https://github.com/pedroh183/asyncvssync
This project contains a small FastAPI application backed by a PostgreSQL database and a pair of benchmark clients used to compare synchronous and asynchronous HTTP requests.
https://github.com/pedroh183/asyncvssync
async asyncio asyncpg fastapi postgresql sync
Last synced: 9 days ago
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This project contains a small FastAPI application backed by a PostgreSQL database and a pair of benchmark clients used to compare synchronous and asynchronous HTTP requests.
- Host: GitHub
- URL: https://github.com/pedroh183/asyncvssync
- Owner: PedroH183
- Created: 2025-06-29T01:20:58.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-06-29T19:33:43.000Z (10 months ago)
- Last Synced: 2025-06-29T19:36:55.489Z (10 months ago)
- Topics: async, asyncio, asyncpg, fastapi, postgresql, sync
- Language: Python
- Homepage:
- Size: 13.7 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Async vs Sync Benchmark
This project contains a small FastAPI application backed by a PostgreSQL database and a pair of benchmark clients used to compare synchronous and asynchronous HTTP requests. It can be used to observe latency and throughput differences when making many concurrent requests.
## Results
### Sync
### Async
## Requirements
- Python 3.13+
- PostgreSQL database
The project dependencies are declared in `pyproject.toml`. Install them with `pip`:
```bash
pip install -r uv.lock
```
## Environment Variables
The database connection details are provided through environment variables:
- `DATABASE_URL` – connection string used by the application
- `DB_NAME`, `DB_USER`, `DB_PASSWORD`, `DB_HOST`, `DB_PORT` – used by the data population script
Create a `.env` file or export the variables in your shell before running the code.
## Running the Application
Start the FastAPI server with `uvicorn`:
```bash
uvicorn main:app --reload
```
The service exposes a single endpoint:
- `GET /clientes/{id}` – returns a client record from the database
## Populating Sample Data
Use the `generator_fake_clients.py` script to seed the database with sample clients:
```bash
python generator_fake_clients.py
```
## Benchmark Clients
Two benchmark scripts are provided:
- `benchmark_client_async.py` – performs requests using `httpx.AsyncClient`
- `benchmark_client_sync.py` – performs requests using `requests`
Each script will issue 10,000 requests against the running API and print throughput and latency metrics.
Run them with:
```bash
python benchmark_client_async.py
```
```bash
python benchmark_client_sync.py
```
Compare the output numbers to evaluate the performance differences between asynchronous and synchronous requests.