semvec/pypi-packages huggingface dataset:
vpf-730 0.9.0
a library to read data from the Biral VPF-730 Present weather sensor
License: MIT
Requires Python: >=3.9

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# vpf-730

A package to read data from the [Biral VPF-730](https://www.biral.com/product/vpf-730-visibility-present-weather-sensor/#product-overview) Present weather sensor.

## installation

```
pip install vpf-730
```

## quick start

Make sure your Sensor is connected and find out the port it is connected to. For a detailed documentation please see the [Docs](https://rubclim.github.io/vpf-730).

**Versions > `0.5.0` contain a full rewrite with lots of breaking changes**

### `logger` as a CLI

The logger: Communication and continuous data logging

```bash
vpf-730 logger --serial-port /dev/ttyS0
```

### `sender` as a CLI

The sender: Sending data to a remote server

```bash
VPF730_API_KEY=deadbeef vpf-730 sender \
--get-endpoint "https://api.example/com/vpf-730/status" \
--post-endpoint "https://api.example/com/vpf-730/data"
```

## `comm` CLI

It is also possible to manually send `ASCII` commands to the sensor. `\r\n` must not be specified

```bash
vpf-730 comm --serial-port /dev/ttyUSB0 R?
```

Returns:

```console
 200,2.515,16.5,12.2,5.00,12.3,00.00,00.00,101,086,000,02,03,00,+001.9,4040
```

### as a package

```python
from vpf_730 import VPF730

vpf730 = VPF730(port='/dev/ttyS1')
print(vpf730.measure())
```
fra 2.4.0
Simple Recommendation System, content based.
License: MIT
Requires Python: >=3.9,<4.0

# FRA
Fra is a Recommendation based framework. It was created with the idea of have an option for creating content-based recommendations easily via API.


## Architecture

![Architecture diagram](docs/architecture_1.png)

## Requirements
* pyenv (optional but recommended)
* poetry
* python 3.9+
* postgres
* redis
* docker (optional)

## Installation
* create a virtualenv
    >pyenv virtualenv 3.9.15 fra
    >pyenv activate fra
* create a database and update the config.py file with the name and host
    >psql; create database fra; \q
* install the requirements
    >poetry install
* migrate the models 
    > flask --app server/app db upgrade


## Running the app

* activate the environment
    > pyenv activate fra
* run the app
    > flask --app server/app run

-- For async jobs that process recommendations

    > celery -A motor.tasks worker  --loglevel=info  


## Running the app with docker

- Run the docker-compose
   > docker-compose up

That command will start all the services and the web server can be accessed via browser on http://localhost:5000

OpenAPI docs will be online on YOURDOMAIN/api/swagger/ui

Follow this order to be able to get recommendations:
1. create an organization
2. add users to the organization
3. add the files with the data (some examples on example_data folder)
4. add file mapping
5. add user ratings
6. get recommendations


## TODO

* Build and publish on GCP
* Add more data set to the examples
powerplayer 0.2.1
A command line interface to play music
License: MIT
Requires Python: >=3.7,<4.0

# Powerplayer
https://pypi.org/project/powerplayer/
A python based terminal music player
Inspired by [Pauloo27](https://github.com/Pauloo27)'s [Tuner](https://github.com/Pauloo27/tuner)
## OS
Tested in Windows 10(x86_64)
Should work in MAC and Linux
## Installation
### Prerequisites

- VLC Media Player
- Python ^3.7
### Windows
Open the powershell and type
```pip install powerplayer```
``` pip uninstall youtube_dl && pip install git+https://github.com/ytdl-org/youtube-dl.git@master#egg=youtube_dl ```                                         

### Linux/Mac
Open the terminal and type
```pip3 install powerplayer```
``` pip3 uninstall youtube_dl && pip3 install git+https://github.com/ytdl-org/youtube-dl.git@master#egg=youtube_dl ``` 
## Usage
After installation, type `pplay` in the terminal 
It is fine if the output is this
![image](https://user-images.githubusercontent.com/77975448/127959037-abe6f843-fafd-4f89-9c45-91d2bd6867b6.png)

### Then to play music from youtube, type
```pplay yt songname```

The output should look like this

![image](https://user-images.githubusercontent.com/77975448/125312335-cf050180-e351-11eb-9aae-2f5d20c1df9b.png)