I am a beginner in Python.
I read virtualenv is preferred during Python project development.
I couldn't understand this point at all. Why is virtualenv preferred?
Virtualenv keeps your Python packages in a virtual environment localized to your project, instead of forcing you to install your packages system-wide.
There are a number of benefits to this,
the first and principle one is that you can have multiple virtulenvs, so you
can have multiple sets of packages that for different projects, even
if those sets of packages would normally conflict with one another.
For instance, if one project you are working on runs on Django 1.4
and another runs on Django 1.6, virtualenvs can keep those projects
fully separate so you can satisfy both requirements at once.
the second, make it easy for you to release your project with its own dependent
modules.Thus you can make it easy to create your requirements.txt
file.
the third, is that it allows you to switch to another installed python interpreter for that project*. Very useful (Think old 2.x scripts), but sadly not available in the now built-in venv.
Note that virtualenv is about "virtual environments" but is not the same as "virtualization" or "virtual machines" (this is confusing to some). For instance, VMWare is totally different from virtualenv.
A Virtual Environment, put simply, is an isolated working copy of Python which allows you to work on a specific project without worry of affecting other projects.
For example, you can work on a project which requires Django 1.3 while also maintaining a project which requires Django 1.0.
VirtualEnv helps you create a Local Environment(not System wide) Specific to the Project you are working upon.
Hence, As you start working on Multiple projects, your projects would have different Dependencies (e.g different Django versions) hence you would need a different virtual Environment for each Project. VirtualEnv does this for you.
As, you are using VirtualEnv.. Try VirtualEnvWrapper : https://pypi.python.org/pypi/virtualenvwrapper
It provides some utilities to create switch and remove virtualenvs easily, e.g:
mkvirtualenv <name>: To create a new Virtualenv
workon <name> : To use a specified virtualenv
and some others
Suppose you are working on multiple projects, one project requires certain version of python and other project requires some other version. In case you are not working on virtual environment both projects will access the same version installed in your machine locally which in case can give error for one.
While in case of virtual environment you are creating a new instance of your machine where you can store all the libraries, versions separately. Each time you can create a new virtual environment and work on it as a new one.
There is no real point to them in 2022, they are a mechanism to accomplish what C#, Java, Node, and many other ecosystems have done for years without virtual environments.
Projects need to be able to specify their package and interpreter dependencies in isolation from other projects. Virtual Environments are a fine but legacy solution to that issue. (Vs a config file which specifies interpreter version and local __pypackages__)
pep 582 aims to address this lack of functionality in the python ecosystem.
Related
I create small apps and tools for automation. I've been using one project and one interpreter virtual env. (Python 3.9) With bunch of packages like pandas, numpy, Google APIs etc.. Needless to say, I also need to implement version control system (Github).
Would be good to use the same Virtual environment for many projects in this case, since I've been using more or less the same packages for my work. How would this affect py2app?
Associate this virtual environment with the current project is ticked. If I untick then I can use this environment in another project. Although, I need to know whether this change would affect Py2App.
I'm not a super experienced in terms of this but I need to look under the hood to have the best and smoothest solution.
Many thanks.
Problem:
We have two different python service which should be ran in a single server. Where we have a dependency clash. Say Project A needs module - older version while Project B needs the same module but with newer version.
To isolate we found Python Virtual Environment will solve this issue.
But the real question for me is the Virtual environment will be stable
and accepted on the production level usage.
Or Is there any other way we can approach for the problem.
Yes, you can
You can create virtual environment for first service where python version will be different and for second service, you can use different python version.
you can set these environment in running path of your services (for example in supervisor which we use for running process)
[program:service1]
command=path_to_virtualenv_for_service1 python service1.py
[program:service2]
command=path_to_virtualenv_for_service2 python service2.py
It is perfectly acceptable to use a virtual environment in production. In fact, it is often encouraged as it will ensure that any updates to the Python packages for one of the projects will not break the other.
A good alternative is to use separate Docker containers for each of the projects.
I created a django project and its interpreter is an 3.5.2 ENV, all the extensions that I install in Pycharm it doesn't recognize them, when I try to add them in Installed APPS, they aren't available.
But if the interpreter is only python.exe it recognizes.
So, How do I change the intrepeter of a project that is set to the 3.5 2 ENV to another, I don't know exatly what ENV is, and why it doesn't allow me to use installed extensions.
Go to preferences then project. You can set the interpreter there.
I assume the ENV you are talking about is a virtual environment. You normally create your project inside a virtual environment in order to maintain project-specific dependencies. E.g. If you install a dependency in your virtual environment, it can be accessed ONLY from that container. So, it is not installed system-wide and therefore cannot be accessed by things outside of the ENV.
Makes sense because you don't really want to install project specific things system-wide. E.g. what if you wanted to work on one project with Django 1.10 and another with 1.8? You would create two virtualenvs to encapsulate each!
I know it doesn't answer your main question but it may help to understand what's going on.
https://virtualenv.pypa.io/en/stable/
Another newbie to django here. I was wondering if it is recommended/not-recommended to run two different projects in the same virtualenv folder that have the same django version. To be more clear, is it necessary to create separate virtualenv everytime I want to start a new project when i know that i am using same django version for all projects. I am using python django on OSX.
It really depends on the situation. Suppose if your Project A need to use Pip version 17.01 to run while your project B need to use Pip version 18.01 to run. So It is not possible to use 1 virtual env to run multiple project but the downside of having multiple virtual environments is it consume much space & resource of PC.
I have reinstalled my operating system (moved from windows XP to Windows 7).
I have reinstalled Python 2.7.
But i had a lot of packages installed in my old environment.
(Django, sciPy, jinja2, matplotlib, numpy, networkx, to name just a view)
I still have my old Python installation lying around on a data partition, so i wondered if i can just copy-paste the old Python library folders onto the new installation?
Or do i need to reinstall every package?
Do the packages keep any information in registry, system variables or similar?
Does it depend on the package?
That's the point where you must be able to layout your project, thus having special tools for that.
Normally, Python packages do not do such wierd things as dealing with registry (unless they are packaged via MSI installer). The problems may start with packages that contain C extensions, so moving to another version of OS or from 32 to 64-bit architecture will require recompiling/rebuilding of those. So, it would be much better to reinstall all packages to new system as written below.
Your demands may vary, but you definitely must choose the way of building your environment. If you don't have and plan to have a large variety of projects you may consider the first approach as follows below, the second approach is more likely for setting up development environment for different projects or for different versions of the same project.
Global environment (your Python installation in your system along with installed packages).
Here you can consider using pip. In this case your project can have requirements file containing all needed packages for your project. Basically, requirements file is a text file containing package names (on PyPI and their versions).
Isolated environment. It can be achieved using special tools or specially organized path.
Here where pip can be gracefully combined with virtualenv. This way is highly recommended by a lot of developers (I must remind that Python 3.3 that will soon be released contains virtualenv as a part of standard library). This approach assumes creating virtual shell with its own instance of Python interpreter and installed packages.
Another popular tool for achieving isolated environment is called buildout. It lays out your project source and dependencies in one path so you achieve the same effect as virtualenv creates. The great advantage of buildout that it's built upon an idea of pluggable recipes (pieces of code implementing different common project deployment tasks) and there are hundreds of stable and reliable recipes over Internet.
Both virtualenv and buildout help you to remove head-ache when installing dependencies and solve the problem of different versions of the same package kept on a single machine.
Choose your destiny...
The short answer to this question is "no", since packages can execute arbitrary code on installation and do whatever the heck they want wherever they want on your system.
Just reinstall all of them.