semvec/pypi-packages huggingface dataset:
AsyncioMinimalModbus 1.0.0
Async Easy-to-use Modbus RTU and Modbus ASCII implementation for Python
Requires Python: >=3.6

# Asyncio Minimal Modbus

![Build Status](https://github.com/guyradford/asynciominimalmodbus/actions/workflows/pipeline.yml/badge.svg)

Async library wrapping the Easy-to-use Modbus RTU and Modbus ASCII implementation 
[Minimal Modbus](https://pypi.org/project/minimalmodbus/).

This library is purely an asyncio wrapper for Minimal Modbus, it supports the same interface, and should be 100% 
drop in other than needing to add `await`.

Supports and Tested on Python 3.6, 3.7, 3.8. 3.9 and 3.10.

## Installation

```shell
pip install AsyncioMinimalModbus
```

### Dependencies
* Minimal Modbus v2.0.1 or greater, 
* pySerial 3.0 or greater.


## Features as described by Minimal Modbus
>MinimalModbus is an easy-to-use Python module for talking to instruments (slaves)
>from a computer (master) using the Modbus protocol, and is intended to be running on th*e mast*er.
>The only dependence is the pySerial module (also pure Python).
>
>There are convenience functions to handle floats, strings and long integers
>(in different byte orders).
?
>This software supports the 'Modbus RTU' and 'Modbus ASCII' serial communication
>versions of the protocol, and is intended for use on Linux, OS X and Windows platforms.

Minimal Modbus Documentation: [https://minimalmodbus.readthedocs.io/en/stable/](https://minimalmodbus.readthedocs.io/en/stable/)


## Contributing

* Issues: [https://github.com/guyradford/asynciominimalmodbus/issues](https://github.com/guyradford/asynciominimalmodbus/issues)
* GitHub: [https://github.com/guyradford/asynciominimalmodbus](https://github.com/guyradford/asynciominimalmodbus)
latexexpr 0.4.1
Module for easy LaTeX typesetting of algebraic expressions in symbolic form with automatic substitution and result computation.
Requires Python: >=3.6

# LaTeX Expression

The *LaTex Expression* is a python module for easy LaTeX typesetting of algebraic
expressions in symbolic form with automatic substitution and result computation.

It was originally written by [Jan Stransky](https://mech.fsv.cvut.cz/~stransky)
from Czech Technical University, Faculty of Civil Engineering, Department of
Structural Mechanics, but the latest update was done in 2015.

## Usage
Install using pip
```
pip install latexexpr
```

Enjoy
```
import latexexpr
v1 = latexexpr.Variable('H_{ello}',3.25,'m')
print(f'$$ {v1} $$')
v2 = latexexpr.Variable('W^{orld}',5.63,'m')
print(f'$$ {v2} $$')
e1 = latexexpr.Expression('E_{xample}',v1+v2,'m')
print(f'$$ {e1} $$')
```

## Links
* [Documentation](https://kajusk.github.io/latexexpr/)
* [Original webpage](https://mech.fsv.cvut.cz/~stransky/en/software/latexexpr/)
* [Original documentation](https://mech.fsv.cvut.cz/~stransky/software/latexexpr/doc/index.html)


## License
The project is released under [LGPL v3](https://www.gnu.org/licenses/lgpl-3.0.en.html)

# Changelog

# Version 0.4
Released 2022-05-31

* Project adopted by Jakub Kaderka
* Ported to python3
* Formated to match PEP-8
* Updated project structure and published to PyPI

# Version 0.3
Released 2015-03-03 by Jan Stransky

* Added Sympy extension
* Improved documentation

# Version 0.2
Released 2014-03-25 by Jan Stransky

* Added basic support of symbolic variables
* Python classes changed to 'new style'
* Improved documentation
* Improved examples

# Version 0.1
Released 2013-10-29 by Jan Stransky

* Initial release
kard-private-api 2.1
Control and Automate your Kard account
Requires Python: >=3.6

# Kard Private Api
[![License: GPL v3](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](http://www.gnu.org/licenses/gpl-3.0)
![](https://komarev.com/ghpvc/?username=ghrlt-kard-private-api&color=brightgreen&label=Repository%20views)  

Python wrapper of Kard neobank private API

Made with the help [HTTP Toolkit](https://httptoolkit.tech/) for trafic sniffing <3 It's an awesome tool!


