This section covers the basics of how to install Python packages.

Navigate to the Python downloads page: Python downloads. Click on the link/button to download Python 2.7.x. Follow the installation instructions (leave all defaults as. This shouldn’t be a problem because Python 2.7 is installed by default in recent versions of OpenSuSE, Ubuntu, and Red Hat Fedora. In the nutty odd case when someone has Python 3 but not Python 2.7, read your distribution’s documentation for how to use the package manager and get Python 2.7 and IDLE. Read Also: How to install Python 3.8 on Mac using pyenv Buy me a coffee 1. Python Download The Python. Download Python 3.8 First of all download the Python 3.8 package by clicking following link Consider reading: How to install Python 3.7 on Raspberry PI 2. Install Python 3.8 on Mac Now lets install it by double-clicking on the downloaded pkg file.

It’s important to note that the term “package” in this context is being used asa synonym for a distribution (i.e. a bundle ofsoftware to be installed), not to refer to the kind of package that you import in your Python source code (i.e. a container ofmodules). It is common in the Python community to refer to a distribution using the term “package”. Using the term “distribution”is often not preferred, because it can easily be confused with a Linuxdistribution, or another larger software distribution like Python itself.

Contents

This section describes the steps to follow before installing other Pythonpackages.

Before you go any further, make sure you have Python and that the expectedversion is available from your command line. You can check this by running:

You should get some output like Python3.6.3. If you do not have Python,please install the latest 3.x version from python.org or refer to theInstalling Python section of the Hitchhiker’s Guide to Python.

Note

If you’re a newcomer and you get an error like this:

It’s because this command and other suggested commands in this tutorialare intended to be run in a shell (also called a terminal orconsole). See the Python for Beginners getting started tutorial foran introduction to using your operating system’s shell and interacting withPython.

Note

If you’re using an enhanced shell like IPython or the Jupyternotebook, you can run system commands like those in this tutorial byprefacing them with a ! character:

It’s recommended to write {sys.executable} rather than plain python inorder to ensure that commands are run in the Python installation matchingthe currently running notebook (which may not be the same Pythoninstallation that the python command refers to).

Note

Due to the way most Linux distributions are handling the Python 3migration, Linux users using the system Python without creating a virtualenvironment first should replace the python command in this tutorialwith python3 and the pip command with pip3--user. Do notrun any of the commands in this tutorial with sudo: if you get apermissions error, come back to the section on creating virtual environments,set one up, and then continue with the tutorial as written.

Additionally, you’ll need to make sure you have pip available. You cancheck this by running:

If you installed Python from source, with an installer from python.org, orvia Homebrew you should already have pip. If you’re on Linux and installedusing your OS package manager, you may have to install pip separately, seeInstalling pip/setuptools/wheel with Linux Package Managers.

If pip isn’t already installed, then first try to bootstrap it from thestandard library:

If that still doesn’t allow you to run pip:

• Securely Download get-pip.py1

• Run pythonget-pip.py. 2 This will install or upgrade pip.Additionally, it will install setuptools and wheel if they’renot installed already.

  Warning

  Be cautious if you’re using a Python install that’s managed by youroperating system or another package manager. get-pip.py does notcoordinate with those tools, and may leave your system in aninconsistent state. You can use pythonget-pip.py--prefix=/usr/local/to install in /usr/local which is designed for locally-installedsoftware.

While pip alone is sufficient to install from pre-built binary archives,up to date copies of the setuptools and wheel projects are usefulto ensure you can also install from source archives:

See section below for details,but here’s the basic venv3 command to use on a typical Linux system:

This will create a new virtual environment in the tutorial_env subdirectory,and configure the current shell to use it as the default python environment.

Python “Virtual Environments” allow Python packages to be installed in an isolated location for a particular application,rather than being installed globally. If you are looking to safely installglobal command line tools,see Installing stand alone command line tools.

