semvec/pypi-packages huggingface dataset:
Rockefeller 1.2.4
Money, currencies and exchange rates library.
License: MIT
Keywords: money currency exchange rates

Rockefeller: Money made easy.
=============================

Library for dealing with money and currency conversion in Python. It provides tools for storing currencies and exchange rates, converting from one currency to another and fetching exchange rates from different services.

Features
--------

- Money manipulation.
- Money currencies conversion.
- Currency manipulation.
- Currency storage.
- Exchange Rate manipulation.
- Exchange rate fetching and storage.

Installation
------------

To install rockefeller, simply:

.. code-block:: bash

    $ pip install rockefeller

Or, directly from the main repository:

.. code-block:: bash

    $ pip install -e git+http://github.com/anler/Rockefeller.git#egg=Rockefeller

See `project's website`_ for more information.

.. _project's website: http://anler.github.io/Rockefeller
.. :changelog:

History
-------

1.2.2 (Wed 27 Nov 2013 06:30:49 PM CET)
+++++++++++++++++++++++++++++++++++++++

- Fixing repo url in setup.py

1.2.1 (Wed 27 Nov 2013 06:13:27 PM CET)
+++++++++++++++++++++++++++++++++++++++

- Updating README to point to new repo url

1.2.0 (Sun 20 Oct 2013 01:01:25 AM CEST)
++++++++++++++++++++++++++++++++++++++++

- Python 3.3 compatibility
- Continuous integration with Tox
- Money object support for divmod built-in function
- New money property: rounded_amount and rockefeller.round_amount function

1.1.0 (Fri Apr 12 16:26:02 CEST 2013)
+++++++++++++++++++++++++++++++++++++

- Raising a ``ExchangeError`` exception if converting money from one currency to another fails. Before was just returning ``None``

1.0.0 (Fri Mar 30 03:19:23 CEST 2013)
+++++++++++++++++++++++++++++++++++++

- First version!
pytest-stepwise 0.4
Run a test suite one failing test at a time.
License: MIT

Introduction
============

pytest-stepwise is a plugin for `pytest <http://pytest.org/>`_ that run
all tests until a test fails, and then continue next test run from where
the last run failed. You may think of it as a combination of the  ``-x``
option, which exits the test run after a failing test, and the ``--lf``
option from pytest-cache, which only runs failing tests.

pytest-stepwise depends on pytest-cache, which will be installed as a
dependency.


How to use it?
==============

0. Install the plugin - ``pip install pytest-stepwise``.
1. Run ``py.test --stepwise`` (you can also use the alias ``--sw``).
2. Watch the test fail and fix it.
3. Run ``py.test --stepwise`` again. The test suite will continue to run
   right from where it was.

Use the ``--skip`` option to ignore one failing test and stop the
test execution on the second failing test instead. This is useful if you
get stuck on a failing test and just want to ignore it until later.


When is this useful?
====================

pytest-stepwise was written for use when a large part of the test suite
is failing. In this case, pytest-stepwise allows you to focus on fixing
one test at the time instead of being overwhelmed by all failing
tests. It should however be noted that all tests need to be re-run after
to make sure that any changes made when fixing one test has not broken
some other test.

Please submit an issue if you have any suggestions regarding use cases
of pytest-stepwise.


Compatibility
=============

pytest-stepwise is compatible with pytest 2.2 -> 2.8.
For pytest 2.7 and earlier, ``pytest-cache`` is required as a dependency.


Changelog
=========

* 0.1 - Initial version.
* 0.2 - Clear cache after test run when the plugin is not active.
  Added  ``--skip`` option.
* 0.3 - Fixed issue when failing tests are removed.
  Fixed compatibility with ``--pdb`` option.
  Stop on errors as well as on test failures.
* 0.4 - Refactoring, pytest 2.8 compatiblity. Stop test execution on
  collection errors.
dbTable 0.0.4
A library to provide Table data constructs over SQLite Databases
License: MIT
Keywords: datascience data science numpy database sqlite table column

dbTable
^^^^^^^

dbTable is a innovative library built on the Python SQLite Library that
allows you to manipulate views on tables in Databases, select data from
them, and modify them in many ways. This library abstracts out all SQL
queries with native Python syntax, and has built-in lazy computation as
well. Furthermore, this library provides an interface to load tables
from SQLite into in-memory table structures like Pandas DataFrames or
Numpy Array for further analysis.

Check out the full documentation at `DOCUMENTATION`_

Quickstart Guide:

1) Installation

Make sure you have numpy and tabulate installed

::

    pip install numpy
    pip install tabulate

Install dbTable through PyPI (This’ll automatically install numpy and
tabulate)

::

    pip install dbTable

You can also install the built distribution in the dist/ folder, or for
portable cases, just download the dbTable.py file, and place it in your
project folder

2) Load dbTable into your interpreter/project

.. code:: python

    import dbTable

3) Make a connection to a database

.. code:: python

    db = Database('test.db') # Replace with your database or use ":memory:" to load an in-memory database

4) Select a table:

.. code:: python

    table1 = db['table1'] 

5) Exporting / Importing

To convert a dbTable to any other form, use:

.. code:: python

    new_df = db['table1'].to_df() # Returns a Pandas DataFrame Object
    new_table = db['table1'].to_table() # Returns a UCB Datascience Table 
    new_ndarray = db['table1'].to_numpy_array() # Returns a Numpy Array

To save a DataFrame, UCB Table, or Numpy Array, use:

.. code:: python

    db.store_table(new_df,'newtablename')

Here’s a sampling of modifications and filters you can do with dbTable

.. code:: python

    table2 = table1.select(['col1','col2']) # Selecting columns from database
    table3 = table2.where(table2['col1']> 20) # Filters
    table4 = table3.sort('col2',descending=False) # Sort data
    grouped_table = table4.group(table4['col1'])
    table4['col2'] = table4['col1']*10 # Modify columns
    table4['col3'] = table4['col1']+table4['col2']
    table4['col3'] *= 2

Have fun!

Check out the full documentation at `DOCUMENTATION`_

.. _DOCUMENTATION: http://dibya.xyz/dbTable/documentation.html
vcab 1.0.0
Bridge tool to connect VCP and absinthe
License: MIT

vcp + absinthe:

Bridge tool to connect `VCP <https://github.com/voidpp/vcp>`_ and `absinthe <https://github.com/voidpp/absinthe>`_

Provides an interface to search files in VCP's projects determined folders and opens with `absinthe-client <https://github.com/voidpp/absinthe-client>`_.