semvec/pypi-packages huggingface dataset:
CGMMissingData 0.1.0
MICE + Random Forest + KNN to handle missing values of CGM device
Requires Python: >=3.9

# CGMMissingData

This package runs a missing-data benchmark using:
- MICE (IterativeImputer)
- Random Forest
- KNN

Defaults:
- Target: LBORRES (glucose level)
- Features: TimeSeries, TimeDifferenceMinutes, USUBJID


How to Run?
- Install python on your device. I am showing all the steps 
- Go to your project folder. e.g., cd C:\XYZ\Downloads\CGMMissingData_project
- Create venv (if not already created):
py -m venv .venv
- Activate venv:
.\.venv\Scripts\activate.bat
- Install and Verify
python -m pip install --upgrade pip
pip install -e .
python -c "import CGMMissingData; print(CGMMissingData.__file__)"

- Go to Powershell and paste the following. Make sure you have replaced the location.
Set-Location "C:\XYZ\\CGMMissingData_project\CGMMissingData_project"
Get-ChildItem
- Paste it:
.\.venv\Scripts\python.exe -c "from CGMMissingData import run_missingness_benchmark; r=run_missingness_benchmark('CGMExampleData.csv', mask_rates=[0.05,0.10,0.20,0.30,0.40]); print(r); r.to_csv('results.csv', index=False)"

Instead of 'CGMExampleData.csv, you can replace with your csv name.
- Done!
flowspec_exporter 0.1.2
Add your description here
Requires Python: >=3.13

# FlowSpec Exporter

A tool to export FlowSpec rules from routers and parse them into a structured format.

You can either collect the data directly into a PostgreSQL database or export it and use Prometheus to scrape it.

## Supported Routers

- Cisco IOS
- Juniper JunOS
- Huawei VRP

## Kwown Issues / Limitations

- Long rules may be truncated in the routers output. Hence, the parser may not be able to parse them correctly.
- Routers can interpret rules differently. So even if you send the same rule to different routers, they may appear differently in the output.

## How to Use

- Install the dependencies:

```bash
uv sync --extra all
```

- Edit the `config.toml` with your own values.

- Make sure you have a PostgreSQL database running:

```bash
docker run -d --name timescaledb -p 5432:5432 -e POSTGRES_PASSWORD=password timescale/timescaledb-ha:pg17
```

- Run the worker:

```bash
python -m src.worker
```