pysarflow


Namepysarflow JSON
Version 0.1.0 PyPI version JSON
download
home_pageNone
SummaryAn open-source python library for SAR data processing
upload_time2025-08-21 20:50:32
maintainerNone
docs_urlNone
authorNone
requires_python==3.9.23
licenseMIT
keywords sar sarpy
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # pysarflow

An open-source python library for SAR data processing

> [!WARNING]
> This library is under active development and lot of its functionality is still yet to code.


## Description

Despite the growing usage of SAR data, the processing workflow remains complex and still relies on specialized heavy desktop tools creating huge barriers for students and non-experts. There is a growing need for a modular, open-source and user-friendly workflow that can take Level-1 SAR products and guide users through essential steps ideally ending in products that are usable and compatible with geospatial pipelines.

## Project Structure

```graphql
pysarflow/
├── __init__.py
├── grd.py
├── slc.py
├── utils.py

```

## Installation

To use this package, the esa-snappy library (the Python interface for ESA SNAP) is required before installation of the pysarflow package.  
The follwoing are the steps to install exsa-snappy :

**1. Create and activate a conda environment**   
```bash
conda create -n snap_env python=3.9   
conda activate snap_env  
```
**2. Install Package**
```bash
pip install pysarflow 
```

**3. Install ESA SNAP Desktop**    
Download and install ESA SNAP from the [SNAP website](https://earth.esa.int/eogateway/tools/snap).  
During installation, enable the option to configure Python for SNAP and specify your Python executable path:  
- Use the Python from your conda environment, e.g. *C:\Users\YourUsername\.conda\envs\snap_env\python.exe*  
- If that does not work, try the base environment Python: for example *(C:\ProgramData\Anaconda3\python.exe)*   

**4. Run the snappy-conf script to configure SNAP**  
If you use the base environemnt python or you already have SNAP installed then,  
Open a command prompt, navigate to SNAP’s bin folder, and run:  
```bash
cd "C:\Program Files\esa-snap\bin"   
snappy-conf "C:\Users\YourUsername\.conda\envs\snap_env\python.exe"
```  
You should see: *Configuration finished successfully!*

**4. Verify esa-snappy works**  
Activate your environment and open Python:  
```bash
conda activate snap_env  
python
```
in the Python environment, try importing:  
```bash
import esa_snappy 
from esa_snappy import ProductIO 
```
If no errors occur, your setup is complete! 

## Documentation

For detailed documentation and examples, see the [documentation website](https://rabinatwayana.github.io/pysarflow/).

## Examples

Check out the 'examples' directory for more examples:

## Contributing

Contributions are welcome! Follow [dev setup guide](./docs/dev.md) & Please feel free to submit a Pull Request.

## Acknowledgments

- This library is build as a part of python software development course at Paris Lodron University Salzburg
- Built on top of powerful open-source libraries like numpy, rasterio

## Contributors

[![Contributors](https://contrib.rocks/image?repo=rabinatwayana/pysarflow)](https://github.com/rabinatwayana/pysarflow/graphs/contributors)

