I have python3.7, python3.8, python3.9, and python3.10 in my ubuntu 22.04 system. I created four virtual environments with each of these versions. They are py37, py38, py39, and py310, respectively.
I have a requirement.txt file and want to install those packages to those four venvs. I can manually activate each environment one by one and then install using python3 -m pip install -r requirement.txt.
My question is, is there a way from the terminal I can activate, install and deactivate the venvs using a loop. I am looking for a python solution, though shell scripts are also welcome.
Thanks
Related
I have a 2-part question about conda vs. pip virtual environments. I found great information on the answers What is the difference between pip and conda? and Does Conda replace the need for virtualenv? but still have something unclear.
I have a given python project (say PR) that I need to install and further develop on a linux server (say S) where python is installed with anaconda. Now, the usage/installation instructions of PR tell me to use python to create virtual environment and pip to install all packages. That is,
python3 -m venv PR
pip install --editable . (the dot included at the end)
According to "pip install --editable ./" vs "python setup.py develop" the latter reads the file setup.py (included in PR) which contains a function setup(...) with option install_requires listing all the required packages and installs them automatically. I have tested this on my own computer (which does not have conda) and it works fine. At least no error messages.
Now I need to further develop PR on S. My question Part 1: can I use conda instead of pip to create and update virtual environment? If yes, what would be the conda command replacing pip install --editable . ? I'm positive I will later need to install other packages as well. I'm worried about conflicts between conda/pip.
On S, I have Spyder and no other python IDEs. I have never used Spyder but I'm very familiar with PyCharm (Windows) and VS Code (Linux) so I assume debugging with Spyder will be similar to those. My question Part 2 (tied to Part 1): if I have to use pip to install packages, does Spyder see those? Or can it only see conda-installed packages?
(Edit/update): Thank you Carlos for comments. I continue my question:
I created and activated the virtual environment (VE) with conda
conda create PR_venv
conda activate PR_venv
Installed pip with
conda install pip
(this upgraded pip and installed several other packages too, including newer version of python). Installed PR and its required packages with pip
pip install -e .
Now, if I run the PR package inside this active VE interactively from the terminal, everything works fine. I would like to do the same from within spyder, to get the IDE debugging abilities in my hand.
When I start spyder, open a python file to be run, click "Run" button, it crashes in the import statements.
Spyder cannot see the installed packages. It can see only the local package PR but none of the packages installed by pip for this VE.
I am not sure what is the correct question here; I'm confused how are conda VEs related to spyder/jupyter/ipython ? I cannot find information in the conda documents about this.
I cannot find from spyder documents anything about VEs. Do I have to somehow re-install the packages (how?) inside Spyder? It seems pointless because the packages are installed already.
(Edit/Update 2): The information on https://docs.spyder-ide.org/current/installation.html makes me even more confused: Spyder is presented as both a stand-alone program and as a python package. So do I have to re-install Spyder inside the VE(?!) with
conda activate PR_venv
conda install spyder
Any clarification would be appreciated. I have always thought that the IDEs are stand-alone programs and that's it. This Spyder setup twists my brains into pretzel.
(Spyder maintainer here) About your questions:
can I use conda instead of pip to create and update virtual environment?
Yes, you can. Please see here to learn about the functionality offered by conda for managing environments.
If yes, what would be the conda command replacing pip install --editable . ?
Conda doesn't offer a good replacement for that command. However, you can still use it in a conda environment, as long as all you've installed all your package dependencies with conda before running it. That would avoid mixing conda and pip packages, which usually leads to really bad results.
if I have to use pip to install packages, does Spyder see those? Or can it only see conda-installed packages?
Spyder can work with pip and conda packages without problems. Just make sure of not mixing them (as I said above) and you'll be fine. In addition, please read our documentation to learn how to connect a local Spyder instance to a remote server.
Part 1: yes I can use conda to create VE and pip to install packages
conda create PR_venv
conda activate PR_venv
conda install pip
pip install --editable .
conda list
The last line shows which packages are installed by conda and which by pip (shown as pypi)
Part 2: spyder by default cannot see the packages. Need to do two things:
conda install spyder-kernels
Open Spyder and Tools > Preferences > Python Interpreter > Use the following interpreter > [full path to VE python command]
Restart Spyder. Now it can see the packages.
(Edit:) this link is great: https://github.com/spyder-ide/spyder/wiki/Working-with-packages-and-environments-in-Spyder
I have different venvs in my machine in which I have python 3.10.
Now for a specific project, I realised that python 3.10 is not suitable as some libraries are still not compatible. Therefore when creating a new venv for a new project, I would like to downgrade python, say to 3.8, only for this specific venv.
How can I do that?
What should I type onto the terminal to do this?
PS: I use VS and its terminal to create venv
The recommended way by python.org
The recommended way of managing virtual environments since Python 3.5 is with the venv module within the Python Standard Library itself.
Source: https://docs.python.org/3/library/venv.html#creating-virtual-environments
That is not the same as virtualenv, which is a third party package, outside the Python Standard Library.
Source: https://pypi.org/project/virtualenv/
Dangerous to downgrade (and to upgrade)
Depending on if your system itself uses Python, it could be dangerous for system stability to change the system Python version. Your system might need exactly that version of Python. That is true with Ubuntu.
Install another version of Python
Safer than downgrading or upgrading is installing other versions of Python on the same system.
