semvec/pypi-packages huggingface dataset:
qsys 0.0.4
Python QSYS QRC Wrapper

# Python QSYS QRC Wrapper
* Control QSC QSYS Core devices with python

# ToDo
* Flaskify... 
* Document, document, document

# Use
* For each QSC Core on the network instantiate a "Core" class
* When adding control objects they will "cast" themselves to the parent core class
    * The parent Core class instance is required as keyword arg "parent" when creating control objects
```python
#!/usr/bin/python3
import time
from qsys.classes import Core,Control,ChangeGroup

#returns epoch time
from qsys.helpers import epoch

def main():
    #See qsys.py for parameters in Core class
    #The initiail EngineStatus response parameters from the device will get added to Core.__dict__
    #You can pass "port" as well, but it defaults to 1710
    myCore = Core(Name='myCore',User='',Password='',ip='192.168.61.2')

    #Open the socket,creates "listen" and "keepalive" threads
    myCore.start()

    #ValueType can be a list of potential value types [int,float] or a single type "str" etc
    #This object is assumed to be a "gain" control object, so we can pass [int,float]
    gainControlObject = Control(parent=myCore,Name='namedControlInQsysDesigner',ValueType=[int,float])

    #To constantly monitor the state of your object use a ChangeGroup
    #You need to a ChangeGroup instance to add control objects and set polling rates
    #Parameters that are capitalize are that way because of the QRC parameter protocol
    #Id in this case is just the name of the ChangeGroup
    myChangeGroup = ChangeGroup(parent=myCore,Id='myChangeGroup')
    myChangeGroup.AddControl(gainControlObject)

    #Allow the socket time to connect and parse the initial responses
    time.sleep(2)

    #Set the change group auto poll rate
    #This rate is fast, your mileage may vary
    myChangeGroup.AutoPoll(Rate=0.1)

    #Value = value to set object to
    #TransId = QRC id parameter for transaction ID
    gainControlObject.set(Value=10,TransId=epoch())

    while True:
        print(gainControlObject.state)
        time.sleep(1)

if __name__ == '__main__':
    main()
```

# Notes
* In development, versions will change rapidly. This version doesn't do much yet.. stand by

# References
* https://q-syshelp.qsc.com/Content/External_Control/Q-Sys_Remote_Control/QRC.htm
apriori-python 1.0.4
A simple apriori algorithm python implementation
Requires Python: >=3.6

# Apriori Algorithm Python Implementation

<p align=center>
    <a target="_blank" href="https://travis-ci.com/chonyy/apriori_python" title="Build Status"><img src="https://travis-ci.com/chonyy/apriori_python.svg?branch=master"></a>
    <a target="_blank" href="#" title="pip"><img src="https://img.shields.io/pypi/v/apriori_python?color=brightgreen"></a>
    <a target="_blank" href="#" title="language count"><img src="https://img.shields.io/github/languages/count/chonyy/apriori_python"></a>
    <a target="_blank" href="#" title="top language"><img src="https://img.shields.io/github/languages/top/chonyy/apriori_python?color=orange"></a>
    <a target="_blank" href="https://opensource.org/licenses/MIT" title="License: MIT"><img src="https://img.shields.io/badge/License-MIT-blue.svg"></a>
    <a target="_blank" href="#" title="repo size"><img src="https://img.shields.io/github/repo-size/chonyy/apriori_python"></a>
    <a target="_blank" href="http://makeapullrequest.com" title="PRs Welcome"><img src="https://img.shields.io/badge/PRs-welcome-brightgreen.svg"></a>
</p>

## How to use

### Install the Pypi package using pip

```
pip install apriori_python
```

Then use it like 

```python
from apriori_python import apriori
itemSetList = [['eggs', 'bacon', 'soup'],
                ['eggs', 'bacon', 'apple'],
                ['soup', 'bacon', 'banana']]
freqItemSet, rules = apriori(itemSetList, minSup=0.5, minConf=0.5)
print(rules)  
# [[{'beer'}, {'rice'}, 0.6666666666666666], [{'rice'}, {'beer'}, 1.0]]
# rules[0] --> rules[1], confidence = rules[2]
```

### Clone the repo

To run the program with dataset provided and default values for *minSupport* = 0.5 and *minConfidence* = 0.5

```
python apriori.py -f dataset.csv
```

To run program with dataset and min support and min confidence  

```
python apriori.py -f dataset.csv -s 0.17 -c 0.68
```