How to Install Daft

This guide helps you install Daft based on your specific needs and environment.

For most users, install Daft with a single command:

bash

pip install -U daft

Optional Dependencies

Depending on your use case, you may need to install Daft with additional dependencies.

<div id="daft-install-tool" class="daft-install-tool"> <div class="use-cases"> <h4>Use Cases:</h4>

<div class="checkbox-group">
  <label class="checkbox-item">
    <input type="checkbox" id="huggingface" data-extra="huggingface">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>Hugging Face</strong> <code>huggingface</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="openai" data-extra="openai">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>OpenAI</strong> <code>openai</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="transformers" data-extra="transformers">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>Transformers</strong> <code>transformers</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="ray" data-extra="ray">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>Distributed Computing on Ray</strong> <code>ray</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="turbopuffer" data-extra="turbopuffer">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>Turbopuffer</strong> <code>turbopuffer</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="aws" data-extra="aws">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>AWS Glue or AWS S3 Tables</strong> <code>aws</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="iceberg" data-extra="iceberg">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>Apache Iceberg</strong> <code>iceberg</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="deltalake" data-extra="deltalake">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>Delta Lake</strong> <code>deltalake</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="hudi" data-extra="hudi">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>Apache Hudi</strong> <code>hudi</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="unity" data-extra="unity">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>Unity Catalog (Databricks)</strong> <code>unity</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="lance" data-extra="lance">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>LanceDB</strong> <code>lance</code>
    </div>
  </label>

  <label class="checkbox-item">
    <input type="checkbox" id="clickhouse" data-extra="clickhouse">
    <span class="checkmark"></span>
    <div class="checkbox-content">
      <strong>ClickHouse</strong> <code>clickhouse</code>
    </div>
  </label>
</div>

</div> <div class="command-output"> <h4>Installation Command:</h4> <div class="highlight"> <table class="highlighttable"> <tbody> <tr> <td class="linenos"> <div class="linenodiv"> <pre><span></span><span class="normal">1</span></pre> </div> </td> <td class="code"> <div> <pre><button class="md-clipboard md-icon" title="Copy to clipboard" data-clipboard-target="#install-command > code"></button><code id="install-command" class="language-bash">pip install -U daft</code></pre> </div> </td> </tr> </tbody> </table> </div> </div> </div>

You can also install Daft with all extra dependencies:

bash

pip install -U "daft[all]"

Nightly Builds

Nightly builds are published daily from the latest main branch. These are useful for testing upcoming features and bug fixes before they are released on PyPI.

bash

pip install daft --pre --extra-index-url https://nightly.daft.ai

!!! warning "Stability" Nightly builds may contain unstable or experimental changes. They are not recommended for production use.

Troubleshooting Legacy CPU Support

If you encounter Illegal instruction errors, your CPU may lack support for advanced instruction sets like AVX. Use the LTS version instead:

bash

pip install -U daft-lts

!!! warning "Performance Impact" The LTS version uses limited CPU instructions and cannot leverage vectorized operations, resulting in slower performance. Only use this if the standard package fails to run.