.7.3            py38h1a28f6b_1
cryptography              36.0.0           py38h834c97f_0
idna                      3.3                pyhd3eb1b0_0
libcxx                    12.0.0               hf6beb65_1
libffi                    3.4.2                hc377ac9_2
ncurses                   6.3                  h1a28f6b_2
openssl                   1.1.1m               h1a28f6b_0
pip                       21.2.4           py38hca03da5_0
pycosat                   0.6.3            py38h1a28f6b_0
pycparser                 2.21               pyhd3eb1b0_0
pyopenssl                 22.0.0             pyhd3eb1b0_0
pysocks                   1.7.1            py38hca03da5_0
python                    3.8.11          h35b60ff_4_cpython
python.app                3                py38h1230e6a_0
readline                  8.1.2                h1a28f6b_1
requests                  2.27.1             pyhd3eb1b0_0
ruamel_yaml               0.15.100         py38h1a28f6b_0
setuptools                58.0.4           py38hca03da5_1
six                       1.16.0             pyhd3eb1b0_1
sqlite                    3.37.2               h1058600_0
tk                        8.6.11               hb8d0fd4_0
tqdm                      4.62.3             pyhd3eb1b0_1
urllib3                   1.26.8             pyhd3eb1b0_0
wheel                     0.37.1             pyhd3eb1b0_0
xz                        5.2.5                h1a28f6b_0
yaml                      0.2.5                h1a28f6b_0
zlib                      1.2.11               h5a0b063_4

Environment info
(base) sbesson@Sebastiens-MacBook-Pro ~ % conda info

     active environment : base
    active env location : /Users/sbesson/miniconda3
            shell level : 1
       user config file : /Users/sbesson/.condarc
 populated config files :
          conda version : 4.11.0
    conda-build version : not installed
         python version : 3.8.11.final.0
       virtual packages : __osx=12.3.1=0
                          __unix=0=0
                          __archspec=1=arm64
       base environment : /Users/sbesson/miniconda3  (writable)
      conda av data dir : /Users/sbesson/miniconda3/etc/conda
  conda av metadata url : None
           channel URLs : https://repo.anaconda.com/pkgs/main/osx-arm64
                          https://repo.anaconda.com/pkgs/main/noarch
                          https://repo.anaconda.com/pkgs/r/osx-arm64
                          https://repo.anaconda.com/pkgs/r/noarch
          package cache : /Users/sbesson/miniconda3/pkgs
                          /Users/sbesson/.conda/pkgs
       envs directories : /Users/sbesson/miniconda3/envs
                          /Users/sbesson/.conda/envs
               platform : osx-arm64
             user-agent : conda/4.11.0 requests/2.27.1 CPython/3.8.11 Darwin/21.4.0 OSX/12.3.1
                UID:GID : 501:20
             netrc file : None
           offline mode : False

@bollwyvl https://github.com/conda-forge/pywin32-on-windows-feedstock is noarch, but does it need some more magic to work with osx-arm64?

I don't have a way to test that natively, but on a linux box, with this:
CONDA_SUBDIR=osx-arm64 conda create -c conda-forge -c nodefaults -n foo --dry-run omero-py

i get:

