There are many discussions on how to use conda environment variables in PyCharm projects. These discussions, however, often assume that for each PyCharm project only one conda environment variable is used. Then here is my question: is it possible to have multiple conda enviroment variables for the same project? I give the following example to make my point much clearer:
pycharm_project_name
abc.py (use conda environment variable: TensorFlow)
def.py (use conda environment variable: Caffe)
In this example, the PyCharm project has two python scripts with each depending on its own environment variable. In this case, how could I set the PyCharm project in a proper way?
If your goal is to run the scripts within a particular environment, this is easily acomplished using different run configurations for the different scripts. This will allow you to select the configuration from the dropdown and click play to run it.
The run configuration dialog has a "Python interpreter" option, where you can select the environment to run in.
Unfortunately, there is no simple way to configure different environments for the other popular way of running scripts, which is to right click on them and select the run option from there.
Related
I have a ROS application which has a work space with a setup.bash file and another python script with its own virtual environment.
So far this is what I do in my terminal:
1_ pipenv shell (to activate my python virtual environment).
2_ source ../ros_workspace/devel/setup.bash
3_ python some_python_script.py
This code works as I expect.
However, I want to do the same and run this script in pycharm, where my virtual environment is already activated. But how do I source the setup bash additionaly?
My setup.bash file also looks like the following:
What I have tried also is making a "before launch" as follows:
If you set your virtual environment as your interpreter of choice in PyCharm, it will use that particular virtual environment to run its scripts. However, you can also take advantage of some of the functionality that our run configurations provide.
You can check out the "Before Launch" part of the whole configuration window to enter scripts that you want executed.
Once you've set your configurations, you can then go on to run or debug the configuration. Furthermore, if it is just environment variables that you want to source, you can just put in the environment variables in the "Environment Variables" box.
In case you want to run a shellscript, you will need to create a new shell configuration like so:
Once you've added that configuration, you can then go on to reference it later.
You will now see that you can reference that configuration in question:
I am fairly new to creating Python applications. I have fooling around with some small tutorials and applications using PyCharm and have always created a new project using the Virtualenv environment, ending up with a "venv" folder under my project folder. I have not had any problems with this, but then again I have not done any large projects.
However, I have been wanting to learn Flask want to try to create a new Flask project the proper way. I see in many tutorials that people are creating (and activating) the virtual environment from the (Windows/Linux) Command Line instead even though they are using PyCharm and I was just wondering what the difference is?
When I work on a project in PyCharm, created with Virtualenv, I do not activate the venv before working on it. Is this wrong or is this something that is handled by PyCharm? What if the venv is created from a Command Line? Is it still handled (activated) by PyCharm if working on the project there. And what about the folder structure? Is this affected by how the virtual environment is created? Is there somewhere I can find some "best practices" for the setup / folder structure when creating Flask project within a Virtual Environment?
PyCharm activates the VirtualEnv for you if it is configured to use one and told where it is (more specifically, where the respective Python binary in the VirtualEnv is).
There's no real difference between manually created VirtualEnvs and ones created by PyCharm. (Apart from the framework you select to create one in case this is different from what PyCharm is configured with.)
If you want, you can just create one manually and then point PyCharm to it. Either during creation of the project or later using the Settings dialog (see Settings -> Project -> Project Interpreter). It will then treat it no differently and also activate it for you when working inside the IDE.
A virtual environment is pretty much just a folder which stores installed Python packages and isolates them from the rest of your system. This is so you can work on different projects which may all have competing requirements for external packages, without getting into conflicts. "Activating" a virtual environment just sets certain environment variables in your current shell so it'll use packages from this environment. "Activating" an environment never has any impact beyond your current shell. So activating an environment on the command line won't do anything to PyCharm.
PyCharm integrates a Python interpreter to give you lots of extra functionality. You tell PyCharm which interpreter you want to use for your project and it'll figure out what packages it has available, what version it is, and automatically set everything up properly for running your code from PyCharm etc. You can tell PyCharm to use your system's Python interpreter or an existing virtual environment or even use it to create a new environment. You don't need to do anything special beyond just selecting the right interpreter/environment in the project settings.
