feast.loaders package¶
Submodules¶
feast.loaders.abstract_producer module¶
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class
feast.loaders.abstract_producer.
AbstractProducer
(brokers: str, row_count: int, disable_progress_bar: bool)[source]¶ Bases:
object
Abstract class for Kafka producers
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class
feast.loaders.abstract_producer.
ConfluentProducer
(brokers: str, row_count: int, disable_progress_bar: bool)[source]¶ Bases:
feast.loaders.abstract_producer.AbstractProducer
Concrete implementation of Confluent Kafka producer (confluent-kafka)
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class
feast.loaders.abstract_producer.
KafkaPythonProducer
(brokers: str, row_count: int, disable_progress_bar: bool)[source]¶ Bases:
feast.loaders.abstract_producer.AbstractProducer
Concrete implementation of Python Kafka producer (kafka-python)
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flush
(timeout: Optional[int])[source]¶ Generic flush that implements kafka-python’s flush method.
- Parameters
timeout (Optional[int]) – timeout in seconds to wait for completion.
- Returns
None
- Raises
KafkaTimeoutError – failure to flush buffered records within the provided timeout
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feast.loaders.abstract_producer.
get_producer
(brokers: str, row_count: int, disable_progress_bar: bool) → Union[feast.loaders.abstract_producer.ConfluentProducer, feast.loaders.abstract_producer.KafkaPythonProducer][source]¶ Simple context helper function that returns a AbstractProducer object when invoked.
This helper function will try to import confluent-kafka as a producer first.
This helper function will fallback to kafka-python if it fails to import confluent-kafka.
- Parameters
- Returns
- Concrete implementation of a Kafka producer. Ig can be:
confluent-kafka producer
kafka-python producer
- Return type
Union[ConfluentProducer, KafkaPythonProducer]
feast.loaders.file module¶
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feast.loaders.file.
export_dataframe_to_local
(df: pandas.core.frame.DataFrame, dir_path: Optional[str] = None) → Tuple[str, str, str][source]¶ Exports a pandas DataFrame to the local filesystem.
- Parameters
df (pd.DataFrame) – Pandas DataFrame to save.
dir_path (Optional[str]) – Absolute directory path ‘/data/project/subfolder/’.
- Returns
Tuple of directory path, file name and destination path. The destination path can be obtained by concatenating the directory path and file name.
- Return type
-
feast.loaders.file.
export_source_to_staging_location
(source: Union[pandas.core.frame.DataFrame, str], staging_location_uri: str) → List[str][source]¶ Uploads a DataFrame as an Avro file to a remote staging location.
The local staging location specified in this function is used for E2E tests, please do not use it.
- Parameters
(Union[pd.DataFrame, str] (source) –
Source of data to be staged. Can be a pandas DataFrame or a file path.
- Only four types of source are allowed:
Pandas DataFrame
Local Avro file
GCS Avro file
S3 Avro file
Azure Blob storage Avro file
staging_location_uri (str) –
Remote staging location where DataFrame should be written. .. rubric:: Examples
gs://bucket/path/
s3://bucket/path/
wasbs://bucket@account_name.blob.core.windows.net/path/
- Returns
Returns a list containing the full path to the file(s) in the remote staging location.
- Return type
List[str]
feast.loaders.ingest module¶
feast.loaders.yaml module¶
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feast.loaders.yaml.
yaml_loader
(yml, load_single=False)[source]¶ Loads one or more Feast resources from a YAML path or string. Multiple resources can be divided by three hyphens ‘—’
- Parameters
yml – A path ending in .yaml or .yml, or a YAML string
load_single – Expect only a single YAML resource, fail otherwise
- Returns
Either a single YAML dictionary or a list of YAML dictionaries