semvec/pypi-packages huggingface dataset:
IPlantUML 0.1.1
Package which adds a PlantUML cell magic to IPython.
License: MIT
Keywords: jupyter

.. image:: https://travis-ci.org/jbn/IPlantUML.svg?branch=master
    :target: https://travis-ci.org/jbn/IPlantUML

What is it?
===========

This Python package defines a `PlantUML <http://plantuml.com/>`__ cell
magic for IPython. It lets you generate UML diagrams as inline SVG in
your notebook. I'll add embellishments as needed. But, for now, I just
needed something that worked and existed as a package (in pypi).

I based my code on `Steven Burke <https://github.com/sberke>`__'s
`plantuml
gist <http://chickenbit.com/blog/2014/10/inline-plantuml-diagrams-in-ipython-notebook/>`__.

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

First, install IPlantuml with pip.

.. code:: sh

    pip install iplantuml

Then, install plantuml. On Debian based system you can install plantuml
package. Otherwise you can download ``plantuml.jar`` and copy it to
``/usr/local/bin/plantuml.jar``.

.. code:: sh

    sudo apt install plantuml

Alternatively you can set a custom path for plantuml.jar during
installation

.. code:: sh

    git clone https://github.com/jbn/IPlantUML.git
    cd IPlantUML
    python setup.py install iplantuml --jarpath /my/custom/path/plantuml.jar

Usage
-----

In Ipython, first,

.. code:: python

    import iplantuml

then, create a cell like,

::

    %%plantuml

    @startuml
    Alice -> Bob: Authentication Request
    Bob --> Alice: Authentication Response
    @enduml

The output will be the generated SVG UML diagram.

By default, the magic removes the intermediate (``tmp.uml``) and target
(``tmp.svg``) files. However, if you enter a name in the ``%%plantuml``
line, it retains both files of ``$name.uml`` and ``$name.svg``. For
example,

::

    %%plantuml auth

    @startuml
    Alice -> Bob: Authentication Request
    Bob --> Alice: Authentication Response
    @enduml

generates and retains ``auth.uml`` and ``auth.svg``.
CIUnitTest 1.0.9
Provides test results of unittest in JSON format, in order to be able to use the results programmatically.
License: MIT
Keywords: unittest ci continuous-integration json

CI Unit Test
============

CI Unit Test is a library which enables to retrieve the results of unit tests in JSON format. This may be used in custom Continuous Integration systems which need to process the results of unit tests.

The results can be saved as is to a NoSQL database, or can be returned as a Python object in order to be combined with other information before being saved.

Usage
-----

The results in JSON format can be obtained by using `JsonTestRunner`:

.. code:: python

    suite = unittest.TestLoader().loadTestsFromTestCase(TestsDemo)
    json = ciunittest.JsonTestRunner().run(suite, formatted=True)
    print(json)

Since the first line uses unittest, all unittest features are available, such as the auto-discovery of unit tests in a project directory:

.. code:: python

    suite = unittest.TestLoader().discover(targetPath)

To obtain the results as a Python object, use `ObjectTestRunner`:

.. code:: python

    suite = unittest.TestLoader().loadTestsFromTestCase(TestsDemo)
    result = ciunittest.ObjectTestRunner().run(suite)
    print('Done %d tests in %d ms.' %
          (len(result['results']), result['spentMilliseconds']))

To perform an action at the beginning of every test (independently of the runner being used,) do:

.. code:: python

    suite = unittest.TestLoader().loadTestsFromTestCase(TestsDemo)
    runner = ciunittest.JsonTestRunner()
    runner.on_start = lambda test: print(".", end="", flush=True)
    result = runner.run(suite)
    ...

In the previous code sample, every time the runner is ready to start a new test, a dot is displayed in the terminal.

Similarly, one can execute arbitrary code at the end of every test. The test result, that is `ciunittest.Success`, `ciunittest.Error` or `ciunittest.Failure`, will be passed as a second parameter to the function.

.. code:: python

    runner.on_end = lambda test, result: print(result, flush=True)

The code is inspired by http://pythonhosted.org/gchecky/unittest-pysrc.html

If you have any question or remark, please contact me at arseni.mourzenko@pelicandd.com. Critics are also welcome, since I have used Python for only a few days, and probably get lots of things wrong.
frequently 0.3
Quickly run scripts from other directories or open frequently visited websites
License: MIT

# frequently
## Small tool to make your life easier in the terminal

### - Open websites that you frequently visit

### - Run scripts or executables without having to constantly change directories

### - Specify what executables, commands you want to run or websites you want to open whenever you start the script

##Installation
```bash
$ git clone https://github.com/jordan-patterson/frequently.git
$ sudo pip3 install requirements.txt
$ ./install.py
```


## Usage
```bash
$ freq -a #run all scripts,commands and websites that you specify 
$ freq -w #open all specified websites on start
$ freq -e #run all specified scripts on start
$ freq -c #run all specified commands on start
$ freq #does not perform any action
```