There's no reason to activate the environment from the command line if you're not going to use it from the command line. Of course, using Flask and running its server from the command line and keeping it running in the background may be useful. Not sure if PyCharm would give you an easy or integrated option to have persistent processes run in the background. You could still select the same virtual environment in PyCharm and use it to run your tests in it directly from PyCharm, use its debugger etc.
I prefer to keep the venv out of the project folder and store all venvs in ~/.virtualenvs/ or such. It declutters the project folder and prevents accidentally checking those files into the version control system.
I was just wondering what the difference is?
There's many tools for creating and using virtual environments and there's no difference between them, the only difference between them is their commands syntax (or the way it interact with users, e.g. for Pycharm you set some settings via GUI).
Is this wrong or is this something that is handled by PyCharm?
There's nothing wrong with it. As long as you have a venv (or .venv) directory in the root of your project and it is executable for any user, Pycharm will use it and it activates this virtual environment for you (without telling you). If Pycharm was not able to do that, (because of trouble in finding venv or activating/executing it!) then it will show you messages to fix its problems and it can't run your project till you fix them.
It's better to create your virtual environment in .venv directory right into the root directory of your project. (It's kind of conventional)
See python virtual environments and configuring pycharm virtualenv as well.
I'm teaching a beginners python class, the environment is Anaconda, VS Code and git (plus a few extras from a requirements.txt).
For the windows students this runs perfectly, however the mac students have an existing python (2.7) to contend with.
The windows students (i.e. they have a windows computer), their environment when they debug matches their console environment. However the mac students seem to be locked to their 2.7 environment.
I've tried aliasing, as suggested here and here
alias python2='python'
alias python='python3'
alias pip2='pip'
alias pip='pip3'
I've modified the .bash_profile file
echo 'export PATH="/Users/$USER/anaconda3/bin:$PATH"' >>.bash_profile
Both of these seem to work perfectly to modify their Terminal environments, when launched externally to VS Code. Neither seem to do anything to the environment launched from [cmd]+[`].
I've also tried conda activate base in the terminal, which seems to have no effect on a python --version or a which python
They can run things using python 3, but that means that they need to remember that they are different to the other 2/3 of the students. It's othering for them, and more work for me!
The students are doing fine, launching things from their external terminal, but it would streamline things greatly if the environments could be as consistent as possible across the OSs.
Whilst they are complete beginners, they can run a shell script. They currently have one that installs pip requirements and vs code extensions.
Is there a configuration that will keep the terminal in line with the debug env?
In my opinion the best practice is to create Python virtual environments (personally I love using conda environments, especially on Mac where you stuck with unremovable old Python version). Then VSCode will automatically (after installing very powerful Python extension) find all your virtual environments. This way you will teach your students a good practice of handling Python zoo a.k.a. package incompatibilities. Terminal environments settings will be consistent with VSCode, without being dependent on unneeded any more aliases. Obviously, virtual environments are OS independent, so you will be more consistent and remove unnecessary confusion between different students.
The additional bonus of the virtenvs is that you can create one exactly according to your requirements.txt and switch from one to another with a single click (in terminal it takes two commands: deactivate -> activate).
You can read more about how to handle Python virtual environments on VSCode site
Given the aliases are run just once and are not persistent in .bash_profile, python targets the default interpreter rather than the expected conda python3 interpreter.
Try to symlink conda's python3 executable to capture the python namespace
ln -sf /Users/$USER/anaconda3/bin/python3 /Users/$USER/anaconda3/bin/python
This will create or update the symlink. Use the same approach for pip and pip3.
Python in vscode let's you select which interpreter will be used to run the scripts.
It is in settings under "python.pythonPath", just set it to point to the interpreter of choice.
It can be set on a project basis as well (which is how you ensure that a project that has a virtual environment will execute using that interpreter and packages), you just select Workspace in the settings pane and add the desired python interpreter there.
We are trying to add venv functionality to our python project ie when one runs project an venv is created in project path and project runs on that venv.
