Pip Brew

  1. Pip Breakdown
  2. Pip Brewery
Pip Brew


Check out our guide for installing Python 3 on OS X.

Iv never had pip from any home-brew, including primo. Maybe add a bit more BB to ur batch, 07:27 AM #7. View Profile View Forum Posts Private Message. Brew is an open source, community-maintained software for installing general software packages on OS X. (I was introduced to Brew when Pip wasn’t working successfully on my Mac, especially with the High Sierra OS version. Brew installed all my necessary modules right away.) You can find its repository written in Ruby on GitHub. Install the latest version of Brain Brew on PyPi.org with pip install brain-brew. Virtual environment using pipenv is recommended!:exclamation: See the Brain Brew Starter Projectfor a working clone-able Git repo. From this repo you can now create a functional Brain Brew setup automatically, with your own flashcards! Simply by running.

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 The version shipped with OS X may be out of date from theofficial current Python release,which is considered the stable production version.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.


If you already have Xcode installed, do not install OSX-GCC-Installer.In combination, the software can cause issues that are difficult todiagnose.


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

I have turned on smart sync for mac as OSX wasn't recognising online only files as not being on the hard drive. This solvedf this issue. However, dropbox is now syncing sporadically or not at all, and I have to restart dropbox to get it to update any new files and then when it does it starts syncing 3-4 possibly phantom files and indicates it. Dropbox Update for Mac Dropbox Update is a process that makes sure the Dropbox desktop application is running the latest version. Dropbox Update is installed alongside the Dropbox desktop application on Mac computers running a supported macOS. On macOS and Windows, open your Dropbox desktop app preferences, and click the General tab. Can I disable auto-updates? Like many programs and applications, Dropbox may automatically update to the latest version. These updates are rolled out gradually after a new update is available, and are necessary to keep the desktop app functioning. The Dropbox desktop experience helps you organize your content, connect your tools and bring your team together in one place. Read more about Dropbox for desktop. Get the desktop experience today. One organized place that brings work into focus and keeps teams in sync—right from your desktop. Dropbox sync mac desktop.

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 [email protected] 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.

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.

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.

This page is a remixed version of another guide,which is available under the same license.

TensorFlow 2 packages are available

  • tensorflow —Latest stable release with CPU and GPU support (Ubuntu and Windows)
  • tf-nightly —Preview build (unstable) . Ubuntu and Windows include GPU support .

Older versions of TensorFlow

For TensorFlow 1.x, CPU and GPU packages are separate:

  • tensorflow1.15 —Release for CPU-only
  • tensorflow-gpu1.15 —Release with GPU support (Ubuntu and Windows)

System requirements

  • Python 3.6–3.8
    • Python 3.8 support requires TensorFlow 2.2 or later.
  • pip 19.0 or later (requires manylinux2010 support)
  • Ubuntu 16.04 or later (64-bit)
  • macOS 10.12.6 (Sierra) or later (64-bit) (no GPU support)
    • macOS requires pip 20.3 or later
  • Windows 7 or later (64-bit)
  • Raspbian 9.0 or later
  • GPU support requires a CUDA®-enabled card (Ubuntu and Windows)
Note: Installing TensorFlow 2 requires a newer version of pip .

Hardware requirements

  • Starting with TensorFlow 1.6, binaries use AVX instructions which may not run on older CPUs.
  • Read the GPU support guide to set up a CUDA®-enabled GPU card on Ubuntu or Windows.

1. Install the Python development environment on your system

Check if your Python environment is already configured:

Requires Python 3.6–3.8, pip and venv >= 19.0

If these packages are already installed, skip to the next step.
Otherwise, install Python , the pip package manager , and venv :



Install using the Homebrew package manager:


Install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017, and 2019 . Starting with the TensorFlow 2.1.0 version, the msvcp140_1.dll file is required from this package (which may not be provided from older redistributable packages). The redistributable comes with Visual Studio 2019 but can be installed separately:

  1. Go to the Microsoft Visual C++ downloads ,
  2. Scroll down the page to the Visual Studio 2015, 2017 and 2019 section.
  3. Download and install the Microsoft Visual C++ Redistributable for Visual Studio 2015, 2017 and 2019 for your platform.

Make sure long paths are enabled on Windows.

Install the 64-bit Python 3 release for Windows (select pip as an optional feature).

Raspberry Pi

Requirements for the Raspbian operating system:


Caution: Upgrading the system pip can cause problems .
If not in a virtual environment, use python3 -m pip for the commands below. This ensures that you upgrade and use the Python pip instead of the system pip .

2. Create a virtual environment (recommended)

Python virtual environments are used to isolate package installation from the system.

Ubuntu / macOS

Create a new virtual environment by choosing a Python interpreter and making a ./venv directory to hold it:

Activate the virtual environment using a shell-specific command:

When the virtual environment is active, your shell prompt is prefixed with (venv) .

Install packages within a virtual environment without affecting the host system setup. Start by upgrading pip :

And to exit the virtual environment later:


Create a new virtual environment by choosing a Python interpreter and making a .venv directory to hold it:

Pip BrewBrew

Activate the virtual environment:

Install packages within a virtual environment without affecting the host system setup. Start by upgrading pip :

Pip Breakdown

And to exit the virtual environment later:


While the TensorFlow provided pip package is recommended, a community-supported Anaconda package is available. To install, read the Anaconda TensorFlow guide .

3. Install the TensorFlow pip package

Choose one of the following TensorFlow packages to install from PyPI :

  • tensorflow —Latest stable release with CPU and GPU support (Ubuntu and Windows) .
  • tf-nightly —Preview build (unstable) . Ubuntu and Windows include GPU support .
  • tensorflow1.15 —The final version of TensorFlow 1.x.
Package dependencies are automatically installed. These are listed in the setup.py file under REQUIRED_PACKAGES .

Virtual environment install

Verify the install:

Pip Brew

System install

Verify the install:

Pip Brewery

Success: If a tensor is returned, you've installed TensorFlow successfully. Read the tutorials to get started.

Package location

A few installation mechanisms require the URL of the TensorFlow Python package. The value you specify depends on your Python version.

Version URL
Python 3.6 GPU support https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp36-cp36m-manylinux2010_x86_64.whl
Python 3.6 CPU-only https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp36-cp36m-manylinux2010_x86_64.whl
Python 3.7 GPU support https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp37-cp37m-manylinux2010_x86_64.whl
Python 3.7 CPU-only https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp37-cp37m-manylinux2010_x86_64.whl
Python 3.8 GPU support https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp38-cp38-manylinux2010_x86_64.whl
Python 3.8 CPU-only https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp38-cp38-manylinux2010_x86_64.whl
macOS (CPU-only)
Python 3.6 https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp36-cp36m-macosx_10_9_x86_64.whl
Python 3.7 https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp37-cp37m-macosx_10_9_x86_64.whl
Python 3.8 https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp38-cp38-macosx_10_14_x86_64.whl
Python 3.6 GPU support https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp36-cp36m-win_amd64.whl
Python 3.6 CPU-only https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp36-cp36m-win_amd64.whl
Python 3.7 GPU support https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp37-cp37m-win_amd64.whl
Python 3.7 CPU-only https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp37-cp37m-win_amd64.whl
Python 3.8 GPU support https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp38-cp38-win_amd64.whl
Python 3.8 CPU-only https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp38-cp38-win_amd64.whl
Raspberry PI (CPU-only)
Python 3, Pi0 or Pi1 https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.3.0rc2-cp35-none-linux_armv6l.whl
Python 3, Pi2 or Pi3 https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.3.0rc2-cp35-none-linux_armv6l.whl