This documentation is for an older version (1.4.7) of Dagster. You can view the version of this page from our latest release below.
import hashlib
import inspect
import os
import re
from abc import abstractmethod
from functools import partial
from itertools import chain
from typing import (
Any,
Callable,
Dict,
Iterable,
List,
Mapping,
NamedTuple,
Optional,
Sequence,
Set,
Tuple,
Union,
cast,
)
import yaml
from dagster import (
AssetKey,
AssetOut,
AutoMaterializePolicy,
FreshnessPolicy,
Nothing,
Output,
ResourceDefinition,
SourceAsset,
_check as check,
)
from dagster._core.definitions import AssetsDefinition, multi_asset
from dagster._core.definitions.cacheable_assets import (
AssetsDefinitionCacheableData,
CacheableAssetsDefinition,
)
from dagster._core.definitions.events import CoercibleToAssetKey, CoercibleToAssetKeyPrefix
from dagster._core.definitions.metadata import MetadataValue, TableSchemaMetadataValue
from dagster._core.definitions.metadata.table import TableSchema
from dagster._core.errors import DagsterInvalidDefinitionError, DagsterInvalidInvocationError
from dagster._core.execution.context.init import build_init_resource_context
from dagster._utils.merger import merge_dicts
from dagster_airbyte.resources import AirbyteCloudResource, AirbyteResource, BaseAirbyteResource
from dagster_airbyte.types import AirbyteTableMetadata
from dagster_airbyte.utils import (
generate_materializations,
generate_table_schema,
is_basic_normalization_operation,
)
def _table_to_output_name_fn(table: str) -> str:
return table.replace("-", "_")
def _build_airbyte_asset_defn_metadata(
connection_id: str,
destination_tables: Sequence[str],
table_to_asset_key_fn: Callable[[str], AssetKey],
asset_key_prefix: Optional[Sequence[str]] = None,
normalization_tables: Optional[Mapping[str, Set[str]]] = None,
upstream_assets: Optional[Iterable[AssetKey]] = None,
group_name: Optional[str] = None,
io_manager_key: Optional[str] = None,
schema_by_table_name: Optional[Mapping[str, TableSchema]] = None,
freshness_policy: Optional[FreshnessPolicy] = None,
auto_materialize_policy: Optional[AutoMaterializePolicy] = None,
) -> AssetsDefinitionCacheableData:
asset_key_prefix = (
check.opt_sequence_param(asset_key_prefix, "asset_key_prefix", of_type=str) or []
)
# Generate a list of outputs, the set of destination tables plus any affiliated
# normalization tables
tables = list(
chain.from_iterable(
chain(
[destination_tables], normalization_tables.values() if normalization_tables else []
)
)
)
outputs = {
_table_to_output_name_fn(table): AssetKey(
[*asset_key_prefix, *table_to_asset_key_fn(table).path]
)
for table in tables
}
internal_deps: Dict[str, Set[AssetKey]] = {}
metadata_encodable_normalization_tables = (
{k: list(v) for k, v in normalization_tables.items()} if normalization_tables else {}
)
# If normalization tables are specified, we need to add a dependency from the destination table
# to the affilitated normalization table
if len(metadata_encodable_normalization_tables) > 0:
for base_table, derived_tables in metadata_encodable_normalization_tables.items():
for derived_table in derived_tables:
internal_deps[derived_table] = {
AssetKey([*asset_key_prefix, *table_to_asset_key_fn(base_table).path])
}
# All non-normalization tables depend on any user-provided upstream assets
for table in destination_tables:
internal_deps[table] = set(upstream_assets or [])
return AssetsDefinitionCacheableData(
keys_by_input_name=(
{asset_key.path[-1]: asset_key for asset_key in upstream_assets}
if upstream_assets
else {}
),
keys_by_output_name=outputs,
internal_asset_deps=internal_deps,
group_name=group_name,
key_prefix=asset_key_prefix,
can_subset=False,
metadata_by_output_name=(
{
table: {"table_schema": MetadataValue.table_schema(schema_by_table_name[table])}
for table in tables
}
if schema_by_table_name
else None
),
freshness_policies_by_output_name=(
{output: freshness_policy for output in outputs} if freshness_policy else None
),
auto_materialize_policies_by_output_name=(
{output: auto_materialize_policy for output in outputs}
if auto_materialize_policy
else None
),
extra_metadata={
"connection_id": connection_id,
"group_name": group_name,
"destination_tables": destination_tables,
"normalization_tables": metadata_encodable_normalization_tables,
"io_manager_key": io_manager_key,
},
)
def _build_airbyte_assets_from_metadata(
assets_defn_meta: AssetsDefinitionCacheableData,
resource_defs: Optional[Mapping[str, ResourceDefinition]],
) -> AssetsDefinition:
metadata = cast(Mapping[str, Any], assets_defn_meta.extra_metadata)
connection_id = cast(str, metadata["connection_id"])
group_name = cast(Optional[str], metadata["group_name"])
destination_tables = cast(List[str], metadata["destination_tables"])
normalization_tables = cast(Mapping[str, List[str]], metadata["normalization_tables"])
io_manager_key = cast(Optional[str], metadata["io_manager_key"])
@multi_asset(
name=f"airbyte_sync_{connection_id[:5]}",
deps=list((assets_defn_meta.keys_by_input_name or {}).values()),
outs={
k: AssetOut(
key=v,
metadata=(
{
k: cast(TableSchemaMetadataValue, v)
for k, v in assets_defn_meta.metadata_by_output_name.get(k, {}).items()
}
if assets_defn_meta.metadata_by_output_name
else None
),
io_manager_key=io_manager_key,
freshness_policy=(
assets_defn_meta.freshness_policies_by_output_name.get(k)
if assets_defn_meta.freshness_policies_by_output_name
else None
),
dagster_type=Nothing,
)
for k, v in (assets_defn_meta.keys_by_output_name or {}).items()
},
internal_asset_deps={
k: set(v) for k, v in (assets_defn_meta.internal_asset_deps or {}).items()
},
compute_kind="airbyte",
group_name=group_name,
resource_defs=resource_defs,
)
def _assets(context, airbyte: AirbyteResource):
ab_output = airbyte.sync_and_poll(connection_id=connection_id)
for materialization in generate_materializations(
ab_output, assets_defn_meta.key_prefix or []
):
table_name = materialization.asset_key.path[-1]
if table_name in destination_tables:
yield Output(
value=None,
output_name=_table_to_output_name_fn(table_name),
metadata=materialization.metadata,
)
# Also materialize any normalization tables affiliated with this destination
# e.g. nested objects, lists etc
if normalization_tables:
for dependent_table in normalization_tables.get(table_name, set()):
yield Output(
value=None,
output_name=_table_to_output_name_fn(dependent_table),
)
else:
yield materialization
return _assets
[docs]def build_airbyte_assets(
connection_id: str,
destination_tables: Sequence[str],
asset_key_prefix: Optional[Sequence[str]] = None,
group_name: Optional[str] = None,
normalization_tables: Optional[Mapping[str, Set[str]]] = None,
deps: Optional[Sequence[Union[CoercibleToAssetKey, AssetsDefinition, SourceAsset]]] = None,
upstream_assets: Optional[Set[AssetKey]] = None,
schema_by_table_name: Optional[Mapping[str, TableSchema]] = None,
freshness_policy: Optional[FreshnessPolicy] = None,
) -> Sequence[AssetsDefinition]:
"""Builds a set of assets representing the tables created by an Airbyte sync operation.
Args:
connection_id (str): The Airbyte Connection ID that this op will sync. You can retrieve this
value from the "Connections" tab of a given connector in the Airbyte UI.
destination_tables (List[str]): The names of the tables that you want to be represented
in the Dagster asset graph for this sync. This will generally map to the name of the
stream in Airbyte, unless a stream prefix has been specified in Airbyte.
normalization_tables (Optional[Mapping[str, List[str]]]): If you are using Airbyte's
normalization feature, you may specify a mapping of destination table to a list of
derived tables that will be created by the normalization process.
asset_key_prefix (Optional[List[str]]): A prefix for the asset keys inside this asset.
