Python API Reference¶

Preql¶

class preql.Preql(db_uri: str = 'sqlite://:memory:', print_sql: bool = False, auto_create: bool = False, autocommit: bool = False)¶

Provides an API to run Preql code from Python

Example

>>> import preql
>>> p = preql.Preql()
>>> p('[1, 2]{item+1}')
[2, 3]

__init__(db_uri: str = 'sqlite://:memory:', print_sql: bool = False, auto_create: bool = False, autocommit: bool = False)¶

Initialize a new Preql instance

Parameters:	db_uri (str, optional) – URI of database. Defaults to using a non-persistent memory database. print_sql (bool, optional) – Whether or not to print every SQL query that is executed (default defined in settings)

load(filename, rel_to=None)¶

Load a Preql script

Parameters:	filename (str) – Name of script to run rel_to (Optional[str]) – Path to which `filename` is relative.

import_pandas(**dfs)¶

Import pandas.DataFrame instances into SQL tables

Example

>>> pql.import_pandas(a=df_a, b=df_b)

class preql.api.TablePromise(interp, inst)¶

Returned by Preql whenever the result is a table

Fetching values creates queries to database engine

to_json()¶: Returns table as a list of rows, i.e. [{col1: value, col2: value, ...}, ...]

to_pandas()¶: Returns table as a Pandas dataframe (requires pandas installed)

__eq__(other)¶

Compare the table to a JSON representation of it as list of objects

Essentially: return self.to_json() == other