semvec/pypi-packages huggingface dataset:
pymindergas 0.1.12
A python module to post meter readings to Mindergas

# pymindergas

A module to post meter readings to [MinderGas.nl][mindergas].

## Installation

```shell
$ pip3 install pymindergas
```

## Usage

In order to be able to post readings, you first need to obtain an [API][api] token.

The `postReading()` method requires an authentication token (String) and the meter reading (Float). The reading date can be any valid date (String), but is optional.

Parameter | Required | Description
--- | --- | ---
token | yes | String
reading | yes | Float
date | no | Any date string that can be [parsed][parse]. If not passed, uses today.

Code sample:

```python
from datetime import date
from datetime import timedelta
from pymindergas import Mindergas

token = "supersecretstring"
reading = 1234.567
yesterday = date.today() - timedelta(days = 1)

# Post reading as yesterday's
success = Mindergas().postReading(token, reading, yesterday.strftime('%y-%m-%d'))
print(success)

# Post reading as today's
success = Mindergas().postReading(token, reading)
print(success)
```

## Disclaimer

This is an open source project and does not have any affiliation with [MinderGas.nl][mindergas].

All product names, trademarks and registered trademarks in this repository are property of their respective owners. All images in this repository are used by the project for identification purposes only.

[mindergas]: https://www.mindergas.nl/
[api]: https://www.mindergas.nl/member/api
[parse]: https://dateutil.readthedocs.io/en/stable/parser.html#dateutil.parser.parse
kama-prom-plugin 0.0.5
Prometheus plugin for KAMA
Requires Python: >=3.9

# Todo

## Testing

For the tests to run, a Prometheus installation **must**
be running in your cluster with:
- namespace = `monitoring`
- main service = `monitoring-prometheus-server`. 

Use the 
**[Community Prometheus Helm Chart](https://artifacthub.io/packages/helm/prometheus-community/prometheus)**
to do this the easy way.  

In the future, these fields will be configurable via environment variables.
pytu 0.1.5
My personal Python Tuuls :-)
Requires Python: >=3.7,<4.0

# PyTu
My personal Python Tuuls :-) 

## Install & init
```
> pip install pytu
```

```py
from pytu.tools import Tools  # general python tools
from pytu.matt import Matt    # GUI autoMATion tool based on PyAutoGUI
```

## Logging
```py
Tools.log('Hello world')  # prints "[2022-02-07 16:31:14] Hello world"

Tools.log_path = "log/{year}-{month}-{day}_{hour}.log"  # from now log messages are also saved in text file
```

## Type conversions
```py
Tools.str(datetime.now())                      # "2022-02-07 16:31:14"
Tools.str("5.1234000")                         # "5.1234"
Tools.str(ValueError('something went wrong'))  # "ValueError: something went wrong"

Tools.datetime('7.2.2022')    # datetime(2022, 2, 7)
Tools.datetime('2/7/2022')    # datetime(2022, 2, 7)
Tools.datetime('2022-07-02')  # datetime(2022, 2, 7)
```

## Automation 
```py
# Init
matt = Matt(
	cache_file = 'temp/cache/matt.json',
	logger = Tools,
)
matt.set_ui({                     # recommended, but not mandatory
	'btn_ok' => 'ui/btn_ok.png',
	'btn_home' => 'ui/btn_home.png',
	'msg_ok' => 'ui/msg_ok.png',
	'msg_error' => 'ui/msg_error.png',
	'homescreen' => 'ui/homescreen.png',
})

# Automate
matt.click('btn_ok')

found = matt.which(['msg_ok', 'msg_error'])  # waits for one of the messages to show up
if found == 'msg_error':
	print('Error message found')
elif found == 'msg_ok':
	matt.click('btn_home')
	matt.wait('homepage')
```
drawitor 0.1.1
Draw Images or GIFs in your terminal.
Requires Python: >=3.10,<4.0
Keywords: commands,utilities,cli

## Drawitor

Draw Images/GIFs in your terminal.

## Install

```sh
pip install drawitor
```

## CLI Tool

```sh
drawitor cat_dancing.gif
```

## Library

The library is written in a simple functional style.

```python
from drawitor import draw

draw("my_img.png")

draw("super_cute_dog.gif")
```

Check the CLI tool [source code](./drawitor/__main__.py) for an usage example.

## Licence

Released under the MIT Licence
wazuh-api-rest 0.0.1
Wazuh Api Rest
Requires Python: >=3.9

# Wazuh Api Rest
This application expose an api rest for handling User and User's tasks.

# Run Local Test Server
This application use docker and docker compose to run a local server. So first make sure you
have this two installed in your pc.

Steps to run the local server:

```bash
$ docker-compose up
```
After application start you can access the OpenApi documentation at [http:://localhost:5002/docs](http://localhost:5002/docs)

# Run Local Development Server

You need to create a virtualenv and install the dependencies with pip:
```bash
$ python3 -m venv $PWD/myvenv
$ source myvenv/bin/activate
$ pip install -r requirements.txt
```

For test your development you can run the application in debug mode like this:

```bash
$ python src/setups/runapp.py --debug
```
 After application start you can access the OpenApi documentation in [http:://localhost:5002/docs](http://localhost:5002/docs)
 
 # Run tests
 In order to run the unit test suit, first you need to setup the PYTHONPATH envvar like this
 
```bash
$ export PYTHONPATH=$PWD/src
```
For run test do
```bash
$ python -m pytest test
```
# Build for Distribution
If you need build a distribution package run the following command:
```bash
$python -m build
``` 
Then you will see a new folder named `dist/` which contains the `.tar.gz` and `.whl` file for
distribution.

# Deploy in Heroku

For deploy in Heroku you need first login to your account and then run the following commands:

- Run container login
```bash
$heroku container:login
```
Then create a new app, choose a name for your app, for example I will use `your-app-name`

```bash
$heroku create your-app-name
```
Now you need to push your container and link it to your app
```bash
$heroku container:push web -a your-app-name
```
Last step is release 
```bash
$heroku container:release web -a your-app-name
```
Now you can access your app at `your-app-name.herokuapp.com/docs`