If left blank, assets will have a key of `AssetKey([table_name])`.
deps (Optional[Sequence[Union[AssetsDefinition, SourceAsset, str, AssetKey]]]):
A list of assets to add as sources.
upstream_assets (Optional[Set[AssetKey]]): Deprecated, use deps instead. A list of assets to add as sources.
freshness_policy (Optional[FreshnessPolicy]): A freshness policy to apply to the assets
"""
if upstream_assets is not None and deps is not None:
raise DagsterInvalidDefinitionError(
"Cannot specify both deps and upstream_assets to build_airbyte_assets. Use only deps"
" instead."
)
asset_key_prefix = check.opt_sequence_param(asset_key_prefix, "asset_key_prefix", of_type=str)
# Generate a list of outputs, the set of destination tables plus any affiliated
# normalization tables
tables = chain.from_iterable(
chain([destination_tables], normalization_tables.values() if normalization_tables else [])
)
outputs = {
table: AssetOut(
key=AssetKey([*asset_key_prefix, table]),
metadata=(
{"table_schema": MetadataValue.table_schema(schema_by_table_name[table])}
if schema_by_table_name
else None
),
freshness_policy=freshness_policy,
)
for table in tables
}
internal_deps = {}
# If normalization tables are specified, we need to add a dependency from the destination table
# to the affilitated normalization table
if normalization_tables:
for base_table, derived_tables in normalization_tables.items():
for derived_table in derived_tables:
internal_deps[derived_table] = {AssetKey([*asset_key_prefix, base_table])}
upstream_deps = deps
if upstream_assets is not None:
upstream_deps = list(upstream_assets)
# All non-normalization tables depend on any user-provided upstream assets
for table in destination_tables:
internal_deps[table] = set(upstream_deps) if upstream_deps else set()
@multi_asset(
name=f"airbyte_sync_{connection_id[:5]}",
deps=upstream_deps,
outs=outputs,
internal_asset_deps=internal_deps,
compute_kind="airbyte",
group_name=group_name,
)
def _assets(context, airbyte: BaseAirbyteResource):
ab_output = airbyte.sync_and_poll(connection_id=connection_id)
# No connection details (e.g. using Airbyte Cloud) means we just assume
# that the outputs were produced
if len(ab_output.connection_details) == 0:
for table_name in destination_tables:
yield Output(
value=None,
output_name=_table_to_output_name_fn(table_name),
)
if normalization_tables:
for dependent_table in normalization_tables.get(table_name, set()):
yield Output(
value=None,
output_name=_table_to_output_name_fn(dependent_table),
)
else:
for materialization in generate_materializations(ab_output, asset_key_prefix):
table_name = materialization.asset_key.path[-1]
if table_name in destination_tables:
yield Output(
value=None,
output_name=_table_to_output_name_fn(table_name),
metadata=materialization.metadata,
)
# Also materialize any normalization tables affiliated with this destination
# e.g. nested objects, lists etc
if normalization_tables:
for dependent_table in normalization_tables.get(table_name, set()):
yield Output(
value=None,
output_name=_table_to_output_name_fn(dependent_table),
)
else:
yield materialization
return [_assets]
def _get_schema_types(schema: Mapping[str, Any]) -> Sequence[str]:
"""Given a schema definition, return a list of data types that are valid for this schema."""
types = schema.get("types") or schema.get("type")
if not types:
return []
if isinstance(types, str):
return [types]
return types
def _get_sub_schemas(schema: Mapping[str, Any]) -> Sequence[Mapping[str, Any]]:
"""Returns a list of sub-schema definitions for a given schema. This is used to handle union types."""
return schema.get("anyOf") or schema.get("oneOf") or [schema]
def _get_normalization_tables_for_schema(
key: str, schema: Mapping[str, Any], prefix: str = ""
) -> Mapping[str, AirbyteTableMetadata]:
"""Recursively traverses a schema, returning metadata for the tables that will be created by the Airbyte
normalization process.
For example, a table `cars` with a nested object field `limited_editions` will produce the tables
`cars` and `cars_limited_editions`.
