如何通知 conda 安装更高版本的 apache-beam？
How do I inform conda to install a later version of apache-beam?
我是 Conda 新手，我正在尝试通过使用 miniconda 安装 python 软件包 apache-beam 来熟悉它。我可以在 https://anaconda.org/conda-forge/apache-beam 看到最新的可用版本是 v2.22.0
然而，当我尝试使用 conda install -c conda-forge/label/cf201901 apache-beam 安装时，它会尝试安装 v2.16.0:
# conda install -c conda-forge/label/cf201901 apache-beam
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: \
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- defaults/linux-64::mock==2.0.0=py37_0
- defaults/linux-64::pyarrow==0.13.0=py37he6710b0_0
- defaults/linux-64::mkl_random==1.1.1=py37h0573a6f_0
- defaults/linux-64::arrow-cpp==0.13.0=py37h117bdfb_0
- defaults/noarch::requests==2.25.1=pyhd3eb1b0_0
- defaults/linux-64::cryptography==2.3.1=py37hc365091_0
- defaults/noarch::packaging==20.8=pyhd3eb1b0_0
- defaults/noarch::pytest-xdist==2.2.0=pyhd3eb1b0_0
- conda-forge/linux-64::behave==1.2.6=py37h89c1867_1003
- conda-forge/linux-64::parse_type==0.5.2=py37h89c1867_3
- defaults/linux-64::pytest==6.2.1=py37h06a4308_0
- defaults/noarch::python-dateutil==2.8.1=py_0
- defaults/noarch::pytest-forked==1.3.0=py_0
- defaults/linux-64::mkl-service==2.3.0=py37he8ac12f_0
- defaults/linux-64::numpy-base==1.19.2=py37hfa32c7d_0
- defaults/linux-64::pandas==1.1.5=py37ha9443f7_0
- defaults/linux-64::requests-kerberos==0.12.0=py37_0
- defaults/noarch::urllib3==1.26.2=pyhd3eb1b0_0
- defaults/linux-64::numpy==1.19.2=py37h54aff64_0
- defaults/linux-64::mkl_fft==1.2.0=py37h23d657b_0
- defaults/noarch::python-hdfs==2.5.8=py_0
- defaults/linux-64::pyopenssl==19.0.0=py37_0
done
## Package Plan ##
environment location: /opt/conda/envs/python3
added / updated specs:
- apache-beam
The following packages will be downloaded:
package | build
---------------------------|-----------------
apache-beam-2.16.0 | py37h516909a_0 3.4 MB conda-forge
grpcio-1.16.0 | py37hd60e7a3_0 1.0 MB conda-forge/label/cf201901
oauth2client-4.1.3 | py_0 66 KB conda-forge
protobuf-3.6.0 | py37hf484d3e_0 609 KB main
six-1.11.0 | py37_1001 21 KB conda-forge/label/cf201901
------------------------------------------------------------
Total: 5.1 MB
The following NEW packages will be INSTALLED:
apache-beam conda-forge/linux-64::apache-beam-2.16.0-py37h516909a_0
grpcio conda-forge/label/cf201901/linux-64::grpcio-1.16.0-py37hd60e7a3_0
oauth2client conda-forge/noarch::oauth2client-4.1.3-py_0
protobuf main/linux-64::protobuf-3.6.0-py37hf484d3e_0
six conda-forge/label/cf201901/linux-64::six-1.11.0-py37_1001
这是为什么？
您的命令无法为您提供最新版本的一个可能原因是，当您为 conda forge 指定 cf201901 标签时它不可用，您可以在 website:
而且当您尝试明确指定版本时：
$ conda install -c conda-forge/label/cf201901 apache-beam=2.22
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
PackagesNotFoundError: The following packages are not available from current channels:
- apache-beam=2.22
Current channels:
- https://conda.anaconda.org/conda-forge/label/cf201901/linux-64
- https://conda.anaconda.org/conda-forge/label/cf201901/noarch
- https://repo.anaconda.com/pkgs/main/linux-64
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/r/linux-64
- https://repo.anaconda.com/pkgs/r/noarch
To search for alternate channels that may provide the conda package you're
looking for, navigate to
https://anaconda.org
and use the search bar at the top of the page.
