Arakawa
Build interactive reports in seconds using Python.
Arakawa makes it simple to build interactive reports in seconds using Python.
Import Arakawa's Python library into your script or notebook and build reports programmatically by wrapping components such as:
- Pandas DataFrames
- Plots from Python visualization libraries such as Bokeh, Altair, Plotly, and Folium
- Markdown and text
- Files, such as images, PDFs, JSON data, etc.
- Interactive forms which run backend Python functions
Arakawa reports are interactive and can also contain pages, tabs, drop downs, and more. Once created, reports can be exported as HTML, shared as standalone files, or embedded into your own application, where your viewers can interact with your data and visualizations.
Getting Started
Check out our Quickstart to build a report in 3m.
Installing Arakawa
pip install arakawa
Examples
📊 Share plots, data, and more as reports
Create reports from pandas DataFrames, plots from your favorite libraries, and text.
import altair as alt
from vega_datasets import data
import arakawa as ar
df = data.iris()
fig = (
alt.Chart(df)
.mark_point()
.encode(
x="petalLength:Q",
y="petalWidth:Q",
color="species:N"
)
)
view = ar.Blocks(
ar.Plot(fig),
ar.DataTable(df)
)
ar.save_report(view, path="simple_example.html")
🎛 Layout using interactive blocks
Add dropdowns, selects, grid, pages, and 10+ other interactive blocks.
...
view = ar.Blocks(
ar.Formula("x^2 + y^2 = z^2"),
ar.Group(
ar.BigNumber(
heading="Number of percentage points",
value="84%",
change="2%",
is_upward_change=True
),
ar.BigNumber(
heading="Simple Statistic", value=100
), columns=2
),
ar.Select(
ar.Plot(fig, label="Chart"),
ar.DataTable(df, label="Data")
),
)
ar.save_report(view, path="layout_example.html")
See the documentation for more details.
Acknowledgement
This project is fork of datapane/datapane and original codes are written by StackHut Limited (trading as Datapane).
1 maintainer
Metadata
1 maintainer
Release files for arakawa 0.4.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| arakawa-0.4.4.tar.gz | 4.8 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| arakawa-0.4.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 9.4 MB
Release files / arakawa-0.4.4.tar.gz
| Download URL | arakawa-0.4.4.tar.gz |
|---|---|
| Size | 4.8 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
876f18a49215fe129292eebaf1c386b01c72085626d11cf3d582206a3ecb2bdc
|
|
BLAKE2b-256 checksum How to use checksums |
a26c68765187680bc6aa4a0efb418a234bafa8e763101e71aca5864a6ec6f8f8
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
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Signed by GitHub Actions, verified by PyPI on Sep 24, 2026.
Transparency logRelease files / arakawa-0.4.4-py3-none-any.whl
| Download URL | arakawa-0.4.4-py3-none-any.whl |
|---|---|
| Size | 4.6 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
3ec0abd54d569a070da5346af1a9bd5b71061b431455f4dce29d22597c880b1a
|
|
BLAKE2b-256 checksum How to use checksums |
808d88a35332365bf6341a5df7077206121ddbd41ab3399a9debfccc485e8990
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 24, 2026.
Transparency log