            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "pysarflow",
    "maintainer": null,
    "docs_url": null,
    "requires_python": "==3.9.23",
    "maintainer_email": null,
    "keywords": "sar, sarpy",
    "author": null,
    "author_email": "Rabina Twayana <rabinatwayana123@gmail.com>",
    "download_url": "https://files.pythonhosted.org/packages/d7/00/dbf9568d40f6c913a5df53fe1a9ce432f487052b296b81170306cfb08287/pysarflow-0.1.0.tar.gz",
    "platform": null,
    "description": "# pysarflow\n\nAn open-source python library for SAR data processing\n\n> [!WARNING]\n> This library is under active development and lot of its functionality is still yet to code.\n\n\n## Description\n\nDespite the growing usage of SAR data, the processing workflow remains complex and still relies on specialized heavy desktop tools creating huge barriers for students and non-experts. There is a growing need for a modular, open-source and user-friendly workflow that can take Level-1 SAR products and guide users through essential steps ideally ending in products that are usable and compatible with geospatial pipelines.\n\n## Project Structure\n\n```graphql\npysarflow/\n\u251c\u2500\u2500 __init__.py\n\u251c\u2500\u2500 grd.py\n\u251c\u2500\u2500 slc.py\n\u251c\u2500\u2500 utils.py\n\n```\n\n## Installation\n\nTo use this package, the esa-snappy library (the Python interface for ESA SNAP) is required before installation of the pysarflow package.  \nThe follwoing are the steps to install exsa-snappy :\n\n**1. Create and activate a conda environment**   \n```bash\nconda create -n snap_env python=3.9   \nconda activate snap_env  \n```\n**2. Install Package**\n```bash\npip install pysarflow \n```\n\n**3. Install ESA SNAP Desktop**    \nDownload and install ESA SNAP from the [SNAP website](https://earth.esa.int/eogateway/tools/snap).  \nDuring installation, enable the option to configure Python for SNAP and specify your Python executable path:  \n- Use the Python from your conda environment, e.g. *C:\\Users\\YourUsername\\.conda\\envs\\snap_env\\python.exe*  \n- If that does not work, try the base environment Python: for example *(C:\\ProgramData\\Anaconda3\\python.exe)*   \n\n**4. Run the snappy-conf script to configure SNAP**  \nIf you use the base environemnt python or you already have SNAP installed then,  \nOpen a command prompt, navigate to SNAP\u2019s bin folder, and run:  \n```bash\ncd \"C:\\Program Files\\esa-snap\\bin\"   \nsnappy-conf \"C:\\Users\\YourUsername\\.conda\\envs\\snap_env\\python.exe\"\n```  \nYou should see: *Configuration finished successfully!*\n\n**4. Verify esa-snappy works**  \nActivate your environment and open Python:  \n```bash\nconda activate snap_env  \npython\n```\nin the Python environment, try importing:  \n```bash\nimport esa_snappy \nfrom esa_snappy import ProductIO \n```\nIf no errors occur, your setup is complete! \n\n## Documentation\n\nFor detailed documentation and examples, see the [documentation website](https://rabinatwayana.github.io/pysarflow/).\n\n## Examples\n\nCheck out the 'examples' directory for more examples:\n\n## Contributing\n\nContributions are welcome! Follow [dev setup guide](./docs/dev.md) & Please feel free to submit a Pull Request.\n\n## Acknowledgments\n\n- This library is build as a part of python software development course at Paris Lodron University Salzburg\n- Built on top of powerful open-source libraries like numpy, rasterio\n\n## Contributors\n\n[![Contributors](https://contrib.rocks/image?repo=rabinatwayana/pysarflow)](https://github.com/rabinatwayana/pysarflow/graphs/contributors)\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "An open-source python library for SAR data processing",
    "version": "0.1.0",
    "project_urls": {
        "Documentation": "https://rabinatwayana.github.io/pysarflow",
        "Repository": "https://github.com/rabinatwayana/pysarflow/"
    },
    "split_keywords": [
        "sar",
        " sarpy"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "4e7d2469febb079334d560937fe072d8eec599ead748330652b4dc581cabfd79",
                "md5": "09f3a173563288a445cb5e6ec650ef06",
                "sha256": "ea6e6d65bbc88d50ff63f2fc817dfc65c8806e64a5e0007d2e55c00317715e93"
            },
            "downloads": -1,
            "filename": "pysarflow-0.1.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "09f3a173563288a445cb5e6ec650ef06",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": "==3.9.23",
            "size": 19681,
            "upload_time": "2025-08-21T20:50:30",
            "upload_time_iso_8601": "2025-08-21T20:50:30.923595Z",
            "url": "https://files.pythonhosted.org/packages/4e/7d/2469febb079334d560937fe072d8eec599ead748330652b4dc581cabfd79/pysarflow-0.1.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "d700dbf9568d40f6c913a5df53fe1a9ce432f487052b296b81170306cfb08287",
                "md5": "5e431631c987d3331423a387a9d302dd",
                "sha256": "de2de3945cc0fbbb446a7a5b6b72a2124f6ae9f0e5f21fd2a29e3404fed5fd1b"
            },
            "downloads": -1,
            "filename": "pysarflow-0.1.0.tar.gz",
            "has_sig": false,
            "md5_digest": "5e431631c987d3331423a387a9d302dd",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": "==3.9.23",
            "size": 19733,
            "upload_time": "2025-08-21T20:50:32",
            "upload_time_iso_8601": "2025-08-21T20:50:32.319122Z",
            "url": "https://files.pythonhosted.org/packages/d7/00/dbf9568d40f6c913a5df53fe1a9ce432f487052b296b81170306cfb08287/pysarflow-0.1.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-08-21 20:50:32",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "rabinatwayana",
    "github_project": "pysarflow",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "pysarflow"
}
        
Elapsed time: 0.54632s