semvec/pypi-packages huggingface dataset:
pyclilib-tatsukenji 0.2.0
Build CLI Tools with ease
Requires Python: >=3.6

# pyclilib
Python Library to create CLI tools using Subject-Verb-Object pattern
```
my-cmd [my-namespace] my-action my-resource [pos_args] [--options]
```

# Quickstart 1: CLI without Namespaces
1. `pip install pyclilib`
2. Create a hello world CLI
```python
import clilib

@clilib.decorator.resource
class MyResource():
    @clilib.decorator.get
    def get(self):
        print "Hello world"

clilib.run("mycli")
```
3. Run your program
```
$ python example.py get my-resource
Hello world
```

# Quickstart 1: CLI with Namespaces
1. `pip install clilib`
2. Create the runner, `example.py`
```python
import clilib

clilib.init("mycli")
clilib.run("mycli")
```
3. Namespaces are sub-packages of an expected local `namespace` package
```
$ mkdir -p namespace namespace/my-namespace
$ touch namespace/__init__.py namespace/my-namespace/__init__.py
```
```python
# namespace/my-namespace/__init__.py
import clilib

@clilib.decorator.resource
class MyResource():
    @clilib.decorator.verb
    def get(self):
        print("Hello World")
```
4. Run your program
```
$ python example.py my-namespace get my-resource
Hello World
```

# Notes
- You can either have `cli namespace action resource` **OR** `cli action resource` in the future

# Roadmap
- [ ] Global Config -- [Potential](https://docs.python.org/3.2/library/argparse.html#the-namespace-object)
- [ ] Namespace
- [ ] Conditional Args
- [ ] CLI without resource ex. `git init`

# Testing
- flake8
- pytest
- pylogrus

# TODO
- How to make log level configurable?
Since decorators run during "compile"(?) time, setting the level through `clilib.run("foo", logging.DEBUG)` will set the level after the decorators do their thing.
Same story with `clilib._log_level = logging.DEBUG`
pygtk-form 0.0.3
Create forms very easily for your scripts with GTK !
Requires Python: >=3.6

# PYGTK FORM

Create forms very easily for your scripts with GTK !
Just call a function, with the data you want to recover, and a callback!

![pygtk_form examples](https://github.com/cestoliv/pygtk_form/blob/main/images/presentation.png)

Install the module with:

	pip install pygtk_form
	
## Read the documentation please!
In addition, it takes time to write ...
[The documentation in question](https://cestoliv.github.io/pygtk_form/)

## Example
![pygtk_form examples](https://raw.githubusercontent.com/cestoliv/pygtk_form/main/images/cool_form.png)

And here is the (very simple code) !

	import pygtk_form

	def say_hello(data):
		if data:
			print("Hello " + data["pseudo"] + ", I know you are using " + data["distribution"] + "!")
		else:
			print("Ho no ... You canceled ...")

	pygtk_form.spawn_form({
		"title": "Cool form",
		"default_size": [400, 300],
		"theme": "windows_light",
		"resizable": True,
		"fields": [
			{
				"id": "pseudo",
				"type": "text",
				"text": "",
				"label": "Your username",
				"max_length": 255
			},
			{
				"id": "distribution",
				"type": "combobox",
				"label": "What distribution do you use ?",
				"default": "manjaro",
				"items": [
					{"id": "fedora", "name": "Fedora"},
					{"id": "ubuntu", "name": "Ubuntu"},
					{"id": "debian", "name": "Debian"},
					{"id": "manjaro", "name": "Manjaro"},
					{"id": "arch", "name": "Arch (BTW)"}
				]
			}
		]
	}, say_hello)
recast-workflow 1.0.2
tool for creating Yadage workflows for RECAST
Requires Python: >=3.6

Recast Workflow
===============

Recast_workflow is a tool for creating new computation workflow for
running physics analyses. The generated workflows are interpreted by the
`Yadage engine`_ and are stored as .yml files. The package comes with a
command line interface as well as a python library.

Read the documentation `here`_.

This was developed as part of IRIS-HEP fellowship. The full proposal can
be viewed `here <https://iris-hep.org/fellows/vovechkin.html>`__.

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

You can use pip to install recast-workflow:

::

   pip install recast-workflow

Recast-workflow was not developed for Windows file systems, so Windows
users are reccomended to work inside a docker image:

::

   docker pull recast/workflow

Development Notes
-----------------

To install and run all tests:

::

   git clone url
   cd recast_workflow
   python3 -m venv ./venv
   source venv/bin/activate
   source dev_setup.sh
   pip install -e .[test]
   pytest

.. _Yadage engine: https://github.com/yadage/yadage
.. _here: https://recast-wf.readthedocs.io/en/latest/