For more information on Airbyte's normalization process, see:
https://docs.airbyte.com/understanding-airbyte/basic-normalization/#nesting
"""
out: Dict[str, AirbyteTableMetadata] = {}
# Object types are broken into a new table, as long as they have children
sub_schemas = _get_sub_schemas(schema)
for sub_schema in sub_schemas:
schema_types = _get_schema_types(sub_schema)
if not schema_types:
continue
if "object" in schema_types and len(sub_schema.get("properties", {})) > 0:
out[prefix + key] = AirbyteTableMetadata(
schema=generate_table_schema(sub_schema.get("properties", {}))
)
for k, v in sub_schema["properties"].items():
out = merge_dicts(
out, _get_normalization_tables_for_schema(k, v, f"{prefix}{key}_")
)
# Array types are also broken into a new table
elif "array" in schema_types:
out[prefix + key] = AirbyteTableMetadata(
schema=generate_table_schema(sub_schema.get("items", {}).get("properties", {}))
)
if sub_schema.get("items", {}).get("properties"):
for k, v in sub_schema["items"]["properties"].items():
out = merge_dicts(
out, _get_normalization_tables_for_schema(k, v, f"{prefix}{key}_")
)
return out
def _clean_name(name: str) -> str:
"""Cleans an input to be a valid Dagster asset name."""
return re.sub(r"[^a-z0-9]+", "_", name.lower())
class AirbyteConnectionMetadata(
NamedTuple(
"_AirbyteConnectionMetadata",
[
("name", str),
("stream_prefix", str),
("has_basic_normalization", bool),
("stream_data", List[Mapping[str, Any]]),
],
)
):
"""Contains information about an Airbyte connection.
Attributes:
name (str): The name of the connection.
stream_prefix (str): A prefix to add to all stream names.
has_basic_normalization (bool): Whether or not the connection has basic normalization enabled.
stream_data (List[Mapping[str, Any]]): Unparsed list of dicts with information about each stream.
"""
@classmethod
def from_api_json(
cls, contents: Mapping[str, Any], operations: Mapping[str, Any]
) -> "AirbyteConnectionMetadata":
return cls(
name=contents["name"],
stream_prefix=contents.get("prefix", ""),
has_basic_normalization=any(
is_basic_normalization_operation(op.get("operatorConfiguration", {}))
for op in operations.get("operations", [])
),
stream_data=contents.get("syncCatalog", {}).get("streams", []),
)
@classmethod
def from_config(cls, contents: Mapping[str, Any]) -> "AirbyteConnectionMetadata":
config_contents = cast(Mapping[str, Any], contents.get("configuration"))
check.invariant(
config_contents is not None, "Airbyte connection config is missing 'configuration' key"
)
return cls(
name=contents["resource_name"],
stream_prefix=config_contents.get("prefix", ""),
has_basic_normalization=any(
is_basic_normalization_operation(op.get("operator_configuration", {}))
for op in config_contents.get("operations", [])
),
stream_data=config_contents.get("sync_catalog", {}).get("streams", []),
)
def parse_stream_tables(
self, return_normalization_tables: bool = False
) -> Mapping[str, AirbyteTableMetadata]:
"""Parses the stream data and returns a mapping, with keys representing destination
tables associated with each enabled stream and values representing any affiliated
tables created by Airbyte's normalization process, if enabled.
