clirunner VS q

I love Click for building Python command line interfaces (CLI). One useful feature Click provides is a CliRunner() helper class for testing. CliRunner invokes the script in an isolated environment allowing you to pass arguments, etc. Occasionally I work on projects that don't use Click. For example, if I want to provide a python3 -m packagename script that is ancillary to the primary use case and don't want to include Click as a dependency or want something that can be distributes as a stand-alone script without dependencies. In this case I'd usually use argparse. However, CLIs built with argparse (or old-fashioned manual sys.argv parsing) aren't nearly as easy to test. Thus I created clirunner which is a port of Click's test helper to work with non-Click apps. The API is compatible with Click's CliRunner so if you ever move a project to use Click, the tests should need little to no modification.

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