semvec/pypi-packages huggingface dataset:
ealib 0.4.0
An open source Python library for mathematical optimization
Requires Python: >=3.11

=======
PyEALib
=======

Copyright (c) 2014-2024 Jérémie DECOCK <jd.jdhp@gmail.com> (www.jdhp.org)

* Web site: http://www.jdhp.org/software_en.html#ealib
* Online documentation: https://jdhp-dev.gitlab.io/ealib
* Source code: https://gitlab.com/ealib
* Issue tracker: https://gitlab.com/jdhp-dev/ealib/issues
* Pytest code coverage: https://jdhp-dev.gitlab.io/ealib/htmlcov/index.html
* PyEALib on PyPI: https://pypi.org/project/ealib


Description
===========

An open source Python library for mathematical optimization

Note:

    This project is still in beta stage, so the API is not finalized yet.


Dependencies
============

PyEALib requires Python 3.11 (or newer) and Python packages listed in the `requirements.txt` file.


.. _install:

Installation (development environment)
======================================

Posix (Linux, MacOSX, WSL, ...)
-------------------------------

From the PyEALib source code::

    conda deactivate         # Only if you use Anaconda...
    python3 -m venv env
    source env/bin/activate
    python3 -m pip install --upgrade pip
    python3 -m pip install -r requirements-dev.txt


Windows
-------

From the PyEALib source code::

    conda deactivate         # Only if you use Anaconda...
    python3 -m venv env
    env\Scripts\activate.bat
    python3 -m pip install --upgrade pip
    python3 -m pip install -r requirements-dev.txt


Installation (production environment)
=====================================

::

    pip install ealib


Documentation
=============

* Online documentation: https://jdhp-dev.gitlab.io/ealib
* API documentation: https://jdhp-dev.gitlab.io/ealib/api.html


Build and run the Python Docker image
=====================================

Build the docker image
----------------------

From the PyEALib source code::

    docker build -t ealib:latest .

Run unit tests from the docker container
----------------------------------------

From the PyEALib source code::

    docker run ealib pytest

Run an example from the docker container
----------------------------------------

From the PyEALib source code::

    docker run ealib python3 /app/examples/hello.py


Bug reports
===========

To search for bugs or report them, please use the PyEALib Bug Tracker at:

    https://gitlab.com/jdhp-dev/ealib/issues


License
=======

This project is provided under the terms and conditions of the `MIT License`_.


.. _MIT License: http://opensource.org/licenses/MIT
.. _command prompt: https://en.wikipedia.org/wiki/Cmd.exe
vegetable 1.1.1
Tabular data formatter with column types/formatting options and other features.

Format tabular data in various ways with explicitly defined columns
that can each have their own expected types, formatting and highlighting.

Features
========

-  Specify columns with data types / widths, formatting functions,
   null-value indicators and processing exception indicators.
-  Auto-sizing columns when presented with a full table of data.
-  Ability to format individual rows for output before all data has 
   been gathered.
-  Quick switching of output formats between tabular text, JSON,
   YAML & delimited fields.
-  Value highlighting rules: by ranges, trends, min/max and others.


Quick Start
===========

::

        # pip install vegetable first
        from vegetable import Table

        t = Table()
        t.column("Supplier")
        t.column("Cost", type=float)
        t.row(["Convenience store", 12.99])
        t.row(["Wholesaler", "10.29"])
        t.row(["Internet store", 11.56])
        t.row(["Dodgy pub geezer", 5.00])
        print(t)



Manual Installation From Repo
=============================

::

        $ git clone https://github.com/mousefad/python-vegetable vegetable
        $ cd vegetable
        $ python -m venv .
        $ . bin/activate
        $ pip install --upgrade pip
        $ pip install .
        $ export PYTHONPATH="$PYTHONPATH:$PWD"

To run `examples/network_traffic` you may also need to `pip install click`.


Complete Data Mode
------------------

Values can be added to a `Table()` instace directly row-by-row with `row()`. 
When `__str__()` is invoked, the whole table will be formatted and returned. 
An advantage of this approach is that column widths will be automatically 
re-sized if needed (for columns where `expand=True` was used on column 
creation).

The output format can also be easily switched:

::

        t = Table()
        t.column("Name")
        t.column("Hobby")
        t.row(["'Bob'", "Just having a whale of a time."])
        t.row(["Stang, "Monsterism."])
        print(t, end="\n\n")
        t.formatter = YamlFormat()
        print(t)


Line-by-Line Mode
-----------------

In applications where we want to print data as it is gathered, we can 
get string values for the table headers, separators and rows with 
`header_str()`, `separator_str()` `mast_head()` and `row_str(...)` 
functions:

::

        t = Table()
        t.column("Item Desc")
        t.column("Qty", type=int)
        print(t.mast_head())
        for desc, num in gather_data():
            print(t.row_str([desc, num]))


TODO
====

-  Better unit test coverage
-  Multi-column sorting