| Name | data7 JSON |
| Version |
0.12.1
JSON |
| download |
| home_page | None |
| Summary | Data7 streams CSV/Parquet datasets over HTTP from SQL queries. |
| upload_time | 2025-07-24 08:44:46 |
| maintainer | None |
| docs_url | None |
| author | Julien Maupetit |
| requires_python | <4.0,>=3.11 |
| license | MIT |
| keywords |
database
dataset
sql
parquet
csv
http
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Data7 ⚡ Open your data in minutes
> Pronounced data·set (**7** like **sept** in French).
## The idea 💡
**TL;DR** Data7 is a high performance web server that generates dynamic datasets
(in [CSV](https://en.wikipedia.org/wiki/Comma-separated_values) or
[Parquet](https://en.wikipedia.org/wiki/Apache_Parquet) formats) from existing
databases and streams them over HTTP 🎉
## A quick example
Let say you have a `restaurant` table in your PostgreSQL database, and you want
to make this table an always-up-to-date dataset that can be easily used by the
rest of the world.
All you have to do is to initialize your project:
```sh
data7 init
```
✍️ Edit configuration files:
```yaml
# settings.yaml
production:
host: "https://data7.wonderful-places.org"
port: 80
# .secrets.yaml
production:
DATABASE_URL: "postgresql+asyncpg://user:pass@server:port/wonderful-places"
# data7.yaml
production:
datasets:
- basename: restaurants
query: "SELECT * FROM restaurant"
```
🏎️ Fire up the `data7` server:
```sh
data7 run
```
💥 Your dataset is available at:
- [https://data7.wonderful-places.org/d/restaurants.csv](https://data7.wonderful-places.org/d/restaurants.csv)
(CSV)
- [https://data7.wonderful-places.org/d/restaurants.parquet](https://data7.wonderful-places.org/d/restaurants.parquet)
(Parquet)
## Documentation
The complete documentation of the project is avaiable at:
[https://jmaupetit.github.io/data7/](https://jmaupetit.github.io/data7/)
## License
This work is released under the MIT License.
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