所以尽量省略标签并指定你想要的版本：
conda install -c conda-forge apache-beam=2.22
不过我怀疑您已经将 conda-forge 添加到您的默认频道，因为您的输出已经显示 apache-beam 是从没有标签的 conda-forge 频道中提取的。
因此，如果以上仍然不起作用，则您当前环境中存在包（版本）冲突，conda 无法解决 apache-beam 版本 2.22
如果你只是为你需要的项目创建一个新的环境就可以解决这个问题apache-beam:
conda create -n <some name> -c conda-forge apache-beam
这将创建一个可以激活的环境
conda activate <some name>
@FlyingTeller 的回答准确地描述了问题和解决方案，但分享一些额外信息也无妨。
我忘了说我正在 docker 图像中构建我的 conda 环境，并且 docker 图像在 CI 管道中重建。为了确保我有一个可重复的构建，我在我的 repo 中有一个 environment.yaml 文件，它就是我用来构建 conda env 的文件。
在过去的一个月里，我不得不多次更改 environment.yaml 文件（我安装了 sh、apache-beam、pytest、pytest- xdict, ipython, behave...我认为这是我安装它们的顺序）我这样做的策略是：
docker run myimage:most-recently-built-tagconda install 所需的包- 导出新版本 environment.yaml
- 提交新版本 environment.yaml 到 repo
在这样做的过程中，我发现安装的 apache-beam 版本是 2.16.0，并且相互冲突的依赖项意味着我无法升级 apache-beam。
我创建了一个新环境并发布了 conda install sh apache-beam pytest pytest-xdict ipython behave，成功解决了所有依赖项并安装了 apache-beam=2.2.0。
因此我认为当我想对 environment.yaml 进行更改时，我的策略应该是：
- 创建一个新的 conda 环境
conda install 一个命令中所有需要的包- 导出一个新的 environment.yaml 并将其提交到存储库，以便它可以用于在 CI 中构建我的 docker 图像管道
欢迎对以上任何内容发表评论。
更新。这是我的 Dockerfile，它构建了一个 conda 环境，我可以从中导出 environment.yaml
FROM debian:buster-slim
RUN apt-get update && apt-get install curl gnupg -y
RUN curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring \
--fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" \
> /etc/apt/sources.list.d/conda.list
RUN MINICONDA_VERSION=4.9.2 && \
CONDA_VERSION='4.9.*' && \
CONDA_DIR=/opt/conda && \
cd /tmp && \
curl -O https://repo.anaconda.com/miniconda/Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh && \
/bin/bash Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh -f -b -p $CONDA_DIR && \
rm Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh && \
$CONDA_DIR/bin/conda config --system --set auto_update_conda false && \
$CONDA_DIR/bin/conda config --system --set show_channel_urls true && \
$CONDA_DIR/bin/conda config --system --remove channels defaults && \
$CONDA_DIR/bin/conda config --system --add channels main && \
$CONDA_DIR/bin/conda config --system --set env_prompt '({name}) ' && \
$CONDA_DIR/bin/conda config --system --append envs_dirs /opt/conda/envs/ && \
$CONDA_DIR/bin/conda config --system --append pkgs_dirs /opt/conda/pkgs/ && \
$CONDA_DIR/bin/conda update --quiet --yes --all conda="${CONDA_VERSION}" && \
$CONDA_DIR/bin/conda config --system --append channels conda-forge && \
$CONDA_DIR/bin/conda create -n py3 python=3.7
RUN bash -c "source /opt/conda/bin/activate /opt/conda/envs/py3 && conda install apache-beam sh pytest pytest-xdist ipython behave"
RUN echo "source /opt/conda/bin/activate /opt/conda/envs/py3" >> /root/.bashrc
并通过 运行:
生成我的 environment.yaml
docker build . -t conda-beam && \
