semvec/pypi-packages huggingface dataset:
power-markets 0.1
Power market datasets
Requires Python: >=3.7

Power Markets
===============

This package includes data from power markets in Europe.

After installing the package, data is available as an [intake catalog](https://intake.readthedocs.io/en/latest/index.html). As an example:

```python
import intake

generation = intake.cat["markets"].generation(country="EL").read()
available_capacity = intake.cat["markets"].capacity(country="EL").read()
```

In addition, the package offers two CLI commands: one to download data from TSOs and one to extract datasets.


The type of data to download can be:
- `dispatch` includes the inputs and results of the day-ahead scheduling
- `availabilities` includes data about the available capacity for all dispatchable power
generation units
- `reservoirs` includes data about the filling rates of the hydropower plants
- `ntc` includes data about the net transfer capability for power imports and exports.


The datasets to extract from the raw data can be:
- `load`: extracts the load dataset from the `dispatch` data
- `reserves`: extracts the secondary reserves dataset from the `dispatch` data
- `committed`: extracts the committed capacity dataset from the `dispatch` data
- `imports`: extracts the power imports dataset from the `dispatch` data
- `exports`: extracts the power exports dataset from the `dispatch` data
- `res`: extracts the RES generation dataset from the `dispatch` data
- `available`: extracts the available capacity dataset from the `availabilities` data
- `reservoirs`: extracts the water reservoir levels (for hydro plants) dataset from the `reservoirs` data
- `ntc_imports`: extracts dataset for total NTC (net transfer capacity) for imports from the `ntc` data
- `ntc_exports`: extracts dataset for total NTC (net transfer capacity) for exports from the `ntc` data.

Use
```bash
power-markets fetch -h
```
to see the arguments for the `fetch` command, and 

```bash
power-markets extract -h
```

for the `extract` command.

The `power-markets` package can be installed using pip:

```bash
pip install power-markets
```
pseudolm 1.0.1
Python package to perfrom psuedo-likelihood maximisation inference on Ising models

[![CodeFactor](https://www.codefactor.io/repository/github/maxkloucek/pyplm/badge)](https://www.codefactor.io/repository/github/maxkloucek/pyplm)

## PyPLM: a Pseudo-Likelihood Maximization (PLM) python package

This python package implements the Pseudo-Likelihood Maximization (PLM) technique to solve the inverse Ising problem (equivalently known as pairwise Maximum Entropy modelling). The method allows the interaction network of systems of binary variables to be reconstructed, and relies on performing logistic regression.

PyPLM is structured around a single pipeline (the data_pipeline), which allows data to be generated and inferred. PyPLM also implements Firth's logistic regression penalty.

### Installation

```
git clone https://github.com/maxkloucek/pyplm.git
cd pyplm
pip install .
```

### Usage Examples

Please see example_2DIsing.py for an overview of how to use the pyplm data_pipeline. All data is stored using the hdf5 file format. To perform some elementary analysis, first run `python example_2DIsing.py`, and then see the  `example_2DIsing_analysis.ipynb` notebook (requires jupyter notebook to be installed).

If you use this package for any scientific purpose then please cite: 
https://arxiv.org/abs/2301.05556
racing-report-SWAGhettie 0.0.3
App that sorts racing results and store it in logs
Requires Python: >=3.11.0

# Module Documentation: qualifying_report
The qualifying_report module provides functionality to read data from two log files 
containing start and end times for each driver's lap, calculates the lap times, sorts the results, 
and writes the output to a new file. 
It also provides functionality to print the leaderboard or driver's information from the generated report.

# Functions
build_report(folder_path: str = '') -> None
This function reads in data from two log files containing start and end times for each driver's lap, 
calculates the lap times, sorts the results, and writes the output to a new file.


print_report(folder_path: str = '', driver_name: str = '', desc: bool = False, asc: bool = False) -> None
This function prints the leaderboard or driver's information from the generated report.


main() -> None
This function parses command-line arguments, builds a report or prints driver information 
based on the provided arguments.