Imagine you have an application that needs version 1 of LibFoo, but anotherapplication requires version 2. How can you use both these applications? If youinstall everything into /usr/lib/python3.6/site-packages (or whatever yourplatform’s standard location is), it’s easy to end up in a situation where youunintentionally upgrade an application that shouldn’t be upgraded.

Or more generally, what if you want to install an application and leave it be?If an application works, any change in its libraries or the versions of thoselibraries can break the application.

Also, what if you can’t install packages into theglobal site-packages directory? For instance, on a shared host.

In all these cases, virtual environments can help you. They have their owninstallation directories and they don’t share libraries with other virtualenvironments.

Currently, there are two common tools for creating Python virtual environments:

• venv is available by default in Python 3.3 and later, and installspip and setuptools into created virtual environments inPython 3.4 and later.

• virtualenv needs to be installed separately, but supports Python 2.7+and Python 3.3+, and pip, setuptools and wheel arealways installed into created virtual environments by default (regardless ofPython version).

The basic usage is like so:

Using venv:

Using virtualenv:

For more information, see the venv docs or the virtualenv docs.

The use of source under Unix shells ensuresthat the virtual environment’s variables are set within the currentshell, and not in a subprocess (which then disappears, having nouseful effect).

In both of the above cases, Windows users should _not_ use thesource command, but should rather run the activatescript directly from the command shell like so:

Managing multiple virtual environments directly can become tedious, so thedependency management tutorial introduces ahigher level tool, Pipenv, that automatically manages a separatevirtual environment for each project and application that you work on.

pip is the recommended installer. Below, we’ll cover the most commonusage scenarios. For more detail, see the pip docs,which includes a complete Reference Guide.

The most common usage of pip is to install from the Python PackageIndex using a requirement specifier. Generally speaking, a requirement specifier iscomposed of a project name followed by an optional version specifier. PEP 440 contains a fullspecificationof the currently supported specifiers. Below are some examples.

To install the latest version of “SomeProject”:

To install a specific version:

To install greater than or equal to one version and less than another:

To install a version that’s “compatible”with a certain version: 4

In this case, this means to install any version “1.4.*” version that’s also“>=1.4.2”.

pip can install from either Source Distributions (sdist) or Wheels, but if both are presenton PyPI, pip will prefer a compatible wheel.

Wheels are a pre-built distribution format that provides faster installation compared to SourceDistributions (sdist), especially when aproject contains compiled extensions.

If pip does not find a wheel to install, it will locally build a wheeland cache it for future installs, instead of rebuilding the source distributionin the future.

Upgrade an already installed SomeProject to the latest from PyPI.

To install packages that are isolated to thecurrent user, use the --user flag:

For more information see the User Installs sectionfrom the pip docs.

Note that the --user flag has no effect when inside a virtual environment- all installation commands will affect the virtual environment.

If SomeProject defines any command-line scripts or console entry points,--user will cause them to be installed inside the user base’s binarydirectory, which may or may not already be present in your shell’sPATH. (Starting in version 10, pip displays a warning wheninstalling any scripts to a directory outside PATH.) If the scriptsare not available in your shell after installation, you’ll need to add thedirectory to your PATH:

• On Linux and macOS you can find the user base binary directory by runningpython-msite--user-base and adding bin to the end. For example,this will typically print ~/.local (with ~ expanded to the absolutepath to your home directory) so you’ll need to add ~/.local/bin to yourPATH. You can set your PATH permanently by modifying ~/.profile.

• On Windows you can find the user base binary directory by running py-msite--user-site and replacing site-packages with Scripts. Forexample, this could returnC:UsersUsernameAppDataRoamingPython36site-packages so you wouldneed to set your PATH to includeC:UsersUsernameAppDataRoamingPython36Scripts. You can set your userPATH permanently in the Control Panel. You may need to log out for thePATH changes to take effect.

Install a list of requirements specified in a Requirements File.

Install a project from VCS in “editable” mode. For a full breakdown of thesyntax, see pip’s section on VCS Support.