"""
tables: Dict[str, AirbyteTableMetadata] = {}
enabled_streams = [
stream for stream in self.stream_data if stream.get("config", {}).get("selected", False)
]
for stream in enabled_streams:
name = cast(str, stream.get("stream", {}).get("name"))
prefixed_name = f"{self.stream_prefix}{name}"
schema = (
stream["stream"]["json_schema"]
if "json_schema" in stream["stream"]
else stream["stream"]["jsonSchema"]
)
normalization_tables: Dict[str, AirbyteTableMetadata] = {}
schema_props = schema.get("properties", schema.get("items", {}).get("properties", {}))
if self.has_basic_normalization and return_normalization_tables:
for k, v in schema_props.items():
for normalization_table_name, meta in _get_normalization_tables_for_schema(
k, v, f"{name}_"
).items():
prefixed_norm_table_name = f"{self.stream_prefix}{normalization_table_name}"
normalization_tables[prefixed_norm_table_name] = meta
tables[prefixed_name] = AirbyteTableMetadata(
schema=generate_table_schema(schema_props),
normalization_tables=normalization_tables,
)
return tables
def _get_schema_by_table_name(
stream_table_metadata: Mapping[str, AirbyteTableMetadata]
) -> Mapping[str, TableSchema]:
schema_by_base_table_name = [(k, v.schema) for k, v in stream_table_metadata.items()]
schema_by_normalization_table_name = list(
chain.from_iterable(
[
[
(k, v.schema)
for k, v in cast(
Dict[str, AirbyteTableMetadata], meta.normalization_tables
).items()
]
for meta in stream_table_metadata.values()
]
)
)
return dict(schema_by_normalization_table_name + schema_by_base_table_name)
class AirbyteCoreCacheableAssetsDefinition(CacheableAssetsDefinition):
def __init__(
self,
key_prefix: Sequence[str],
create_assets_for_normalization_tables: bool,
connection_to_group_fn: Optional[Callable[[str], Optional[str]]],
connection_to_io_manager_key_fn: Optional[Callable[[str], Optional[str]]],
connection_filter: Optional[Callable[[AirbyteConnectionMetadata], bool]],
connection_to_asset_key_fn: Optional[Callable[[AirbyteConnectionMetadata, str], AssetKey]],
connection_to_freshness_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[FreshnessPolicy]]
],
connection_to_auto_materialize_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[AutoMaterializePolicy]]
] = None,
):
self._key_prefix = key_prefix
self._create_assets_for_normalization_tables = create_assets_for_normalization_tables
self._connection_to_group_fn = connection_to_group_fn
self._connection_to_io_manager_key_fn = connection_to_io_manager_key_fn
self._connection_filter = connection_filter
self._connection_to_asset_key_fn: Callable[[AirbyteConnectionMetadata, str], AssetKey] = (
connection_to_asset_key_fn or (lambda _, table: AssetKey(path=[table]))
)
self._connection_to_freshness_policy_fn = connection_to_freshness_policy_fn or (
lambda _: None
)
self._connection_to_auto_materialize_policy_fn = (
connection_to_auto_materialize_policy_fn or (lambda _: None)
)
contents = hashlib.sha1() # so that hexdigest is 40, not 64 bytes
contents.update(",".join(key_prefix).encode("utf-8"))
contents.update(str(create_assets_for_normalization_tables).encode("utf-8"))
if connection_filter:
contents.update(inspect.getsource(connection_filter).encode("utf-8"))
super().__init__(unique_id=f"airbyte-{contents.hexdigest()}")
@abstractmethod
def _get_connections(self) -> Sequence[Tuple[str, AirbyteConnectionMetadata]]:
pass
def compute_cacheable_data(self) -> Sequence[AssetsDefinitionCacheableData]:
asset_defn_data: List[AssetsDefinitionCacheableData] = []
for connection_id, connection in self._get_connections():
stream_table_metadata = connection.parse_stream_tables(
self._create_assets_for_normalization_tables
)
schema_by_table_name = _get_schema_by_table_name(stream_table_metadata)
table_to_asset_key = partial(self._connection_to_asset_key_fn, connection)
asset_data_for_conn = _build_airbyte_asset_defn_metadata(
connection_id=connection_id,
destination_tables=list(stream_table_metadata.keys()),
normalization_tables={
table: set(metadata.normalization_tables.keys())
for table, metadata in stream_table_metadata.items()
},
asset_key_prefix=self._key_prefix,
