I created a package, containing Pipfile, and I want to test with docker.
I want to install packages written in Pipfile with pip, without creating virutalenv.
# (do something to create some-file)
RUN pip install (some-file)
How to do?
Eventually pip should be able to do this itself, at least that's what they say. Currently, that is not yet implemented.
For now, a Pipfile is a TOML file, so you can use a TOML parser to extract the package constraints and emit them in a format that will be recognized by pip. For example, if your Pipfile contains only simple string version specifiers, this little script will write out a requirements.txt file that you can then pass to pip install -r:
import sys
import toml
with open(sys.argv[1]) as f:
result = toml.load(f)
for package, constraint in result['packages'].items():
if constraint == '*':
print(package)
else:
print(f'{package} {constraint}')
If your Pipfile contains more complicated constructs, you'll have to edit this code to account for them.
An alternative that you might consider, which is suitable for a Docker container, is to use pipenv to install the packages into the system Python installation and just remove the generated virtual environment afterwards.
pipenv install --system
pipenv --rm
However, strictly speaking that doesn't achieve your stated goal of doing this without creating a virtualenv.
One of the other answers lead to me to this, but wanted to explicitly call it out, and why it's a useful solution.
Pipenv is useful as it helps you create a virtual environment. This is great on your local dev machine as you will often have many projects, with different dependencies etc.
In CICD, you will be using containers that are often are only spun up for a few minutes to complete part of your CICD pipeline. Since you will spin up a new container each time you run your pipeline, there is no need to create a virtual environment in your container to keep things organised. You can simply install all your dependencies directly to the main OS version of python.
To do this, run the below command in your CICD pipeline:
pipenv install --system
Related
My question is do i have to install django every single time in my virtual environment in order to run my python files? and is this taking up bunch of space on my machine? My project also uses "matplotlib" and every virtual environment i create it also asks me to import the matplotlib module too. its getting annoying. do i have to do this every time?
Im new to Django. I wanted to run some python files in django but they weren't working, so after some research i found out i needed to run my pycharm project in a virtual environment in order to run these python files.
my folders look like this pycharmProjects -> my project
I enter pycharmProjects and I set up virtual environment using "pienv shell". Then i run "python3 manage.py runserver". It turns out i must install django in the virtual environment before the files run.
Short answer is no, you don't have to use a virtual environment at all and can install your dependancies globally instead. However you will soon find that it will cause a lot of issues. The main reason you would create a virtual environment is to give control of your dependancies and prevent bugs that could be caused because of them having their wires crossed between projects.
Short answer yes.
If you create a virualenv you have to install all packages, that your program needs.
Long answer:
You could install django system wide and then create a virtualenv with the option
--system-site-packages then django would be used from your globally installed python.
(Or you install everything just in your global python, put I personally don't think this is good practice)
If you work with many different projects I think you will avoid a lot of trouble if you use one virtualenv per project.
Trouble meaning that one project breaks, because one pip install for another project changed the version of one package and one project can't handle the newer version.
I would recommend to create a requirements.txt file for each project, that lists the dependencies then you can create the virtualenv with following command
pip install -r requirements.txt
if you have requirement.txt files, then you can create virtualenvs rather quickly if going back to an old project and you can delete the virtualenvs whenever you run out of disk space. If you want to be an the safe side, type pip freeze > pipfreeze.txt prior to deleting the virtualenv and use pip install -r pipfreeze.txt if you want to create one with the same modules and the same versions.
You also might want to look at direnv or autoenv if working on a linux like system.
This will automatically switch to the required virtualenv when changing to a project's working directory.
I've been going around but was not able to find a definitive answer...
So here's my question..
I come from javascript background. I'm trying to pickup python now.
In javascript, the basic practice would be to npm install (or use yarn)
This would install some required module in a specific project.
Now, for python, I've figured out that pip install is the module manager.
I can't seem to figure out how to install this specific to a project (like how javascript does it)
Instead, it's all global.. I've found --user flag, but that's not really I'm looking for.
I've come to conclusion that this is just a complete different schema and I shouldn't try to approach as I have when using javascript.
