semvec/pypi-packages huggingface dataset:
py_ev 0.0.10
Poker hand evaluator written and tested in Python
Keywords: poker

Lightweight poker library
=========================

py_ev is about to be a light-weight poker open-source library written
and tested in Python to help all programmers around the world build
their poker connected applications.

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

.. code:: python

   pip install py_ev

Requirements
------------

-  ``Python 3.x``

Current functionalities
-----------------------

.. code:: python

   from py_ev import Evaluator

   ev = Evaluator()

-  Evaluator

   -  evaluate()

   .. code:: python

      print(ev.evaluate([(3, 3), (3, 2)], [(2, 2), (11, 3), (3, 4), (10, 2), (7, 3)]))
      # prints 4000420

   -  equity()

   .. code:: python

      print(ev.equity(100000, [(2, 3), (3, 2)], [(3, 3), (4, 2)]))
      # 100000 hands evaluated
      # prints (20.28, 30.8, 48.93)
      # Function returns a tuple: (cards_1_won, cards_2_won, draw)

Future development
------------------

Those are just examples of possible directions. Concrete decisions will
be made when some contributors join the project.

1. Adding the most popular poker variants: PLO, 6plus.
2. Hand history and tournaments summaries parsers.
3. Data extraction from poker operators (hhs-mining, traffic-mining,
   etc).
4. Sitting scripts.

Feel free to open a feature request.

How to join this project?
-------------------------

1. It’s as easy as clicking a “star” icon on the top. It really helps!
2. We are looking for contributors. If you feel like joining the ranks,
   read `THIS`_ article.

Every help is appreciated. No matter what your programming skills are.
You can: - improve README - write new testcases - document code with
Docstrings - **and of course write a new feature!**

Feel free to contact me privately on jkbielan@gmail.com

.. _THIS: https://gist.github.com/MarcDiethelm/7303312

.. |License: MIT| image:: https://img.shields.io/badge/License-MIT-yellow.svg
.. |Build Status| image:: https://travis-ci.org/JBielan/py_ev.svg?branch=master
   :target: https://travis-ci.org/JBielan/py_ev
.. |codecov| image:: https://codecov.io/gh/JBielan/py_ev/branch/master/graph/badge.svg
   :target: https://codecov.io/gh/JBielan/py_ev
PW-explorer 0.0.25
An Extensible Possible World Explorer for Answer Set Programming

# An Extensible Possible Worlds Explorer for Answer Set Programming

### To get started (using Conda) -- recommended

1. ```conda create -n your-pwe-env-name```
2. Activate the environment created above using 

    ```conda activate your-pwe-env-name``` or ```source activate your-pwe-env-name```  (depending on the version of conda).
3. Install DLV from [here](http://www.dlvsystem.com/dlv/#1) and ensure it is available in the path.
4. ```conda install -c potassco clingo ```
5. ```conda install -c anaconda graphviz```
6. ```conda install -c anaconda pygraphviz```
7. ```pip install PW_explorer```

(To use PWE in Jupyter Notebooks, install Jupyter)

8. ```conda install -c anaconda jupyter```
9. Install [PWE-NB-Extension](https://github.com/idaks/PWE-NB-Extension) to activate Notebook-specific functionality like in-line editing, etc. using:

    ```pip install PWE_NB_Extension```

   Load the extension in the notebook using ```%load_ext PWE_NB_Extension```

### Alternatively, to get started (using venv):

1. Install clingo. PW_explorer has been tested with clingo version: 5.2.1

2. Install DLV.

3. Make sure the packages graphviz>=0.8.2 and pygraphviz>=1.5 are installed. These are required to be able to use the visualization functionality. You can find instructions to install pygraphviz [here](http://pygraphviz.github.io/documentation/pygraphviz-1.3.1/install.html).

These commands usually work as well:

  a.  ```apt-get install python-dev graphviz libgraphviz-dev pkg-config``` OR ```brew install graphviz``` 

  b.  ```pip3 install pygraphviz```

  (Might need to run them using sudo)

  [StackOverflow Reference](https://stackoverflow.com/questions/40528048/pip-install-pygraphviz-no-package-libcgraph-found)

4. ```python3 -m venv /path/to/new/virtual/environment```

5. ```source /path/to/new/virtual/environment/bin/activate```

6. ```python3 -m pip install PW_explorer```

To deactivate the virtualenv after you're done working:

7. ```deactivate```

Repeat Step 5 to resume work and Step 7 to exit the virtualenv again.


#### Launch a ASP+PWE friendly computing environment on Binder

[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/idaks/PW-explorer/master)

### General System Architecture:

![PWE-UML-Diagram](https://user-images.githubusercontent.com/14302941/54492765-54b63680-4897-11e9-933b-3efc34eb7106.png)


#### PWE Demos available [here](https://github.com/idaks/PWE-demos)
loadtest 0.0.2
Load testing tool
Keywords: loadtest

# loadtest

Load tester and benchmark tool for Python programmers.

## Installation:
```bash
pip install loadtest
```
## Basic usage

```python
def request_func():
    import requests
    response = requests.get("https://jsonplaceholder.typicode.com/todos/1")

    if response.status_code != 200:
        print(response.status_code)
    else:
        sample = {
          "userId": 1,
          "id": 1,
          "title": "delectus aut autem",
          "completed": False
        }
        if response.json() != sample:
            print(response.json())
    return response

from loadtest import LoadTester
load_tester = LoadTester(n_jobs=10, worker=request_func, count=100)
load_tester.start()
```
TraceManager 0.0.1
The code architecture allows a simple method to be monitored with python.

# azmisahin-software-web-component-trace-manager-python
The code architecture allows a simple method to be monitored with python.

# Test
```shell
python -m unittest tests/test_unittest.py
```

# Paket

Setuptools whell araÃ§larÄ± gÃ¼ncelleniyor.
```shell
python -m pip install --user --upgrade setuptools wheel
```
steppygraph 0.1.10
A Python DSL for AWS Step Functions

# Steppy Graph - An alpha-quality DSL for Step Functions

Example Usage:
```
s = StateMachine()
    res = Resource(name="foores", type=ResourceType.LAMBDA)
    s.next(Task(resource=res, name="Kermit", comment='Foo'))
    s.next(Wait(name="Waiting time", comment='Foo', seconds=2))
    s.next(Pass(name="Pass the buck"))
    s.next(Task(resource=res, name="Miss Piggy", comment='Foo'))
    s.build()

    print(s.to_json())
```
should produce output similar to:
```
{
    "StartAt": "Kermit",
    "States": {
        "Kermit": {
            "Comment": "Foo",
            "End": false,
            "Next": "Waiting time",
            "Resource": "arn:aws:lambda:::function:foores",
            "TimeoutSeconds": 600,
            "Type": "Task"
        },
        "Miss Piggy": {
            "Comment": "Foo",
            "End": true,
            "Resource": "arn:aws:lambda:::function:foores",
            "TimeoutSeconds": 600,
            "Type": "Task"
        },
        "Pass the buck": {
            "Comment": "",
            "End": false,
            "Next": "Miss Piggy",
            "Type": "Pass"
        },
        "Waiting time": {
            "Comment": "Foo",
            "End": false,
            "Next": "Pass the buck",
            "Seconds": 2,
            "Type": "Wait"
        }
    },
    "TimeoutSeconds": 600
}
```

Note - states added via the next() method in StateMachine are always "autoconnected", that is they have a boolean
flag set which will automatically wire them up to the next state in the graph. Use add_state for states that you want to
add without any auto-connection of the Next attribute.