tresql VS spyql

* https://github.com/mrumkovskis/tresql

I'm really excited about languages that build on or are compiled to SQL, in the long-term (because I think it will take a very long time to build adoption).

The ones that particularly excite me are shorthands for SQL, even though their heavy use of symbols may be a detriment. One particular use case is in easily defining authorization policies.

I am not very excited by datalog/prolog-based languages because I think logic languages are too unnatural to ever go mainstream. But I'd be excited to be wrong or for logic languages to become more friendly.

Here are some others I'm watching.

  * https://github.com/mrumkovskis/tresql

Are there any policy-language-libraries-backed-by-sql like Polar but that aren't based on logic programming languages? I don't really want to learn logic programming for this purpose nor do I want to require it on my coworkers.

I guess I'm just looking for a SQL shorthand that can easily interpolate request variables and session variables but that gets declared in code where a route is declared. Just spitballing but something like `(blogs.id = $req.blogid).userid = $session.userid OR (users.id = $session.userid).isAdmin`.

This [0] is close but it doesn't have enough momentum to be usable in every language you'd want.

[0] https://github.com/mrumkovskis/tresql

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!

SPyQL documentation: spyql.readthedocs.io

spyql – Query data on the command line with SQL-like SELECTs powered by Python expressions

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

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).

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.

I thought this library was pretty nifty for json. It's also relatively fast compared to most json parsers: https://github.com/dcmoura/spyql