Function query

query function can perform a query on a dataset.

Parameters description for query():

Name	Type	Description	Default
datastore	string	A backend datastore, i.e., `'rdflib'` or `'duckdb'`	REQUIRED
dataset	string OR `DuckPyConnection` object OR `GeistGraph` object	(1) A string indicates the name of the dataset stored on disk OR (2) a `DuckPyConnection` object OR a `GeistGraph` object for dataset in memory	REQUIRED
inputfile	string	File containing the query	REQUIRED
isinputpath	bool	True if the inputfile is the file path, otherwise the inputfile is the content	REQUIRED
hasoutput	bool	True to store the query results as a CSV file or print them out	REQUIRED
config	dict	A dictionary with configurations when `hasoutput=True`	see below

Description for the config parameter:

Name	Type	Description	Default
outputroot	string	Path of the directory to store the query results	`'./'`
outputfile	string	Path of the file to store the query results	`None`

Example 1: all rows of the df table in test dataset on disk (query from a string)

There exist a file with the path of .geistdata/duckdb/test.duckdb. The following code returns a Pandas data frame named res with query results, and a DuckPyConnection object.

import geist

# Query the df table of the test dataset
(res, conn) = geist.query(datastore='duckdb', dataset='test', inputfile="SELECT * FROM df;", isinputpath=False, hasoutput=False)

Example 2: all rows of the df table in test dataset on disk (query from a file)

There exist a file with the path of .geistdata/duckdb/test.duckdb. The following code returns a Pandas data frame named res with query results, and a DuckPyConnection object.

Here is the query.txt file:

SELECT * FROM df;

Code:

import geist

# Query the df table of the test dataset
(res, conn) = geist.query(datastore='duckdb', dataset='test', inputfile="query.txt", isinputpath=True, hasoutput=False)

Example 3: all rows of the df table in test dataset in memory (query from a string)

Suppose conn is a DuckPyConnection object points to a DuckDB dataset in memory. The following code returns a Pandas data frame named res with query results, and the same DuckPyConnection object.

import geist

# Query the df table of the test dataset
(res, conn) = geist.query(datastore='duckdb', dataset=conn, inputfile="SELECT * FROM df;", isinputpath=False, hasoutput=False)

Example 4: all rows of the df table in test dataset in memory (query from a file)

Suppose conn is a DuckPyConnection object points to a DuckDB dataset in memory. The following code returns a Pandas data frame named res with query results, and the same DuckPyConnection object.

Here is the query.txt file:

SELECT * FROM df;

Code:

import geist

# Query the df table of the test dataset
(res, conn) = geist.query(datastore='duckdb', dataset=conn, inputfile="query.txt", isinputpath=True, hasoutput=False)