> ## Documentation Index
> Fetch the complete documentation index at: https://nixtlaverse.nixtla.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Install | StatsForecast

> Install StatsForecast with pip or conda

You can install the *released version* of `StatsForecast` from the
[Python package index](https://pypi.org) with:

```shell theme={null}
pip install statsforecast
```

or

```shell theme={null}
conda install -c conda-forge statsforecast
```

> **Warning**
>
> We are constantly updating StatsForecast, so we suggest fixing the
> version to avoid issues. `pip install statsforecast=="1.0.0"`

> **Tip**
>
> We recommend installing your libraries inside a python virtual or
> [conda
> environment](https://docs.conda.io/projects/conda/en/latest/user-guide/install/macos.html).

#### Extras

The following features can also be installed by specifying the extra
inside the install command,
e.g. `pip install 'statsforecast[extra1,extra2]'`

* **polars**: provide polars dataframes to StatsForecast.
* **plotly**: use `StatsForecast.plot` with the plotly backend.
* **dask**: perform distributed forecasting with dask.
* **spark**: perform distributed forecasting with spark.
* **ray**: perform distributed forecasting with ray.

#### Development version

If you want to try out a new feature that hasn’t made it into a release
yet you have the following options:

* Install from our nightly wheels:
  `pip install --extra-index-url=http://nixtla-packages.s3-website.us-east-2.amazonaws.com --trusted-host nixtla-packages.s3-website.us-east-2.amazonaws.com statsforecast`
* Install from github:
  `pip install git+https://github.com/Nixtla/statsforecast`. This
  requires that you have a C++ compiler installed, so we encourage you
  to try the previous option first.