semvec/pypi-packages huggingface dataset:
s1swotcolocs 2025.9.10.post1
Python lib to create co-locations between Sentinel-1 IW or EW images and SWOT KaRin swath.
License: MIT
Requires Python: >=3.9
Keywords: SAR, SWOT, colocations, sea-state

# s1swotcolocs

[![PyPI version](https://img.shields.io/pypi/v/s1swotcolocs.svg)](https://pypi.python.org/pypi/s1swotcolocs)
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Python lib to create co-locations between Sentinel-1 IW or EW images and SWOT KaRin swath.

-   Free software: MIT license
-   Documentation: [https://s1swotcolocs.readthedocs.io](https://s1swotcolocs.readthedocs.io).

# Features

---

-   Find temporal and spatial co-locations between Sentinel-1 (S1) Level-1/Level-2 products and SWOT Level-3 (L3) SSH data.
-   Process S1 IW (Interferometric Wide swath) and EW (Extra Wide swath) modes.
-   Interface with CDSE (Copernicus Data Space Ecosystem) for S1 data discovery.
-   Generate output defining co-located S1 and SWOT data segments.
-   Configurable time delta for co-location criteria.
-   Utility functions for geospatial operations and data handling relevant to S1 and SWOT.

# usage

```python
   import s1swotcolocs
```

# alias

## creating meta-data colocation files

```bash
# to use the lib within a docker image
./coloc_SWOT_L3_with_S1_CDSE_TOPS_sequential_wrapper.py --startdate 20250616 --stopdate 20250616 --confpath src/s1swotcolocs/localconfig.yml

# to use the lib
coloc_SWOT_L3_with_S1_CDSE_TOPS_sequentiel --startmonth 20250616 --stopmonth 20250616 --confpath src/s1swotcolocs/localconfig.yml --outputdir /tmp/
```

## illustration of a co-location between SWOT KaRIn swath and Sentinel-1 IW swath

![coloc_swot_iw](docs/_static/figures/illustrate_coloc_s1_swot_iw.png)

## illustration of a co-location between SWOT KaRIn reduced swath and Sentinel-1 IW swath

For triple co-location (KaRin ,SWOT-nadir, IW Level-2 WAV) purposes it oculd be important to limit the KarIn swath to the low incidence part of the swath.

![coloc_swot_iw](docs/_static/figures/illustrate_coloc_s1_swot_iw_nadir.png)
aclib.pyi 1.1.3
compile and pack python project to exe with pyd.
License: MIT
Requires Python: >=3.6


# Installation
    pip install aclib.pyi


# Usage

``` python
# from aclib.pyi import compile, pyipack
from aclib import pyi

compileddir = pyi.compile(...)
if compileddir:
    pyi.pyipack(...)
```
pyquarks 0.0.0.1
Delivering small additions which matter
License: MIT
Requires Python: >=3.7

![PyQuarks Banner](./res/img/PyQuarks-Banner.png)

# PyQuarks

**PyQuarks** is a compact, modular Python library for general-purpose data manipulation. Whether you're sorting, searching, transforming, or analyzing, PyQuarks offers a clean and reliable foundation for working with data.

This project is a curated library of reusable logic, organized for clarity, built for simplicity. While currently focused on core algorithmic tools, the long-term goal is to evolve PyQuarks into a lightweight framework for structured data workflows.

## Features

- **Core Modules**: Includes essential algorithms for sorting, searching, filtering, and transformation.
- **Zero Dependencies**: Built entirely with standard Python, no external libraries required.
- **Modular Structure**: Functions and classes are grouped logically for easy access and reuse.
- **Scalable Design**: Written with extensibility in mind, ready to grow as needed.

## Use Cases

- Rapid prototyping of algorithmic logic
- Educational reference for learning or teaching Python algorithms
- Lightweight utilities for data manipulation tasks
- Foundation for future library expansion

## Roadmap

- CLI interface for running selected modules
- Optional configuration system for chaining operations
- Expanded documentation and examples

## Vision

PyQuarks is about clarity, utility, and control. It’s a personal project built under constraints, with the goal of creating something useful, maintainable, and expandable.

## Getting Started

To start using PyQuarks, install via pip or clone the repository and explore the available [modules](./MODULES.md).

### PyPI (pip):
```bash
pip install pyquarks
```

### Clone Git
```bash
git clone https://github.com/Prospy006/pyquarks.git
cd pyquarks
```

### Example usage:

```py
import pyquarks

# Create a linked list
ll = pq.LinkedList()

# Insert values
ll.insert(420)
ll.insert(69)
ll.insert(6)

# Display list
ll.display() # output: [420, 69, 6]

# Delete byval or byind
ll.delete_byval(6) # deletes last value
ll.delete_byind(0) # deletes first value
ll.display() # output: [69]
```