High_Level Source

async dffml.high_level.source.load(source: BaseSource, *args: str) → AsyncIterator[Record]

Yields records from a source.

Yields all the records from the source, if record keys are given then only those records are yielded.

Parameters:

• source (BaseSource) – Data source to use. See Sources for sources and options.

• *args (str) – Records to be returned. If empty, all the records in a source will be returned.

Returns:

Record object

Return type:

asynciterator

Examples

>>> import asyncio
>>> from dffml import *
>>>
>>> source = CSVSource(filename="load.csv", allowempty=True, readwrite=True)
>>>
>>> async def main():
...     await save(
...         source,
...         Record("1", data={"features": {"A": 0, "B": 1}}),
...         Record("2", data={"features": {"A": 3, "B": 4}}),
...     )
...
...     # All records in source
...     async for record in load(source):
...         print(record.export())
...
...     # For specific records in a source
...     async for record in load(source, "1"):
...         print(record.export())
...
...     # Lightweight source syntax
...     async for record in load("load.csv", "2"):
...         print(record.export())
>>>
>>> asyncio.run(main())
{'key': '1', 'features': {'A': 0, 'B': 1}, 'extra': {}}
{'key': '2', 'features': {'A': 3, 'B': 4}, 'extra': {}}
{'key': '1', 'features': {'A': 0, 'B': 1}, 'extra': {}}
{'key': '2', 'features': {'A': 3, 'B': 4}, 'extra': {}}

async dffml.high_level.source.save(source: BaseSource, *args: Record) → None

Update a source’s knowledge about given records.

For each record given, call update on the source. Effectively saving all the records to the source.

Parameters:

• source (BaseSource) – Data source to use. See Sources for sources and options.

• *args (list) – Records to be saved.

Examples

>>> import asyncio
>>> import pathlib
>>> from dffml import *
>>>
>>> source = CSVSource(filename="save.csv", allowempty=True, readwrite=True)
>>>
>>> async def main():
...     await save(
...         source,
...         Record(
...             "myrecord",
...             data={
...                 "features": {"Years": 0, "Expertise": 1, "Trust": 0.1},
...                 "prediction": {"Salary": {"value": 10, "confidence": 1.0}},
...             }
...         )
...     )
...     print(pathlib.Path("save.csv").read_text().strip())
>>>
>>> asyncio.run(main())
key,tag,Expertise,Trust,Years,prediction_Salary,confidence_Salary
myrecord,untagged,1,0.1,0,10,1.0