Collecting package metadata (current_repodata.json): ...working... done
Solving environment: ...working... failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): ...working... done
Solving environment: ...working... done
Package Plan
environment location: ~/mc3/envs/foo
added / updated specs:
- omero-py
The following packages will be downloaded:
package                    |            build
---------------------------|-----------------
appdirs-1.4.4              |     pyh9f0ad1d_0          13 KB
brotlipy-0.7.0             |py39hb18efdd_1004         341 KB
bzip2-1.0.8                |       h3422bc3_4         148 KB
ca-certificates-2021.10.8  |       h4653dfc_0         139 KB
certifi-2021.10.8          |   py39h2804cbe_2         145 KB
cffi-1.15.0                |   py39h52b1de0_0         219 KB
cryptography-36.0.2        |   py39hbe5e4b8_1         1.3 MB
freetype-2.10.4            |       h17b34a0_1         874 KB
future-0.18.2              |   py39h2804cbe_5         714 KB
giflib-5.2.1               |       h27ca646_2          72 KB
jbig-2.1                   |    h3422bc3_2003          42 KB
jpeg-9e                    |       h3422bc3_0         257 KB
lcms2-2.12                 |       had6a04f_0         369 KB
lerc-3.0                   |       hbdafb3b_0         145 KB
libblas-3.9.0              |13_osxarm64_openblas          12 KB
libcblas-3.9.0             |13_osxarm64_openblas          12 KB
libcxx-13.0.1              |       h6a5c8ee_0         1.1 MB
libdeflate-1.10            |       h3422bc3_0          56 KB
libffi-3.4.2               |       h3422bc3_5          38 KB
libgfortran-5.0.0.dev0     |11_0_1_hf114ba7_23          19 KB
libgfortran5-11.0.1.dev0   |      hf114ba7_23         901 KB
libiconv-1.16              |       h642e427_0         1.3 MB
liblapack-3.9.0            |13_osxarm64_openblas          12 KB
libopenblas-0.3.18         |openmp_h5dd58f0_0         3.9 MB
libpng-1.6.37              |       hf7e6567_2         293 KB
libtiff-4.3.0              |       h77dc3b6_3         595 KB
libwebp-1.2.2              |       h0d20362_0          79 KB
libwebp-base-1.2.2         |       h3422bc3_1         600 KB
libxcb-1.13                |    h9b22ae9_1004         345 KB
libzlib-1.2.11             |    h90dfc92_1014          55 KB
llvm-openmp-13.0.1         |       h455960f_1         276 KB
lz4-c-1.9.3                |       hbdafb3b_1         147 KB
ncurses-6.3                |       hc470f4d_0         919 KB
numpy-1.22.3               |   py39h690d673_1         5.7 MB
omero-py-5.11.1            |     pyhd8ed1ab_0         1.8 MB
openjpeg-2.4.0             |       h062765e_1         422 KB
openssl-1.1.1n             |       h90dfc92_0         1.7 MB
pillow-9.1.0               |   py39hd72dd6b_0        45.2 MB
pthread-stubs-0.4          |    h27ca646_1001           6 KB
pysocks-1.7.1              |   py39h2804cbe_5          28 KB
python-3.9.12              |hfc7342c_1_cpython        12.3 MB
python_abi-3.9             |           2_cp39           4 KB
pywin32-on-windows-0.1.0   |     pyh1179c8e_3           5 KB
pyyaml-6.0                 |   py39hb18efdd_4         166 KB
readline-8.1               |       hedafd6a_0         259 KB
setuptools-62.0.0          |   py39h2804cbe_0         1.3 MB
sqlite-3.37.1              |       h7e3ccbd_0         1.6 MB
tk-8.6.12                  |       he1e0b03_0         3.2 MB
xorg-libxau-1.0.9          |       h27ca646_0          12 KB
xorg-libxdmcp-1.1.3        |       h27ca646_0          18 KB
xz-5.2.5                   |       h642e427_1         222 KB
yaml-0.2.5                 |       h3422bc3_2          86 KB
zeroc-ice-3.6.5            |   py39h6e8f42b_3         2.3 MB
zlib-1.2.11                |    h90dfc92_1014          85 KB
zstd-1.5.2                 |       h861e0a7_0         369 KB
------------------------------------------------------------
                                       Total:        92.0 MB

