如何修复自定义 conda 包的 conda UnsatisfiableError？
How do I fix conda UnsatisfiableError of my custom conda package?
我正在尝试打包我的 python 代码以在 Anaconda 云中发布。
文件夹结构如下所示：
.
├── conda-recipe
│ ├── build.bat
│ ├── build.sh
│ └── meta.yaml
├── demos
│ ├── datasets
│ │ ├── com-amazon.all.dedup.cmty.txt
│ │ ├── com-amazon.ungraph.txt
│ │ ├── email-Eu-core-department-labels.txt
│ │ └── email-Eu-core.txt
│ ├── directed_example.ipynb
│ ├── email_eu_core_network_evaluation-Copy1.ipynb
│ ├── node_classification.ipynb
│ └── zacharys_karate_club_evaluation.ipynb
├── LICENSE.txt
├── README.md
├── setup.py
├── sten
│ ├── embedding.py
│ └── __init__.py
├── test
│ ├── __init__.py
│ └── test_system.py
├── zachary_computed.png
└── zachary_expected.png
meta.yaml 文件：
package:
name: sten
version: "0.1.0"
source:
path: ..
build:
number: 0
noarch: generic
requirements:
build:
- python >=3.7
- setuptools
run:
- python >=3.7
- pypardiso >=0.2.2
- numpy >=1.18.1
- networkx >=2.4
- scipy >=1.4.1
- markdown
test:
imports:
- sten.embedding
about:
home: https://github.com/monomonedula/simple-graph-embedding
license: Apache License 2.0
license_file: LICENSE.txt
summary: Simple deterministic algorithm for generating graph nodes topological embeddings.
我用来构建包的命令（haasad 是 pypardiso 包的频道名称）：
conda build conda-recipe -c haasad
构建成功，我已经上传到这里：
https://anaconda.org/monomonedula/sten
然而，安装后使用本地构建如下：
conda install sten --use-local -c haasad
并将构建上传到云端
conda install -c monomonedula sten -c haasad
我遇到了几个问题。
- 当使用 python 3.7 我无法导入我的包，即使它在
conda list 中列出（我仔细检查了所有内容，我使用了正确的解释器）。
- 当使用 python 3.8 时，我可以导入并使用它，但由于未知原因我无法安装 stellargraph。错误信息：
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
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 each other:
Output in format: Requested package -> Available versions
conda search sten -c monomonedula --info 的输出：
sten 0.1.0 py38_0
-----------------
file name : sten-0.1.0-py38_0.tar.bz2
name : sten
version : 0.1.0
build : py38_0
build number: 0
size : 16 KB
license : Apache License 2.0
subdir : noarch
url : https://conda.anaconda.org/monomonedula/noarch/sten-0.1.0-py38_0.tar.bz2
md5 : 53661562513861f9433b252c8ae7b5f4
timestamp : 2020-05-23 19:24:36 UTC
dependencies:
- markdown
- networkx >=2.4
- numpy >=1.18.1
- pypardiso >=0.2.2
- python >=3.7
- scipy >=1.4.1
sten 0.1.0 py38_0
-----------------
file name : sten-0.1.0-py38_0.tar.bz2
name : sten
version : 0.1.0
build : py38_0
build number: 0
size : 16 KB
license : Apache License 2.0
subdir : noarch
url : https://conda.anaconda.org/monomonedula/noarch/sten-0.1.0-py38_0.tar.bz2
md5 : 53661562513861f9433b252c8ae7b5f4
timestamp : 2020-05-23 19:24:36 UTC
dependencies:
- markdown
- networkx >=2.4
- numpy >=1.18.1
- pypardiso >=0.2.2
- python >=3.7
- scipy >=1.4.1
conda search stellargraph -c stellargraph --info 的输出：
stellargraph 1.0.0 py_0
-----------------------
file name : stellargraph-1.0.0-py_0.tar.bz2
name : stellargraph
version : 1.0.0
build : py_0
build number: 0
size : 7.8 MB
license : Apache Software
subdir : noarch
url : https://conda.anaconda.org/stellargraph/noarch/stellargraph-1.0.0-py_0.tar.bz2
md5 : e62b9c897d0a5481159c1e7cb8024717
timestamp : 2020-05-05 07:54:44 UTC
dependencies:
- gensim >=3.4.0
- ipykernel
- ipython
- matplotlib >=2.2
- networkx >=2.2
- numpy >=1.14
- pandas >=0.24
- python >=3.6
- scikit-learn >=0.20
- scipy >=1.1.0
- tensorflow >=2.1.0
我在这里缺少什么以及如何正确打包它？
问题出在您的 meta.yaml 文件中。根据 Anaconda blog post:
Noarch generic packages allow users to distribute docs, datasets, and source code in conda packages
和
Noarch Python packages cut down on the overhead of building multiple different pure Python packages on different architectures and Python versions by sorting out platform and Python version-specific differences at install time
因为你想分发一个纯 python 包，你应该使用 noarch: python。此外，您不需要在 build 和 run 中设置 python 版本。我在下面包含了更新的 meta.yaml。它还包含构建脚本，因此您不再需要 build.sh 和 build.bat 文件。它还将许可部分修复为 conda 将接受的内容（它仍然是 Apache 2.0）。
package:
name: sten
version: "0.1.0"
source:
path: ..
build:
number: 0
noarch: python
script: {{ PYTHON }} setup.py install
requirements:
build:
- python
- setuptools
run:
- python
- pypardiso >=0.2.2
- numpy >=1.18.1
- networkx >=2.4
- scipy >=1.4.1
- markdown
test:
imports:
- sten.embedding
about:
home: https://github.com/monomonedula/simple-graph-embedding
license: Apache-2.0
license_family: Apache
license_file: LICENSE.txt
summary: Simple deterministic algorithm for generating graph nodes topological embeddings.
以下是我使用上述 meta.yaml 文件构建和安装此包的步骤：
git clone https://github.com/monomonedula/simple-graph-embedding
cd simple-graph-embedding/
git checkout 'refactor&cleanup'
# Replace contents of `meta.yaml`
rm conda-recipe/build.sh conda-recipe/build.bat
conda create --yes -n testing python=3.7 conda-build conda-verify
conda activate testing
conda-build --channel haasad .
这是我在 3.7 环境中安装包的方法。您会在 conda-build 日志输出的底部找到 sten-0.1.0-py_0.tar.bz2 的完整路径。
conda install -n testing /home/jakub/miniconda3/envs/testing/conda-bld/noarch/sten-0.1.0-py_0.tar.bz2
conda activate testing
$CONDA_PREFIX/bin/python -c "import sten"
我也在python3.8环境下测试了安装。
conda create --yes -n testing3.8 python=3.8
conda install -n testing3.8 /home/jakub/miniconda3/envs/testing/conda-bld/noarch/sten-0.1.0-py_0.tar.bz2
conda activate testing3.8
$CONDA_PREFIX/bin/python -c "import sten"
conda install --use-local sten 对我不起作用 - 有一个 GitHub issue 关于它。
我正在尝试打包我的 python 代码以在 Anaconda 云中发布。 文件夹结构如下所示：
.
├── conda-recipe
│ ├── build.bat
│ ├── build.sh
│ └── meta.yaml
├── demos
│ ├── datasets
│ │ ├── com-amazon.all.dedup.cmty.txt
│ │ ├── com-amazon.ungraph.txt
│ │ ├── email-Eu-core-department-labels.txt
│ │ └── email-Eu-core.txt
│ ├── directed_example.ipynb
│ ├── email_eu_core_network_evaluation-Copy1.ipynb
│ ├── node_classification.ipynb
│ └── zacharys_karate_club_evaluation.ipynb
├── LICENSE.txt
├── README.md
├── setup.py
├── sten
│ ├── embedding.py
│ └── __init__.py
├── test
│ ├── __init__.py
│ └── test_system.py
├── zachary_computed.png
└── zachary_expected.png
meta.yaml 文件：
package:
name: sten
version: "0.1.0"
source:
path: ..
build:
number: 0
noarch: generic
requirements:
build:
- python >=3.7
- setuptools
run:
- python >=3.7
- pypardiso >=0.2.2
- numpy >=1.18.1
- networkx >=2.4
- scipy >=1.4.1
- markdown
test:
imports:
- sten.embedding
about:
home: https://github.com/monomonedula/simple-graph-embedding
license: Apache License 2.0
license_file: LICENSE.txt
summary: Simple deterministic algorithm for generating graph nodes topological embeddings.
