def test_table_stores_with_extractor():
document_store = LocalDocumentStore()
document_store.put("test.doc", create_document())
pipeline = Pipeline(document_store, stop_on_exception=False)
pipeline.add_store('output', TableDataStore(columns=['cheese']))
def extractor(document, context):
# An example of how we might
# extract into a dict
#
context.get_store('output').add(['test'])
return document
pipeline.add_step(extractor)
context = pipeline.run()
assert context.get_store('output').count() == 1
def test_table_stores_with_extractor():
document_store = JsonDocumentStore("/tmp/test-json-store",
force_initialize=True)
document_store.add(create_document())
pipeline = Pipeline(document_store, stop_on_exception=False)
pipeline.add_store('output', TableDataStore(columns=['cheese']))
def extractor(document, context):
# An example of how we might
# extract into a dict
#
context.get_store('output').add(['test'])
return document
pipeline.add_step(extractor)
context = pipeline.run()
assert pipeline.context.get_store('output').count() == 1
def test_dict_stores_with_extractor():
document_store = JsonDocumentStore("/tmp/test-json-store",
force_initialize=True)
document_store.add(create_document())
pipeline = Pipeline(document_store, stop_on_exception=False)
pipeline.add_store('output', DictDataStore())
def extractor(document, context):
# An example of how we might
# extract into a dict
#
context.get_store('output').add({'cheese': 'test'})
return document
pipeline.add_step(extractor)
stats = pipeline.run().statistics
assert pipeline.context.get_store('output').count() == 1