emrichen
csvq
| emrichen | csvq | |
|---|---|---|
| 2 | 14 | |
| 103 | 1,450 | |
| 1.9% | - | |
| 4.4 | 2.7 | |
| 12 months ago | 5 months ago | |
| Python | Go | |
| MIT License | MIT License |
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emrichen
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Yq is a portable yq: command-line YAML, JSON, XML, CSV and properties processor
Templating yaml with a text templating language like Helm's templating language is a terrible idea. Templating objects and serializing them to Yaml (with input also being Yaml) I find quite nice: https://github.com/con2/emrichen
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docker compose in production - ideas
I was actually thinking the same thing, I'm tired of copy/pasting the compose files every time and changing but a few lines. Like a Helm template engine of sorts. I stumbled upon https://github.com/con2/emrichen some months ago for that very purpose.
csvq
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Fx – Terminal JSON Viewer
sure can do, if you already use that shell [1], but personally I like specific tools for specific jobs such as jq [2], fx, csvq [3] etc, there's value in decoupling shells from utils (modularity, speed, innovation etc).
[1] I don't but tempted to try, like its data-types concept
[2] https://jqlang.github.io/jq/
[3] https://github.com/mithrandie/csvq
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Tool to interact with CSV
csvq
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Can SQL be used without an RDBMS?
There is a way of running SQL-like queries against CSV files.
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Yq is a portable yq: command-line YAML, JSON, XML, CSV and properties processor
Lately I have had to do a lot of flat file analysis and tools along these lines have been a godsend. Will check this out.
My go to lately has been csvq (https://mithrandie.github.io/csvq/). Really nice to be able run complicated selects right over a CSV file with no setup at all.
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Wie fusioniert man CSV tables?
csvq (https://mithrandie.github.io/csvq/)
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Tool to explore big data sets
I usually do this with awk, my largest target files being half a TB in size for a project last year (and far too large to hold entirely in RAM). There are some other utilities like csvq and csvsql both of which let you write SQL-style queries against CSV files, but I'm not sure how they perform on large files. There's a nice list of CSV manipulation tools too if any of those jog your memory.
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sqly - execute SQL against CSV / JSON with shell
Apparently, there were many who thought the same thing; Tools to execute SQL against CSV were trdsql, q, csvq, TextQL. They were highly functional, hoewver, had many options and no input completion. I found it just a little difficult to use.
- One-liner for running queries against CSV files with SQLite
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Most efficient way to query .CSV files for Mac?
Please check out this tool https://github.com/mithrandie/csvq
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Looking for: library to turn SQL (or abstracted) to code & execute against custom backend (slice of structs)
If you are looking to query nondb data with sql statements then you may want to check something like https://github.com/mithrandie/csvq (SQL for csv).
What are some alternatives?
gojq - Pure Go implementation of jq
querycsv - QueryCSV enables you to load CSV files and manipulate them using SQL queries then after you finish you can export the new values to a CSV file
dasel - Select, put and delete data from JSON, TOML, YAML, XML and CSV files with a single tool. Supports conversion between formats and can be used as a Go package.
q - q - Run SQL directly on delimited files and multi-file sqlite databases
jmespath.spec - JMESPath Specification
yq - yq is a portable command-line YAML, JSON, XML, CSV, TOML and properties processor
aws-cli - Universal Command Line Interface for Amazon Web Services
yq - Command-line YAML, XML, TOML processor - jq wrapper for YAML/XML/TOML documents
zsv - zsv+lib: tabular data swiss-army knife CLI + world's fastest (simd) CSV parser
miller - Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
parsem - Parser for YAML, JSON and NEON templates.
duckdb - DuckDB is an in-process SQL OLAP Database Management System