我用来构建包的命令（haasad 是 pypardiso 包的频道名称）：
conda build conda-recipe -c haasad
构建成功，我已经上传到这里：
https://anaconda.org/monomonedula/sten
然而，安装后使用本地构建如下：
conda install sten --use-local -c haasad
并将构建上传到云端
conda install -c monomonedula sten -c haasad
我遇到了几个问题。
- 当使用 python 3.7 我无法导入我的包，即使它在
conda list中列出（我仔细检查了所有内容，我使用了正确的解释器）。 - 当使用 python 3.8 时，我可以导入并使用它，但由于未知原因我无法安装 stellargraph。错误信息：
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
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 each other:
Output in format: Requested package -> Available versions
conda search sten -c monomonedula --info 的输出：
sten 0.1.0 py38_0
-----------------
file name : sten-0.1.0-py38_0.tar.bz2
name : sten
version : 0.1.0
build : py38_0
build number: 0
size : 16 KB
license : Apache License 2.0
subdir : noarch
url : https://conda.anaconda.org/monomonedula/noarch/sten-0.1.0-py38_0.tar.bz2
md5 : 53661562513861f9433b252c8ae7b5f4
timestamp : 2020-05-23 19:24:36 UTC
dependencies:
- markdown
- networkx >=2.4
- numpy >=1.18.1
- pypardiso >=0.2.2
- python >=3.7
- scipy >=1.4.1
sten 0.1.0 py38_0
-----------------
file name : sten-0.1.0-py38_0.tar.bz2
name : sten
version : 0.1.0
build : py38_0
build number: 0
size : 16 KB
license : Apache License 2.0
subdir : noarch
url : https://conda.anaconda.org/monomonedula/noarch/sten-0.1.0-py38_0.tar.bz2
md5 : 53661562513861f9433b252c8ae7b5f4
timestamp : 2020-05-23 19:24:36 UTC
dependencies:
- markdown
- networkx >=2.4
- numpy >=1.18.1
- pypardiso >=0.2.2
- python >=3.7
- scipy >=1.4.1
conda search stellargraph -c stellargraph --info 的输出：
stellargraph 1.0.0 py_0
-----------------------
file name : stellargraph-1.0.0-py_0.tar.bz2
name : stellargraph
version : 1.0.0
build : py_0
build number: 0
size : 7.8 MB
license : Apache Software
subdir : noarch
url : https://conda.anaconda.org/stellargraph/noarch/stellargraph-1.0.0-py_0.tar.bz2
md5 : e62b9c897d0a5481159c1e7cb8024717
timestamp : 2020-05-05 07:54:44 UTC
dependencies:
- gensim >=3.4.0
- ipykernel
- ipython
- matplotlib >=2.2
- networkx >=2.2
- numpy >=1.14
- pandas >=0.24
- python >=3.6
- scikit-learn >=0.20
- scipy >=1.1.0
- tensorflow >=2.1.0
我在这里缺少什么以及如何正确打包它？
问题出在您的 meta.yaml 文件中。根据 Anaconda blog post:
Noarch generic packages allow users to distribute docs, datasets, and source code in conda packages
和
Noarch Python packages cut down on the overhead of building multiple different pure Python packages on different architectures and Python versions by sorting out platform and Python version-specific differences at install time
因为你想分发一个纯 python 包，你应该使用 noarch: python。此外，您不需要在 build 和 run 中设置 python 版本。我在下面包含了更新的 meta.yaml。它还包含构建脚本，因此您不再需要 build.sh 和 build.bat 文件。它还将许可部分修复为 conda 将接受的内容（它仍然是 Apache 2.0）。
package:
name: sten
version: "0.1.0"
source:
path: ..
build:
number: 0
noarch: python
script: {{ PYTHON }} setup.py install
requirements:
build:
- python
- setuptools
run:
- python
- pypardiso >=0.2.2
- numpy >=1.18.1
- networkx >=2.4
- scipy >=1.4.1
- markdown
test:
imports:
- sten.embedding
about:
home: https://github.com/monomonedula/simple-graph-embedding
license: Apache-2.0
license_family: Apache
license_file: LICENSE.txt
summary: Simple deterministic algorithm for generating graph nodes topological embeddings.
以下是我使用上述 meta.yaml 文件构建和安装此包的步骤：
git clone https://github.com/monomonedula/simple-graph-embedding
cd simple-graph-embedding/
git checkout 'refactor&cleanup'
# Replace contents of `meta.yaml`
rm conda-recipe/build.sh conda-recipe/build.bat
conda create --yes -n testing python=3.7 conda-build conda-verify
conda activate testing
conda-build --channel haasad .
这是我在 3.7 环境中安装包的方法。您会在 conda-build 日志输出的底部找到 sten-0.1.0-py_0.tar.bz2 的完整路径。
conda install -n testing /home/jakub/miniconda3/envs/testing/conda-bld/noarch/sten-0.1.0-py_0.tar.bz2
conda activate testing
$CONDA_PREFIX/bin/python -c "import sten"
我也在python3.8环境下测试了安装。
conda create --yes -n testing3.8 python=3.8
conda install -n testing3.8 /home/jakub/miniconda3/envs/testing/conda-bld/noarch/sten-0.1.0-py_0.tar.bz2
conda activate testing3.8
$CONDA_PREFIX/bin/python -c "import sten"
conda install --use-local sten 对我不起作用 - 有一个 GitHub issue 关于它。