For example, in Ubuntu 20.04, to install Python 3.9:
# Update package lists
me#mydevice:~$ sudo apt update
# Add the deadsnakes repository
me#mydevice:~$ sudo add-apt-repository ppa:deadsnakes/ppa
# Install Python 3.9
me#mydevice:~$ sudo apt install python3.9
Install the venv package and create a venv virtual environment
# Install the venv package for Python 3.9
me#mydevice:~$ sudo apt install python3.9-venv
# Make a folder for venv virtual environments
me#mydevice:~$ mkdir ~/.venvs
# Create a new venv virtual environment with Python 3.9 in it
me#mydevice:~$ python3.9 -m venv ~/.venvs/my-venv-name
# Activate the new venv
me#mydevice:~$ source ~/.venvs/my-venv-name/bin/activate
(my-venv-name) me#mydevice:~$
Check versions within the venv virtual environment
# Check the Python version inside the venv:
(my-venv-name) me#mydevice:~$ python -V
Python 3.9.9
# Check the Pip version inside the venv:
(my-venv-name) me#mydevice:~$ pip3 --version
pip 21.2.4 from /home/me/.venvs/my-venv-name/lib/python3.9/site-packages/pip (python 3.9)
Deactivate the venv virtual environment
(my-venv-name) me#mydevice:~$ deactivate
me#mydevice:~$
Check versions outside any virtual environments
# Check Python version:
me#mydevice:~$ python -V
Python 3.8.10
# Check the Pip version:
me#mydevice:~$ pip3 --version
pip 20.0.2 from /home/me/.venvs/my-venv-name/lib/python3.8/site-packages/pip (python 3.8)
Install more Python versions
To install more Python versions, just change the version number from 3.9 to which ever version you choose, that is available from the deadsnakes repository.
I believe the best way to work with different python versions in isolation is pyenv, managing virtual environments can be done with pyenv-virtualenv.
I think this article from Real Python does a good job at explaining how to manage different python versions as well as different virtual environments.
For posterity, with the tools mentioned above you can do the following (once the proper python versions are installed)
pyenv virtualenv <python_version> <environment_name>
# Then activate it
pyenv local <environment_name>
Now that you've created a virtual environment in the folder, it should be picked up any time you enter the folder. VSCode should also pick it up, as per its documentation.
P.S: The reason I think it's a good approach it's because it allows you to manage python versions as well as environments with a single tool. Each version is installed only once, in one place, which should help because it reduces complexity.
Simple and recent
Supposed that you have a different version of Python installed in your system. To check use the following command to check:
> py --list
-3.10-64 *
-3.7-64
And you want to create a new virtual environment for python 3.7 on a 'test_env' directory. Run the following command:
> py -3.7 -m venv test_env
Then activate the test_env by running the following command on Windows PowerShell:
> .\test_env\Scripts\Activate.ps1
Or Linux:
$ source test_env/bin/activate
Check:
python --version
Python 3.7.0
You can have multiple python versions installed at the same time and you can create virtual environments with the needed version. Make sure you have installed the python version you need and then specify its location when you create the virtual environment:
virtualenv -p <path-to-new-python-installation> <new-venv-name>
Example:
virtualenv -p C:\Users\ssharma\AppData\Local\Programs\Python\Python38\python.exe venv38
This will create a virtual environment called venv38 with Python 3.8.
you can do it by using "virtualenv" library. It can be installed with command pip install virtualenv
then followed by command
virtualenv "name_of_your_environment" #no quotes
and then use the following code to activate your venv
"name_of_your_environment"\Scripts\activate #NOTE YOU MUST BE at your directory where you created your env.
its for VS CODE but I prefer installing conda and then creating env on conda prompt using conda which later you can access to vs code to and its easy to activate that env from anywhere just type conda activate 'name_of_your_env' on vs terminal
You can use anaconda:
conda create -n mypython3.8 python=3.8
For merely the sake of enough porridge in your stew.
For a project I made a virtual environment (venv) using Python3. I installed all the necessary dependencies using a simple bash script (see picture below) after I activated my venv. (I verified the installed packages using: pip3 list and concluded that every dependency was installed succesfully.)
My project uses snakemake, so I ran this snakemake commando:
snakemake --snakefile Snakefile.py all
I get this error:
I know it has to do something with the venv, because without the venv snakemake runs perfectly. I have read the Snakemake installation documents and it says I have to install conda and make & activate a conda venv. But, I do not have the sudo privileges to download and install conda (I work on a protected server).
What is happening and does someone know a fix?
One possible reason could be the difference in Python versions. What version of Python does the pip3 prepare environment for?
As I can see from the picture provided, the invalid syntax may be because of the version of Python doesn't support f-strings.
Imagine the following two scenarios: when you run Snakemake manually, you use the latest Python3 (e.g. 3.9). But if the pip3 is configured for an older version (e.g. 3.5), you can configure a very different environment for Python3.5 that doesn't support f-strings.
I am new to Ubuntu and Python virtualenv. Since I realized the importance of virtualenv, I'd like to use it by default whenever I run python(from installing packages, to using Jupyter) so that I don't need to run source bin/activate every time.
I am working with Python 3.6 and I am having a project for which I created requirements.txt file using pipreqs. But when I run pip install -r requirements.txt, the build fails because a specific library GDAL can be installed only using those three commands:
conda create -n gdal_test python=3.5
activate gdal_test
conda install gdal
What is the best way to deal with this if I want everyone to be able to install things without issues on different local machines and different EC2 instances on AWS and using microservices? Obviously only running requirements file is not going to work. Is Docker a solution? If so, how? Do I also need a setup.py file? Thanks.