The following NEW packages will be INSTALLED:
appdirs            conda-forge/noarch::appdirs-1.4.4-pyh9f0ad1d_0
brotlipy           conda-forge/osx-arm64::brotlipy-0.7.0-py39hb18efdd_1004
bzip2              conda-forge/osx-arm64::bzip2-1.0.8-h3422bc3_4
ca-certificates    conda-forge/osx-arm64::ca-certificates-2021.10.8-h4653dfc_0
certifi            conda-forge/osx-arm64::certifi-2021.10.8-py39h2804cbe_2
cffi               conda-forge/osx-arm64::cffi-1.15.0-py39h52b1de0_0
charset-normalizer conda-forge/noarch::charset-normalizer-2.0.12-pyhd8ed1ab_0
cryptography       conda-forge/osx-arm64::cryptography-36.0.2-py39hbe5e4b8_1
freetype           conda-forge/osx-arm64::freetype-2.10.4-h17b34a0_1
future             conda-forge/osx-arm64::future-0.18.2-py39h2804cbe_5
giflib             conda-forge/osx-arm64::giflib-5.2.1-h27ca646_2
idna               conda-forge/noarch::idna-3.3-pyhd8ed1ab_0
jbig               conda-forge/osx-arm64::jbig-2.1-h3422bc3_2003
jpeg               conda-forge/osx-arm64::jpeg-9e-h3422bc3_0
lcms2              conda-forge/osx-arm64::lcms2-2.12-had6a04f_0
lerc               conda-forge/osx-arm64::lerc-3.0-hbdafb3b_0
libblas            conda-forge/osx-arm64::libblas-3.9.0-13_osxarm64_openblas
libcblas           conda-forge/osx-arm64::libcblas-3.9.0-13_osxarm64_openblas
libcxx             conda-forge/osx-arm64::libcxx-13.0.1-h6a5c8ee_0
libdeflate         conda-forge/osx-arm64::libdeflate-1.10-h3422bc3_0
libffi             conda-forge/osx-arm64::libffi-3.4.2-h3422bc3_5
libgfortran        conda-forge/osx-arm64::libgfortran-5.0.0.dev0-11_0_1_hf114ba7_23
libgfortran5       conda-forge/osx-arm64::libgfortran5-11.0.1.dev0-hf114ba7_23
libiconv           conda-forge/osx-arm64::libiconv-1.16-h642e427_0
liblapack          conda-forge/osx-arm64::liblapack-3.9.0-13_osxarm64_openblas
libopenblas        conda-forge/osx-arm64::libopenblas-0.3.18-openmp_h5dd58f0_0
libpng             conda-forge/osx-arm64::libpng-1.6.37-hf7e6567_2
libtiff            conda-forge/osx-arm64::libtiff-4.3.0-h77dc3b6_3
libwebp            conda-forge/osx-arm64::libwebp-1.2.2-h0d20362_0
libwebp-base       conda-forge/osx-arm64::libwebp-base-1.2.2-h3422bc3_1
libxcb             conda-forge/osx-arm64::libxcb-1.13-h9b22ae9_1004
libzlib            conda-forge/osx-arm64::libzlib-1.2.11-h90dfc92_1014
llvm-openmp        conda-forge/osx-arm64::llvm-openmp-13.0.1-h455960f_1
lz4-c              conda-forge/osx-arm64::lz4-c-1.9.3-hbdafb3b_1
ncurses            conda-forge/osx-arm64::ncurses-6.3-hc470f4d_0
numpy              conda-forge/osx-arm64::numpy-1.22.3-py39h690d673_1
omero-py           conda-forge/noarch::omero-py-5.11.1-pyhd8ed1ab_0
openjpeg           conda-forge/osx-arm64::openjpeg-2.4.0-h062765e_1
openssl            conda-forge/osx-arm64::openssl-1.1.1n-h90dfc92_0
pillow             conda-forge/osx-arm64::pillow-9.1.0-py39hd72dd6b_0
pip                conda-forge/noarch::pip-22.0.4-pyhd8ed1ab_0
pthread-stubs      conda-forge/osx-arm64::pthread-stubs-0.4-h27ca646_1001
pycparser          conda-forge/noarch::pycparser-2.21-pyhd8ed1ab_0
pyopenssl          conda-forge/noarch::pyopenssl-22.0.0-pyhd8ed1ab_0
pysocks            conda-forge/osx-arm64::pysocks-1.7.1-py39h2804cbe_5
python             conda-forge/osx-arm64::python-3.9.12-hfc7342c_1_cpython
python_abi         conda-forge/osx-arm64::python_abi-3.9-2_cp39
pywin32-on-windows conda-forge/noarch::pywin32-on-windows-0.1.0-pyh1179c8e_3
pyyaml             conda-forge/osx-arm64::pyyaml-6.0-py39hb18efdd_4
readline           conda-forge/osx-arm64::readline-8.1-hedafd6a_0
requests           conda-forge/noarch::requests-2.27.1-pyhd8ed1ab_0
setuptools         conda-forge/osx-arm64::setuptools-62.0.0-py39h2804cbe_0
sqlite             conda-forge/osx-arm64::sqlite-3.37.1-h7e3ccbd_0
tk                 conda-forge/osx-arm64::tk-8.6.12-he1e0b03_0
tzdata             conda-forge/noarch::tzdata-2022a-h191b570_0
urllib3            conda-forge/noarch::urllib3-1.26.9-pyhd8ed1ab_0
wheel              conda-forge/noarch::wheel-0.37.1-pyhd8ed1ab_0
xorg-libxau        conda-forge/osx-arm64::xorg-libxau-1.0.9-h27ca646_0
xorg-libxdmcp      conda-forge/osx-arm64::xorg-libxdmcp-1.1.3-h27ca646_0
xz                 conda-forge/osx-arm64::xz-5.2.5-h642e427_1
yaml               conda-forge/osx-arm64::yaml-0.2.5-h3422bc3_2
zeroc-ice          conda-forge/osx-arm64::zeroc-ice-3.6.5-py39h6e8f42b_3
zlib               conda-forge/osx-arm64::zlib-1.2.11-h90dfc92_1014
zstd               conda-forge/osx-arm64::zstd-1.5.2-h861e0a7_0

