I'm new to django and I'm trying to find out which way to build project is better:
Build own virtualenv for each (including core django packages, which available via systemm repository) project
or
use packages from debian repository (if available, otherwise put it in virtualenv).
As I understand, in case any security update the repository version will receive patch asap, however virtualenv version I'll need patch myself.
However in case of movement to another server virtual will cause less issues, then repository version.
What is the best practices?
As far as I know virtualenv is used by almost every django developer.
It is also good practice to have versions in your requirements.txt so that if some of the packages change you'll have your project working in production.
I think virtualenv is de facto the best practice for development with Python (not just with Django)
Related
Hopefully this isn't too stupid of a question, concerning the use of pipenv for the same Django project on different computer systems. The scenario is that I'm using pipenv with a test Django project on one laptop, everything works fine, using VS Code and it's using the proper pipenv environment for the Python environment within VS Code.
The project however is within Dropbox so when I'm using a different laptop, which I do sometimes, one is my work laptop the other is my personal one at home, I can work on the same project wherever I left off. So you can probably deduce the issue I'm having.
I'm using pipenv environment A on my work laptop for the Django project. But when I open the project in VS Code on my personal laptop at home I have to keep specifying the proper pipenv environment to use, which obviously is different than the one on my work laptop.
Maybe I shouldn't be working this way and should just work on one laptop for the project, but I imagine others have done the same with similar setups before.
Is there a "proper" way to do this, using different pipenv environments on different machines for the same Django project? Should I copy over the pipenv environment to each machine as well? Or am I missing something really simple here?
First, use version control. (git is the defacto standard these days and there are plenty of services to choose from)
For using pipenv, you want to keep your Pipfile and Pipfile.lock in your repository (these are the only files you should be copying related to your environment from system to system).
The local environment is then built on each machine where it is needed by using pipenv sync or pipenv sync --dev (to install dev specific requirements).
So the related virtualenv will be created on each system in which you are developing your project.
This is a Django and Python and maybe just a general web development question.
what's the difference between using virtualenv vs vagrant vs virtual box and etc... ?
I'm kinda confused as to when to use which one :/ I've been using virtual env this whole time and creating new virtual environments for different projects....
Is this the right way to do it?
One virtualenv per project?
I'm not really sure when and where vagrant comes into play...Am I supposed to set up vagrant and then use virtualenv?
This is probably a silly question but...if I were to be working on this project with other people. Would they too have to set up a virtual env? Just to collaborate?
Wouldn't it make more sense that we all work on our local machines and then push it into the main branch? I'm just kinda confused .... I feel like I'm doing it all wrong...
Thanks for the replies everybody!
Virtualenv sets up a local sandbox for you to install Python modules into.
Vagrant is an automation tool for creating Virtual Machines.
VirtualBox is a free, open source environment for running virtual machines, like those created by Vagrant.
Virtualenv is really about all you'll need to do sandboxed development on your local machine. We use Vagrant at my work to automate the creation of VMs. This way new developers coming on to a project have basically zero configuration to do in order to start working.
If you're collaborating with other devs, they don't need to do any of the above to work on your Django project, but if there's a lot of configuration involved that can't be done with pip and a requirements.txt, then you might look at Vagrant to ease some of that automation.
But you are correct in your assumption that you can all just work on a local branch and push back to the repo. Everything else is just icing.
Virtualenv is a python construct that holds a specific set of packages, separate from your system packages. The version of Python and its packages that came with your OS or that you installed separately is a "system package".
Virtualbox is totally different -- it's a VM, an entire operating system in a box.
I'm not familiar with Vagrant.
All you need is virtualenv. Create a new virtualenv for each project (they're very lightweight!) You need to do this because the whole point of virtualenv is to isolate the exact packages and versions of those packages you need for your project. Then activate the virtualenv and use pip install to install the packages you need, presumably starting with Django itself.
Once you have all the packages you need, use pip freeze > requirements.txt to create a file called requirements.txt that records all of the packages you've decided to use.
When other people collaborate on your project, they can start a virtualenv, pull your code into it, and run pip install -r requirements.txt to replicate your environment. They can even modify requirements.txt, push that back to you via your version control system, and you can run pip install -r requirements.txt yourself to modify your environment to match their changes.
This is all essential because without virtualenv, the problem of, for instance, having one project on your computer that requires Django 1.4 and one that requires Django 1.5 becomes very complicated.
Virtualenv is not an entire operating system in a box, just a python environment, so even if you are using it, you are still working on your local machine.
We use virtualenv and a Ubuntu virtual machine. Here's why:
virtualenv allows us to have isolated Python environments on a given operating system instance
Using Ubuntu dekstop in a virtual machine for our Python development mimics what it will look like when deployed on the server which is also Ubuntu. This means that we understand precisely the external OS package dependencies and configuration. You don't get this easily when you use OSX or Windows for development and Linux for deployment.
One important point is that a virtual machine is portable. You can take a snapshot and deploy it elsewhere easily. With Vagrant and Ansible combination you can automate a remote deployment.
I am finally going to start using virtualenv for my Django projects on my development machine. Before I start I want to know if there are any special considerations for dealing with my existing projects. My presumed workflow is something like:
make a new virtualenv
activate the new virtualenv
Install Django in there
pip install all the packages I know I need for my existing project
copy my Django project files, app files, and git files into the project folder within the virtualenv.
Edit
6. make requirements file for deployment
This is obviously very simplified but are there any steps or considerations I am fundamentally missing? Is git going to be happy about moving? Also is it best practice to have a separate virtualenv for each Django project?
I know this is not a typical code problem, but I hope those that know more than I do can point me in the right direction.
