semvec/pypi-packages huggingface dataset:
acond-heat-pump 1.2.2
A unofficial python library to interface with an Acond heat pump using the Modbus TCP protocol.
Requires Python: <4.0,>=3.12

# Acond Heat Pump

A unofficial python library to interface with an Acond heat pump
using the Modbus TCP protocol.

Acond Modbus is described in [Loxone Library Acond integration](https://api.library.loxone.com/downloader/file/1231/Acond_ModbusTCP%20sw%20xxx.41%20-%20ENG.pdf).

### ❗Warning❗
Library is tested only with Acond PRO N heat pump as I don't have access to other models.
If you have a different model and you want to test it, please let me know the results.

## Usage

### Connecting to the Heat Pump

```python
from acond_heat_pump import AcondHeatPump

heat_pump = AcondHeatPump('192.168.1.16')
heat_pump.connect()
```

### Reading Data

```python
response = heat_pump.read_data()
print(response)
```

### Setting Temperatures

```python
heat_pump.set_indoor_temperature(25.0, circuit=1)
heat_pump.set_dhw_temperature(45.0)
heat_pump.set_water_back_temperature(35.0)
heat_pump.set_pool_temperature(28.0)
heat_pump.set_water_cool_temperature(20.0)
```

### Setting Modes

```python
from acond_heat_pump import RegulationMode, HeatPumpMode

heat_pump.set_regulation_mode(RegulationMode.MANUAL)
heat_pump.change_setting(mode=HeatPumpMode.AUTOMATIC)
```

### Closing the Connection

```python
heat_pump.close()
```

## Running Tests

Run the unit tests using `unittest`:

```sh
python -m unittest discover tests
```

## License

This project is licensed under the MIT License.
Topsis-Sahil-102316091 1.0.0
A Python package for TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution)
Requires Python: >=3.6

# Topsis-Sahil-102316091

A Python package to implement TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution).

## Installation

```bash
pip install Topsis-Sahil-102316091
```

## Usage

### Command Line

```bash
topsis <InputDataFile> <Weights> <Impacts> <OutputResultFileName>
```

Example:

```bash
topsis data.csv "1,1,1,1,1" "+,+,+,+,+" result.csv
```

### Python Script

```python
from topsis.main import topsis_logic
import pandas as pd

# Load your dataframe
df = pd.read_csv("data.csv")

# processing...
# ...
```

## License

MIT
spectral-line-finder 0.2.1
Find and match lines in spectroscopic data from NIST.
Requires Python: >=3.12

# Spectral Line Finder

A simple tool to browse, filter and visualize atomic spectral line data in the terminal, built using the awesome [Textual](https://textual.textualize.io/) library. The data is retrieved from the [NIST atomic spectra database](https://physics.nist.gov/PhysRefData/ASD/lines_form.html) and cached on disk. Since the [Trump administration defunded](https://www.npr.org/2025/03/26/nx-s1-5340687/trump-cuts-nist-atomic-spectra-lab-advanced-chips-medical-devices) [the entire atomic spectroscopy group at NIST](https://howonearthradio.org/archives/10056) in 2025 we can only hope this data remains available to scientists. There is [some hope](https://www.callabmag.com/nist-group-finds-new-home/), after all.

## Screenshots

![screenshot of filter dialog](https://raw.githubusercontent.com/davidfokkema/spectral-line-finder/refs/heads/main/docs/images/screenshot-filter.png)

![screenshot of data table](https://raw.githubusercontent.com/davidfokkema/spectral-line-finder/refs/heads/main/docs/images/screenshot-table.png)

![screenshot of spectrum plot](https://raw.githubusercontent.com/davidfokkema/spectral-line-finder/refs/heads/main/docs/images/screenshot-plot.png)

## Usage

To run this application, use uv

```sh
uvx spectral-line-finder
```

or install this package from PyPI.

The filter dialog allows for selecting one or multiple elements and filtering the data based on ionization stage, observed wavelength, relative intensity, or the initial and final energy levels. Once filtered, the data is displayed in a table but the (filtered) spectrum can also be visualized in a spectrum plot.
pylocc 1.5.2
Add your description here
Requires Python: >=3.10

# Python Loc Counter - PYLOCC
![Tests](https://github.com/cirius1792/pylocc/actions/workflows/tests.yml/badge.svg) ![Coverage](https://raw.githubusercontent.com/Cirius1792/pylocc/refs/heads/main/coverage.svg)
<p align="center">
    <img src="https://cirius1792.github.io/pylocc/img/pylocc_logo_transparent.png" alt="pylocc logo" width="400"/>
</p>

`pylocc` is a command-line tool for counting lines of code in various programming languages. It helps you get a quick overview of the size and composition of your codebase.

This project draws instiparion from [scc](https://github.com/boyter/scc) and uses the same language.json file. 

## Features
Please have a look at the [documentaiton page](https://cirius1792.github.io/pylocc/) for more details. 

*   Counts lines of code, comments, and blank lines.
*   Supports a wide range of programming languages.
*   Can process single files or entire directories.
*   Provides both aggregated and per-file reports.
*   Easy to use and configure.

## Requirements

- Python >= 3.10

## Installation

### From Pypi
```bash
 pip install pylocc

 pylocc --help
 ```
### From Source

1.  Clone the repository:
    ```bash
    git clone https://github.com/your-username/pylocc.git
    ```
2.  Navigate to the project directory:
    ```bash
    cd pylocc
    ```
3.  Install the dependencies:
    ```bash
    uv run pylocc
    ```

## Usage

To use `pylocc`, run the following command:

```bash
pylocc [OPTIONS] <file_or_directory>
```
or
```bash
uv run pylocc --help
Usage: pylocc [OPTIONS] FILE

  Run pylocc on the specified file or directory.

Options:
  --by-file      Generate report by file.
  --output FILE  Stores the output report in csv format to the given path
  --help         Show this message and exit.

```

### Options

*   `--by-file`: Generate a report for each file individually.
*   `--output <path>`: Save the report to a file.

### Examples

*   Count lines of code in a single file:
    ```bash
    pylocc my_file.py
    ```
*   Count lines of code in a directory and all its subdirectories:
    ```bash
    pylocc my_project/
    ```
*   Generate a per-file report:
    ```bash
    pylocc --by-file my_project/
    ```
*   Save the report to a file:
    ```bash
    pylocc --output report.csv my_project/
    ```

## Configuration

`pylocc` uses a `language.json` file to define the comment syntax for different languages. You can customize this file to add new languages or modify existing ones.

Each language entry in `language.json` has the following structure:

```json
{
  "LanguageName": {
    "extensions": ["ext1", "ext2"],
    "line_comment": ["//"],
    "multi_line": [["/*", "*/"]]
  }
}
```

*   `extensions`: A list of file extensions for the language.
*   `line_comment`: A list of strings that represent single-line comments.
*   `multi_line`: A list of pairs of strings that represent the start and end of multi-line comments.

## Contributing

Contributions are welcome! Please feel free to open an issue or submit a pull request.