Jupyter Storage Explorer
A file explorer for cloud storage and data lakes, right inside your Jupyter notebook, in the spirit of Azure Storage Explorer.
Browse Amazon S3, Azure Data Lake / Blob Storage, Google Cloud Storage, local disks and more; preview Parquet files, Delta Lake tables, CSV, Excel, JSON and other formats; page through, sort and filter tables; get ready-to-run code that loads the data into your notebook; and upload, download, move and edit files without leaving JupyterLab.
Highlights
StorageExplorer: any fsspec storage, several in one explorer; copy and paste between storages and notebooks.DataExplorer: page, sort and filter any dataframe; get the result back in code.- Previews of Delta Lake, Parquet, CSV, JSON, Excel, text and images, with code to load them.
- Background file operations with progress and Cancel; folder operations only in Unsafe mode.
- Bookmarks, remembered queries, transfer rules, and a JupyterLab launcher item.
Installation
pip install jupyter-storage-explorer
Install the package for your storage too:
| Storage | Package | Address |
|---|---|---|
| Amazon S3 | s3fs |
s3://bucket/path |
| Azure Data Lake / Blob Storage | adlfs |
abfs://container@account.dfs.core.windows.net/path |
| Google Cloud Storage | gcsfs |
gs://bucket/path |
| Local disk, in-memory | (included) | /path, memory:// |
Previewing and querying data files needs a data library, e.g. pip install polars deltalake. If one is missing, the
preview tells you what to install.
Quick start
From the JupyterLab launcher
The separate package jupyter-storage-explorer-launcher
adds Storage Explorer to JupyterLab's launcher and command palette, opening the explorer in its own tab:
pip install jupyter-storage-explorer-launcher
From Python code
from jupyter_storage_explorer import StorageExplorer
StorageExplorer("s3://my-bucket/data")
The explorer appears as the cell's output. Options after the address are passed to the storage package, e.g.
StorageExplorer("s3://my-bucket/data", profile="analytics"). Double-click a file to preview it; right-click for
everything else.
To browse a dataframe and get the rows you filtered back:
import polars as pl
from jupyter_storage_explorer import DataExplorer
explorer = DataExplorer(pl.scan_parquet("s3://my-bucket/lake/sales/*.parquet"))
explorer
explorer.result().collect() # after filtering and sorting in the widget
The notebooks folder has a demo of each widget (storage_explorer.ipynb, data_explorer.ipynb) on sample data made
by make_samples.py.
Documentation
- StorageExplorer: storages, using the explorer, unsafe operations, transfer policy, remembered states, supported formats, format options and all the options.
- DataExplorer: the data
browser,
result(),on_change(),QuerySettingsand the options. - The launcher: installing it
and configuring its tab with
launcher.pyfiles. - Development: building from source, the JupyterLab extension, releasing, and customizing the explorer's icons with CSS.
Requirements
- Python 3.11 or later
- JupyterLab 4. The widgets also show in other Jupyter frontends, but dragging files from JupyterLab's file browser works only in JupyterLab.
- For querying data: a recent polars (tested with polars 2.0).
DataExplorerworks with any dataframe narwhals supports; with polars installed, data in memory is queried with polars, which is faster.
1 maintainer
Metadata
1 maintainer
Release files for jupyter-storage-explorer 0.7.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| jupyter_storage_explorer-0.7.1.tar.gz | 387.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| jupyter_storage_explorer-0.7.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 577.3 kB
Release files / jupyter_storage_explorer-0.7.1.tar.gz
| Download URL | jupyter_storage_explorer-0.7.1.tar.gz |
|---|---|
| Size | 387.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Download URL | jupyter_storage_explorer-0.7.1-py3-none-any.whl |
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| Size | 189.6 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
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