For cleaning up the directory after running above commands, python setup.py clean is not sufficient. After copying out the build result, simply running git clean-xdf under python-package is an efficient way to remove generated cache files. If you find weird behaviors in Python build or running linter, it might be caused by those cached files. Doing it Right¶. Let’s install a real version of Python. Before installing Python, you’ll need to install a C compiler. The fastest way is to install the Xcode Command Line Tools by running xcode-select-install.
Note
Check out our guide for installing Python 3 on OS X.
Mac OS X comes with Python 2.7 out of the box.
- Mac OSX(1.9.1)/Ubuntu16.04(1.7.2) A note about types Point Cloud is a heavily templated API, and consequently mapping this into Python using Cython is challenging.
- This project can always use your help, time and attention. I am looking for help (pull-requests!) with the following work items: Documentation around running macOS on popular cloud providers (Hetzner, GCP, AWS). See the Is This Legal? Section and associated references. Test QEMU's accel=hvf flag on.
- Python 3 (released in 2008) is the newest version of Python, and most features have not changed. Most packages have been updated to Python 3 by now (2016). So, if your lab does not have a preference, I recommend using Python 3. There are a couple key differences for novice programmers: In Python 2, you can print with print 42 or print(42).
You do not need to install or configure anything else to use Python. Having saidthat, I would strongly recommend that you install the tools and librariesdescribed in the next section before you start building Python applications forreal-world use. In particular, you should always install Setuptools, as it makesit much easier for you to install and manage other third-party Python libraries.
The version of Python that ships with OS X is great for learning, but it’s notgood for development. The version shipped with OS X may be out of date from theofficial current Python release,which is considered the stable production version.
Doing it Right¶
Let’s install a real version of Python.
Before installing Python, you’ll need to install a C compiler. The fastest wayis to install the Xcode Command Line Tools by runningxcode-select--install. You can also download the full version ofXcode from the Mac App Store, or theminimal but unofficialOSX-GCC-Installerpackage.
Note
If you already have Xcode installed, do not install OSX-GCC-Installer.In combination, the software can cause issues that are difficult todiagnose.
Note
If you perform a fresh install of Xcode, you will also need to add thecommandline tools by running xcode-select--install on the terminal.
While OS X comes with a large number of Unix utilities, those familiar withLinux systems will notice one key component missing: a decent package manager.Homebrew fills this void.
To install Homebrew, open Terminal oryour favorite OS X terminal emulator and run
The script will explain what changes it will make and prompt you before theinstallation begins.Once you’ve installed Homebrew, insert the Homebrew directory at the topof your PATH environment variable. You can do this by adding the followingline at the bottom of your ~/.profile file
Now, we can install Python 2.7:
Because python@2 is a “keg”, we need to update our PATH again, to point at our new installation:
Homebrew names the executable python2 so that you can still run the system Python via the executable python.
Setuptools & Pip¶
Homebrew installs Setuptools and pip for you.
Mac Python Update
Setuptools enables you to download and install any compliant Pythonsoftware over a network (usually the Internet) with a single command(easy_install). It also enables you to add this network installationcapability to your own Python software with very little work.
pip is a tool for easily installing and managing Python packages,that is recommended over easy_install. It is superior to easy_installin several ways,and is actively maintained.
Virtual Environments¶
Osx Python Update
A Virtual Environment (commonly referred to as a ‘virtualenv’) is a tool to keep the dependencies required by different projectsin separate places, by creating virtual Python environments for them. It solves the“Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keepsyour global site-packages directory clean and manageable.
For example, you can work on a project which requires Django 1.10 while alsomaintaining a project which requires Django 1.8.
Mac Python Update Pip
To start using this and see more information: Virtual Environments docs.
Macos Python Update
This page is a remixed version of another guide,which is available under the same license.