docker run --entrypoint bash conda-beam:latest -c \
"source /opt/conda/bin/activate /opt/conda/envs/py3 \
&& conda env export"
我刚才运行的时候，返回
name: py3
channels:
- main
- conda-forge
dependencies:
- _libgcc_mutex=0.1=main
- apache-beam=2.22.0=py37h8f50634_0
- apipkg=1.5=py37_0
- arrow-cpp=0.15.1=py37h7cd5009_5
- attrs=20.3.0=pyhd3eb1b0_0
- backcall=0.2.0=py_0
- behave=1.2.6=py37h89c1867_1003
- blas=1.0=mkl
- boost-cpp=1.71.0=h7b6447c_0
- brotli=1.0.9=he6710b0_2
- brotlipy=0.7.0=py37h27cfd23_1003
- bzip2=1.0.8=h7b6447c_0
- c-ares=1.17.1=h27cfd23_0
- ca-certificates=2020.12.8=h06a4308_0
- certifi=2020.12.5=py37h06a4308_0
- cffi=1.14.4=py37h261ae71_0
- chardet=4.0.0=py37h06a4308_1003
- crcmod=1.7=py37hc8dfbb8_1003
- cryptography=3.3.1=py37h3c74f83_0
- cython=0.29.21=py37h2531618_0
- decorator=4.4.2=py_0
- dill=0.3.1.1=py37_1
- docopt=0.6.2=py37_0
- double-conversion=3.1.5=he6710b0_1
- execnet=1.7.1=py_0
- fastavro=0.23.5=py37h7b6447c_0
- future=0.18.2=py37_1
- gflags=2.2.2=he6710b0_0
- glog=0.4.0=he6710b0_0
- grpc-cpp=1.26.0=hf8bcb03_0
- grpcio=1.31.0=py37hf8bcb03_0
- httplib2=0.17.0=py37hc8dfbb8_1
- icu=58.2=he6710b0_3
- idna=2.10=py_0
- importlib-metadata=2.0.0=py_1
- importlib_metadata=2.0.0=1
- iniconfig=1.1.1=py_0
- intel-openmp=2020.2=254
- ipython=7.19.0=py37hb070fc8_0
- ipython_genutils=0.2.0=pyhd3eb1b0_1
- jedi=0.18.0=py37h06a4308_0
- krb5=1.18.2=h173b8e3_0
- ld_impl_linux-64=2.33.1=h53a641e_7
- libboost=1.71.0=h97c9712_0
- libedit=3.1.20191231=h14c3975_1
- libevent=2.1.8=h1ba5d50_1
- libffi=3.3=he6710b0_2
- libgcc-ng=9.1.0=hdf63c60_0
- libprotobuf=3.11.2=hd408876_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- lz4-c=1.8.1.2=h14c3975_0
- mkl=2020.2=256
- mkl-service=2.3.0=py37he8ac12f_0
- mkl_fft=1.2.0=py37h23d657b_0
- mkl_random=1.1.1=py37h0573a6f_0
- mock=2.0.0=py37_0
- more-itertools=8.6.0=pyhd3eb1b0_0
- ncurses=6.2=he6710b0_1
- numpy=1.19.2=py37h54aff64_0
- numpy-base=1.19.2=py37hfa32c7d_0
- oauth2client=4.1.3=py_0
- openssl=1.1.1i=h27cfd23_0
- packaging=20.8=pyhd3eb1b0_0
- pandas=1.2.0=py37ha9443f7_0
- parse=1.18.0=pyh9f0ad1d_0
- parse_type=0.5.2=py37h89c1867_3
- parso=0.7.0=py_0
- pbr=5.5.1=py_0
- pexpect=4.8.0=pyhd3eb1b0_3
- pickleshare=0.7.5=pyhd3eb1b0_1003
- pip=20.3.3=py37h06a4308_0
- pluggy=0.13.1=py37_0
- prompt-toolkit=3.0.8=py_0
- protobuf=3.11.2=py37he6710b0_0
- ptyprocess=0.7.0=pyhd3eb1b0_2
- py=1.10.0=pyhd3eb1b0_0
- pyarrow=0.15.1=py37h0573a6f_0
- pyasn1=0.4.8=py_0
- pyasn1-modules=0.2.8=py_0
- pycparser=2.20=py_2
- pydot=1.3.0=py37_0
- pygments=2.7.3=pyhd3eb1b0_0
- pykerberos=1.2.1=py37h680d80a_2
- pymongo=3.11.2=py37h2531618_0
- pyopenssl=20.0.1=pyhd3eb1b0_1
- pyparsing=2.4.7=py_0
- pysocks=1.7.1=py37_1
- pytest=6.2.1=py37h06a4308_0
- pytest-forked=1.3.0=py_0