## Installation
`pip install kard-private-api`

Either create a file named `secrets.json` in your working directory, with the following content:
```json
{
	"vendorIdentifier": null,
	"userAgent": "ghrlt/kard-private-api /v2.1",
	"accessToken": null,
	"refreshToken": null,
	"accountPin": "Your pin (0000)",
	"accountTel": "Your phone number (06 00 00 00 00)"
}
```
or don't, and input them in your console when asked.


## Usage
```python
import kard_private_api as kardapi

k = kardapi.Kard()
k.init()

...

```

**You are ready!**<br>
Start with some examples [here](https://github.com/ghrlt/kard-private-api/tree/master/examples)


## FAQ
#### How does it login to my Kard account?

The login processus include:
	- Generating a unique identifier, linked to your account
	- If new uid, confirm sms otp, else pass
	- Confirm PIN code
Then, and only then, we have the `accessToken` and `refreshToken`, which is your account sesame.

The wrapper will automatically create and store your uid and obtain and store your tokens, in the current working directory


## License

This repository and all of its content is under the [GNU GPLv3](https://github.com/ghrlt/kard-private-api/blob/master/LICENSE) license.


## Disclaimer
I shall not, and will not be liable for any misuse or unauthorised use, leading or not to damage to any third-party.
This API is to be used for educational purposes only.


## Support me
<a href="https://s.kard.eu/ghrlt/5.0"><img alt="Support me through bank card" src="https://www.svgrepo.com/show/301678/piggybank-pig.svg" href="https://s.kard.eu/ghrlt/5.0" width="40" height="40"></a>
<a href="https://discord.gg/cQY9hc7XHm"><img alt="Send me a Discord Nitro" src="https://discord.com/assets/f8389ca1a741a115313bede9ac02e2c0.svg" href="https://discord.gg/cQY9hc7XHm" width="40" height="40"></a>
<a href="https://kard.eu?r=GAEHER"><img alt="Subscribe to Kard" src="https://uploads-ssl.webflow.com/5fc53498e2555190106eb531/5fc5a6996e50deb8447505e4_logo-purple.svg" href="https://kard.eu?r=GAEHER" width="40" height="40"></a>
neuralintentsplus 0.0.4
Simple interface for working with intents and chatbots. A built upon version of Neuralnines package.
Keywords: python,neural,machine learning,chatbots,chat,artificial intelligence,virtual assistant


# neuralintents

Still in a buggy alpha state.

## Setting Up A Basic Assistant

```python

from neuralintents import GenericAssistant

assistant = GenericAssistant('intents.json', model_name="test_model")
assistant.train_model()
assistant.save_model()

done = False

while not done:
    message = input("Enter a message: ")
    if message == "STOP":
        done = True
    else:
        assistant.request(message)
```

## Binding Functions To Requests

```python
from neuralintents import GenericAssistant

def function_for_greetings():
    print("You triggered the greetings intent!")
    # Some action you want to take

def function_for_stocks():
    print("You triggered the stocks intent!")
    # Some action you want to take

mappings = {'greeting' : function_for_greetings, 'stocks' : function_for_stocks}

assistant = GenericAssistant('intents.json', intent_methods=mappings ,model_name="test_model")
assistant.train_model()
assistant.save_model()

done = False

while not done:
    message = input("Enter a message: ")
    if message == "STOP":
        done = True
    else:
        assistant.request(message)
```
## Sample intents.json File
```json
{"intents": [
  {"tag": "greeting",
    "patterns": ["Hi", "How are you", "Is anyone there?", "Hello", "Good day", "Whats up", "Hey", "greetings"],
    "responses": ["Hello!", "Good to see you again!", "Hi there, how can I help?"],
    "context_set": ""
  },
  {"tag": "goodbye",
    "patterns": ["cya", "See you later", "Goodbye", "I am Leaving", "Have a Good day", "bye", "cao", "see ya"],
    "responses": ["Sad to see you go :(", "Talk to you later", "Goodbye!"],
    "context_set": ""
  },
  {"tag": "stocks",
    "patterns": ["what stocks do I own?", "how are my shares?", "what companies am I investing in?", "what am I doing in the markets?"],
    "responses": ["You own the following shares: ABBV, AAPL, FB, NVDA and an ETF of the S&P 500 Index!"],
    "context_set": ""
  }
]
}
```