Difference between revisions of "Install Python Packages in a Python virtual environment"
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=== Create Virtual Environment === | === Create Virtual Environment === | ||
− | Users can '''create''' as many virtual environments, each in their own directory, as needed. | + | Users can '''create''' as many virtual environments, each in their own directory, as needed. Note: if you are running on a machine that uses the module system to configure your computing environment, you might first need to load the desired python module to gain access to the version of python you'd like to run, e.g., via <code>module load python/3.9.4</code>. |
− | * python2: <code> | + | * python2: <code>python2 -m virtualenv <your virtual environment directory></code> |
* python3: <code>python3 -m venv <your virtual environment directory></code> | * python3: <code>python3 -m venv <your virtual environment directory></code> | ||
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<pre>pip list modules</pre> | <pre>pip list modules</pre> | ||
− | * '''Example''': | + | === Sample workflow === |
+ | |||
+ | * '''Example''': Create a new environment, and install <code>tensorflow</code> and <code>keras</code>: | ||
<pre> | <pre> | ||
− | $ module load python3 | + | $ module load python3 |
+ | (note: python3 is an example, the actual module on the cluster you are using may be different) | ||
+ | (use the "module avail" command to view the list of python versions you can load; it might be something like python/3.6) | ||
$ python3 -m venv tensorflow | $ python3 -m venv tensorflow | ||
$ source tensorflow/bin/activate | $ source tensorflow/bin/activate | ||
− | (tensorflow) $ pip install --upgrade pip | + | (tensorflow)$ pip install --upgrade pip |
Collecting pip | Collecting pip | ||
Using cached https://files.pythonhosted.org/packages/30/db/9e38760b32e3e7f40cce46dd5fb107b8c73840df38f0046d8e6514e675a1/pip-19.2.3-py2.py3-none-any.whl | Using cached https://files.pythonhosted.org/packages/30/db/9e38760b32e3e7f40cce46dd5fb107b8c73840df38f0046d8e6514e675a1/pip-19.2.3-py2.py3-none-any.whl | ||
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Successfully uninstalled pip-18.1 | Successfully uninstalled pip-18.1 | ||
Successfully installed pip-19.2.3 | Successfully installed pip-19.2.3 | ||
− | (tensorflow) | + | |
+ | (tensorflow)$ pip install tensorflow keras | ||
Collecting tensorflow | Collecting tensorflow | ||
Using cached https://files.pythonhosted.org/packages/de/f0/96fb2e0412ae9692dbf400e5b04432885f677ad6241c088ccc5fe7724d69/tensorflow-1.14.0-cp36-cp36m-manylinux1_x86_64.whl | Using cached https://files.pythonhosted.org/packages/de/f0/96fb2e0412ae9692dbf400e5b04432885f677ad6241c088ccc5fe7724d69/tensorflow-1.14.0-cp36-cp36m-manylinux1_x86_64.whl | ||
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: | : | ||
Successfully installed absl-py-0.8.0 astor-0.8.0 gast-0.2.2 google-pasta-0.1.7 grpcio-1.23.0 h5py-2.9.0 keras-2.2.5 keras-applications-1.0.8 keras-preprocessing-1.1.0 markdown-3.1.1 numpy-1.17.1 protobuf-3.9.1 pyyaml-5.1.2 scipy-1.3.1 six-1.12.0 tensorboard-1.14.0 tensorflow-1.14.0 tensorflow-estimator-1.14.0 termcolor-1.1.0 werkzeug-0.15.5 wheel-0.33.6 wrapt-1.11.2 | Successfully installed absl-py-0.8.0 astor-0.8.0 gast-0.2.2 google-pasta-0.1.7 grpcio-1.23.0 h5py-2.9.0 keras-2.2.5 keras-applications-1.0.8 keras-preprocessing-1.1.0 markdown-3.1.1 numpy-1.17.1 protobuf-3.9.1 pyyaml-5.1.2 scipy-1.3.1 six-1.12.0 tensorboard-1.14.0 tensorflow-1.14.0 tensorflow-estimator-1.14.0 termcolor-1.1.0 werkzeug-0.15.5 wheel-0.33.6 wrapt-1.11.2 | ||
− | (tensorflow) | + | |
+ | (tensorflow)$ pip list modules | ||
Package Version | Package Version | ||
-------------------- ------- | -------------------- ------- |
Latest revision as of 13:24, 30 April 2021
Manage Modules in Your Python Virtual Environment
Users can manage their own python environment (including installing needed modules) using virtual environments (works with python2 and python3). Please see the documentation on virtual environments on python.org for details.