- pytest-xdist=2.2.0=pyhd3eb1b0_0
- python=3.7.9=h7579374_0
- python-avro=1.9.2.1=py37hc8dfbb8_1
- python-dateutil=2.8.1=py_0
- python-hdfs=2.5.8=py_0
- python_abi=3.7=1_cp37m
- pytz=2020.5=pyhd3eb1b0_0
- pyyaml=5.3.1=py37h7b6447c_1
- re2=2020.11.01=h2531618_1
- readline=8.0=h7b6447c_0
- requests=2.25.1=pyhd3eb1b0_0
- requests-kerberos=0.12.0=py37_0
- rsa=4.7=pyhd3eb1b0_0
- setuptools=51.1.2=py37h06a4308_3
- sh=1.14.1=py37h06a4308_0
- six=1.11.0=py37_1
- snappy=1.1.8=he6710b0_0
- sqlite=3.33.0=h62c20be_0
- thrift-cpp=0.11.0=h02b749d_3
- tk=8.6.10=hbc83047_0
- toml=0.10.1=py_0
- traitlets=5.0.5=py_0
- typing-extensions=3.7.4.3=0
- typing_extensions=3.7.4.3=py_0
- uriparser=0.9.3=he6710b0_1
- urllib3=1.26.2=pyhd3eb1b0_0
- wcwidth=0.2.5=py_0
- wheel=0.36.2=pyhd3eb1b0_0
- xz=5.2.5=h7b6447c_0
- yaml=0.2.5=h7b6447c_0
- zipp=3.4.0=pyhd3eb1b0_0
- zlib=1.2.11=h7b6447c_3
- zstd=1.3.7=h0b5b093_0
prefix: /opt/conda/envs/py3
我是 Conda 新手，我正在尝试通过使用 miniconda 安装 python 软件包 apache-beam 来熟悉它。我可以在 https://anaconda.org/conda-forge/apache-beam 看到最新的可用版本是 v2.22.0
然而，当我尝试使用 conda install -c conda-forge/label/cf201901 apache-beam 安装时，它会尝试安装 v2.16.0:
# conda install -c conda-forge/label/cf201901 apache-beam
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: \
The environment is inconsistent, please check the package plan carefully
The following packages are causing the inconsistency:
- defaults/linux-64::mock==2.0.0=py37_0
- defaults/linux-64::pyarrow==0.13.0=py37he6710b0_0
- defaults/linux-64::mkl_random==1.1.1=py37h0573a6f_0
- defaults/linux-64::arrow-cpp==0.13.0=py37h117bdfb_0
- defaults/noarch::requests==2.25.1=pyhd3eb1b0_0
- defaults/linux-64::cryptography==2.3.1=py37hc365091_0
- defaults/noarch::packaging==20.8=pyhd3eb1b0_0
- defaults/noarch::pytest-xdist==2.2.0=pyhd3eb1b0_0
- conda-forge/linux-64::behave==1.2.6=py37h89c1867_1003
- conda-forge/linux-64::parse_type==0.5.2=py37h89c1867_3
- defaults/linux-64::pytest==6.2.1=py37h06a4308_0
- defaults/noarch::python-dateutil==2.8.1=py_0
- defaults/noarch::pytest-forked==1.3.0=py_0
- defaults/linux-64::mkl-service==2.3.0=py37he8ac12f_0
- defaults/linux-64::numpy-base==1.19.2=py37hfa32c7d_0
- defaults/linux-64::pandas==1.1.5=py37ha9443f7_0
- defaults/linux-64::requests-kerberos==0.12.0=py37_0
- defaults/noarch::urllib3==1.26.2=pyhd3eb1b0_0
- defaults/linux-64::numpy==1.19.2=py37h54aff64_0
- defaults/linux-64::mkl_fft==1.2.0=py37h23d657b_0
- defaults/noarch::python-hdfs==2.5.8=py_0
- defaults/linux-64::pyopenssl==19.0.0=py37_0
done
## Package Plan ##
environment location: /opt/conda/envs/python3
added / updated specs:
- apache-beam
The following packages will be downloaded:
package | build
---------------------------|-----------------
