EndoReg-DB
EndoReg-DB helps clinical teams manage endoscopy data and prepare it for research. It is a reusable Django application with shared data models, terminology, report and video processing, and authenticated APIs.
Start with the project overview. Then follow the contributor roadmap to explore the system, set it up locally, and choose a contribution.
Quick start
This checkout uses Python 3.12, uv, and the environment in devenv.nix.
From the repository root:
direnv allow
devenv tasks run agent:sync
uv run python manage.py migrate
uv run python manage.py setup_endoreg_db
setup_endoreg_db loads base data and runs setup checks. To load base data
separately, use load_base_db_data as described in the
configuration guide. That guide also covers
environment variables, deployment roles, and protected storage.
Explore and contribute
| Your goal | Start here |
|---|---|
| Understand the project | Capabilities and deployment roles |
| Make a first contribution | Contributor roadmap |
| Explore development areas | Project development |
| Integrate an application | API, access, and security |
| Run a deployment | Deployment and operations |
| Try the data models | Django shell examples |
| Check feature progress | Feature tracker |
Development
Run the fast test lane:
devenv tasks run test:fast
Read AGENTS.md for contribution rules and required checks. The documentation index links to guides, contracts, and runbooks.
Data handling
Local watchers and authenticated APIs use shared import services. Applications access media through center-scoped APIs. Deployments provide encrypted storage as required by their storage profile.
Read the privacy guide and video storage contract before changing these workflows. See backup and recovery for recovery procedures.
Repository map
| Path | Contents |
|---|---|
endoreg_db/ |
Application, services, models, commands, and seed data |
docs/ |
Architecture, APIs, guides, and runbooks |
setup/ |
Configuration, privacy, and AI setup |
feature-tracking/ |
Feature scope, acceptance criteria, and verification evidence |
tests/ |
Automated tests grouped by application area |
scripts/ |
Repository tools and checks; GPU diagnostics are in diagnostics/ |
workflow/ |
Reusable workflow profiles |
Further reading: AI model setup, companion tools, historical Wiki references, and license.
Metadata
Release files for endoreg-db 1.6.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| endoreg_db-1.6.0.tar.gz | 1.5 MB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| endoreg_db-1.6.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl | CPython 3.12 | CPython 3.12 | Linux glibc 2.17+ x86-64 | Details |
Total release size: 4.1 MB
Release files / endoreg_db-1.6.0.tar.gz
| Download URL | endoreg_db-1.6.0.tar.gz |
|---|---|
| Size | 1.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
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|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.14
|
Release files / endoreg_db-1.6.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
| Download URL | endoreg_db-1.6.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl |
|---|---|
| Size | 2.6 MB |
| Tags | CPython 3.12 Linux glibc 2.17+ x86-64 |
|
SHA-256 checksum How to use checksums |
59dea732d0625d0b29e8a5aad8b177901ee63411b7a8dc631d74bc6a6bcc4404
|
|
BLAKE2b-256 checksum How to use checksums |
bbfbfc3409d7ea153295e1ca8425771285b8124bb0854d5550bec47c12cab214
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.14
|
Security for endoreg-db 1.6.0
Provenance
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No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
