semvec/pypi-packages huggingface dataset:
my-moodle 0.4.6
Download Moodle Course content.
Requires Python: >=3.9


# [My Moodle](https://pypi.org/project/my-moodle/ "My Moodle")

A Python package to download data from Moodle.

## Sample Usage

The following is a sample usage of the package:

```python

%pip install my-moodle

from my_moodle import (ConfigUtility, MoodleDataDownloader)

def main() -> None:
    """Main function"""

    program, server, token = ConfigUtility.check_and_read_config()

    moodle_data_downloader: MoodleDataDownloader = MoodleDataDownloader(
        program, server, token, data_dir=""
    )
    moodle_data_downloader.download_my_data()


# Call the main function
if __name__ == "__main__":
    main()
```

## Get Moodle Token

Using <https://moodle.maynoothuniversity.ie> as an example:

1. Open <https://moodle.maynoothuniversity.ie/user/managetoken.php>
2. Copy the key for Moodle mobile web service.
3. Place it in file [config.ini](config.ini)

```ini
[App]
program = Content Management Systems
server = https://moodle.maynoothuniversity.ie
token = INSERT_YOUR_TOKEN # e.g. 63c1774a3eaf47db816c57ba1abafd40
```

*Note: The token is a secret key, do not share it with anyone.*

---
Copyright &copy; 2024 Mark Crowe <https://github.com/marcocrowe>. All rights reserved.
mecs 1.0.5
Library for stemming Madurese text

mecs is a Madurese python stemming library that allows you to transform word in the Madurese language (Bahasa Madura) to their basic form (lemma).
This application also presents the affixes of the word (prefix, suffix and nasal).

## Instalation

```bash
pip install mecs
```

## Example Usage

```python
# import package
from mecs import Stem

# Create stemmer
st = Stem.Stemmer()

# stem
term = "romana"
st.stemming(term)

print("lemma : ", st.lemma)
# roma

print("prefix : ", st.prefix)
# None

print("suffix : ", st.suffix)
# na

print("nasal : ", st.nasal)
# None

```

## Demo

Live demo : [Click here!](http://93.188.163.245:8502/)

## References

- Rachman, F. H., Ifada, N., Wahyuni, S., Ramadani, G. D., & Pawitra, A. (2022, November). ModifiedECS (mECS) Algorithm for Madurese-Indonesian Rule-Based Machine Translation. In _Proceedings of The 2022 International Conference of Science and Information Technology in Smart Administration (ICSINTESA)_ (pp. 51-56). IEEE. DOI: [10.1109/ICSINTESA56431.2022.10041470](https://doi.org/10.1109/ICSINTESA56431.2022.10041470)
- Ifada, N., Rachman, F. H., Syauqy, M. W. M. A., Wahyuni, S., & Pawitra, A. (2023). MadureseSet: Madurese-Indonesian Dataset. _Data in Brief, 48,_ 109035. DOI: [10.1016/j.dib.2023.109035](https://doi.org/10.1016/j.dib.2023.109035)