semvec/pypi-packages huggingface dataset:
markit-gateway 2.0.1
IMU message broker
Requires Python: >=3.7

# MARKIT Gateway

This repo contains code to interact with [rfmarkit-esp-node](https://github.com/mvig-robotflow/rfmarkit-esp-node).

## Get Started

```shell
git clone https://github.com/mvig-robotflow/rfmarkit-gateway.git
python setup.py install
```

Or from PYPI:

```shell
python -m pip install markit-gateway
```

## Documentation

For documentation, please refer to [rfmarkit-gateway/docs](https://github.com/mvig-robotflow/rfmarkit-gateway/docs).
podloot 0.1
A podcast downloader and manager using RSS feeds

# Podloot

Podloot is a podcast downloader and manager using RSS feeds. It provides a command-line interface for downloading and managing podcast episodes from RSS feeds.

## Features

- Download episodes from a single RSS feed or a file containing multiple feeds.
- Get information about a specific podcast episode.
- Get the artwork URL for a podcast.
- Check for duplicate episodes in a podcast.

## Installation

You can install Podloot using pip:

```bash
pip install git+https://github.com/gusanmaz/podloot.git
```

Usage

### Download episodes from a file with multiple RSS feeds

`podloot download <feed_file> <destination>`

### Download episodes from a single RSS feed

`podloot download_single <feed_url> <destination>`

### Get information about a specific podcast episode

`podloot info <podcast_dir> <audio_file>`

### Get the artwork URL for a podcast

`podloot artwork <podcast_dir>`

### Check for duplicate episodes in a podcast

`podloot duplicates <podcast_dir>`

## Contributing

Pull requests and bug reports are welcome. For major changes, please open an issue first to discuss what you would like to change.

## License

[MIT License](https://choosealicense.com/licenses/mit/)

``As for improvements to features and code, here are a few suggestions: 1. Add functionality to download only the latest episode or a specific number of latest episodes. 2. Allow users to limit the download of episodes based on a date range or the age of the episodes. 3. Implement automatic episode cleanup based on user-defined criteria, such as age or total storage space used. 4. Add support for downloading episodes in parallel to speed up the download process. 5. Implement a more interactive CLI using a library like `click` to provide a more user-friendly experience. Remember to thoroughly test any new features or code changes before committing them to the repository.``
databaseutils 0.0.1
Connect to databases from Python
Requires Python: >=3.6

# Cmotions DatabaseUtils

Databaseutils is a Python library created by [The Analytics Lab](https://www.theanalyticslab.nl/), which is powered by [Cmotions](https://cmotions.nl/). This library combines our most used functionality when it comes to connecting to databases from Python. Nothing fancy, but very useful for our consultants. Mostly since this package is used in other packages, which makes our workflow simpler and more efficient.

Since we love to share what we do, why not also do that with our packages, that is why we've decided to make (almost) all of our packages open source, this way we hope to give back to the community that brings us so much. Enjoy!

## Installation
Install Databaseutils using pip

```bash
pip install databaseutils
```

## Usage
```python
# package containing example datasets
from pydataset import data

# the Cmotions DatabaseUtils functionality
from databaseutils import db_utils

# load data
df = data("iris")

# create a database connection to SQL Server using the credentials provided in a .env file
db_conn = db_utils(server=os.getenv("DB1_SERVER"), db=os.getenv("DB1_DATABASE"), server_name=os.getenv("DB1_SERVER_NAME"), usr=os.getenv("DB1_USERNAME"), pwd=os.getenv("DB1_PASSWORD"), driver=os.getenv("DB1_DRIVER"), port=os.getenv("DB1_PORT"))

# create a database connection to SQL Server using Windows credentials
db_conn = db_utils(server="localhost", db="localtemp")

# get an overview of all active schemas in the database
db_conn.list_all_active_schemas()

# get an overview of all tables in the database within the specified schemas
db_conn.list_all_tables(schema=['dbo'])

# load the data from an entire table
cars = db_conn.retrieve_table_from_sql(table="cars", schema="dbo")

# write a table to the SQL database, when possible the package will use BCP to optimize the efficiency of the process
db_conn.write_dataframe_to_sql(data=df, table="mynewtable", schema="dbo", replace_if_exists=False, index=False, dtype=None)

```

## Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.

## License
[GNU General Public License v3.0](https://choosealicense.com/licenses/gpl-3.0/)

## Contributors
Jeanine Schoonemann<br>
[Contact us](mailto:info@theanalyticslab.nl)