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# Contents API

The Jupyter Notebook web application provides a graphical interface for creating, opening, renaming, and deleting files in a virtual filesystem.

The `ContentsManager` class defines an abstract API for translating these interactions into operations on a particular storage medium. The default implementation, `FileContentsManager`, uses the local filesystem of the server for storage and straightforwardly serializes notebooks into JSON. Users can override these behaviors by supplying custom subclasses of ContentsManager.

This section describes the interface implemented by ContentsManager subclasses. We refer to this interface as the Contents API.

## Data Model

### Filesystem Entities

ContentsManager methods represent virtual filesystem entities as dictionaries, which we refer to as models.

Models may contain the following entries:

Key | Type | Info
--- | --- | ---
name | unicode | Basename of the entity.
path | unicode | Full (API-style) path to the entity.
type | unicode | The entity type. One of `"notebook"`, `"file"` or `"directory"`.
created | datetime | Creation date of the entity.
last_modified | datetime | Last modified date of the entity.
content | variable | The “content” of the entity. (See Below)
mimetype | unicode or `None` | The mimetype of `content`, if any. (See Below)
format | unicode or `None` | The format of `content`, if any. (See Below)
[optional] hash | unicode or `None` | The hash of the contents. It cannot be null if `hash_algorithm` is defined.
[optional] hash_algorithm | unicode or `None` | The algorithm used to compute hash value. It cannot be null if `hash` is defined.

Certain model fields vary in structure depending on the `type` field of the model. There are three model types: notebook, file, and directory.

- `notebook` models

    - The `format` field is always `"json"`.

    - The `mimetype` field is always `None`.

    - The `content` field contains a `nbformat.notebooknode.NotebookNode` representing the .ipynb file represented by the model. See the NBFormat documentation for a full description.

    - The `hash` field a hexdigest string of the hash value of the file. If `ContentManager.get` not support hash, it should always be `None`.

    - `hash_algorithm` is the algorithm used to compute the hash value.

- `file` models

    - The `format` field is either `"text"` or `"base64"`.

    - The `mimetype` field is `text/plain` for text-format models and `application/octet-stream` for base64-format models.

    - The `content` field is always of type `unicode`. For text-format file models, `content` simply contains the file’s bytes after decoding as UTF-8. Non-text (`base64`) files are read as bytes, base64 encoded, and then decoded as UTF-8.

    - The `hash` field a hexdigest string of the hash value of the file. If `ContentManager.get` not support hash, it should always be `None`.

    - `hash_algorithm` is the algorithm used to compute the hash value.

- `directory` models

    - The `format` field is always `"json"`.

    - The `mimetype` field is always `None`.

    - The `content` field contains a list of content-free models representing the entities in the directory.

    - The `hash` field is always `None`.

Note

In certain circumstances, we don’t need the full content of an entity to complete a Contents API request. In such cases, we omit the `mimetype`, `content`, and `format` keys from the model. This most commonly occurs when listing a directory, in which circumstance we represent files within the directory as content-less models to avoid having to recursively traverse and serialize the entire filesystem.

Sample Models

    # Notebook Model with Content and Hash
    {
        "content": {
            "metadata": {},
            "nbformat": 4,
            "nbformat_minor": 0,
            "cells": [
                {
                    "cell_type": "markdown",
                    "metadata": {},
                    "source": "Some **Markdown**",
                },
            ],
        },
        "created": datetime(2015, 7, 25, 19, 50, 19, 19865),
        "format": "json",
        "last_modified": datetime(2015, 7, 25, 19, 50, 19, 19865),
        "mimetype": None,
        "name": "a.ipynb",
        "path": "foo/a.ipynb",
        "type": "notebook",
        "writable": True,
        "hash": "f5e43a0b1c2e7836ab3b4d6b1c35c19e2558688de15a6a14e137a59e4715d34b",
        "hash_algorithm": "sha256",
    }

    # Notebook Model without Content
    {
        "content": None,
        "created": datetime.datetime(2015, 7, 25, 20, 17, 33, 271931),
        "format": None,
        "last_modified": datetime.datetime(2015, 7, 25, 20, 17, 33, 271931),
        "mimetype": None,
        "name": "a.ipynb",
        "path": "foo/a.ipynb",
        "type": "notebook",
        "writable": True,
    }

### API Paths

ContentsManager methods represent the locations of filesystem resources as API-style paths. Such paths are interpreted as relative to the root directory of the notebook server. For compatibility across systems, the following guarantees are made:

- Paths are always `unicode`, not `bytes`.

- Paths are not URL-escaped.

- Paths are always forward-slash (/) delimited, even on Windows.

- Leading and trailing slashes are stripped. For example, `/foo/bar/buzz/` becomes `foo/bar/buzz`.

