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Eliminate devops
For Python 3.7 releases, we provide two binary installer options for download. The default variant is 64-bit-only and works on macOS 10.9 (Mavericks) and later systems. We also continue to provide a 64-bit/32-bit variant that works on all versions of macOS from 10.6 (Snow Leopard) on. Using Python on a Mac¶ Author. Com Python on a Mac running macOS is in principle very similar to Python on any other Unix platform, but there are a number of additional features such as the IDE and the Package Manager that are worth pointing out. I am new to python. I am using python 3.5 on mac os x el capitan. I tried using the command 'pip install requests' in the python interpreter IDLE. But it throws invalid 'syntax error'.
Whether you’re a big, small or medium enterprise, Anaconda will support your organization. As a free and open-source distribution of Python and R programming language, it’s aim is to easily scale a single user on one laptop to thousands of machines. If you’re looking for a hassle-free data science platform, this is the one for you.
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Extensive packages
Anaconda is leading the way for innovative data science platforms for enterprises of all sizes.
Anaconda provides you with more than 1,500 packages in its distribution. In it you will find the Anaconda navigator (a graphical alternative to command line interface), Conda package, virtual environment manager, and GUI. What makes Conda different from other PIP package managers is how package dependencies are managed. PIP installs Python package dependencies, even if they’re in conflict with other packages you’ve already installed. So, for example, a program can suddenly stop working when you’re installing a different package with a different version of the NumPy library. Everything will appear to work but, you data will produce different results because you didn’t install PIP in the same order. This is where Conda comes in. It analyzes your current environment and installations. This includes version limitations, dependencies, and incompatibility. As an open source package, it can be individually installed from the Anaconda repository, Anaconda Cloud or even the conda install command.
You can even create and share custom packages using the conda build command. The developers will then compile and build all the packages in the Anaconda repository, providing binaries for Windows, Linux and MacOS. Basically, you won’t worry about installing anything because Conda knows everything that’s been installed in your computer.
Extend your reach with Anaconda Navigator
The built in graphical user interface or GUI allows you to launch applications while managing Conda packages, environments and channels. This means the GUI will complete the process of installing packages without asking for a command-line command. It even includes these applications by default: JupyterLab & Jupyter Notebook / QtConsole / Spyder / Glueviz / Orange / RStudio / Visual Studio Code.
Where can you run this program?
Anaconda 2019.07 has these system requirements:
- Operating system: Windows 7 or newer, 64-bit macOS 10.10+, or Linux, including Ubuntu, RedHat, CentOS 6+.
- System architecture: Windows- 64-bit x86, 32-bit x86; MacOS- 64-bit x86; Linux- 64-bit x86, 64-bit Power8/Power9.
- 5 GB disk space or more.
Anaconda developers recommends you to install Anaconda for the local user so you won’t need administrator permissions. Or, you can opt to install Anaconda system wide, which does require administrator permissions.
Is there a better alternative?
If you’re looking for simple Python-dedicated environment, then you need PyCharm. Targeted specifically for Python programmers, this integrated development environment is filled with programming tools that can impress both new and experienced developers. It provides all the tools in a centralized system so you can increase your efficiency and effectiveness. Features like code analysis, graphical debugger, and unit tester helps you integrate Python programs with version control systems. In fact, every single output you make will be capable of web development from different web frameworks like Django, web2py, and Flask. It offers automated tools like code refactorings, PEP8 checks, and testing assistance to create your code, but what stands out the most is Smart Assistance. It fixes any of your errors or complete portions of your code. With PyCharm, you can expect a neat and maintainable code.
Our take
Anaconda’s host of innovative options makes it the best data science platform for all enterprises. By offering superior collaboration tools, scalability, and security, you never have to worry about gathering big data again.
Should you download it?
If you have experience with other package management and deployment programs, then make the big switch by downloading Anaconda.
Highs
- Extensive data science tools
- Functions can be scaled
- Flexible nodes
- Reliable cloud storage
Lows
- Complex for beginners
- Hard to maximize by small organizations
- Minimal automated features
Anacondafor Mac
5.0.0
Note
Check out our guide for installing Python 3 on OS X.
Mac OS X comes with Python 2.7 out of the box.
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.
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.
Python Tutorial
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¶
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.
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For example, you can work on a project which requires Django 1.10 while alsomaintaining a project which requires Django 1.8.
To start using this and see more information: Virtual Environments docs.
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This page is a remixed version of another guide,which is available under the same license.