alx-xlx/.gitignore

Install Python3 - Linux

To check if your system has any Python Version already Installed

$ python --version
$ python2 --version
$ python3 --version

If you don't have Python3 installed then follow along

$ sudo apt-get update
$ sudo apt-get install python3.6

Ubuntu 17.10, Ubuntu 18.04 (and above) come with Python 3.6 by default. You should be able to invoke it with the command python3.
Ubuntu 16.10 and 17.04 do not come with Python 3.6 by default, but it is in the Universe repository. You should be able to install it with the following commands:
```
$ sudo apt-get update
$ sudo apt-get install python3.6
```
You can then invoke it with the command python3.6.
If you are using Ubuntu 14.04 or 16.04, Python 3.6 is not in the Universe repository, and you need to get it from a Personal Package Archive (PPA). For example, to install Python from the “deadsnakes” PPA, do the following:
```
$ sudo add-apt-repository ppa:deadsnakes/ppa
$ sudo apt-get update
$ sudo apt-get install python3.6
```
As above, invoke with the command python3.6.

Managing Python dependencies

Getting started

Begin by using pip to install Pipenv and its dependencies,

pip install pipenv

Then change directory to the folder containing your Python project and initiate Pipenv,

cd my_project
pipenv install

This will create two new files, Pipfile and Pipfile.lock, in your project directory, and a new virtual environment for your project if it doesn’t exist already. If you add the --two or --three flags to that last command above, it will initialise your project to use Python 2 or 3, respectively. Otherwise the default version of Python will be used.

Managing Python dependencies

Pipfiles contain information about the dependencies of your project, and supercede the requirements.txt file that is typically used in Python projects. If you’ve initiated Pipenv in a project with an existing requirements.txt file, you should install all the packages listed in that file using Pipenv, before removing it from the project.

To install a Python package for your project use the install keyword. For example,

pipenv install beautifulsoup4

will install the current version of the Beautiful Soup package. A package can be removed in a similar way with the uninstall keyword,

pipenv uninstall beautifulsoup4

The package name, together with its version and a list of its own dependencies, can be frozen by updating the Pipfile.lock. This is done using the lock keyword,

pipenv lock

It’s worth adding the Pipfiles to your Git repository, so that if another user were to clone the repository, all they would have to do is install Pipenv on their system and then type,

pipenv install

Then Pipenv would automagically locate the Pipfiles, create a new virtual environment and install the necessary packages.

Managing your development environment

There are usually some Python packages that are only required in your development environment and not in your production environment, such as unit testing packages. Pipenv will let you keep the two environments separate using the --dev flag. For example,

pipenv install --dev nose2

will install nose2, but will also associate it as a package that is only required in your development environment. This is useful because now, if you were to install your project in your production environment with,

pipenv install

the nose2 package won’t be installed by default. However, if another developer were to clone your project into their own development environment, they could use the --dev flag,

pipenv install --dev

and install all the dependencies, including the development packages.

Running your code

In order to activate the virtual environment associated with your Python project you can simply use the shell keyword,

pipenv shell

You can also invoke shell commands in your virtual environment, without explicitly activating it first, by using the run keyword. For example,

pipenv run which python

will run the which python command in your virtual environment, and display the path where the python executable, that is associated with your virtual environment, is located. This feature is a neat way of running your own Python code in the virtual environment,

pipenv run python my_project.py

If you’re like me and shudder at having to type so much every time you want to run Python, you can always set up an alias in your shell, such as,

alias prp="pipenv run python"

Keeping it simple

I hope this post has shown you how to manage your Python projects with Pipenv. It has been around for less than a month now, so I, for one, will be interested to see how it develops over time. I certainly don’t want, or expect, it to become exactly like Bundler for Ruby, but I’ll definitely champion it for simplifying the management of dependencies in Python projects. I hope you do too!