Metadata-Version: 2.1
Name: highcharts-core
Version: 1.0.0rc2
Summary: High-end Data Visualization for the Python Ecosystem
Project-URL: Homepage, https://highchartspython.com
Project-URL: Documentation, https://core-docs.highchartspython.com/en/latest/
Project-URL: Support, https://www.highchartspython.com/get-help
Project-URL: Source Code, https://github.com/highcharts-for-python/highcharts-core
Project-URL: History, https://github.com/highcharts-for-python/highcharts-core/blob/master/CHANGES.rst
Project-URL: Bug Tracker, https://github.com/highcharts-for-python/highcharts-core/issues
Author-email: HCP LLC <support@highchartspython.com>
License-File: LICENSE
Keywords: charts,data visualization,data viz,graphing,highcharts,highcharts JS,plotting
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Web Environment
Classifier: Framework :: Jupyter
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Manufacturing
Classifier: Intended Audience :: Science/Research
Classifier: License :: Other/Proprietary License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
Classifier: Topic :: Office/Business
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Code Generators
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Utilities
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Description-Content-Type: text/x-rst

###################################################
Highcharts for Python Toolkit
###################################################

**High-end data visualization for the Python ecosystem**

The **Highcharts for Python Toolkit** is a Python library that provides a Python wrapper
for the fantastic `Highcharts JS <https://www.highcharts.com>`__ suite of JavaScript data
visualization libraries, with full integration into the robust Python ecosystem. 

The toolkit is composed of several different libraries, each of which provides comprehensive support for a component of the Highcharts JS suite:

.. list-table::
  :widths: 30 30 40
  :header-rows: 1

  * - Python Library
    - JavaScript Library
    - Description
  * - **Highcharts Core for Python** 
    - `Highcharts Core (JS) <https://www.highcharts.com/products/highcharts/>`__
    - (this library) the core Highcharts data visualization library
  * - `Highcharts Stock for Python <https://stock-docs.highchartspython.com/>`__ 
    - `Highcharts Stock (JS) <https://www.highcharts.com/products/stock/>`__
    - the robust time series visualization extension to Highcharts Core
  * - `Highcharts Maps <https://maps-docs.highchartspython.com/>`__ 
    - `Highcharts Maps (JS) <https://www.highcharts.com/products/maps/>`__
    - the rich map visualization extension to Highcharts Core
  * - `Highcharts Gantt <https://gantt-docs.highchartspython.com/>`__
    - `Highcharts Gantt (JS) <https://www.highcharts.com/products/gantt/>`__
    - the Gantt charting extension to Highcharts Core
  * - (all libraries in the Python toolkit)
    - The **Highcharts Export Server** 
    - enabling the programmatic creation of static (downloadable) data visualizations

In order to integrate **Highcharts for Python** into the Python ecosystem, the library
features native integration with:

  * **Jupyter Labs/Notebook**. You can now produce high-end and interactive plots and
    renders using the full suite of Highcharts visualization capabilities.
  * **Pandas**. Automatically produce data visualizations from your Pandas dataframes
  * **PySpark**. Automatically produce data visualizations from data in a PySpark
    dataframe.
  * ...and even more use-case specific integrations in each tool in the toolkit.

**COMPLETE DOCUMENTATION:** https://core-docs.highchartspython.com/en/latest/index.html

--------------------

***************
Installation
***************

To install **Highcharts Core for Python**, just execute:

.. code:: bash

 $ pip install highcharts-core


-------------

************************************
Why Highcharts for Python?
************************************

Odds are you are aware of `Highcharts JS <https://www.highcharts.com>`__. If not, why not?
It is the world's most popular, most powerful, category-defining JavaScript data
visualization library. If you are building a web or mobile app/dashboard that will be
visualizing data in some fashion, you should absolutely take a look at the Highcharts
suite of solutions. Just take a look at some of their fantastic
`demo visualizations <https://www.highcharts.com/demo>`_.

`Highcharts JS <https://www.highcharts.com>`__ is a JavaScript library. It is written in
JavaScript, and is specifically used to configure and render data visualizations in a
web browser (or other JavaScript-executing) environment. As a JavaScript
library, its audience is JavaScript developers. But what about the broader ecosystem of
Python developers and data scientists?

Python is increasingly used as the technology of choice for data science and for
the backends of leading enterprise-grade applications. In other words, Python is
often the backend that delivers data and content to the front-end...which then renders it
using JavaScript and HTML.

