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Installing Tahoe-LAFS

Tahoe-LAFS is a secure, decentralized, and fault-tolerant storage system. To see an overview of the architecture and security properties, see Welcome to Tahoe LAFS! <../about-tahoe>

Tahoe-LAFS can be installed and used on any of the following operating systems.

Microsoft Windows

To install Tahoe-LAFS on Windows:

  1. Make sure you have Powershell installed. See PowerShell installation.

  2. Install the latest version of Python 3. Download the .exe file at the python website.

  3. Open the installer by double-clicking it. Select the Add Python to PATH check-box, then click Install Now.

  4. Start PowerShell and enter the following command to verify python installation:

    python --version

  5. Enter the following command to install Tahoe-LAFS:

    pip install tahoe-lafs

  6. Verify installation by checking for the version:

    tahoe --version

If you want to hack on Tahoe's source code, you can install Tahoe in a virtualenv on your Windows Machine. To learn more, see install-on-windows.

Linux, BSD, or MacOS

Tahoe-LAFS can be installed on MacOS, many Linux and BSD distributions. If you are using Ubuntu or Debian, run the following command to install Tahoe-LAFS:

apt-get install tahoe-lafs

If you are working on MacOS or a Linux distribution which does not have Tahoe-LAFS packages, you can build it yourself:

  1. Make sure the following are installed:

    • Python 3's latest version: Check for the version by running python --version.
    • pip: Most python installations already include pip. However, if your installation does not, see pip installation.

  2. Install Tahoe-LAFS using pip:

    pip install tahoe-lafs

  3. Verify installation by checking for the version:

    tahoe --version

If you are looking to hack on the source code or run pre-release code, we recommend you install Tahoe-LAFS on a virtualenv instance. To learn more, see install-on-linux.

You can always write to the tahoe-dev mailing list or chat on the Libera.chat IRC if you are not able to get Tahoe-LAFS up and running on your deployment.