with a local of:

conda info
 active environment : base
active env location : ~/mc3
        shell level : 1
   user config file : ~/.condarc

populated config files : ~/.condarc
conda version : 4.12.0
conda-build version : 3.21.8
python version : 3.9.10.final.0
virtual packages : __cuda=11.4=0
__linux=5.4.0=0
__glibc=2.31=0
__unix=0=0
__archspec=1=x86_64
base environment : ~/mc3  (writable)
conda av data dir : ~/mc3/etc/conda
conda av metadata url : None
channel URLs : https://conda.anaconda.org/conda-forge/linux-64
https://conda.anaconda.org/conda-forge/noarch
package cache : ~/mc3/pkgs
~/.conda/pkgs
envs directories : ~/mc3/envs
~/.conda/envs
platform : linux-64
user-agent : conda/4.12.0 requests/2.25.1 CPython/3.9.10 Linux/5.4.0-105-generic ubuntu/20.04.4 glibc/2.31
UID:GID : 1000:1000
netrc file : None
offline mode : False

so maybe:

try without defaults
try updating conda

maybe with the new solver?

try mamba
try solving first with conda-lock --kind explicit and creating from that

But if none of that works, accept having to drop noarch: python

Thanks @bollwyvl, dropping defaults from environment.yml was sufficient to get the package installed. Now running into a separate runtime error but this can be safely closed

sufficient to get the package installed.

:tada:

separate runtime error but this can be safely closed

If it's related to pywin32-on-windows, please share!

If it's related to pywin32-on-windows, please share!

No nothing related to pywin32. I am getting the same issue as https://github.com/conda-forge/zeroc-ice-feedstock/pull/21#issuecomment-1087946339 i.e. this is an issue to the zeroc-ice recipe

authors: bollwyvl manics sbesson

repo: conda-forge/omero-py-feedstock


text:
Make noarch: generic

Checklist

[x] Used a fork of the feedstock to propose changes
[x] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[x] Ensured the license file is being packaged.

Hi! This is the friendly automated conda-forge-linting service.
I wanted to let you know that I linted all conda-recipes in your PR (recipe) and found some lint.
Here's what I've got...
For recipe:

noarch packages can't have selectors. If the selectors are necessary, please remove noarch: generic.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

@conda-forge-admin, please update circle

Hi! This is the friendly automated conda-forge-webservice.
I just wanted to let you know that I updated the circle-ci deploy key and followed the project.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

authors: conda-forge-linter isuruf xhochy

repo: conda-forge/parquet-cpp-feedstock


text:
pip in-tree-builds breaks some packages

For eg: archspec wheel doesn't have any of the files.

See also https://github.com/python-poetry/poetry/issues/2895

Incredible detective work! Thanks @isuruf!

authors: isuruf ocefpaf

repo: conda-forge/poetry-core-feedstock


text:
Update meta.yaml

Checklist

[x] Used a personal fork of the feedstock to propose changes
[x] Bumped the build number (if the version is unchanged)
[x] Reset the build number to 0 (if the version changed)
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[x] Ensured the license file is being packaged.

The scipy dependency version differs depending on the python version, we cannot translate this in a conda recipe of a noarch package (noarch packages can't have selectors) thus we should let go older python versions. We need this fix for publishing nrtk-explorer.

@bjrichardwebster Need your input here as well.
@vicentebolea nrtk and pybsm  are currently supporting python versions 3.8 and above. If we modify the host version of pybsm, that would affect nrtk as  well.

.

Yes, I am not very well verse in conda forge but it seems that there is no other way (maybe other than making the package not noarch). The current state makes this package unusable as a dependency.
Here is how you can do this with a non noarch pkg: https://github.com/conda-forge/staged-recipes/pull/26184/files

.

Yes, I am not very well verse in conda forge but it seems that there is no other way (maybe other than making the package not noarch). The current state makes this package unusable as a dependency.
Here is how you can do this with a non noarch pkg: https://github.com/conda-forge/staged-recipes/pull/26184/files

I'll try to make some changes to the nrtk-explorer recipe.

I just noticed that the reason that we do not see this error in this package is that noarch package just tests with the latest python, while arch packages (such as nrtk-explorer) tests with all the supported python versions.