There are numerous Python frameworks (Django, Flask, Tornado, etc.) with specific
capabilities to simplify integration with Javascript frontend frameworks (React, Angular,
VueJS, etc.). But facilitating that with Highcharts has historically been very difficult.
Part of this difficulty is because the Highcharts JavaScript suite - while supporting JSON as a
serialization/deserialization format - leverages
JavaScript object literals to expose the
full power and interactivity of its data visualizations. And while it's easy to serialize
JSON from Python, serializing and deserializing to/from JavaScript object literal notation
is much more complicated. This means that Python developers looking to integrate with
Highcharts typically had to either invest a lot of effort, or were only able to leverage
a small portion of Highcharts' rich functionality.

So I wrote the **Highcharts for Python** toolkit to bridge that gap.

**Highcharts for Python** provides Python object representation for *all* of the
JavaScript objects defined in the
`Highcharts JS API <https://api.highcharts.com/highcharts/>`__. It provides automatic data
validation, and exposes simple and standardized methods for serializing those Python
objects back-and-forth to JavaScript object literal notation.

Key Highcharts for Python Features
======================================

* **Clean and consistent API**. No reliance on "hacky" code, ``dict``
  and JSON serialization, or impossible to maintain / copy-pasted "spaghetti code".
* **Comprehensive Highcharts Support**. Every single Highcharts chart type and every
  single configuration option is supported in the **Highcharts for Python** toolkit.
  This includes the over 70 data visualization types supported by
  `Highcharts JS <https://www.highcharts.com/product/highcharts/>`__ and the 50+
  technical indicator visualizations available in
  `Highcharts Stock <https://www.highcharts.com/product/stock/>`__, with full support for
  the rich JavaScript formatter (JS callback functions)
  capabilities that are often needed to get the most out of Highcharts' visualization and
  interaction capabilities.

  .. note:: 
    
    **See Also**

    * `Supported Visualizations <https://core-docs.highchartspython.com/en/latest/visualizations.html>`__

* **Simple JavaScript Code Generation**. With one method call, produce production-ready
  JavaScript code to render your interactive visualizations using Highcharts' rich
  capabilities.
* **Easy and Robust Chart Download**. With one method call, produce high-end static
  visualizations that can be downloaded or shared as files with your audience. Produce
  static charts using the Highsoft-provided **Highcharts Export Server**, or using your own private export
  server as needed.
* **Integration with Pandas and PySpark**. With two lines of code, produce a high-end
  interactive visualization of your Pandas or PySpark dataframe.
* **Consistent code style**. For Python developers, switching between Pythonic code
  conventions and JavaScript code conventions can be...annoying. So
  **Highcharts for Python** applies Pythonic syntax with automatic conversion between
  Pythonic ``snake_case`` notation and JavaScript ``camelCase`` styles.

|

**Highcharts for Python** vs Alternatives
==============================================

For a discussion of **Highcharts for Python** in comparison to alternatives, please see
the **COMPLETE DOCUMENTATION:** https://core-docs.highchartspython.com/en/latest/index.html

---------------------

********************************
Hello World, and Basic Usage
********************************

1. Import Highcharts Core for Python
==========================================

.. code-block:: python
  
  # PRECISE-LOCATION PATTERN: BEST PRACTICE!
  # This method of importing Highcharts for Python objects yields the fastest
  # performance for the import statement. However, it is more verbose and requires
  # you to navigate the extensive Highcharts Core for Python API.

  # Import classes using precise module indications. For example:
  from highcharts_core.chart import Chart
  from highcharts_core.global_options.shared_options import SharedOptions
  from highcharts_core.options import HighchartsOptions
  from highcharts_core.options.plot_options.bar import BarOptions
  from highcharts_core.options.series.bar import BarSeries

  # CATCH-ALL PATTERN
  # This method of importing Highcharts for Python classes has relatively slow
  # performance because it imports hundreds of different classes from across the entire
  # library. This performance impact may be acceptable to you in your use-case, but
  # do use at your own risk.

  # Import objects from the catch-all ".highcharts" module.
  from highcharts_core import highcharts

  # You can now access specific classes without individual import statements.
  highcharts.Chart
  highcharts.SharedOptions
  highcharts.HighchartsOptions
  highcharts.BarOptions
  highcharts.BarSeries


2. Create Your Chart
================================

  .. code-block:: python

    # from a JavaScript file
    my_chart = highcharts.Chart.from_js_literal('my_js_literal.js')

    # from a JSON file
    my_chart = highcharts.Chart.from_json('my_json.json')

    # from a Python dict
    my_chart = highcharts.Chart.from_dict(my_dict_obj)

    # from a Pandas dataframe
    my_chart = highcharts.Chart.from_pandas(df,
                                            property_map = {
                                                'x': 'transactionDate',
                                                'y': 'invoiceAmt',
                                                'id': 'id'
                                            },
                                            series_type = 'line')

