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there is https://github.com/mikefarah/yq which is jq for yaml
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And if you don't like jq syntax, here's how you can use JSON in Bash using jello, a tool I wrote that works very similarly to jq but uses pure Python syntax:
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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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.
yq is great and so is dasel. Dasel is nice because it works uniformly across input types.
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miller
Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
Another tool I've been meaning to get better at is mlr, which is a format-agnostic data viewing/manipulation cli tool. I hadn't heard of dasel before today. Had you heard of mlr, and if so, how would you compare dasel and mlr? While I would love to LEARNALLTHETOOLS, my brain doesn't have room for that many.
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I just found https://github.com/mithrandie/csvq which is SQL for CSV files, which I thought was pretty cool.
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https://jmespath.org/ (used by the AWS CLI tools)
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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Thanks again for the jq writeup and for the dasel pointer. I'll be adding dasel to my mental shortlist of tools to learn. Which is not such a short list....
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I found this last week for CSV https://github.com/BurntSushi/xsv of course *after* spending several hours manipulating them by hand