However, I can't really find a good document why this method was favored.
It may be just my problem but I just can't not think about how I'm consistently bloating my pip global folder with modules that I'm only ever gonna use once for some single project.
Thanks.
A.) Anaconda (the simplest) Just download “Anaconda” that contains a lots of python modules pre installed just use them and it also has code editors. You can creat multiple module collections with the GUI.
B.) Venv = virtual environments (if you need something light and specific that contains specific packages for every project
macOS terminal commands:
Install venv
pip install virtualenv
Setup Venve (INSIDE BASE Project folder)
python3 -m venv thenameofyourvirtualenvironment
Start Venve
source thenameofyourvirtualenvironment/bin/activate
Stop Venve
deactivate
while it is activated you can install specific packages ex.:
pip -q install bcrypt
C.) Use “Docker” it is great if you want to go in depth and have a solide experience, but it can get complicated.
Pip is a program used to manage Python distribution. You usually have one system distribution which is by default managed by Pip. When you do pip install scipy, you install package scipy to your system Python. Everytime you try to import scipy after it will work because your system Python has it.
Project specific distributions are acomplished by using virtual environments. python -m venv env or venv env creates a copy of system Python interpreter, pip, setuptools and a couple of other essential tools. In other words, virtual environment created this way is empty.
To use created virtual environement one should use source env/bin/activate. After that, everytime you invoke python command it will use activated Python interpreter. When you install packages using pip, it will install them in the virtual environment rather than to your system python. To use system Python again use deactivate.
Such usage is actually prefered for projects because some user applications could rely on system Python and some packages, and installing, updating etc. could be potentionally dangerous.
Further reading: venv documentation
I have a python library that I am wanting to help out with and fix some issues. I just don't know how to test my changes given the complexity of how python/pip installs libraries.
I have the library installed with pip and I can run python code connecting to the library by doing an "from import *". But now that I want to make changes to it I pulled the code with git and plan to branch to work on my changes. That's fine. I will then do a pull request to merge any changes given tests pass.
But after I make a change, how do I integrate my changes into python to test out the changes I made with the library? Can pip install my custom/modified version of the library?
I have looked around and haven't successfully found an answer to this but perhaps I'm not looking in the right spot.
Can pip install my custom/modified version of the library?
Yes.
There are various ways of approaching this question. A common solution is the use of Python virtual environments. This allows you to create an isolated Python environment that does not share the same packages as your system Python install. You can then install things into it (such as your modified Python library) to test it out.
To get started, you need the virtualenv tool. This is probably available as a package for your distribution, but you can also install it using pip. Once you have it, you can run in the same directory as your code:
virtualenv .venv
This creates a virtuelenv named .venv. You can call it anything you want, but naming it .venv (or anything starting with a .) means it won't clutter up the output of ls in your workspace.
Next, you need to activate the virtualenv:
. .venv/bin/activate.sh
This modifies your $PATH to place the virtualenv at the front of the list of directories. Now when you type python or pip, you'll be using the virtualenv version.
If your code has a setup.py file, you can install it like this:
pip install -e .
The -e means you want to perform an "editable" install, which means python will use the code "in place", and any changes you make will be immediately visible to the code you use for testing.
When you're done, you can run:
deactivate
This will remove the changes that activate made to your environment.
For more information:
Pipenv & Virtual Environments discusses a higher level tool for managing virtual environments.
Virtualenvwrapper is another take on a higher level management tool.
I primarily work these days with Python 2.7 and Django 1.3.3 (hosted on Heroku) and I have multiple projects that I maintain. I've been working on a Desktop with Ubuntu running inside of a VirtualBox, but recently had to take a trip and wanted to get everything loaded up on my notebook. But, what I quickly discovered was that virtualenv + Github is really easy for creating projects, but I struggled to try and get them moved over to my notebook. The approach that I sort of came up with was to create new virtualenv and then clone the code from github. But, I couldn't do it in the folder that I really wanted because it would say the folder is not empty. So, I would clone it to a tmp folder than them cut/paste the everthing into where I really wanted it. Not TERRIBLE, but I just feel like I'm missing something here and that it should be easier. Maybe clone first, then mkvirtualenv?