    # from a PySpark dataframe
    my_chart = highcharts.Chart.from_pyspark(df,
                                             property_map = {
                                                 'x': 'transactionDate',
                                                 'y': 'invoiceAmt',
                                                 'id': 'id'
                                             },
                                             series_type = 'line')

    # from a CSV
    my_chart = highcharts.Chart.from_csv('/some_file_location/filename.csv'
                                         column_property_map = {
                                            'x': 0,
                                            'y': 4,
                                            'id': 14
                                         },
                                         series_type = 'line')

    # from a HighchartsOptions configuration object
    my_chart = highcharts.Chart.from_options(my_options)

    # from a Series configuration
    my_chart = highcharts.Chart.from_series(my_series)


3. Configure Global Settings (optional)
=============================================

  .. code-block:: python

    # Import SharedOptions
    from highcharts_core.global_options.shared_options import SharedOptions

    # from a JavaScript file
    my_global_settings = SharedOptions.from_js_literal('my_js_literal.js')

    # from a JSON file
    my_global_settings = SharedOptions.from_json('my_json.json')

    # from a Python dict
    my_global_settings = SharedOptions.from_dict(my_dict_obj)

    # from a HighchartsOptions configuration object
    my_global_settings = SharedOptions.from_options(my_options)


4. Configure Your Chart / Global Settings
================================================

  .. code-block:: python

    from highcharts_core.options.title import Title
    from highcharts_core.options.credits import Credits

    # Using dicts
    my_chart.title = {
        'align': 'center'
        'floating': True,
        'text': 'The Title for My Chart',
        'use_html': False,
    }

    my_chart.credits = {
        'enabled': True,
        'href': 'https://www.highcharts.com/',
        'position': {
            'align': 'center',
            'vertical_align': 'bottom',
            'x': 123,
            'y': 456
        },
        'style': {
            'color': '#cccccc',
            'cursor': 'pointer',
            'font_size': '9px'
        },
        'text': 'Chris Modzelewski'
    }

    # Using direct objects
    from highcharts_core.options.title import Title
    from highcharts_core.options.credits import Credits

    my_title = Title(text = 'The Title for My Chart', floating = True, align = 'center')
    my_chart.options.title = my_title

    my_credits = Credits(text = 'Chris Modzelewski', enabled = True, href = 'https://www.highcharts.com')
    my_chart.options.credits = my_credits


5. Generate the JavaScript Code for Your Chart
=================================================

Now having configured your chart in full, you can easily generate the JavaScript code
that will render the chart wherever it is you want it to go:

  .. code-block:: python

    # as a string
    js_as_str = my_chart.to_js_literal()

    # to a file (and as a string)
    js_as_str = my_chart.to_js_literal(filename = 'my_target_file.js')


6. Generate the JavaScript Code for Your Global Settings (optional)
=========================================================================

  .. code-block:: python

    # as a string
    global_settings_js = my_global_settings.to_js_literal()

    # to a file (and as a string)
    global_settings_js = my_global_settings.to_js_literal('my_target_file.js')


7. Generate a Static Version of Your Chart
==============================================

  .. code-block:: python

    # as in-memory bytes
    my_image_bytes = my_chart.download_chart(format = 'png')

    # to an image file (and as in-memory bytes)
    my_image_bytes = my_chart.download_chart(filename = 'my_target_file.png',
                                             format = 'png')

--------------

***********************
Getting Help/Support
***********************

The **Highcharts for Python** toolkit comes with all of the great support that you are used to from working with the 
Highcharts JavaScript libraries. When you license the toolkit, you are welcome to use any of the following tools to get 
help using the toolkit. In particular, you can:

  * Use the `Highcharts Forums <https://highcharts.com/forum>`__
  * Use `Stack Overflow <https://stackoverflow.com/questions/tagged/highcharts-for-python>`__ with the 
    ``highcharts-for-python`` tag
  * `Report bugs or request features <https://github.com/highcharts-for-python/highcharts-core/issues>`__  in the 
    library's Github repository
  * `File a support ticket <https://www.highchartspython.com/get-help>`__ with us
  * `Schedule a live chat or video call <https://www.highchartspython.com/get-help>`__ with us

**FOR MORE INFORMATION:** https://www.highchartspython.com/get-help

-----------------

*********************
Contributing
*********************

We welcome contributions and pull requests! For more information, please see the
`Contributor Guide <https://core-docs.highchartspython.com/en/latest/contributing.html>`__. And thanks to all those who've already contributed!

-------------------

*********************
Testing
*********************

We use `TravisCI <https://travisci.org>`_ for our build automation and
`ReadTheDocs <https://readthedocs.org>`_ for our documentation.

Detailed information about our test suite and how to run tests locally can be
found in our Testing Reference.