apache-beam-2.16.0 | py37h516909a_0 3.4 MB conda-forge
grpcio-1.16.0 | py37hd60e7a3_0 1.0 MB conda-forge/label/cf201901
oauth2client-4.1.3 | py_0 66 KB conda-forge
protobuf-3.6.0 | py37hf484d3e_0 609 KB main
six-1.11.0 | py37_1001 21 KB conda-forge/label/cf201901
------------------------------------------------------------
Total: 5.1 MB
The following NEW packages will be INSTALLED:
apache-beam conda-forge/linux-64::apache-beam-2.16.0-py37h516909a_0
grpcio conda-forge/label/cf201901/linux-64::grpcio-1.16.0-py37hd60e7a3_0
oauth2client conda-forge/noarch::oauth2client-4.1.3-py_0
protobuf main/linux-64::protobuf-3.6.0-py37hf484d3e_0
six conda-forge/label/cf201901/linux-64::six-1.11.0-py37_1001
这是为什么？
您的命令无法为您提供最新版本的一个可能原因是，当您为 conda forge 指定 cf201901 标签时它不可用，您可以在 website:
而且当您尝试明确指定版本时：
$ conda install -c conda-forge/label/cf201901 apache-beam=2.22
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
PackagesNotFoundError: The following packages are not available from current channels:
- apache-beam=2.22
Current channels:
- https://conda.anaconda.org/conda-forge/label/cf201901/linux-64
- https://conda.anaconda.org/conda-forge/label/cf201901/noarch
- https://repo.anaconda.com/pkgs/main/linux-64
- https://repo.anaconda.com/pkgs/main/noarch
- https://repo.anaconda.com/pkgs/r/linux-64
- https://repo.anaconda.com/pkgs/r/noarch
To search for alternate channels that may provide the conda package you're
looking for, navigate to
https://anaconda.org
and use the search bar at the top of the page.
所以尽量省略标签并指定你想要的版本：
conda install -c conda-forge apache-beam=2.22
不过我怀疑您已经将 conda-forge 添加到您的默认频道，因为您的输出已经显示 apache-beam 是从没有标签的 conda-forge 频道中提取的。
因此，如果以上仍然不起作用，则您当前环境中存在包（版本）冲突，conda 无法解决 apache-beam 版本 2.22
如果你只是为你需要的项目创建一个新的环境就可以解决这个问题apache-beam:
conda create -n <some name> -c conda-forge apache-beam
这将创建一个可以激活的环境
conda activate <some name>
@FlyingTeller 的回答准确地描述了问题和解决方案，但分享一些额外信息也无妨。
我忘了说我正在 docker 图像中构建我的 conda 环境，并且 docker 图像在 CI 管道中重建。为了确保我有一个可重复的构建，我在我的 repo 中有一个 environment.yaml 文件，它就是我用来构建 conda env 的文件。
在过去的一个月里，我不得不多次更改 environment.yaml 文件（我安装了 sh、apache-beam、pytest、pytest- xdict, ipython, behave...我认为这是我安装它们的顺序）我这样做的策略是：
docker run myimage:most-recently-built-tagconda install所需的包- 导出新版本 environment.yaml
- 提交新版本 environment.yaml 到 repo
在这样做的过程中，我发现安装的 apache-beam 版本是 2.16.0，并且相互冲突的依赖项意味着我无法升级 apache-beam。
我创建了一个新环境并发布了 conda install sh apache-beam pytest pytest-xdict ipython behave，成功解决了所有依赖项并安装了 apache-beam=2.2.0。
因此我认为当我想对 environment.yaml 进行更改时，我的策略应该是：
- 创建一个新的 conda 环境
conda install一个命令中所有需要的包- 导出一个新的 environment.yaml 并将其提交到存储库，以便它可以用于在 CI 中构建我的 docker 图像管道
欢迎对以上任何内容发表评论。
更新。这是我的 Dockerfile，它构建了一个 conda 环境，我可以从中导出 environment.yaml
FROM debian:buster-slim
RUN apt-get update && apt-get install curl gnupg -y