It's not a crushing problem, but I'm thinking about making some more changes (like getting ride of the VirtualBox and just going with a Dual boot system) and it would be great if I could make it a bit smoother. :)
Finally, I found and read a few posts about moving git repos between computers, but I didn't see any dealing with Virtualenv (maybe I just missed it).
EDIT: Just to be clear and avoid confusion, I'm not try to "move" the virtualenv. I'm just talking about best way to create a new one. Install the packages, and then clone the repo from github.
The only workflow you should need is:
git clone repo_url somedir
cd somedir
virtualenv <name of environment directory>
source <name of environment directory>/bin/activate
pip install -r requirements.txt
This assumes that you have run pip freeze > requirements.txt (while the venv is activated) to list all the virtualenv-pip-installed libraries and checked it into the repo.
That's because you're not even supposed to move virtualenvs to different locations on one system (there's relocation support, but it's experimental), let alone from one system to another. Create a new virtualenv:
Install virtualenv on the other system
Get a requirements.txt, either by writing one or by storing the output of pip freeze (and editing the output)
Move the requirements.txt to the other system, create a new virtualenv, and install the libraries via pip install -r requirements.txt.
Clone the git repository on the other system
For more advanced needs, you can create a bootstrapping script which includes virtualenv + custom code to set up anything else.
EDIT: Having the root of the virtualenv and the root of your repository in the same directory seems like a pretty bad idea to me. Put the repository in a directory inside the virtualenv root, or put them into completely separate trees. Not only you avoid git (rightfully -- usually, everything not tracked by git is fair game to delete) complaining about existing files, you can also use the virtualenv for multiple repositories and avoid name collisions.
In addition to scripting creating a new virtualenv, you should make a requirements.txt file that has all of your dependencies (e.g Django1.3), you can then run pip install -r requirements.txt and this will install all of your dependencies for you.
You can even have pip create this for you by doing pip freeze > stable-req.txt which will print out you dependencies as there are in your current virtualenv. You can then keep the requirements.txt under version control.
The nice thing about a virtualenv is that you can describe how to make one, and you can make it repeatedly on multiple platforms.
So, instead of cloning the whole thing, clone a method to create the virtualenv consistently, and have that in your git repository. This way you avoid platform-specific nasties.
I'd like to start developing an existing Python module. It has a source folder and the setup.py script to build and install it. The build script just copies the source files since they're all python scripts.
Currently, I have put the source folder under version control and whenever I make a change I re-build and re-install. This seems a little slow, and it doesn't settle well with me to "commit" my changes to my python install each time I make a modification. How can I cause my import statement to redirect to my development directory?
Use a virtualenv and use python setup.py develop to link your module to the virtual Python environment. This will make your project's Python packages/modules show up on the sys.path without having to run install.
Example:
% virtualenv ~/virtenv
% . ~/virtenv/bin/activate
(virtenv)% cd ~/myproject
(virtenv)% python setup.py develop
Virtualenv was already mentioned.
And as your files are already under version control you could go one step further and use Pip to install your repo (or a specific branch or tag) into your working environment.
See the docs for Pip's editable option:
-e VCS+REPOS_URL[#REV]#egg=PACKAGE, --editable=VCS+REPOS_URL[#REV]#egg=PACKAGE
Install a package directly from a checkout. Source
will be checked out into src/PACKAGE (lower-case) and
installed in-place (using setup.py develop).
Now you can work on the files that pip automatically checked out for you and when you feel like it, you commit your stuff and push it back to the originating repository.
To get a good, general overview concerning Pip and Virtualenv see this post: http://www.saltycrane.com/blog/2009/05/notes-using-pip-and-virtualenv-django
Install the distrubute package then use the developer mode. Just use python setup.py develop --user and that will place path pointers in your user dir location to your workspace.
Change the PYTHONPATH to your source directory. A good idea is to work with an IDE like ECLIPSE that overrides the default PYTHONPATH.