For this to work we used vurtualenv's create environment method and activatethis.py the method creates venv ,
However when project runs it still uses host machine packages. Instead of using venv ones
Am I doing anything wrong..is it possible to do this??
PS: I have tried both site-packages true and false in create environment method .. however to no help
Adding more info:
Commands used are
venv_dir = os.path.join("path to project")
virtualenv.create_environment(venv_dir)
execfile(os.path.join(venv_dir, "bin", "activate_this.py"))
Also updated path environment variable to include bin of venv
After this I expect my code (after this) to run in virtual environment.
I am not using any ide and expect the code to create venv at runtime
Using python 2.7
Is there any other way to run project in virtual environment at run time without any ide in Ubuntu server environment.
You haven't provided enough information for us to come up with a solution to your exact problem, although I will do my best to help you out.
You should not be creating a venv every time you run the project, which it sounds like you are doing. This is essentially creating a new interpreter every single time you run your project. If you're using a decent IDE, such as PyCharm, you should be able to set this up properly through the project settings.
There are plenty of tutorials out there regarding setting up venv and virtualenv on your computer, and given that we don't know much about your system, your best bet is doing some further research.
Essentially, you need to
Create a venv for the project (and a new one for each project you make from here on out, unless you want to use the machine's interpreter)
Set the project interpreter to the venv you just created. Place any external libraries within ...\venv\Lib\site-packages
Hope this helps.
been searching for this with no success, i don't know if i am missing something but i have a virtualenv already but how do i create a project to associate the virtualenv with, thanks
P.S. Am on windows
I could be wrong here, but I do not believe that a virtualenv is something that is by its very nature something that you associate with a project. When you use a virtualenv, you're basically saying, "I'm taking this Python interpreter, installing what I want on it, and setting it aside from the Python interpreter that the entire computer uses by default." Virtualenv does not have a concept of a Python "project"; it is just a custom version of a Python interpreter that you run code through. There are tools in IDEs like PyCharm that enable you to associate a project with a virtualenv, but those are another layer on top of the base software.
In order to use a virtualenv with a project, you will need to "activate" it every time you wish to use it. The documentation for activating a virtualenv on Windows is found here.
EDIT:
Saw that you had virtualenvwrapper tagged in your post, so I did a bit of hunting on that. It would appear that there is the mkproject command, which creates a project folder and then associates it with a virtualenv interpreter. Documentation on it can be found here.
Requirements:
Virtual Env
Pycharm
Go to Virtual env and type which python
Add remote project interpreter (File > Default Settings > Project Interpreter (cog) add remote)
You'll need to set up your file system so that PyCharm can also open the project.
NOTE:
do not turn off your virtual environment without saving your run configurations that will cause pycharm to see your run configurations as corrupt
There's a button on the top right that reads share enable this and your run configs will be saved to a .idea file and you'll have a lot less issues
If you already have your virtualenv installed you just need to start using it.
Create your projects virtual environment using virtualenv env_name on cmd. To associate a specific version of python with your environment use: virtualenv env_name -p pythonx.x;
Activate your environment by navigating into its Scripts folder and executing activate.
Your terminal now is using your virtual environment, that means every python package you install and the python version you run will be the ones you configured inside your env.
I like to create environments with the names similar to my projects, I always use one environment to each project, that helps keeping track of which packages my specific projects need to run.
If you haven't read much about venvs yet, try googling about requirements.txt along with pip freeze command those are pretty useful to keep track of your project's packages.
I like Pipenv: Python Dev Workflow for Humans to manage environments:
Pipenv is a tool that aims to bring the best of all packaging worlds (bundler, composer, npm, cargo, yarn, etc.) to the Python world. Windows is a first-class citizen, in our world.
It automatically creates and manages a virtualenv for your projects, as well as adds/removes packages from your Pipfile as you install/uninstall packages. It also generates the ever-important Pipfile.lock, which is used to produce deterministic builds.
Pipenv is primarily meant to provide users and developers of applications with an easy method to setup a working environment.