vresto 0.0.17

satellite product browser

vresto

A beautiful, professional Python toolkit for searching and accessing Copernicus Sentinel satellite data

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Features

• 🗺️ Interactive Map Interface - Visually search and filter satellite products
• 🔍 Smart Search - Filter by location, date range, cloud cover, and product type
• 📦 Product Management - Download quicklooks and metadata from S3
• 🐍 Professional API - Clean Python API for programmatic access
• 🔐 Secure - Handle S3 credentials safely with static key support
• ⚡ Efficient - Batch operations and smart caching

⚡ Quick Start with Docker 🐳

The fastest way to run vresto is by using Docker Compose 🚢

You only need Docker and Docker Compose installed on your machine. If you don't have them yet, you can find installation instructions on the Docker website and Docker Compose documentation.

Start vresto in just a few steps:

1. Clone the repository and go to its main directory

   git clone https://github.com/kalfasyan/vresto.git && cd vresto
   

2. Start the application with Docker Compose

   docker compose up -d
   

✅ Done! 🎉

You're all set—your vresto dashboard is now running at:
🌐 http://localhost:8610

Note: You'll need to set Copernicus credentials to use the search functionality. You can do this by:

1. Setting environment variables in the docker-compose.yml:

   environment:
     - COPERNICUS_USERNAME=[e-mail]
     - COPERNICUS_PASSWORD=your_password
   

2. Or by creating a .env file in the project root before running docker compose up:

   export COPERNICUS_USERNAME="[e-mail]"
   export COPERNICUS_PASSWORD="your_password"
   

🚀 Essential Docker & Docker Compose Commands

# Start the app in background (Docker Compose)
docker compose up -d

# View logs (Docker Compose)
docker compose logs -f

# Stop and remove services (Docker Compose)
docker compose down

# Rebuild and start (Docker Compose)
docker compose up -d --build

# Run the container directly (plain Docker)
docker run -d -p 8610:8610 \
  --name vresto-dashboard \
  vresto:latest

# View logs (plain Docker)
docker logs -f vresto-dashboard

# Stop and remove the container (plain Docker)
docker stop vresto-dashboard && docker rm vresto-dashboard

Quick Start

Note: You need Copernicus credentials to use vresto. Get free access at https://dataspace.copernicus.eu/

Installation

From PyPI (recommended for users):

pip install vresto

For development:

git clone https://github.com/kalfasyan/vresto.git
cd vresto
uv pip install -e .

Configuration

Configure your credentials (see Setup Guide for details):

export COPERNICUS_USERNAME="[e-mail]"
export COPERNICUS_PASSWORD="your_password"

Or run the interactive setup helper which writes a .env in the project root:

python scripts/setup_credentials.py

Launch the App

Simply run:

make app

Or directly with Python:

python src/vresto/ui/app.py

Opens at http://localhost:8610

Command-Line Interface (CLI):

Quick searches and downloads from the terminal:

# 🔍 Search for products
vresto-cli search-name "S2A_MSIL2A_20200612" --max-results 5

# 📸 Download quicklook (preview image)
vresto-cli download-quicklook "S2A_MSIL2A_20200612T023601_N0500_R089_T50NKJ_20230327T190018" --output ./quicklooks

# 📋 Download metadata
vresto-cli download-metadata "S2A_MSIL2A_20200612T023601_N0500_R089_T50NKJ_20230327T190018" --output ./metadata

# 🎨 Download specific bands
vresto-cli download-bands "S2A_MSIL2A_20200612T023601_N0500_R089_T50NKJ_20230327T190018" "B04,B03,B02" --resolution 10 --output ./data

For complete CLI documentation, see the CLI Guide.

API usage:

Get started with just a few lines of Python:

from vresto.api import CatalogSearch, CopernicusConfig
from vresto.products import ProductsManager

# Initialize
config = CopernicusConfig()
catalog = CatalogSearch(config=config)
manager = ProductsManager(config=config)

# 🔍 Search for a product by name
products = catalog.search_products_by_name("S2A_MSIL2A", max_results=5)

# 📸 Download quicklook and metadata
for product in products:
    quicklook = manager.get_quicklook(product)
    metadata = manager.get_metadata(product)
    if quicklook:
        quicklook.save_to_file(f"{product.name}.jpg")

# 🎨 Download specific bands for analysis/visualization
manager.download_product_bands(
    product=products[0].name,
    bands=["B04", "B03", "B02"],  # Red, Green, Blue
    resolution=10,
    dest_dir="./data"
)

For more examples, see the examples/ directory and API Guide.

For detailed setup and usage, see the documentation below.

Documentation

• Setup Guide ⭐ Start here - Installation, credentials setup, and configuration
• API Guide - Programmatic usage examples and reference
• AWS CLI Guide - Direct S3 access with AWS CLI
• Contributing - Development setup

Requirements

• Python 3.9+
• uv package manager (optional but recommended)

License

See LICENSE.txt