semvec/pypi-packages huggingface dataset:
voltops 0.2.0
A Python library for electronic formulas and signal processing
Requires Python: >=3.7

# Voltops

**Voltops** is a Python library built for electronics and signal processing enthusiasts. Whether you're an engineer, student, or hobbyist, this package offers intuitive functions for working with electrical formulas and analyzing signals with ease. Every function is **physics-aware**—values carry metadata (DC/AC, RMS/peak, phase, frequency) so you catch mistakes before they propagate.

---

## Installation

```bash
pip install voltops
```

---

## Quick Start

### Basic Electronic Formulas

```python
from voltops.formulas.basic import BasicFormulas

# Calculate voltage using Ohm's Law: V = I * R
voltage = BasicFormulas.ohms_law(current=2, resistance=5)
print(f"Voltage: {voltage.value} V (kind={voltage.metadata.kind})")

# Calculate power: P = V * I
power = BasicFormulas.power(voltage=voltage, current=2)
print(f"Power: {power.value} W")
```

### Frequency Spectrum Analysis

```python
import numpy as np
from voltops.signal_processing.transforms import Transforms

# Generate a simple sine wave signal
t = np.linspace(0, 1, 1000, endpoint=False)
signal = np.sin(2 * np.pi * 10 * t)

# Get the frequency spectrum
freqs, amps = Transforms.frequency_spectrum(signal, sampling_rate=1000)
```

### Filtering Signals

```python
from voltops.signal_processing.filters import Filters

# Create a signal with multiple frequency components
t = np.linspace(0, 1, 1000, endpoint=False)
signal = np.sin(2 * np.pi * 10 * t) + 0.5 * np.sin(2 * np.pi * 20 * t)

# Apply a low-pass filter with a cutoff at 15 Hz
filtered_signal = Filters.low_pass_filter(signal, cutoff=15, sampling_rate=1000)
```


## Features

- **Physics-aware quantities**: Voltage, Current, Resistance/Impedance, Power, Frequency, and Phase objects with waveform metadata.
- **Electronic Formulas**: Ohm's Law, power, and more—now returning safe quantity objects.
- **Signal Processing**: FFT, DFT, filtering, and spectral analysis.
- **Extensible API**: Easy-to-use, modular design for seamless integration.

Learn more about the design direction in [`docs/philosophy.md`](docs/philosophy.md).


## Contributing

Contributions are welcome!  
If you'd like to report a bug, request a feature, or contribute code, feel free to open an issue or submit a pull request on [GitHub](https://github.com/madhurthareja/voltops).


## Maintainers

This library is actively developed and maintained by **Madhur Thareja**.


## License

Licensed under the [MIT License](https://opensource.org/licenses/MIT).  
Feel free to use, modify, and distribute this library.
zz-tools 2.3.7
MCGT utilities
Requires Python: >=3.9

# MCGT: Model of Gravitational Time Curvature

[![Zenodo](https://zenodo.org/badge/DOI/10.5281/zenodo.XXXXXXX.svg)](https://doi.org/10.5281/zenodo.XXXXXXX)
[![Python 3.10+](https://img.shields.io/badge/python-3.10+-blue.svg)](https://www.python.org/downloads/)

Official repository for the MCGT research project, focused on Gravitational Wave Phase Analysis and Cosmological Invariants.

## 🚀 Key Features
- **Sobol 8D Sampling**: Production-grade parameter space exploration.
- **Reproducible Pipeline**: All chapters certified with SHA256 consistency checks.
- **Physics Modules**: From CMB spectra to GW phase residuals.

## 🛠 Installation
```bash
git clone https://github.com/JeanPhilipLalumiere/MCGT.git
pip install -r requirements.txt
```

## 📊 Verification
```bash
python zz-manifests/diag_consistency.py zz-manifests/manifest_master.json
```

*For French version, see [README_fr.md](README_fr.md).*
declaro 0.0.1
The Functional Python Stack - pure functions, typed data, no class magic
Requires Python: >=3.11
Keywords: database, functional, pure-functions, schema, typing, validation

# Declaro

**The Functional Python Stack**

> Pure functions. Typed data. No class magic.

## Vision

Declaro is a collection of tools for developers who believe:

- **Data is just data** - Dicts and TypedDicts, not objects with hidden state
- **Functions transform data** - Pure functions with no side effects
- **Types should be explicit** - Declared upfront, enforced everywhere
- **Testing should be trivial** - Same input, same output, always

## Packages

| Package | Description | Status |
|---------|-------------|--------|
| `declaro-persistum` | Schema-first database toolkit | In development |
| `declaro-ximenez` | Type enforcement with memorable errors | Planned |
| `declaro-api` | FastAPI integration | Planned |

## Installation

```bash
# Install everything
pip install declaro[all]

# Or pick what you need
pip install declaro-persistum
pip install declaro-ximenez
pip install declaro-api
```

## Philosophy

```python
# Not this (classes, state, magic)
class User(BaseModel):
    email: str

    @validator("email")
    def validate_email(cls, v):
        ...

# This (data, functions, clarity)
User = TypedDict("User", {"email": str})

def validate_user(user: dict) -> list[Error]:
    return check_email(user.get("email", ""))
```

## Links

- [GitHub](https://github.com/adamzwasserman/declaro)
- [Documentation](https://github.com/adamzwasserman/declaro)

## License

MIT