@conda-forge-admin, please rerender

@vicentebolea  PTAL at the current state. I think the proposed changes to this recipe should resolve the issues you are having with nrtk-explorer.
FYI, I've started a similar PR for nrtk : https://github.com/conda-forge/nrtk-feedstock/pull/8

authors: barry-ravichandran vicentebolea

repo: conda-forge/pybsm-feedstock


text:
Add auto merge

@conda-forge-admin, please add bot automerge

@conda-forge-admin, please add bot automerge

Hi! This is the friendly automated conda-forge-webservice.
I just wanted to let you know that I added bot automerge in conda-forge/pylatte-feedstock#2.

authors: conda-forge-linter jan-janssen

repo: conda-forge/pylatte-feedstock


text:
update to v1.0.39

Checklist

[x] Used a personal fork of the feedstock to propose changes
[x] Bumped the build number (if the version is unchanged)
[x] Reset the build number to 0 (if the version changed)
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[x] Ensured the license file is being packaged.

@conda-forge-admin, please rerender

repo: conda-forge/pynmeagps-feedstock


text:
Produce Python 3.7 build

@conda-forge-admin, please rerender
I hope this works as intended…

Hi! This is the friendly automated conda-forge-webservice.
I just wanted to let you know that I rerendered the recipe in conda-forge/pyosf-feedstock#7.

authors: conda-forge-linter hoechenberger

repo: conda-forge/pyosf-feedstock


text:
@conda-forge-admin, please add bot automerge

@conda-forge-admin, please add bot automerge

Hi! This is the friendly automated conda-forge-webservice.
I just wanted to let you know that I added bot automerge in conda-forge/python-crontab-feedstock#10.

authors: conda-forge-linter scopatz

repo: conda-forge/python-crontab-feedstock


text:
Revert "cpu only"

Reverts conda-forge/pytorch_sparse-feedstock#7

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.


text:
Replace sysroot in qmake build metadata

This change was suggested by @isuruf last year.  I assume it's still a valid suggestion.  (Sorry this PR is so late!)
Closes conda-forge/qt-feedstock/issues/201

Checklist

[x] Used a personal fork of the feedstock to propose changes
[x] Bumped the build number (if the version is unchanged)
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

Seems like this is working as intended:
INFO :: Time taken to mark (prefix) and mark+peform ("qmake build metadata")
        390 replacements in 97 files was 2.97 seconds

Folded into https://github.com/conda-forge/qt-main-feedstock/pull/43

authors: Tobias-Fischer conda-forge-linter hmaarrfk stuarteberg

repo: conda-forge/qt-main-feedstock


text:
R3.5

Checklist

[x] Used a fork of the feedstock to propose changes
[x] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[x] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[x] Ensured the license file is being packaged.

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.
I do have some suggestions for making it better though...
For recipe:

Using toolchain directly in this manner is deprecated.  Consider using the compilers outlined here.

authors: cbrueffer conda-forge-linter

repo: conda-forge/r-rcppeigen-feedstock


text:
use bazel 6.5

Checklist

[x] Used a personal fork of the feedstock to propose changes
[x] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

See this comment

Bumped the build number and marked for automerge.

cc @h-vetinari

repo: conda-forge/ray-packages-feedstock


text:
Bump pycalphad dependency

Checklist

[ ] Used a personal fork of the feedstock to propose changes
[ ] Bumped the build number (if the version is unchanged)
[ ] Reset the build number to 0 (if the version changed)
[ ] Re-rendered with the latest conda-smithy (Use the phrase @conda-forge-admin, please rerender in a comment in this PR for automated rerendering)
[ ] Ensured the license file is being packaged.

Hi! This is the friendly automated conda-forge-webservice.
It appears you are making a pull request from a branch in your feedstock and not a fork. This procedure will generate a separate build for each push to the branch and is thus not allowed. See our documentation for more details.
Please close this pull request and remake it from a fork of this feedstock.
Have a great day!

Hi! This is the friendly automated conda-forge-linting service.
I just wanted to let you know that I linted all conda-recipes in your PR (recipe) and found it was in an excellent condition.

authors: bocklund conda-forge-linter

repo: conda-forge/scheil-feedstock


text:
Please rely on pytorch global pinning

The upstream requirements are just because it's too hard to distribute through pip otherwise. For compatibility with the rest of the conda-forge ecosystem, please remove the pins and let this be handled by the bots.

Added one comment in the PR.
About the overall pins, did you find anything in the docs about this? I couldn't find it.

authors: BastianZim h-vetinari

repo: conda-forge/torchdata-feedstock