Skip to main content

Add your description here

Project description

Arakawa

Overview

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
# or
conda install -c conda-forge

Examples

📊 Share plots, data, and more as reports

Create reports from pandas DataFrames, plots from your favorite libraries, and text.

Simple example with text, plot and table

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.

Complex layout

...

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).

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

arakawa-0.0.1a6.tar.gz (174.9 kB view details)

Uploaded Source

Built Distribution

arakawa-0.0.1a6-py3-none-any.whl (69.2 kB view details)

Uploaded Python 3

File details

Details for the file arakawa-0.0.1a6.tar.gz.

File metadata

  • Download URL: arakawa-0.0.1a6.tar.gz
  • Upload date:
  • Size: 174.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for arakawa-0.0.1a6.tar.gz
Algorithm Hash digest
SHA256 da30c6e15df7deafb510c22b0dc07549fc420f7862381e4f7577630e8332a258
MD5 325ac98a85d878797ece6f322801e354
BLAKE2b-256 f412e5ababd141b22ed8949b09be674f7d9cc464f7d4a85d2ea67ad168f27839

See more details on using hashes here.

Provenance

File details

Details for the file arakawa-0.0.1a6-py3-none-any.whl.

File metadata

  • Download URL: arakawa-0.0.1a6-py3-none-any.whl
  • Upload date:
  • Size: 69.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.10

File hashes

Hashes for arakawa-0.0.1a6-py3-none-any.whl
Algorithm Hash digest
SHA256 292538e82f6c9717cf9c70c2f6c76d50956c1d15631ad989804aabe9b6e265b6
MD5 605dd20e20325885523d0b5f6496793b
BLAKE2b-256 35a064de4051b27159ceac0dd8103656e36868efc8c7c5d140bc0584bd4d51b0

See more details on using hashes here.

Provenance

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