Install from an alternate index

Search an additional index during install, in addition to PyPI

Installing from local src in Development Mode,i.e. in such a way that the project appears to be installed, but yet isstill editable from the src tree.

You can also install normally from src

Install a particular source archive file.

Install from a local directory containing archives (and don’t check PyPI)

To install from other data sources (for example Amazon S3 storage) you cancreate a helper application that presents the data in a PEP 503 compliantindex format, and use the --extra-index-url flag to direct pip to usethat index.

Find pre-release and development versions, in addition to stable versions. Bydefault, pip only finds stable versions.

Install setuptools extras.

“Secure” in this context means using a modern browser or atool like curl that verifies SSL certificates whendownloading from https URLs.

Depending on your platform, this may require root or Administratoraccess. pip is currently considering changing this by making userinstalls the default behavior.

Beginning with Python 3.4, venv (a stdlib alternative tovirtualenv) will create virtualenv environments with pippre-installed, thereby making it an equal alternative tovirtualenv.

The compatible release specifier was accepted in PEP 440and support was released in setuptools v8.0 andpip v6.0

If you need help installing python on OSX, read on.

For the last three years, I’ve used a mac for all my development. I love the fact that everything ‘just works’ on the platform. That said, when you get into scientific computing and data analytics, especially with python, you can run into some issues.

Just like linux, python is included with the operating system. Unlike linux, this can cause problems long-term for you due to upgrades and changes that Apple may make to the python ecosystem.

On OS X, I recommend those of you starting out to go with Anaconda or Enthought Canopy. As I said in “Installing python on Windows“, I prefer Canopy over Anaconda for scientific computing / data analytics but either will work for you. Installing Canopy on the mac is very similar to installing it on Windows…so I’ll let this post be your guide for installing Canopy.

If you want to get into the nitty-gritty and install and configure python and the modules yourself, you can easily do so, but be prepared to spend some time on the command line.

Before we get started installing python on your Mac, we need to install homebrew, which is a package manager for OS X (it acts similar to the ‘apt’ package manager on ubuntu / debian).

To install homebrew, open a terminal and paste the following:

This command installs the homebrew ecosystem onto your machine and preps your machine to be ready to install various packages, including python.

Installing Python on OSX

Step 1: Let’s get python installed via homebrew. In your terminal, type:

This will install a version of python onto your machine and set up your environment to use that version. This helps mitigate any issues you might have down the road if / when Apple makes changes to the system provided python. Additionally, brew installs pip into the system to make it easy to get the necessary modules onto your machine.

From this point on, we are generally going to follow exactly the same steps that I outline in Installing Python on Linux except we don’t need to install any additional tools.

Step 2: Not required, but highly recommended – install a virtual environment. I recommend virtualenv. Install it with this command:

When you are ready to get started on a new project, type the below command to install python into a new virtual environment (the ‘env’ is the name of the environment). You only have to do this once per project. Note: You should use a folder per project to keep your virtual environments separated.

Whenever you want to work on a specific project, change into that folder and type the following. This will set up your environment with all of your installed python modules:

For the purpose of this walk-through let’s create a new directory, set up a new virtual environment and then install the necessary modules.

• Create a folder in your home directory called ‘projects’.
• Type “mkdir projects” to do this from the command line.
• Change into that folder and then type “mkdir install_example” to create another folder inside the projects folder.
• Type “virtualenv env” to create your virtual environment.
• Type “source env/bin/activate” to begin using this environment

Now that we have our environment ready to go, we need to install some of the modules that are most often used when doing data work inside python. These modules are:

• numpy (installed when you install pandas with pip)

The above modules can be installed with one pip command.

How To Download Pip Python On Mac

You’re ready to start working with python for data analysis on your mac. Just remember, for each virtualenv you create, you’ll need to reinstall these modules if you wish to use them.

Python On Mac

Check back here often for more information on using the above modules to actually DO something.