datasette-graphql
roapi
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datasette-graphql | roapi | |
---|---|---|
2 | 24 | |
97 | 3,080 | |
- | 2.0% | |
4.1 | 6.9 | |
20 days ago | about 1 month ago | |
Python | Rust | |
Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
datasette-graphql
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Tuql: Automatically create a GraphQL server from a SQLite database
Impressive how little code is involved here! This is really neat.
The biggest feature I can see that's missing is pagination - it looks like this doesn't have a way to retrieve e.g. ten results, then pass a next token to get back the next set.
Here's how I implemented pagination in my similar datasette-graphql plugin (which also gives you a GraphQL API for an existing SQLite database): https://github.com/simonw/datasette-graphql#pagination
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Are there open source projects to view that would help me understand cursors/pagination/edges/nodes & Inmemorycache ?
My source code is here, but it likely won't be much use to you - it's full of weird introspection because I'm trying to make this work against any database table: https://github.com/simonw/datasette-graphql/blob/1.4/datasette_graphql/utils.py
roapi
- Full-fledged APIs for slowly moving datasets without writing code
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Tuql: Automatically create a GraphQL server from a SQLite database
If your use case is read-only I suggest taking a look at roapi[1]. It supports multiple read frontends (GraphQL, SQL, REST) and many backends like SQLite, JSON, google sheets, MySQL, etc.
[1] https://github.com/roapi/roapi
- Who is using AXUM in production?
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Ask HN: Best way to provide access to large data sets
For smaller datasets then anywhere up to a few mb which isn't so bad reasonable with an API but in theory for historic data it could be up to several gb. I've not seen datasette go that high (IIRC it's a 1000 row return limit by default).
That's what got me intrigued with Atlassians offering, as data lakes tend to be something internal to a company, not something I've ever seen offered as an interaction point to users.
I've also tested out roapi [1] which is nice if the data is in some structured format already (Parquet/JSON)
[1] https://github.com/roapi/roapi
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"thread 'main' panicked at 'no CA certificates found'", when running application in docker container
https://github.com/roapi/roapi/issues/103?
- Roapi 0.9 release adds support for all cloud storage providers
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SQLite-based databases on the Postgres protocol? Yes we can
Very cool and well executed project. Love the sprinkle of Rust in all the other companion projects as well :)
The ROAPI(https://github.com/roapi/roapi) project I built also happened to support a similar feature set, i.e. to expose sqlite through a variety of remote query interfaces including pg wire protocols, rest apis and graphqls.
- Using Rust to write a Data Pipeline. Thoughts. Musings.
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PostgREST – Serve a RESTful API from Any Postgres Database
> why not just accept SQL and cut out all the unnecessary mapping?
You might be interested in what we're building: Seafowl, a database designed for running analytical SQL queries straight from the user's browser, with HTTP CDN-friendly caching [0]. It's a second iteration of the Splitgraph DDN [1] which we built on top of PostgreSQL (Seafowl is much faster for this use case, since it's based on Apache DataFusion + Parquet).
The tradeoff for allowing the client to run any SQL vs a limited API is that PostgREST-style queries have a fairly predictable and low overhead, but aren't as powerful as fully-fledged SQL with aggregations, joins, window functions and CTEs, which have their uses in interactive dashboards to reduce the amount of data that has to be processed on the client.
There's also ROAPI [2] which is a read-only SQL API that you can deploy in front of a database / other data source (though in case of using databases as a data source, it's only for tables that fit in memory).
[0] https://seafowl.io/
[1] https://www.splitgraph.com/connect
[2] https://github.com/roapi/roapi
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Command-line data analytics made easy
It could be the NDJSON parser (DF source: [0]) or could be a variety of other factors. Looking at the ROAPI release archive [1], it doesn't ship with the definitive `columnq` binary from your comment, so it could also have something to do with compilation-time flags.
FWIW, we use the Parquet format with DataFusion and get very good speeds similar to DuckDB [2], e.g. 1.5s to run a more complex aggregation query `SELECT date_trunc('month', tpep_pickup_datetime) AS month, COUNT(*) AS total_trips, SUM(total_amount) FROM tripdata GROUP BY 1 ORDER BY 1 ASC)` on a 55M row subset of NY Taxi trip data.
[0]: https://github.com/apache/arrow-datafusion/blob/master/dataf...
[1]: https://github.com/roapi/roapi/releases/tag/roapi-v0.8.0
[2]: https://observablehq.com/@seafowl/benchmarks
What are some alternatives?
datasette-dashboards - Datasette plugin providing data dashboards from metadata
php-parquet - PHP implementation for reading and writing Apache Parquet files/streams. NOTICE: Please migrate to https://github.com/codename-hub/php-parquet.
csvs-to-sqlite - Convert CSV files into a SQLite database
qframe - Immutable data frame for Go
pluralize - Pluralize or singularize any word based on a count
materialize - The data warehouse for operational workloads.
datasette-auth-github - Datasette plugin that authenticates users against GitHub
delta-rs - A native Rust library for Delta Lake, with bindings into Python
madatdata - 😠 📈 Madatdata ("mad at data") is a TypeScript library for managing and querying SQL databases (so far including Seafowl and Splitgraph, but with an interface that makes it easy to add plugins for other databases).
fluvio - Lean and mean distributed stream processing system written in rust and web assembly.
datasette-chatgpt-plugin - A Datasette plugin that turns a Datasette instance into a ChatGPT plugin
datasette - An open source multi-tool for exploring and publishing data