Load

load feature can import data into an existing dataset on disk or in memory.

You can write a Geist template with the load tag. You can also use CLI or Python API step by step as follows:

CLI: load commandPython API: load functionPython API: load method of the Connection Class

load command can import data into an existing dataset.

There are two subcommands for load:

Usage: geist load [OPTIONS] COMMAND [ARGS]...

Import data into a dataset

Options:
  --help  Show this message and exit.

Commands:
  duckdb  Import data into a SQL dataset
  rdflib  Import data into a RDF dataset

geist load duckdb [OPTIONS]

Usage: geist load duckdb [OPTIONS]

Import data into a SQL dataset

Options:
-d, --dataset TEXT              Name of SQL dataset to load a file (default
                                "kb")
-ifile, --inputfile FILENAME    Path of the file to be loaded as a table
                                [required]
-iformat, --inputformat [csv|json]
                                Format of the file to be loaded as a table
                                (default csv)
-t, --table TEXT                Name of the table to be created  [required]
--help                          Show this message and exit.

Example: load a file into the test dataset

geist load duckdb --dataset test --inputfile test_add.csv --inputformat csv --table df

geist load rdflib [OPTIONS]

Here are options of the load command:

Usage: geist load rdflib [OPTIONS]

Import data into a RDF dataset

Options:
-d, --dataset TEXT              Name of RDF dataset to load a file (default
                                "kb")
-ifile, --inputfile FILENAME    Path of the file to be loaded as triples
                                [required]
-iformat, --inputformat [xml|n3|turtle|nt|pretty-xml|trix|trig|nquads|json-ld|hext|csv]
                                Format of the file to be loaded as triples
                                (default json-ld)
--colnames TEXT                 Column names of triples with the format of
                                [[subject1, predicate1, object1], [subject2,
                                predicate2, object2], ...] when the input
                                format is csv
--help                          Show this message and exit.

Example: load a file into the test dataset

geist load rdflib --dataset test --inputfile test_add.jsonld

load function can import data into an existing 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	Dataset to load an 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 to be loaded	REQUIRED
inputformat	string	Format of the file to be loaded	REQUIRED
isinputpath	bool	`True` if the inputfile is the file path, otherwise the inputfile is the content	REQUIRED
config	dict	A dictionary with configurations for certain backend store	see below

Description for the config parameter:

datastore: duckdb

Name	Type	Description	Default
table	string	Name of the table to be loaded	REQUIRED

Example: load a table into the test dataset

There exist a file with the path of .geistdata/duckdb/test.duckdb. The csv_str will be imported into the df table. Note that the order of table columns should be consistent with the imported data.

import geist

csv_str = """
v1,v2,v3
1,1,1
2,2,2
3,3,3
"""

# Load csv_str to the df table of the test dataset
geist.load(datastore='duckdb', dataset='test', inputfile=csv_str, inputformat='csv', isinputpath=False, config={'table': 'df'})

datastore: rdflib

Name	Type	Description	Default
inmemory	bool	`True` if the new dataset (after loading data) is stored in memory only, otherwise it is stored on disk	`False`
colnames	string	Column names of triples with the format of `[[subject1, predicate1, object1], [subject2, predicate2, object2], ...]`	REQUIRED when `inputformat='csv'`

Example: load a triple into the test dataset

There exist a file with the path of .geistdata/rdflib/test.pkl. The csv_str will be imported into the test RDF dataset.

import geist

csv_str = """
subject,predicate,object
<http://example.com/drewp>,<http://example.com/feels>,"Happy"
"""

# Load csv_str to the df table of the test dataset
geist.load(datastore='rdflib', dataset='test', inputfile=csv_str, inputformat='csv', isinputpath=False, config={"colnames": "[['subject', 'predicate', 'object']]"})

load method of the Connection class imports data into an existing dataset on disk or in memory. It is very similar to the load() function. The only difference is that datastore, dataset, and inmemory parameters do not need to be passed as they have already been specified while initialzing the Connection class.

Parameters description for load method of the Connection class:

Name	Type	Description	Default
inputfile	string	A file to be loaded	REQUIRED
inputformat	string	Format of the file to be loaded	REQUIRED
isinputpath	bool	`True` if the inputfile is the file path, otherwise the inputfile is the content	REQUIRED
config	dict	A dictionary with configurations for certain backend store	see below