RUN curl https://repo.anaconda.com/pkgs/misc/gpgkeys/anaconda.asc | gpg --dearmor > conda.gpg && \
install -o root -g root -m 644 conda.gpg /usr/share/keyrings/conda-archive-keyring.gpg && \
gpg --keyring /usr/share/keyrings/conda-archive-keyring.gpg --no-default-keyring \
--fingerprint 34161F5BF5EB1D4BFBBB8F0A8AEB4F8B29D82806 && \
echo "deb [arch=amd64 signed-by=/usr/share/keyrings/conda-archive-keyring.gpg] https://repo.anaconda.com/pkgs/misc/debrepo/conda stable main" \
> /etc/apt/sources.list.d/conda.list
RUN MINICONDA_VERSION=4.9.2 && \
CONDA_VERSION='4.9.*' && \
CONDA_DIR=/opt/conda && \
cd /tmp && \
curl -O https://repo.anaconda.com/miniconda/Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh && \
/bin/bash Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh -f -b -p $CONDA_DIR && \
rm Miniconda3-py37_${MINICONDA_VERSION}-Linux-x86_64.sh && \
$CONDA_DIR/bin/conda config --system --set auto_update_conda false && \
$CONDA_DIR/bin/conda config --system --set show_channel_urls true && \
$CONDA_DIR/bin/conda config --system --remove channels defaults && \
$CONDA_DIR/bin/conda config --system --add channels main && \
$CONDA_DIR/bin/conda config --system --set env_prompt '({name}) ' && \
$CONDA_DIR/bin/conda config --system --append envs_dirs /opt/conda/envs/ && \
$CONDA_DIR/bin/conda config --system --append pkgs_dirs /opt/conda/pkgs/ && \
$CONDA_DIR/bin/conda update --quiet --yes --all conda="${CONDA_VERSION}" && \
$CONDA_DIR/bin/conda config --system --append channels conda-forge && \
$CONDA_DIR/bin/conda create -n py3 python=3.7
RUN bash -c "source /opt/conda/bin/activate /opt/conda/envs/py3 && conda install apache-beam sh pytest pytest-xdist ipython behave"
RUN echo "source /opt/conda/bin/activate /opt/conda/envs/py3" >> /root/.bashrc
并通过 运行:
生成我的 environment.yamldocker build . -t conda-beam && \
docker run --entrypoint bash conda-beam:latest -c \
"source /opt/conda/bin/activate /opt/conda/envs/py3 \
&& conda env export"
我刚才运行的时候，返回
name: py3
channels:
- main
- conda-forge
dependencies:
- _libgcc_mutex=0.1=main
- apache-beam=2.22.0=py37h8f50634_0
- apipkg=1.5=py37_0
- arrow-cpp=0.15.1=py37h7cd5009_5
- attrs=20.3.0=pyhd3eb1b0_0
- backcall=0.2.0=py_0
- behave=1.2.6=py37h89c1867_1003
- blas=1.0=mkl
- boost-cpp=1.71.0=h7b6447c_0
- brotli=1.0.9=he6710b0_2
- brotlipy=0.7.0=py37h27cfd23_1003
- bzip2=1.0.8=h7b6447c_0
- c-ares=1.17.1=h27cfd23_0
- ca-certificates=2020.12.8=h06a4308_0
- certifi=2020.12.5=py37h06a4308_0
- cffi=1.14.4=py37h261ae71_0
- chardet=4.0.0=py37h06a4308_1003
- crcmod=1.7=py37hc8dfbb8_1003
- cryptography=3.3.1=py37h3c74f83_0
- cython=0.29.21=py37h2531618_0
- decorator=4.4.2=py_0
- dill=0.3.1.1=py37_1
- docopt=0.6.2=py37_0
- double-conversion=3.1.5=he6710b0_1
- execnet=1.7.1=py_0
