# Install the Seldon Core Python module

Seldon Core has a python package `seldon-core` available on PyPI. The package makes it easier to work with Seldon Core if you are using python. The module provides:

* `seldon-core-microservice` executable to serve microservice components in Seldon Core. This is used by the Python Wrapper for Seldon Core.
* `seldon_core.seldon_client` library. Core reference API module to call Seldon Core services (internal microservices or the external API). This is used by the testing executable and can be used by users to build their own clients to Seldon Core in Python.

## Install

Install from PyPI with:

```bash
$ pip install seldon-core
```

### Tensorflow support

Seldon Core adds optional support to send a `TFTensor` as your prediction input. However, most users will prefer to send a `numpy` array, string, binary or JSON input instead. Therefore, in order to avoid including the `tensorflow` dependency on installations where the `TFTensor` support won't be necessary, it isn't installed it by default.

To include the optional `TFTensor` support, you can install `seldon-core` as:

```bash
$ pip install seldon-core[tensorflow]
```

### Google Cloud Storage support

As part of the options to store your trained model, Seldon Core adds optional support to fetch them from GCS (Google Cloud Storage). We are aware that users will usually only require one of the storage backends. Therefore, to avoid bloating the `seldon-core` package, we don't install the GCS dependencies by default.

To include the optional GCS support, you can install `seldon-core` as:

```bash
$ pip install seldon-core[gcs]
```

We are currently looking into options to replace the multiple cloud storage libraries that `seldon-core` requires for a single multi-cloud one. This discussion is currently open on [issue #1028](https://github.com/SeldonIO/seldon-core/issues/1028). Feedback and suggestions are welcome!

### Azure Blob Storage support

As part of the options to store your trained model, Seldon Core adds optional support to fetch them from Azure Blob Storage. We are aware that users will usually only require one of the storage backends. Therefore, to avoid bloating the `seldon-core` package, the Azure Blob Storage dependencies are not installed by default.

To include the optional Azure support, you can install `seldon-core` as:

```bash
$ pip install seldon-core[azure]
```

### Install all extra dependencies

If you want to install `seldon-core` with all its extra dependencies, you can do so as:

```bash
$ pip install seldon-core[all]
```

Keep in mind that this will include some dependencies which may not be used. Therefore, unless necessary, we recommend most users to install the default distribution of `seldon-core` as [documented above](#install).

## Troubleshooting

If you experience problems after installing `seldon-core`, here are some tips to diagnose the issue.

### ImportError: cannot import name 'BlockBlobService'

The library we use to support Azure Blob Storage [released an update](https://github.com/Azure/azure-storage-python/issues/640) which contains breaking changes with previous versions. This update breaks versions of `seldon-core` below or equal to `0.5.0` but it shouldn't affect users on version `0.5.0.2` and above. If you are facing this issue, you should see a stacktrace similar to the one below:

```pytb
.../seldon_core/storage.py in <module>
     23 import re
     24 from urllib.parse import urlparse
---> 25 from azure.storage.blob import BlockBlobService
     26 from minio import Minio
     27 from seldon_core.imports_helper import _GCS_PRESENT

ImportError: cannot import name 'BlockBlobService'
```

The recommended workaround is to update `seldon-core` to version `0.5.0.2` or above. Alternatively, if you can't upgrade to a more recent version, the following also works:

```bash
$ pip install azure-storage-blob==2.1.0 seldon-core
```

## Next Steps

[Create your python inference class](/seldon-core-1/configuration/wrappers-and-sdks/python-language-wrapper/python_component.md)


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