group_name=(
self._connection_to_group_fn(connection.name)
if self._connection_to_group_fn
else None
),
io_manager_key=(
self._connection_to_io_manager_key_fn(connection.name)
if self._connection_to_io_manager_key_fn
else None
),
schema_by_table_name=schema_by_table_name,
table_to_asset_key_fn=table_to_asset_key,
freshness_policy=self._connection_to_freshness_policy_fn(connection),
auto_materialize_policy=self._connection_to_auto_materialize_policy_fn(connection),
)
asset_defn_data.append(asset_data_for_conn)
return asset_defn_data
def _build_definitions_with_resources(
self,
data: Sequence[AssetsDefinitionCacheableData],
resource_defs: Optional[Mapping[str, ResourceDefinition]] = None,
) -> Sequence[AssetsDefinition]:
return [_build_airbyte_assets_from_metadata(meta, resource_defs) for meta in data]
def build_definitions(
self, data: Sequence[AssetsDefinitionCacheableData]
) -> Sequence[AssetsDefinition]:
return self._build_definitions_with_resources(data)
class AirbyteInstanceCacheableAssetsDefinition(AirbyteCoreCacheableAssetsDefinition):
def __init__(
self,
airbyte_resource_def: Union[ResourceDefinition, AirbyteResource],
workspace_id: Optional[str],
key_prefix: Sequence[str],
create_assets_for_normalization_tables: bool,
connection_to_group_fn: Optional[Callable[[str], Optional[str]]],
connection_to_io_manager_key_fn: Optional[Callable[[str], Optional[str]]],
connection_filter: Optional[Callable[[AirbyteConnectionMetadata], bool]],
connection_to_asset_key_fn: Optional[Callable[[AirbyteConnectionMetadata, str], AssetKey]],
connection_to_freshness_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[FreshnessPolicy]]
],
connection_to_auto_materialize_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[AutoMaterializePolicy]]
] = None,
):
super().__init__(
key_prefix=key_prefix,
create_assets_for_normalization_tables=create_assets_for_normalization_tables,
connection_to_group_fn=connection_to_group_fn,
connection_to_io_manager_key_fn=connection_to_io_manager_key_fn,
connection_filter=connection_filter,
connection_to_asset_key_fn=connection_to_asset_key_fn,
connection_to_freshness_policy_fn=connection_to_freshness_policy_fn,
connection_to_auto_materialize_policy_fn=connection_to_auto_materialize_policy_fn,
)
self._workspace_id = workspace_id
self._airbyte_instance: AirbyteResource = (
airbyte_resource_def.process_config_and_initialize()
if isinstance(airbyte_resource_def, AirbyteResource)
else airbyte_resource_def(build_init_resource_context())
)
def _get_connections(self) -> Sequence[Tuple[str, AirbyteConnectionMetadata]]:
workspace_id = self._workspace_id
if not workspace_id:
workspaces = cast(
List[Dict[str, Any]],
check.not_none(
self._airbyte_instance.make_request(endpoint="/workspaces/list", data={})
).get("workspaces", []),
)
check.invariant(len(workspaces) <= 1, "Airbyte instance has more than one workspace")
check.invariant(len(workspaces) > 0, "Airbyte instance has no workspaces")
workspace_id = workspaces[0].get("workspaceId")
connections = cast(
List[Dict[str, Any]],
check.not_none(
self._airbyte_instance.make_request(
endpoint="/connections/list", data={"workspaceId": workspace_id}
)
).get("connections", []),
)
output_connections: List[Tuple[str, AirbyteConnectionMetadata]] = []
for connection_json in connections:
connection_id = cast(str, connection_json.get("connectionId"))
operations_json = cast(
Dict[str, Any],
check.not_none(
self._airbyte_instance.make_request(
endpoint="/operations/list",
data={"connectionId": connection_id},
)
),
)
connection = AirbyteConnectionMetadata.from_api_json(connection_json, operations_json)
# Filter out connections that don't match the filter function
if self._connection_filter and not self._connection_filter(connection):
continue
output_connections.append((connection_id, connection))
return output_connections
def build_definitions(
self, data: Sequence[AssetsDefinitionCacheableData]
) -> Sequence[AssetsDefinition]:
return super()._build_definitions_with_resources(
data, {"airbyte": self._airbyte_instance.get_resource_definition()}
)