Many thanks.
I don't see any big issue on migrating your projects and I think your 5-steps plan is correct, in particular, for steps 3/4/5 (I'd merge them), you can handle project dependencies with pip, possibly using requirement files.
Requirement files are plain text files telling to pip which packages have to be installed in your virtualenv, included your git-tracked projects which eventually can be deployed in your virtual environment as development eggs (they bring with them version control infos).
Once you have a req file, it's a matter of:
pip install -r file.req
to have all needed packages installed in your env.
As you can see from virtualenv docs, a typical req file would contain something like:
django==1.3.0
-e git://git.myproject.org/MyProject.git#egg=MyProject
I usually keep each project in its own virtualenv, so I can deploy it to the production server the same way I do for local development.
I'm a strong proponent of version control, and am starting work on a Django project. I've done a few before, and have tried a few different approaches, but I haven't yet found a decent structure that I actually feel comfortable with.
Here's what I want:
a) Source code checked into version control
b) Preferably the environment is not checked into version control (something like buildout or pip requirements.txt is fine for setting up the environment)
c) A reasonable "get a new developer going" story
d) A reasonable deployment story - preferably the entire deployment environment could be generated by a script on the server
It seems to me like someone has to have done this before, but many hours of searching have all led to half-baked solutions that don't really address all of these.
Any thoughts on where I should look?
Look at fabric to manage deployments.
This is what I use to manage servers/deployments with fabric: louis (it is just a collection of fabric commands). I keep a louisconf.py file with each project.
I'd recommend using a distributed VCS (git, hg,...) instead of svn. The reason being that the ease of branching allows for several schemes for deployment. You can have, for example, production and staging branches. Then you enforce that the only merges into production happen from staging by convention.
As for getting developers started quickly you have it right with pip and requirements.txt. I think that also means that you are using virtualenv, but if not that's the third piece. I'd recommend getting a basic README in place. Have the first assignment of each developer that joins a project be to update the README.
The rough way to get someone on board is to have her checkout the code, create a virtualenv, and install the requirements.
I'd recommend having a settings.py file that works with sqlite3 and such that a new developer can use to just get going fast (ie after installing the requirements). However, how you manage the different settings files depends on your project layout. There should be some set of default settings for new developers to use, though.
I keep a projects/ directory in my home directory (on Linux). When I need to start a new project, I make a new, shortly-named (that sufficiently describes the project) dir in projects/; that becomes the root of a new virtualenv (with --no-site-packages) for that project.
Inside that dir (after I've installed the venv, sourced it, and installed the copy of django I'll be working with), I "django-admin.py startproject" a subdir, normally by the same short name. That dir becomes the root of my hg repo (with a quick hg init and ci), no matter how small the project.
If there's any chance of sharing the project with other developers (a project for work, for example), I include a pip requirements.txt at the repo root. Only project requirements go in there; django-debug-toolbar and django-extensions, staples for my dev workflow, are not project requirements, for example. South, when we use it, is.
As for the django project, I normally keep the default settings.py, possibly with a few changes, and add the local_settings convention to the end of it (try: from local_settings import *; except ImportError: pass). My and other devs' specific environment settings (adding django-extensions and django-debug-toolbar to installed apps, for example) go in local_settings.py, which is not checked in to version control. To help a new dev out, you could provide a template of that file as local_settings.py.temp, or some other name that won't be used for any other purpose, but I find that this unnecessarily clutters the repo.
For personal projects, I normally include a README if I plan on releasing it publicly. At work, we maintain Trac environments and good communication to get new devs up to speed on a project.
As for deployment, as rz mentioned, I hear fabric is really good for that kind of automated local/remote scripting, though I haven't really taken the chance myself to look into it.
For the uninitiated, a typical shell session for this might look like the following:
$ cd ~/projects/
$ mkdir newproj
$ cd newproj/
$ virtualenv --no-site-packages .
$ source bin/activate
(newproj)$ pip install django django-debug-toolbar django-extensions
... installing stuff ...
(newproj)$ django-admin.py startproject newproj
(newproj)$ cd newproj/
(newproj)$ hg init .; hg ci -A -m "Initial code"
Is there a way to run Pinax without virtualenv?
I want to run it without virtualenv as I want to run it on a django-container on mediatemples grid-hosting service. Their containers can scale upto 1Gb of dedicated memory, so I wouldnt have to worry about my own VPS or scaling issues. But their response was:
" because of the way the DjangoContainer works, you won't be able to configure your server to use your virtualenv. Essentially the DjangoContainer is a virtualized server (to which you don't have access other than the AccountCenter tools, or the 'mtd' command line tool) with the specific purpose of serving your Django applications. It mounts your django container folder so that it has your application code, but you cannot modify the version or location of python it uses. This probably means you'll have to use Pinax without virtualenv support, as the general idea of using virtualenv in this way would be to create a custom environment for your Pinax application, which as I mentioned here is impossible to instruct the server to use. "
As of 0.9a1, Pinax can be used without pinax-boot.py which was the virtualenv dependency (we bundled it). Requirements are project-level and must be installed with pip. However, setup_project does enforce a virtual environment when installing requirements (it calls pip for you as a convenience; I would be open to not enforcing a virtual environment here). You can pass --no-reqs to setup_project forcing it to skip dependency installation. You can then run pip yourself and install it however you like.
technically yes, but you would have to change out quite a bit of the configuration that is handed out and hand install a lot of libraries. Pinax has virtualenv as a very low level built in assumption.
you can, all you need to do is find out what is in the virtualenv. set it up and install yolk in the virtual env and type yolk -l to see what you need to install to get it to work.