I have to develop software with the use of several programs together, like Python 3.6 (with specific packages), WKHtmlToPdf and an embedded browser (based on CEF). I should be able to share all this together in one directory, so with a virutal environment of Python 3.6...
My question to you all is: how can I make the paths of a Python virtual env relative.
A second question I have is: is it possible to just activate the virtual env without changing cmd prompts and things? I tried to write a batch file which 1) starts the environment, 2) executes a Py script and 3) runs the embedded browser. That batch file failed after it started the virtual environment...
I should be able to share all this together in one directory, so with a virtual environment
Virtual environments are not portable (they must reside in the same directory on a computer where exist global Python), hence you cannot share a virtual environment.
My question to you all is: how can I make the paths of a Python virtual env relative.
No, and you certainly don't need to do it.
A second question I have is: is it possible to just activate the virtual env without changing cmd prompts
Yes, it's regulated in bin/activate script which you can edit to your taste.
and things?
What "things"? Activating virtual environment means changing PATH, PYTHONPATH and so on, you certainly cannot use virtual environment without changing these and other things.
That batch file failed
If you want us to help you should show us the essential parts of the batch and in what way it failed.
May be you need a different solution like a Docker image. Docker can be installed on Windows though it must be installed on the target computers.
There are also simpler solutions: py2exe, PyInstaller, cx_Freeze. They "compile" python scripts to .exe and accompany that .exe with Python interpreter (in a .dll) and library (in a .zip file). But if your program needs more DLLs you have to copy them to the target computer.
You can also take a look at RVirtualEnv. It allows to create relocatable virtual environments. I don't know if such envs can be copied to a different host, though.
Related
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 have a python file that I'd like to execute using the virtual environment (venv) in the same directory as the file. I'd like it to use this venv regardless of whether the user has activated it or not to avoid accidentally running it without the proper environment. I'd like this to work on both Linux and Windows (via Git Bash).
The issue is that venv puts python under the "bin" directory on Linux but under "Scripts" on Windows and I can't seem to find a way to change this behavior when creating it. I tried creating it with Git Bash in hopes that it would "trick" python into using a bin directory instead of Scripts, but that didn't work.
The following shebang works well on Linux:
#!.venv3/bin/python
And this one works well on Windows:
#!.venv3/Scripts/python
But what will work on both? I know that one option would be to create a shell script that activates the environment based on the detected os (using $OSTYPE), but I'd like to avoid this if possible as it isn't otherwise necessary.
You could use the Windows version of the shebang:
#!.venv3/Scripts/python
and then create a symbolic link on the Linux side:
.venv3/Scripts -> .venv3/bin
I just tried this with one of my virtual envs. It worked fine for me. I didn't test the Windows case, but of course, that has to work as we're using the correct shebang for Windows to begin with.
I'm teaching a beginners python class, the environment is Anaconda, VS Code and git (plus a few extras from a requirements.txt).
For the windows students this runs perfectly, however the mac students have an existing python (2.7) to contend with.
The windows students (i.e. they have a windows computer), their environment when they debug matches their console environment. However the mac students seem to be locked to their 2.7 environment.
I've tried aliasing, as suggested here and here
alias python2='python'
alias python='python3'
alias pip2='pip'
alias pip='pip3'
I've modified the .bash_profile file
echo 'export PATH="/Users/$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.
I have a Python app running on windows that has imports for the following packages:
requests
json
psycopg2
I copy the entire project (I used Pycharms to write the app and import the packages) to a new machine and expected it would work. The new machine is also windows and I'm trying to run my script from the command line (i.e. no Pycharm on the new machine).
Instead, I get an error saying "ModuleNotFoundError: No module named 'requests'"
If I look at the project, I have the directories:
venv
Lib
site-packages
requests
What am I missing/doing wrong?
You have a couple of options here but first the problem. You are exporting your code base to a new machine without the required Modules installed on that machine and/or within your Python project's environment. After you have python installed on your new machine, you need to be sure to point your PyCharm Project to the proper environment.
File > Default Preferences > Project Interpreter
The window that appears on the right will contain a drop down menu labeled Project Interpreter. If you click on the drop down, it should reveal a list of the available Python environments on your machine.
Based on your description of your site-packages directory I would assume you do not have your interpreter pointed the proper environment on your new machine. With that said, you would be better served creating a new virtual python environment on your machine and installing each relevant dependency within that environment.
Take a look at this post here for your first best option on re-creating your old python environment on your new machine.
EDIT: I apologize for not reading the question more thoroughly before answering the questions. If this is running on a Windows machine you will need to double check the environment path python is using. It is very easy to install python at a different PATH than the command line environment is checking on a Windows box. If for example your PATH is pointing to a different version of Python and PIP is installing packages somewhere else this issue can occur. Double check your System PATH for python and which version the command line is running.
On the new machine you must source venv/bin/activate so your path environment variables are set properly. In particular, which python should say venv/bin/python rather than /usr/bin/python. Also, take care to conda env update or pip install -r requirements.txt so you'll have suitable venv libraries on the new machine.
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.