- The empty string (`""`) represents the root directory.

## Writing a Custom ContentsManager

The default ContentsManager is designed for users running the notebook as an application on a personal computer. It stores notebooks as .ipynb files on the local filesystem, and it maps files and directories in the Notebook UI to files and directories on disk. It is possible to override how notebooks are stored by implementing your own custom subclass of `ContentsManager`. For example, if you deploy the notebook in a context where you don’t trust or don’t have access to the filesystem of the notebook server, it’s possible to write your own ContentsManager that stores notebooks and files in a database.

### Required Methods

A minimal complete implementation of a custom `ContentsManager` must implement the following methods:

`ContentsManager.get`(path[, content, type, ...]) | Get a file or directory model.
`ContentsManager.save`(model, path) | Save a file or directory model to path.
`ContentsManager.delete_file`(path) | Delete the file or directory at path.
`ContentsManager.rename_file`(old_path, new_path) | Rename a file or directory.
`ContentsManager.file_exists`([path]) | Does a file exist at the given path?
`ContentsManager.dir_exists`(path) | Does a directory exist at the given path?
`ContentsManager.is_hidden`(path) | Is path a hidden directory or file?

You may be required to specify a Checkpoints object, as the default one, `FileCheckpoints`, could be incompatible with your custom ContentsManager.

## Customizing Checkpoints

Customized Checkpoint definitions allows behavior to be altered and extended.

The `Checkpoints` and `GenericCheckpointsMixin` classes (from `jupyter_server.services.contents.checkpoints`) have reusable code and are intended to be used together, but require the following methods to be implemented.

`Checkpoints.rename_checkpoint`(checkpoint_id, ...) | Rename a single checkpoint from old_path to new_path.
`Checkpoints.list_checkpoints`(path) | Return a list of checkpoints for a given file
`Checkpoints.delete_checkpoint`(checkpoint_id, ...) | delete a checkpoint for a file
`GenericCheckpointsMixin.create_file_checkpoint`(...) | Create a checkpoint of the current state of a file
`GenericCheckpointsMixin.create_notebook_checkpoint`(nb, ...) | Create a checkpoint of the current state of a file
`GenericCheckpointsMixin.get_file_checkpoint`(...) | Get the content of a checkpoint for a non-notebook file.
`GenericCheckpointsMixin.get_notebook_checkpoint`(...) | Get the content of a checkpoint for a notebook.

### No-op example

Here is an example of a no-op checkpoints object - note the mixin comes first. The docstrings indicate what each method should do or return for a more complete implementation.

    class NoOpCheckpoints(GenericCheckpointsMixin, Checkpoints):
        """requires the following methods:"""

        def create_file_checkpoint(self, content, format, path):
            """-> checkpoint model"""

        def create_notebook_checkpoint(self, nb, path):
            """-> checkpoint model"""

        def get_file_checkpoint(self, checkpoint_id, path):
            """-> {'type': 'file', 'content': <str>, 'format': {'text', 'base64'}}"""

        def get_notebook_checkpoint(self, checkpoint_id, path):
            """-> {'type': 'notebook', 'content': <output of nbformat.read>}"""

        def delete_checkpoint(self, checkpoint_id, path):
            """deletes a checkpoint for a file"""

        def list_checkpoints(self, path):
            """returns a list of checkpoint models for a given file,
            default just does one per file
            """
            return []

        def rename_checkpoint(self, checkpoint_id, old_path, new_path):
            """renames checkpoint from old path to new path"""

See `GenericFileCheckpoints` in `notebook.services.contents.filecheckpoints` for a more complete example.

## Testing

`jupyter_server.services.contents.tests` includes several test suites written against the abstract Contents API. This means that an excellent way to test a new ContentsManager subclass is to subclass our tests to make them use your ContentsManager.

Note

PGContents is an example of a complete implementation of a custom `ContentsManager`. It stores notebooks and files in PostgreSQL and encodes directories as SQL relations. PGContents also provides an example of how to reuse the notebook’s tests.

## Asynchronous Support

An asynchronous version of the Contents API is available to run slow IO processes concurrently.

- `AsyncContentsManager`

- `AsyncFileContentsManager`

- `AsyncLargeFileManager`

- `AsyncCheckpoints`

- `AsyncGenericCheckpointsMixin`

Note

In most cases, the non-asynchronous Contents API is performant for local filesystems. However, if the Jupyter Notebook web application is interacting with a high-latent virtual filesystem, you may see performance gains by using the asynchronous version. For example, if you’re experiencing terminal lag in the web application due to the slow and blocking file operations, the asynchronous version can reduce the lag. Before opting in, comparing both non-async and async options’ performances is recommended.