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Rainbow Query Language

Project description

RBQL is an eval-based SQL-like query engine for (not only) CSV file processing. It provides SQL-like language that supports SELECT queries with Python expressions.
RBQL is best suited for data transformation, data cleaning, and analytical queries.

Official Site

Using RBQL as a Python library

If you want to use rbql module as a python library for your own app - please read API Documentation

Using RBQL as a CLI App


$ pip install rbql

Usage example (non-interactive mode):

$ rbql-py --query "select a1, a2 order by a1" --delim , < input.csv

Usage example (interactive mode):

In interactive mode rbql-py will show input table preview so it is easier to type SQL-like query.

$ rbql-py --input input.csv --output result.csv

Main Features

  • Use Python expressions inside SELECT, UPDATE, WHERE and ORDER BY statements
  • Supports multiple input formats
  • Result set of any query immediately becomes a first-class table on its own
  • No need to provide FROM statement in the query - input table is defined by the current context
  • Supports all main SQL keywords
  • Supports aggregate functions and GROUP BY queries
  • Supports user-defined functions (UDF)
  • Provides some new useful query modes which traditional SQL engines do not have
  • Lightweight, dependency-free, works out of the box


  • RBQL doesn't support nested queries, but they can be emulated with consecutive queries
  • Number of tables in all JOIN queries is always 2 (input table and join table), use consecutive queries to join 3 or more tables

Supported SQL Keywords (Keywords are case insensitive)

  • ORDER BY ... [ DESC | ASC ]
  • TOP N

All keywords have the same meaning as in SQL queries. You can check them online

RBQL variables

RBQL for CSV files provides the following variables which you can use in your queries:

  • a1, a2,..., a{N}
    Variable type: string
    Description: value of i-th field in the current record in input table
  • b1, b2,..., b{N}
    Variable type: string
    Description: value of i-th field in the current record in join table B
  • NR
    Variable type: integer
    Description: Record number (1-based)
  • NF
    Variable type: integer
    Description: Number of fields in the current record
  •, b.Person_age, ... a.{Good_alphanumeric_column_name}
    Variable type: string
    Description: Value of the field referenced by it's "name". You can use this notation if the field in the first (header) CSV line has a "good" alphanumeric name
  • a["object id"], a['9.12341234'], b["%$ !! 10 20"] ... a["Arbitrary column name!"]
    Variable type: string
    Description: Value of the field referenced by it's "name". You can use this notation to reference fields by arbitrary values in the first (header) CSV line, even when there is no header at all


  • You can mix all variable types in a single query, example: select a1, b2 JOIN /path/to/b.csv ON a['Item Id'] == b.Identifier WHERE NR > 1 and int(a.Weight) * 100 > int(b["weight of the item"])
  • Referencing fields by header names does not automatically skip the header line (you can use where NR > 1 trick to skip it)
  • If you want to use RBQL as a library for your own app you can define your own custom variables and do not have to support the above mentioned CSV-related variables.

UPDATE statement

UPDATE query produces a new table where original values are replaced according to the UPDATE expression, so it can also be considered a special type of SELECT query. This prevents accidental data loss from poorly written queries.
UPDATE SET is synonym to UPDATE, because in RBQL there is no need to specify the source table.

Aggregate functions and queries

RBQL supports the following aggregate functions, which can also be used with GROUP BY keyword:

Limitation: aggregate functions inside Python expressions are not supported. Although you can use expressions inside aggregate functions.
E.g. MAX(float(a1) / 1000) - valid; MAX(a1) / 1000 - invalid.
There is a workaround for the limitation above for ARRAY_AGG function which supports an optional parameter - a callback function that can do something with the aggregated array. Example:
select a2, ARRAY_AGG(a1, lambda v: sorted(v)[:5]) group by a2

JOIN statements

Join table B can be referenced either by its file path or by its name - an arbitrary string which the user should provide before executing the JOIN query.
RBQL supports STRICT LEFT JOIN which is like LEFT JOIN, but generates an error if any key in the left table "A" doesn't have exactly one matching key in the right table "B".
Limitation: JOIN statements can't contain Python/JS expressions and must have the following form: <JOIN_KEYWORD> (/path/to/table.tsv | table_name ) ON a... == b... [AND a... == b... [AND ... ]]


SELECT EXCEPT can be used to select everything except specific columns. E.g. to select everything but columns 2 and 4, run: SELECT * EXCEPT a2, a4
Traditional SQL engines do not support this query mode.

UNNEST() operator

UNNEST(list) takes a list/array as an argument and repeats the output record multiple times - one time for each value from the list argument.
Example: SELECT a1, UNNEST(a2.split(';'))

LIKE() function

RBQL does not support LIKE operator, instead it provides "like()" function which can be used like this: SELECT * where like(a1, 'foo%bar')

User Defined Functions (UDF)

RBQL supports User Defined Functions
You can define custom functions and/or import libraries in a special file:

  • ~/ - for Python

Examples of RBQL queries

With Python expressions

  • select top 100 a1, int(a2) * 10, len(a4) where a1 == "Buy" order by int(a2) desc
  • select * order by random.random() where NR > 1 - skip header record and random sort
  • select len(a.vehicle_price) / 10, a2 where NR > 1 and a['Vehicle type'] in ["car", "plane", "boat"] limit 20 - referencing columns by names from header record, skipping the header and using Python's "in" to emulate SQL's "in"
  • update set a3 = 'NPC' where a3.find('Non-playable character') != -1
  • select NR, * - enumerate records, NR is 1-based
  • select * where re.match(".*ab.*", a1) is not None - select entries where first column has "ab" pattern
  • select a1, b1, b2 inner join ./countries.txt on a2 == b1 order by a1, a3 - example of join query
  • select MAX(a1), MIN(a1) where a.Name != 'John' group by a2, a3 - example of aggregate query
  • select *a1.split(':') - Using Python3 unpack operator to split one column into many. Do not try this with other SQL engines!

RBQL design principles and architecture

RBQL core idea is based on dynamic code generation and execution with exec and eval functions. Here are the main steps that RBQL engine performs when processing a query:

  1. Shallow parsing: split the query into logical expressions such as "SELECT", "WHERE", "ORDER BY", etc.
  2. Embed the expression segments into the main loop template code
  3. Execute the hydrated loop code

Here you can find a very basic working script (only 15 lines of Python code) which implements this idea:

The diagram below gives an overview of the main RBQL components and data flow: RBQL Diagram


How do I skip header record in CSV files?

You can use the following trick: add ... where NR > 1 ... to your query

And if you are doing math operation you can modify your query like this, example:
select int(a3) * 1000, a2 -> select int(a3) * 1000 if NR > 1 else a3, a2


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