- fastavro=0.23.5=py37h7b6447c_0
- future=0.18.2=py37_1
- gflags=2.2.2=he6710b0_0
- glog=0.4.0=he6710b0_0
- grpc-cpp=1.26.0=hf8bcb03_0
- grpcio=1.31.0=py37hf8bcb03_0
- httplib2=0.17.0=py37hc8dfbb8_1
- icu=58.2=he6710b0_3
- idna=2.10=py_0
- importlib-metadata=2.0.0=py_1
- importlib_metadata=2.0.0=1
- iniconfig=1.1.1=py_0
- intel-openmp=2020.2=254
- ipython=7.19.0=py37hb070fc8_0
- ipython_genutils=0.2.0=pyhd3eb1b0_1
- jedi=0.18.0=py37h06a4308_0
- krb5=1.18.2=h173b8e3_0
- ld_impl_linux-64=2.33.1=h53a641e_7
- libboost=1.71.0=h97c9712_0
- libedit=3.1.20191231=h14c3975_1
- libevent=2.1.8=h1ba5d50_1
- libffi=3.3=he6710b0_2
- libgcc-ng=9.1.0=hdf63c60_0
- libprotobuf=3.11.2=hd408876_0
- libstdcxx-ng=9.1.0=hdf63c60_0
- lz4-c=1.8.1.2=h14c3975_0
- mkl=2020.2=256
- mkl-service=2.3.0=py37he8ac12f_0
- mkl_fft=1.2.0=py37h23d657b_0
- mkl_random=1.1.1=py37h0573a6f_0
- mock=2.0.0=py37_0
- more-itertools=8.6.0=pyhd3eb1b0_0
- ncurses=6.2=he6710b0_1
- numpy=1.19.2=py37h54aff64_0
- numpy-base=1.19.2=py37hfa32c7d_0
- oauth2client=4.1.3=py_0
- openssl=1.1.1i=h27cfd23_0
- packaging=20.8=pyhd3eb1b0_0
- pandas=1.2.0=py37ha9443f7_0
- parse=1.18.0=pyh9f0ad1d_0
- parse_type=0.5.2=py37h89c1867_3
- parso=0.7.0=py_0
- pbr=5.5.1=py_0
- pexpect=4.8.0=pyhd3eb1b0_3
- pickleshare=0.7.5=pyhd3eb1b0_1003
- pip=20.3.3=py37h06a4308_0
- pluggy=0.13.1=py37_0
- prompt-toolkit=3.0.8=py_0
- protobuf=3.11.2=py37he6710b0_0
- ptyprocess=0.7.0=pyhd3eb1b0_2
- py=1.10.0=pyhd3eb1b0_0
- pyarrow=0.15.1=py37h0573a6f_0
- pyasn1=0.4.8=py_0
- pyasn1-modules=0.2.8=py_0
- pycparser=2.20=py_2
- pydot=1.3.0=py37_0
- pygments=2.7.3=pyhd3eb1b0_0
- pykerberos=1.2.1=py37h680d80a_2
- pymongo=3.11.2=py37h2531618_0
- pyopenssl=20.0.1=pyhd3eb1b0_1
- pyparsing=2.4.7=py_0
- pysocks=1.7.1=py37_1
- pytest=6.2.1=py37h06a4308_0
- pytest-forked=1.3.0=py_0
- pytest-xdist=2.2.0=pyhd3eb1b0_0
- python=3.7.9=h7579374_0
- python-avro=1.9.2.1=py37hc8dfbb8_1
- python-dateutil=2.8.1=py_0
- python-hdfs=2.5.8=py_0
- python_abi=3.7=1_cp37m
- pytz=2020.5=pyhd3eb1b0_0
- pyyaml=5.3.1=py37h7b6447c_1
- re2=2020.11.01=h2531618_1
- readline=8.0=h7b6447c_0
- requests=2.25.1=pyhd3eb1b0_0
- requests-kerberos=0.12.0=py37_0
- rsa=4.7=pyhd3eb1b0_0
- setuptools=51.1.2=py37h06a4308_3
- sh=1.14.1=py37h06a4308_0
- six=1.11.0=py37_1
- snappy=1.1.8=he6710b0_0
- sqlite=3.33.0=h62c20be_0
- thrift-cpp=0.11.0=h02b749d_3
- tk=8.6.10=hbc83047_0
- toml=0.10.1=py_0
- traitlets=5.0.5=py_0
- typing-extensions=3.7.4.3=0
- typing_extensions=3.7.4.3=py_0
- uriparser=0.9.3=he6710b0_1
- urllib3=1.26.2=pyhd3eb1b0_0
- wcwidth=0.2.5=py_0
- wheel=0.36.2=pyhd3eb1b0_0
- xz=5.2.5=h7b6447c_0
- yaml=0.2.5=h7b6447c_0
- zipp=3.4.0=pyhd3eb1b0_0
- zlib=1.2.11=h7b6447c_3
- zstd=1.3.7=h0b5b093_0
prefix: /opt/conda/envs/py3