raulrodriguezmesia-blip/automatizacion-convocatorias — explained in plain English
Analysis updated 2026-05-18
Track applications submitted to an academic or administrative call from creation to decision.
Send automatic notifications about a call's status through Slack, Teams, or email.
Monitor service health and request metrics through built in endpoints and Prometheus.
Keep the API responsive when a notification service temporarily fails, using retry and circuit breaker logic.
| raulrodriguezmesia-blip/automatizacion-convocatorias | 0xallam/my-recipe | 0xhassaan/nn-from-scratch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | Python | Python | Python |
| Last pushed | — | 2022-11-22 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | moderate | moderate | moderate |
| Complexity | 3/5 | 2/5 | 4/5 |
| Audience | developer | general | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Docker Desktop and filling in database credentials and JWT keys in an environment file before starting.
This project is a backend system, written in Java using the Spring Boot framework, for managing convocatorias, which are formal calls for applications used by academic institutions and administrative offices, similar to open calls for grants or programs. The README describes it as handling the full lifecycle of a call: setting up the rules for a call, tracking applications in a database with strict data integrity, and sending notifications through channels such as Slack, Teams, and email. The backend follows a layered design that keeps the core business rules separate from technical details like the database or web framework, a pattern often called clean or hexagonal architecture. It stores data in PostgreSQL and uses Redis for caching and for limiting how many requests can be made in a given time window. To keep the service running smoothly when outside systems fail, it includes patterns such as circuit breakers, which stop calling a failing service temporarily, and retry logic with increasing wait times between attempts. For monitoring, the project exposes health check endpoints that report whether the database and Redis connections are working, along with metrics that can be collected by Prometheus, a monitoring tool. Errors are returned in a standardized format following an established web standard for problem details. To run the project, you need Docker Desktop installed. After cloning the repository, you copy an example environment file, fill in your own database credentials and security keys, and then start everything with a single Docker Compose command. The API then becomes available on a local port. The project includes automated tests run through Maven, along with a code quality and coverage check. The README uses ambitious language describing the platform in enterprise terms, though the visible documentation covers a Spring Boot API with the components listed above rather than additional infrastructure. The project currently has no stars.
A Spring Boot backend for managing convocatorias, formal calls for academic or administrative applications, with database tracking and multi-channel notifications.
Mainly Python. The stack also includes Java, Spring Boot, PostgreSQL.
No license information was found in the reviewed material.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
double-check against the repo, no cap.