roapi
xsv
| roapi | xsv | |
|---|---|---|
| 24 | 64 | |
| 3,080 | 10,089 | |
| 0.8% | - | |
| 6.9 | 0.0 | |
| about 1 month ago | 2 months ago | |
| Rust | Rust | |
| Apache License 2.0 | The Unlicense |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
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
xsv
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Show HN: TextQuery – Query and Visualize Your CSV Data in Minutes
I realize it's not really that comparable since these tools don't support SQL, but a more fully functioned CLI tool is - https://github.com/BurntSushi/xsv
They are both fairly good
- Qsv: Efficient CSV CLI Toolkit
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Joining CSV Data Without SQL: An IP Geolocation Use Case
I have done some similar, simpler data wrangling with xsv (https://github.com/BurntSushi/xsv) and jq. It could process my 800M rows in a couple of minutes (plus the time to read it out from the database =)
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Qsv: CSVs sliced, diced and analyzed (fork of xsv)
xsv, which seems to be why qsv was created.
[1] https://github.com/BurntSushi/xsv/issues/267
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I wrote this iCalendar (.ics) command-line utility to turn common calendar exports into more broadly compatible CSV files.
CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller
- Icsp – Command-line iCalendar (.ics) to CSV parser
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ripgrep is faster than {grep, ag, git grep, ucg, pt, sift}
$ git remote -v origin [email protected]:rust-lang/rust (fetch) origin [email protected]:rust-lang/rust (push) $ git rev-parse HEAD 3b0d4813ab461ec81eab8980bb884691c97c5a35 $ time grep -ri burntsushi ./ ./src/tools/cargotest/main.rs: repo: "https://github.com/BurntSushi/ripgrep", ./src/tools/cargotest/main.rs: repo: "https://github.com/BurntSushi/xsv", grep: ./target/debug/incremental/cargotest-2dvu4f2km9e91/s-gactj3ma2j-1b10l4z-2l60ur55ixe6n/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-38cpmhhbdgdyq/s-gactj3luwq-1o12vgp-t61hd8qdyp7t/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-17632op6djxne/s-gawuq5468i-1h69nfw-4gm0s8yhhiun/query-cache.bin: binary file matches grep: ./target/debug/incremental/cargotest-2trm4kt5yom3r/s-gawuq53qqg-bjiezj-lo0gha8ign8w/query-cache.bin: binary file matches grep: ./target/debug/deps/libregex_automata-c74a6d9fd0abd77b.rmeta: binary file matches grep: ./target/debug/deps/libsame_file-a0e0363a2985455d.rlib: binary file matches grep: ./target/debug/deps/libsame_file-a0e0363a2985455d.rmeta: binary file matches grep: ./target/debug/deps/libsame_file-7251d8d3586a319b.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-sysroot/lib/rustlib/x86_64-unknown-linux-gnu/lib/libaho_corasick-999a08e2b700420d.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-sysroot/lib/rustlib/x86_64-unknown-linux-gnu/lib/libregex_automata-0d168be5d25b3ac5.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libregex_automata-7d6bec0156f15da1.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libregex_automata-7d6bec0156f15da1.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-07dee4514b87d99b.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-tools/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-07dee4514b87d99b.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-999a08e2b700420d.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libaho_corasick-999a08e2b700420d.rmeta: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libregex_automata-0d168be5d25b3ac5.rlib: binary file matches grep: ./build/x86_64-unknown-linux-gnu/stage0-rustc/x86_64-unknown-linux-gnu/release/deps/libregex_automata-0d168be5d25b3ac5.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libaho_corasick-992e1ba08ef83436.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libignore-54d41239d2761852.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libsame_file-9a5e3ddd89cfe599.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libregex_automata-8e700951c9869a66.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libignore-54d41239d2761852.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libaho_corasick-992e1ba08ef83436.rlib: binary file matches grep: ./build/bootstrap/debug/deps/libregex_automata-8e700951c9869a66.rmeta: binary file matches grep: ./build/bootstrap/debug/deps/libsame_file-9a5e3ddd89cfe599.rmeta: binary file matches real 16.683 user 15.793 sys 0.878 maxmem 8 MB faults 0
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Any Linux admins willing to try Pygrep?
Unrelated, are you the same burntsushi that wrote xsv?
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Analyzing multi-gigabyte JSON files locally
If it could be tabular in nature, maybe convert to sqlite3 so you can make use of indexing, or CSV to make use of high-performance tools like xsv or zsv (the latter of which I'm an author).
https://github.com/BurntSushi/xsv
https://github.com/liquidaty/zsv/blob/main/docs/csv_json_sql...
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What monitoring tool do you use or recommend?
Oh and there's rad cli shit out there for CSV files too, like xsv
What are some alternatives?
php-parquet - PHP implementation for reading and writing Apache Parquet files/streams. NOTICE: Please migrate to https://github.com/codename-hub/php-parquet.
csvtk - A cross-platform, efficient and practical CSV/TSV toolkit in Golang
qframe - Immutable data frame for Go
miller - Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
materialize - The data warehouse for operational workloads.
ripgrep - ripgrep recursively searches directories for a regex pattern while respecting your gitignore
delta-rs - A native Rust library for Delta Lake, with bindings into Python
Servo - Servo, the embeddable, independent, memory-safe, modular, parallel web rendering engine
fluvio - Lean and mean distributed stream processing system written in rust and web assembly.
Fractalide - Reusable Reproducible Composable Software
datasette - An open source multi-tool for exploring and publishing data
svgcleaner - svgcleaner could help you to clean up your SVG files from the unnecessary data.