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This project automatically downloads taxon-specific images from the GBIF API (https://techdocs.gbif.org/en/openapi/), processes them, and stores both images and metadata in a taxonomically organized structure in a MinIO (https://www.min.io/) bucket.

Project description

๐ŸŒณ GBIF Image Downloader

This project automatically downloads taxon-specific images from the GBIF API, processes them, and stores both images and metadata in a taxonomically organized structure in a MinIO bucket.


Features

  • Loads Latin taxon names from .csv or .xlsx files
  • Resolves taxonKeys automatically via the GBIF API
  • Downloads associated media (images) from GBIF
  • Stores metadata and images in a taxonomic folder structure in MinIO
  • Optionally processes only new GBIF occurrences (crawl_new_entries)
  • Multithreading for parallel processing and uploads
  • Saves Logfiles to persistent volume

Project Structure

โ”œโ”€โ”€ config/
โ”‚   โ””โ”€โ”€ config.yaml                    # Central configuration (bucket, paths, etc.)
โ”œโ”€โ”€ data/
โ”‚   โ”œโ”€โ”€ species_key.csv                # Output: species list with GBIF speciesKeys
โ”‚   โ””โ”€โ”€ tree_list.xlsx                 # Input: original species list
โ”œโ”€โ”€ src/
โ”‚   โ””โ”€โ”€ anhaltai/
โ”‚       โ”œโ”€โ”€ gbif_downloader/
โ”‚       โ”‚   โ”œโ”€โ”€ crawler/
โ”‚       โ”‚   โ”‚   โ”œโ”€โ”€ __init__.py        # Package initialization
โ”‚       โ”‚   โ”‚   โ””โ”€โ”€ base_crawler.py    # Base logic for crawling occurrences
โ”‚       โ”‚   โ”œโ”€โ”€ __init__.py            # Package initialization
โ”‚       โ”‚   โ”œโ”€โ”€ config.py              # Loads global configuration
โ”‚       โ”‚   โ”œโ”€โ”€ config_loader.py       # Loads configuration from YAML
โ”‚       โ”‚   โ”œโ”€โ”€ downloader.py          # Download & upload of occurrences and media
โ”‚       โ”‚   โ”œโ”€โ”€ local_log_handler.py   # Log handler that writes logs to MinIO
โ”‚       โ”‚   โ”œโ”€โ”€ main.py                # Entry point, orchestrates all steps
โ”‚       โ”‚   โ”œโ”€โ”€ tree_list_processor.py # Processes taxon lists, resolves taxonKeys
โ”‚       โ”‚   โ””โ”€โ”€ utils.py               # Utility functions (hashing, upload, etc.)
โ”‚       โ””โ”€โ”€  __init__.py               # Package initialization
โ”‚
โ”œโ”€โ”€ .dockerignore                      # Files to ignore in Docker build
โ”œโ”€โ”€ .env                               # MinIO credentials (not in repo)
โ”œโ”€โ”€ .env-example                       # Example MinIO credentials format
โ”œโ”€โ”€ .gitattributes                     # Git attributes for large file systems
โ”œโ”€โ”€ .gitignore                         # Files to ignore in git
โ”œโ”€โ”€ .gitlab-ci.yml                     # GitLab CI/CD configuration
โ”œโ”€โ”€ Dockerfile                         # Container build
โ”œโ”€โ”€ LICENSE                            # License information
โ”œโ”€โ”€ pyproject.toml                     # Python project configuration
โ”œโ”€โ”€ README.md                          # Project documentation
โ”œโ”€โ”€ requirements.txt                   # Python dependencies
โ””โ”€โ”€ sonar-project.properties           # SonarQube configuration

Usage

Installation

Install dependencies via:

pip install -r requirements.txt

1. Prepare your input file

Create a .csv or .xlsx file with at least the following column:

latin_name
Quercus robur
Fagus sylvatica

2. Adjust your configuration

Edit the file config/config.yaml to set your MinIO connection, output paths, and processing options.
A typical configuration looks like this:

minio:
  bucket: meinewaldki-gbif         # Name of your MinIO bucket
  endpoint: 10.144.46.54:9000           # MinIO/S3 endpoint URL
  secure: false                     # Use HTTPS (true/false)

paths:
  output: gbif/                    # Output directory for images and metadata
  tree_list_input_path: data/tree_list.xlsx      # Path to your input taxon list
  processed_tree_list_path: data/species_key.csv # Path for the processed taxonKey list
  log_dir: logs/                   # Directory for log files

query_params:
  mediaType: StillImage            # Only download images
  limit: 100                       # Number of records per API call
  offset: 0                        # Start offset

options:
  already_preprocessed: True         # Set False to process the taxon list again
  crawl_new_entries: False           # Only process new occurrences if True
  max_threads: 300                   # Number of parallel threads for downloads/uploads
  max_pool_size: 50                  # Max connections in Minio-pool

Query Parameters for GBIF API URL

The parameters used to build the GBIF API request URL are defined in the query_params section of your config/config.yaml. These parameters control which records are fetched from the GBIF API.

Supported parameters:

  • mediaType (e.g. StillImage): Only download records with images.
  • taxonKey: The taxon key.
  • datasetKey: Filter by dataset.
  • country: Filter by country code (e.g. DE for Germany).
  • hasCoordinate: Only records with coordinates (true or false).
  • year, month: Filter by year or month of occurrence.
  • basisOfRecord: Type of record (e.g. HUMAN_OBSERVATION).
  • recordedBy: Filter by collector/observer.
  • institutionCode, collectionCode: Filter by institution or collection.
  • limit: Number of records per API call (pagination, max. 300).
  • offset: Start offset for pagination.

How it works:

  • All parameters in query_params are automatically validated at startup.
  • Only the above parameters are allowed. Invalid parameters will cause the program to stop with an error.

3. Process taxonKey list and resolve taxonKeys

from anhaltai.gbif_downloader.tree_list_processor import TreeListProcessor

processor = TreeListProcessor(input_path="data/tree_list.xlsx",
                              sheet_name="Gehรถlzarten", taxon="speciesKey")
processor.process_tree_list(output_path="data/species_key.csv")

4. Download media and metadata from GBIF

Run the main program:

PYTHONPATH=src python3 src/anhaltai/gbif_extractor/main.py

Note:

  • MinIO credentials must be set in .env see .env-example for the required format.
  • Log files are automatically saved in persistent Volume mnt/logs/.
  • Parallel processing and uploads are controlled by a configurable thread limit.
  • The program will skip old entries if crawl_new_entries is set to True.

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