class AirbyteYAMLCacheableAssetsDefinition(AirbyteCoreCacheableAssetsDefinition):
def __init__(
self,
project_dir: str,
workspace_id: Optional[str],
key_prefix: Sequence[str],
create_assets_for_normalization_tables: bool,
connection_to_group_fn: Optional[Callable[[str], Optional[str]]],
connection_to_io_manager_key_fn: Optional[Callable[[str], Optional[str]]],
connection_filter: Optional[Callable[[AirbyteConnectionMetadata], bool]],
connection_directories: Optional[Sequence[str]],
connection_to_asset_key_fn: Optional[Callable[[AirbyteConnectionMetadata, str], AssetKey]],
connection_to_freshness_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[FreshnessPolicy]]
],
connection_to_auto_materialize_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[AutoMaterializePolicy]]
] = None,
):
super().__init__(
key_prefix=key_prefix,
create_assets_for_normalization_tables=create_assets_for_normalization_tables,
connection_to_group_fn=connection_to_group_fn,
connection_to_io_manager_key_fn=connection_to_io_manager_key_fn,
connection_filter=connection_filter,
connection_to_asset_key_fn=connection_to_asset_key_fn,
connection_to_freshness_policy_fn=connection_to_freshness_policy_fn,
connection_to_auto_materialize_policy_fn=connection_to_auto_materialize_policy_fn,
)
self._workspace_id = workspace_id
self._project_dir = project_dir
self._connection_directories = connection_directories
def _get_connections(self) -> Sequence[Tuple[str, AirbyteConnectionMetadata]]:
connections_dir = os.path.join(self._project_dir, "connections")
output_connections: List[Tuple[str, AirbyteConnectionMetadata]] = []
connection_directories = self._connection_directories or os.listdir(connections_dir)
for connection_name in connection_directories:
connection_dir = os.path.join(connections_dir, connection_name)
with open(os.path.join(connection_dir, "configuration.yaml"), encoding="utf-8") as f:
connection = AirbyteConnectionMetadata.from_config(yaml.safe_load(f.read()))
# Filter out connections that don't match the filter function
if self._connection_filter and not self._connection_filter(connection):
continue
if self._workspace_id:
state_file = f"state_{self._workspace_id}.yaml"
check.invariant(
state_file in os.listdir(connection_dir),
f"Workspace state file {state_file} not found",
)
else:
state_files = [
filename
for filename in os.listdir(connection_dir)
if filename.startswith("state_")
]
check.invariant(
len(state_files) > 0,
"No state files found for connection {} in {}".format(
connection_name, connection_dir
),
)
check.invariant(
len(state_files) <= 1,
"More than one state file found for connection {} in {}, specify a workspace_id"
" to disambiguate".format(connection_name, connection_dir),
)
state_file = state_files[0]
with open(os.path.join(connection_dir, cast(str, state_file)), encoding="utf-8") as f:
state = yaml.safe_load(f.read())
connection_id = state.get("resource_id")
output_connections.append((connection_id, connection))
return output_connections
[docs]def load_assets_from_airbyte_instance(
airbyte: Union[AirbyteResource, ResourceDefinition],
workspace_id: Optional[str] = None,
key_prefix: Optional[CoercibleToAssetKeyPrefix] = None,
create_assets_for_normalization_tables: bool = True,
connection_to_group_fn: Optional[Callable[[str], Optional[str]]] = _clean_name,
io_manager_key: Optional[str] = None,
connection_to_io_manager_key_fn: Optional[Callable[[str], Optional[str]]] = None,
connection_filter: Optional[Callable[[AirbyteConnectionMetadata], bool]] = None,
connection_to_asset_key_fn: Optional[
Callable[[AirbyteConnectionMetadata, str], AssetKey]
] = None,
connection_to_freshness_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[FreshnessPolicy]]
] = None,
connection_to_auto_materialize_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[AutoMaterializePolicy]]
] = None,
) -> CacheableAssetsDefinition:
"""Loads Airbyte connection assets from a configured AirbyteResource instance. This fetches information
about defined connections at initialization time, and will error on workspace load if the Airbyte
instance is not reachable.
