Skip to main content

Python implementation of the LabCAS data access API with flexible security system.

Project description

LabCAS Backend

Repository containing back-end services and configuration for executing EDRN LabCAS data processing workflows.

Starting the Service

Create a .env file (or specify one with --env) and launch it with labcas-backend. Run labcas-backend --help for more information.

By default, API endpoints are served from the root path, such as /auth. If the service is behind a reverse proxy that keeps a subpath in forwarded requests, set LABCAS_SUBPATH_PREFIX in .env, for example LABCAS_SUBPATH_PREFIX=labcas-backend-data-access-api, to serve endpoints such as /labcas-backend-data-access-api/auth.

Zipperlab Integration

To test sending queries to Zipperlab, first get your JWT (above) then do:

curl --request POST --verbose --insecure \
    --cookie "JasonWebToken=`cat /tmp/jwt`" \
    --header "Authentication: Bearer `cat /tmp/jwt`" \
    --header 'Content-Type: application/x-www-form-urlencoded' \
    --data 'email=hello@a.co&query=id:Pre-diagnostic_PDAC_Images/City_of_Hope/COH_0171/COH_01710003/DICOM/I883*' \
    https://localhost:8444/labcas-backend-data-access-api/zip

Make sure you have Zipperlab running and set its URL in ~/labcas.properties.

If you want to send file IDs instead, do:

curl --request POST --verbose --insecure \
    --cookie "JasonWebToken=`cat /tmp/jwt`" \
    --header "Authentication: Bearer `cat /tmp/jwt`" \
    --header 'Content-Type: application/x-www-form-urlencoded' \
    --data 'email=hello@a.co&id=FILE1&id=FILE2&id=FILE3' \
    https://localhost:8444/labcas-backend-data-access-api/zip

Loading Solr Data

If you have downloaded backups of Solr data you can reload it generally as follows:

curl --insecure --verbose "https://localhost:8984/solr/collections/replication?command=restore&location=$BACKUP_PATH/collections"
curl --insecure --verbose "https://localhost:8984/solr/datasets/replication?command=restore&location=$BACKUP_PATH/datasets"
curl --insecure --verbose "https://localhost:8984/solr/files/replication?command=restore&location=$BACKUP_PATH/files"

Replace $BACKUP_PATH with the location of the downloaded backups.# LabCAS Backend (Python)

This package is the Python rewrite of the LabCAS Data Access API. It mirrors the existing Java functionality while providing a modern FastAPI-based stack with an extensible directory abstraction, Redis-backed session management, and a pluggable search layer.

Development

python -m venv .venv
source .venv/bin/activate
pip install --upgrade pip
pip install --editable .
labcas-backend --help

Create a .env file based on env.example before running the service or tests.

Solr Migration

This guide explains how to export data from your old Solr instance (https://localhost:8984/solr) and import it into a newer Solr instance.

The migration is handled by the migrate-solr console script, which is part of the jpl.labcas.backend package. After installing the package, you can use migrate-solr directly.

Prerequisites

  • Python 3.13+ (as required by the package)
  • The jpl.labcas.backend package installed (includes required dependencies like httpx and tqdm)

Quick Start

The migration tool operates in two modes: export (to save cores to files) and import (to load cores from files).

Export Mode

# Export all cores from a Solr instance
migrate-solr --mode export https://localhost:8984/solr

# Export specific cores only
migrate-solr --mode export https://localhost:8984/solr --cores collections,datasets

# Specify backup directory (default: /tmp/solr-backup-<timestamp>)
migrate-solr --mode export https://localhost:8984/solr --backup-dir /path/to/backup

Import Mode

# Import all cores into a Solr instance (from current directory)
migrate-solr --mode import https://newhost:8983/solr

# Import from a specific backup directory
migrate-solr --mode import https://newhost:8983/solr --backup-dir /tmp/solr-backup-20240101-120000

# Import specific cores only
migrate-solr --mode import https://newhost:8983/solr --backup-dir /tmp/solr-backup-20240101-120000 --cores collections,datasets

Your Solr Cores

The LabCAS Solr engine has the following cores:

