Skip to main content

A Jupyter Notebook server extension that provides APIs for fetching hdf5 contents and data. Built on h5py.

Project description

PyPI version npm_version

interactive api docs

jupyterlab-hdf5

Open and explore HDF5 files in JupyterLab. Can handle very large (TB) sized files. Now integrated with the standard filebrowser!

hdf_preview

Currently in early release. Double clicking on an .hdf5 file in the file browser will open it in a special HDF browser. You can then browse through the groups and open the datasets in the .hdf5 file. All datasets will open read only.

For the moment, the browser context menu does not work with .hdf5 files/groups/datasets. Only double clicking is currently supported.

Designed from the ground up to be as efficient as possible. Data will only be fetched as needed to create the visible display. This allows the extension to work with very large files, potentially up to the TB range.

Installation

pip install jupyterlab_hdf
jupyter labextension install @jupyterlab/hdf5

This will install both the server extension and the labextension needed by this plugin.

You can also install the labextension via Jupyterlab's extension manager GUI. Keep in mind that if you use the GUI, you'll still need to install the jupyterlab_hdf server extension via pip.

Development

For a development install, clone the repository and then run the following in the repo dir:

pip install .
jlpm build:dev

To watch for/rebuild on changes to this extension's source code, run:

jlpm run build:watch

What's in this extension

This extension has two main parts: an hdf5 filebrowser plugin, and an hdf5 dataset file type plugin. It also has a plugin (in early development) that provides HDF5 support for the @jupyterlab/dataregistry labextension.

HDF5 Filebrowser

Allows you to navigate an .hdf5 file's groups as though they were directories in a filesystem. Any .hdf5 file on a user's system can be opened by entering its path (relative to the Jupyterlab home directory) in the box at the top of the browser.

HDF5 dataset file type

When you open a dataset using the hdf5 filebrowser, a document will open that displays the contents of the dataset via a grid.

HDF5 DataRegistry support

The @jupyterlab/dataregistry extension allows for exploration of data in a very generalized way. If you have @jupyterlab/dataregistry installed, this plugin will supply HDF5 support for dataregistry.

Status of the latest version

  • filebrowser

    • features
      • allows you to a double click on an .hdf5 file in the main file browser and open it in the new hdf browser
      • the hdf browser allows you to view the contents as groups and datasets and double click to open them
    • Some minor UI issues remain (mostly with the breadcrumbs).
    • The next goal is to get the browser context menus to work correctly with HDF5 types. This will likely require some changes to JupyterLab core, which are currently being investigated.
  • dataset file type

    • features
      • data will load to the grid dynamically as needed
      • the grid can accessed as slices via the "Slice" UI
    • read only
    • the next goal is to enable selection/copying of a dataset's elements
  • @jupyterlab/dataregistry support

    • features
      • allows the opening of .hdf5 files, groups, and datasets in the dataregistry browser
      • offers functionality similar to that of the set of other plugins in this extension

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jupyterlab_hdf-0.3.0.tar.gz (121.3 kB view details)

Uploaded Source

File details

Details for the file jupyterlab_hdf-0.3.0.tar.gz.

File metadata

  • Download URL: jupyterlab_hdf-0.3.0.tar.gz
  • Upload date:
  • Size: 121.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/42.0.1 requests-toolbelt/0.9.1 tqdm/4.32.1 CPython/3.7.4

File hashes

Hashes for jupyterlab_hdf-0.3.0.tar.gz
Algorithm Hash digest
SHA256 92ec748724cd4b029bc3e9f4d51f368db7bd21dea7a79a0541003bbe55abbf74
MD5 0539b1dcd0d738a3db40e551de4e9731
BLAKE2b-256 fb688a87bb01d5fbb21a5fc2208df42daefcff723c228bc1a018635b85fb0b9b

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page