NLDSL documentation¶
Contents:
Installation Instructions¶
This package is available on pip. To install it open a terminal and run:
pip install nldsl
Quick Start¶
NLDSL is a tool to create DSLs for data science, which can be translated into executable code.
A new DSL is created by deriving from the CodeGenerator class and rules are added to it via simple python functions. Besides providing code generation NLDSL allows the user to define DSL-level function, which are then treated as first-class rules. Currently we provide extensions for Pandas and PySpark.
Example
We are going to use the PandasCodeGenerator for this example:
from nldsl import PandasCodeGenerator, grammar
code_gen = PandasCodeGenerator
Define a DSL statement and create executable code:
dsl_stmt = "## x = on df | rename columns old1 to new1, old2 to new2"
python_code = code_gen(dsl_stmt)
Add a new rule to the DSL and use it to create executable code:
new_rule = "#$ my rule $x = rename columns old to $x | drop duplicates"
dsl_stmt = "## x = on df | my rule new"
python_code = code_gen(new_rule + dsl_stmt)
Implement a new rule via python:
def rename_columns(code, args):
col_map = {args[i]:args[i+2] for i in range(0, len(args), 3)}
return code + ".rename(columns={})".format(col_map)
Implement the “rename columns” rule using the @grammar decorator:
@grammar
def rename_columns(code, args):
"""Desc...
Grammar:
rename columns $my_var[$old to $new]
"""
return code + ".rename(columns={})".format(dict(args["my_var"]))
New rule can either be added to a certain instance of code_generator or to the class itself:
code_gen["rename columns"] = rename_columns
PandasCodeGenerator.register_function("rename colummns", rename_columns)