jsonparser VS q

In this article, I will introduce you to a new package called astjson that I have been working on for the last couple of weeks. It is a Go package that allows you to transform and merge JSON objects with unmatched speed. It is based on the jsonparser package by buger aka Leonid Bugaev and extends it with the ability to transform and merge JSON objects at unparalleled performance.

Use this to extract the data value, and handle/unmarshal it accordingly.

jsonparser can decode, but can't encode

Best I've found is this: https://github.com/buger/jsonparser

I was actually just trying to get it into a []byte to use this package which claims it works well for unknown data structures.

`jj` is a little tool I wrote that uses https://github.com/buger/jsonparser

If you don't know the schema or you only need to access one or two fields in a much larger JSON object, I would recommend https://github.com/buger/jsonparser as it provides an easy API to access specific values without fully unmarshaling. This is an unusual use case though, 9 times out of 10 I would tend to use easyjson.

Reading and navigating arbitrary JSON: I've used https://github.com/tidwall/gjson, many others like https://github.com/buger/jsonparser are also out there.

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

I think they're talking about https://github.com/harelba/q, which is not very fast.

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.

Hi, author of q here.

Regarding the error you got, q currently does not autodetect headers, so you'd need to add -H as a flag in order to use the "country" column name. You're absolutely correct on failing-fast here - It's a bug which i'll fix.

In general regarding speed - q supports automatic caching of the CSV files (through the "-C readwrite" flag). Once it's activated, it will write the data into another file (with a .qsql extension), and will use it automatically in further queries in order to speed things considerably.

Effectively, the .qsql files are regular sqlite3 files (with some metadata), and q can be used to query them directly (or any regular sqlite3 file), including the ability to seamlessly join between multiple sqlite3 files.

http://harelba.github.io/q/#auto-caching-examples