  • collections - Collection metadata
  • datasets - Dataset metadata
  • files - File metadata
  • userdata - User data

Migration Process

The migration process consists of two phases:

1. Export Phase

  • Connects to your old Solr instance
  • Exports all documents from each core using cursorMark pagination
  • Saves data as JSON files in the backup directory

2. Import Phase

  • Connects to your new Solr instance
  • Imports documents into corresponding cores
  • Commits changes after import

Important Notes

Before Migration

  1. Create cores in new Solr: The new Solr instance must have the cores created first. You can:

    • Copy the core configuration from solr/src/main/resources/solr-home/ to your new Solr instance
    • Or use the Solr Admin UI: http://newhost:8983/solr/admin/cores?action=CREATE&name=<core>&instanceDir=<core>
  2. Schema compatibility: Ensure the schema.xml files are compatible between old and new Solr versions. You may need to update field types or configurations.

  3. Backup first: Always backup your data before migration!

During Migration

  • The tool will prompt you if a core doesn't exist in the target instance
  • Large cores may take significant time to export/import
  • Progress is shown during the process with progress bars

After Migration

  1. Verify data: Check document counts match:

    curl "https://oldhost:8984/solr/collections/select?q=*:*&rows=0"
    curl "https://newhost:8983/solr/collections/select?q=*:*&rows=0"
    
  2. Update configuration: Update your application's LABCAS_SOLR_URL environment variable

  3. Test thoroughly: Run your application tests to ensure everything works

Alternative: Using Solr Backup API

For very large datasets, you might prefer using Solr's built-in backup API:

Export (on old Solr)

# For each core
curl "https://localhost:8984/solr/collections/replication?command=backup&location=/path/to/backup"

Import (on new Solr)

# Copy backup files to new Solr server, then restore
curl "https://newhost:8983/solr/collections/replication?command=restore&location=/path/to/backup"

Note: This method requires filesystem access to both Solr servers and the cores must have identical configurations.

Troubleshooting

SSL Certificate Errors

If you get SSL errors, the tool skips verification by default. Use --verify-ssl if you want to verify certificates.

Core Not Found

If a core doesn't exist in the new instance, the script will prompt you to create it. Make sure to:

  1. Copy the conf/ directory from the old core
  2. Create the core using Solr Admin API or UI
  3. Then continue with the import

Large Datasets

For very large cores (>1M documents), consider:

  • Running exports during off-peak hours
  • Running export and import separately (export first, then import in a separate command)
  • The tool processes documents in batches of 1000 to manage memory efficiently

Memory Issues

If you encounter memory issues:

  • The tool processes documents in batches of 1000
  • Consider migrating one core at a time using the --cores option
  • Ensure sufficient disk space for backup files

Support

For issues or questions, check:

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jpl_labcas_backend-2.0.0.tar.gz (235.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

jpl_labcas_backend-2.0.0-py3-none-any.whl (51.5 kB view details)

Uploaded Python 3

File details

Details for the file jpl_labcas_backend-2.0.0.tar.gz.

File metadata

  • Download URL: jpl_labcas_backend-2.0.0.tar.gz
  • Upload date:
  • Size: 235.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for jpl_labcas_backend-2.0.0.tar.gz
Algorithm Hash digest
SHA256 7b3439cbbc4acd1c2991c92761d3b25a50a202258583dde144540107030a9350
MD5 81426bade04abe6e5e372e877f774699
BLAKE2b-256 e0f3a834373bc1d1873f0e285af9dec99c3c0d8a3b133374fe104aacbe610e56

See more details on using hashes here.

File details

Details for the file jpl_labcas_backend-2.0.0-py3-none-any.whl.

File metadata

File hashes

Hashes for jpl_labcas_backend-2.0.0-py3-none-any.whl
Algorithm Hash digest
SHA256 0380ed84878e981b4c3400bf6e01e9679e1823086e5050b334870d4af91329f3
MD5 30f6ef24a614d1fec931a0fb675f0645
BLAKE2b-256 f4b989b370640a977b44c26f5377b8972b2ac64283c6cab1932c7a44e9c3990d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page