Create Virtual Environment
Users can create as many virtual environments, each in their own directory, as needed. Note: if you are running on a machine that uses the module system to configure your computing environment, you might first need to load the desired python module to gain access to the version of python you'd like to run, e.g., via module load python/3.9.4
.
- python2:
python2 -m virtualenv <your virtual environment directory>
- python3:
python3 -m venv <your virtual environment directory>
Activate Virtual Environment
Next you need to activate a virtual environment before using it:
source <your virtual environment directory>/bin/activate
Install Python Modules Using pip
After activating your virtual environment, you can now install python modules for the activated environment:
- NOTE: It's always a good idea to update
pip
first:
pip install --upgrade pip
- Install the module:
pip install <module name>
- List installed python modules in the environment:
pip list modules
Sample workflow
- Example: Create a new environment, and install
tensorflow
andkeras
:
$ module load python3 (note: python3 is an example, the actual module on the cluster you are using may be different) (use the "module avail" command to view the list of python versions you can load; it might be something like python/3.6) $ python3 -m venv tensorflow $ source tensorflow/bin/activate (tensorflow)$ pip install --upgrade pip Collecting pip Using cached https://files.pythonhosted.org/packages/30/db/9e38760b32e3e7f40cce46dd5fb107b8c73840df38f0046d8e6514e675a1/pip-19.2.3-py2.py3-none-any.whl Installing collected packages: pip Found existing installation: pip 18.1 Uninstalling pip-18.1: Successfully uninstalled pip-18.1 Successfully installed pip-19.2.3 (tensorflow)$ pip install tensorflow keras Collecting tensorflow Using cached https://files.pythonhosted.org/packages/de/f0/96fb2e0412ae9692dbf400e5b04432885f677ad6241c088ccc5fe7724d69/tensorflow-1.14.0-cp36-cp36m-manylinux1_x86_64.whl : : : Successfully installed absl-py-0.8.0 astor-0.8.0 gast-0.2.2 google-pasta-0.1.7 grpcio-1.23.0 h5py-2.9.0 keras-2.2.5 keras-applications-1.0.8 keras-preprocessing-1.1.0 markdown-3.1.1 numpy-1.17.1 protobuf-3.9.1 pyyaml-5.1.2 scipy-1.3.1 six-1.12.0 tensorboard-1.14.0 tensorflow-1.14.0 tensorflow-estimator-1.14.0 termcolor-1.1.0 werkzeug-0.15.5 wheel-0.33.6 wrapt-1.11.2 (tensorflow)$ pip list modules Package Version -------------------- ------- absl-py 0.8.0 astor 0.8.0 gast 0.2.2 google-pasta 0.1.7 grpcio 1.23.0 h5py 2.9.0 Keras 2.2.5 Keras-Applications 1.0.8 Keras-Preprocessing 1.1.0 Markdown 3.1.1 numpy 1.17.1 pip 19.2.3 protobuf 3.9.1 PyYAML 5.1.2 scipy 1.3.1 setuptools 40.6.2 six 1.12.0 tensorboard 1.14.0 tensorflow 1.14.0 tensorflow-estimator 1.14.0 termcolor 1.1.0 Werkzeug 0.15.5 wheel 0.33.6 wrapt 1.11.2