spyql
yq
spyql | yq | |
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23 | 66 | |
902 | 10,802 | |
- | - | |
0.0 | 9.2 | |
over 1 year ago | 9 days ago | |
Jupyter Notebook | Go | |
MIT License | MIT License |
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spyql
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Fq: Jq for Binary Formats
I prefer a SQL-like format. It’s not as complete but it cover most of the day-to-day use cases. Take a look at https://github.com/dcmoura/spyql (I am the author). Congrats on fq!
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Command-line data analytics made easy with SPyQL
SPyQL documentation: spyql.readthedocs.io
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This Week In Python
spyql – Query data on the command line with SQL-like SELECTs powered by Python expressions
- Command-line data analytics made easy
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Jc – JSONifies the output of many CLI tools
This is great!
I am the author of SPyQL [1]. Combining JC with SPyQL you can easily query the json output and run python commands on top of it from the command-line :-) You can do aggregations and so forth in a much simpler and intuitive way than with jq.
I just wrote a blogpost [2] that illustrates it. It is more focused on CSV, but the commands would be the same if you were working with JSON.
[1] https://github.com/dcmoura/spyql
- The fastest command-line tools for querying large JSON datasets
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Working with more than 10gb csv
You can import the data into a PostgreSQL/MySQL/SQLite/... database and then query the database. However, even with the right choice of indexes, it might take a while to run queries on a table with hundreds of millions of records. You can easily import your data to these databases with SpyQL: $ spyql "SELECT * FROM csv TO sql(table=my_table_name) | sqlite3 my.db" (you would need to create the table my_table_name before running the command).
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ClickHouse Cloud is now in Public Beta
https://github.com/dcmoura/spyql/blob/master/notebooks/json_...
And ClickHouse looks like a normal relational database - there is no need for multiple components for different tiers (like in Druid), no need for manual partitioning into "daily", "hourly" tables (like you do in Spark and Bigquery), no need for lambda architecture... It's refreshing how something can be both simple and fast.
- A SQLite extension for reading large files line-by-line
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I want to convert a large JSON file into Tabular Format.
I thought this library was pretty nifty for json. It's also relatively fast compared to most json parsers: https://github.com/dcmoura/spyql
yq
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Show HN: Flatito, grep for YAML and JSON files
What I often use to just get the full key paths is yq (https://github.com/mikefarah/yq), piping into grep when necessary
yq -o=props
- K8s Service Meshes: The Bill Comes Due
- Using facts and the GitHub API in Ansible
- FLaNK 25 December 2023
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Command line tools I always install on Ubuntu servers
For more information about this command visit https://github.com/mikefarah/yq
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Runtime error with plugin that uses io.popen to run executable during plugin startup
I've been trying to install and config a plugin (papis.nvim) for a couple of days and am having issues with a function that uses io.popen to run yq to convert yaml files to json. I know my install of yq is fine- I can run yq -oj info.yaml from the command line with no issue and it produces the correct json output. I know the function can find the yq executable, but it returns nil. I've saved the error from the yq golang code: panic: runtime error: invalid memory address or nil pointer dereference
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Jaq – A jq clone focused on correctness, speed, and simplicity
- yq has no if-then-else https://github.com/mikefarah/yq/issues/95 which is a poor design (or omission) in my opinion
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HTTPie Desktop: cross-platform API testing client for humans
After which, I use openapi-generator to make a yaml output.
https://gist.github.com/freshteapot/3637e8d2b5ecdf01b7d25246...
- yq version 3.4.1 (Worth noting, the example uses an out of date yq, so a few modifictaions might be needed)
https://github.com/mikefarah/yq
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jq 1.7
For those pining for a similar yaml query tool for working through acres of config: https://github.com/mikefarah/yq
jq is awesome and thanks to the new team for their recent efforts and energy, it massively appreciated.
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That's a Lot of YAML
For anyone looking for such a script, there's some CLIs that make it easy. One is `yq -o props` [1], another way is to use `yq -j` or `yj` [2] to convert to JSON and pipe it to `gron` [3].
[1] https://github.com/mikefarah/yq
[2] https://github.com/sclevine/yj
[3] https://github.com/tomnomnom/gron
What are some alternatives?
prql - PRQL is a modern language for transforming data — a simple, powerful, pipelined SQL replacement
yq - Command-line YAML, XML, TOML processor - jq wrapper for YAML/XML/TOML documents
malloy - Malloy is an experimental language for describing data relationships and transformations.
jq - Command-line JSON processor [Moved to: https://github.com/jqlang/jq]
tresql - Shorthand SQL/JDBC wrapper language, providing nested results as JSON and more
yaml.nvim - 🍒 YAML toolkit for Neovim users
Preql - An interpreted relational query language that compiles to SQL.
csvq - SQL-like query language for csv
prosto - Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby
oq - A performant, and portable jq wrapper to facilitate the consumption and output of formats other than JSON; using jq filters to transform the data.
pxi - 🧚 pxi (pixie) is a small, fast, and magical command-line data processor similar to jq, mlr, and awk.
miller - Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON