Posted   by 

Install Python 3 Mac Anaconda



  1. You don’t need to install Python if you installed Anaconda. You may want to set your path for python and conda if you are on a windows. You can learn more about it.
  2. To verify this, run python -version in each environment. If not the same, create a new virtual environment with that version of Python (Ex. Conda create -name myenv python=x.x.x). Activate the virtual environment (conda activate myenv) conda install -c conda-forge spacy; python -m spacy download encorewebsm.
  3. 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) Windows 7 or later (64-bit) Microsoft Visual C Redistributable for Visual Studio 2015, 2017 and 2019; Raspbian 9.0 or later.

Once done, Anaconda will be installed. Install R Mac users. Step 1) Anaconda uses the terminal to install libraries. The terminal is a quick way to install libraries. We need to be sure to point the installation toward the right path. In our case, we set the location of Anaconda to the Users/USERNAME/.

RSVP for your your local TensorFlow Everywhere event today!

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)
  • 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:

Ubuntu

macOS

Install using the Homebrew package manager:

Windows

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-bitPython 3 release for Windows (select pip as an optional feature).

Raspberry Pi

Requirements for the Raspbian operating system:

Other

Caution:

Install Python 3 Mac Anaconda Download

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 pipInstall python 3 mac anacondaInstall Python 3 Mac Anaconda instead of the system pip.Install python 3 mac anaconda 3.6

2. Create a virtual environment (recommended)

Install Python 3 Mac Anaconda 3.6

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:

Windows

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

Activate the virtual environment:

Python

Install Python 3 Mac Anaconda Jupyter

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

And to exit the virtual environment later:

Conda

While the TensorFlow provided pip package is recommended, acommunity-supportedAnaconda packageis 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 MacREQUIRED_PACKAGES.

Virtual environment install

Verify the install:

System install

Verify the install:

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.

VersionURL
Linux
Python 3.6 GPU supporthttps://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp36-cp36m-manylinux2010_x86_64.whl
Python 3.6 CPU-onlyhttps://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp36-cp36m-manylinux2010_x86_64.whl
Python 3.7 GPU supporthttps://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp37-cp37m-manylinux2010_x86_64.whl
Python 3.7 CPU-onlyhttps://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp37-cp37m-manylinux2010_x86_64.whl
Python 3.8 GPU supporthttps://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-2.4.0-cp38-cp38-manylinux2010_x86_64.whl
Python 3.8 CPU-onlyhttps://storage.googleapis.com/tensorflow/linux/cpu/tensorflow_cpu-2.4.0-cp38-cp38-manylinux2010_x86_64.whl
macOS (CPU-only)
Python 3.6https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp36-cp36m-macosx_10_9_x86_64.whl
Python 3.7https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp37-cp37m-macosx_10_9_x86_64.whl
Python 3.8https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.4.0-cp38-cp38-macosx_10_14_x86_64.whl
Windows
Python 3.6 GPU supporthttps://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp36-cp36m-win_amd64.whl
Python 3.6 CPU-onlyhttps://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp36-cp36m-win_amd64.whl
Python 3.7 GPU supporthttps://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp37-cp37m-win_amd64.whl
Python 3.7 CPU-onlyhttps://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp37-cp37m-win_amd64.whl
Python 3.8 GPU supporthttps://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp38-cp38-win_amd64.whl
Python 3.8 CPU-onlyhttps://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp38-cp38-win_amd64.whl
Raspberry PI (CPU-only)
Python 3, Pi0 or Pi1https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.3.0rc2-cp35-none-linux_armv6l.whl
Python 3, Pi2 or Pi3https://storage.googleapis.com/tensorflow/raspberrypi/tensorflow-2.3.0rc2-cp35-none-linux_armv6l.whl