charts.css.py 0.4.0

charts.css.py brings charts.css to Python.

charts.css.py

charts.css.py provides a python API to convert your 2-dimension data lists into html snippet, which will be rendered into charts by CSS, when serving inside a browser.

• The output of charts.css.py is not images. Consequently, charts.css.py is a pure Python package without any image library dependency. You can use charts.css.py on any platform.
• The output of charts.css.py is a normal HTML table. Search engines and screen readers will be able to consume your data even when CSS rendering is unavailable.
• Once the html snippet is delivered into the browser window, the rendering is done by CSS, which is typically faster than JS-heavy chart libraries.
• Since the output is normal HTML, you could customize its size and position, by defining your own CSS styles.

Installation

pip install charts.css.py

Usage

Just combine the output of charts.css.py functions and the predefined CSS style <link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/charts.css/dist/charts.min.css"> into your html page.

For example, the following code snippet can convert a 2-dimension list into column chart:

from charts.css import column
STYLESHEET = '<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/charts.css/dist/charts.min.css">'
chart = column(
    [
        ["Continent", "1st year", "2nd year", "3rd year", "4th year", "5th year"],
        ["Asia", 20.0, 30.0, 40.0, 50.0, 75.0],
        ["Euro", 40.0, 60.0, 75.0, 90.0, 100.0],
    ],
    headers_in_first_row=True,
    headers_in_first_column=True,
    )
# Now, variable chart contains html snippet of "<table>...</table>", and
# STYLESHEET is just a constant string of "<link href='https://.../charts.css'>".
# You can somehow insert them into the proper places of your full html page.
# Here in this sample, we take a shortcut by simply concatenating them.
open("output.html", "w").write(STYLESHEET + chart)

The output.html will be rendered in browser like this:

Advanced Usage

There are currently 4 different charts implemented: bar, column, line, area. All those methods support many parameters to further customize the chart appearance. bar() and column() also support stacking by value or stacking by percentage. All those features are demonstrated in the different samples in this document.

Lastly, this package also provides a command-line tool csv2chart. You can use it to convert csv file into an html file. For example, csv2chart sample.csv output.html. You can also run csv2chart -h to know all the parameters it supports.

Versioning

charts.css.py uses Semantic Versioning.