Args:
airbyte (ResourceDefinition): An AirbyteResource configured with the appropriate connection
details.
workspace_id (Optional[str]): The ID of the Airbyte workspace to load connections from. Only
required if multiple workspaces exist in your instance.
key_prefix (Optional[CoercibleToAssetKeyPrefix]): A prefix for the asset keys created.
create_assets_for_normalization_tables (bool): If True, assets will be created for tables
created by Airbyte's normalization feature. If False, only the destination tables
will be created. Defaults to True.
connection_to_group_fn (Optional[Callable[[str], Optional[str]]]): Function which returns an asset
group name for a given Airbyte connection name. If None, no groups will be created. Defaults
to a basic sanitization function.
io_manager_key (Optional[str]): The I/O manager key to use for all assets. Defaults to "io_manager".
Use this if all assets should be loaded from the same source, otherwise use connection_to_io_manager_key_fn.
connection_to_io_manager_key_fn (Optional[Callable[[str], Optional[str]]]): Function which returns an
I/O manager key for a given Airbyte connection name. When other ops are downstream of the loaded assets,
the IOManager specified determines how the inputs to those ops are loaded. Defaults to "io_manager".
connection_filter (Optional[Callable[[AirbyteConnectionMetadata], bool]]): Optional function which takes
in connection metadata and returns False if the connection should be excluded from the output assets.
connection_to_asset_key_fn (Optional[Callable[[AirbyteConnectionMetadata, str], AssetKey]]): Optional function which
takes in connection metadata and table name and returns an asset key for the table. If None, the default asset
key is based on the table name. Any asset key prefix will be applied to the output of this function.
connection_to_freshness_policy_fn (Optional[Callable[[AirbyteConnectionMetadata], Optional[FreshnessPolicy]]]): Optional function
which takes in connection metadata and returns a freshness policy for the connection's assets. If None, no freshness policies
will be applied to the assets.
connection_to_auto_materialize_policy_fn (Optional[Callable[[AirbyteConnectionMetadata], Optional[AutoMaterializePolicy]]]): Optional
function which takes in connection metadata and returns an auto materialization policy for the connection's assets. If None, no
auto materialization policies will be applied to the assets.
**Examples:**
Loading all Airbyte connections as assets:
.. code-block:: python
from dagster_airbyte import airbyte_resource, load_assets_from_airbyte_instance
airbyte_instance = airbyte_resource.configured(
{
"host": "localhost",
"port": "8000",
}
)
airbyte_assets = load_assets_from_airbyte_instance(airbyte_instance)
Filtering the set of loaded connections:
.. code-block:: python
from dagster_airbyte import airbyte_resource, load_assets_from_airbyte_instance
airbyte_instance = airbyte_resource.configured(
{
"host": "localhost",
"port": "8000",
}
)
airbyte_assets = load_assets_from_airbyte_instance(
airbyte_instance,
connection_filter=lambda meta: "snowflake" in meta.name,
)
"""
if isinstance(airbyte, AirbyteCloudResource):
raise DagsterInvalidInvocationError(
"load_assets_from_airbyte_instance is not yet supported for AirbyteCloudResource"
)
if isinstance(key_prefix, str):
key_prefix = [key_prefix]
key_prefix = check.list_param(key_prefix or [], "key_prefix", of_type=str)
check.invariant(
not io_manager_key or not connection_to_io_manager_key_fn,
"Cannot specify both io_manager_key and connection_to_io_manager_key_fn",
)
if not connection_to_io_manager_key_fn:
connection_to_io_manager_key_fn = lambda _: io_manager_key
return AirbyteInstanceCacheableAssetsDefinition(
airbyte_resource_def=airbyte,
workspace_id=workspace_id,
key_prefix=key_prefix,
create_assets_for_normalization_tables=create_assets_for_normalization_tables,
connection_to_group_fn=connection_to_group_fn,
connection_to_io_manager_key_fn=connection_to_io_manager_key_fn,
connection_filter=connection_filter,
connection_to_asset_key_fn=connection_to_asset_key_fn,
connection_to_freshness_policy_fn=connection_to_freshness_policy_fn,
connection_to_auto_materialize_policy_fn=connection_to_auto_materialize_policy_fn,
)
[docs]def load_assets_from_airbyte_project(
project_dir: str,
workspace_id: Optional[str] = None,
key_prefix: Optional[CoercibleToAssetKeyPrefix] = None,
create_assets_for_normalization_tables: bool = True,
connection_to_group_fn: Optional[Callable[[str], Optional[str]]] = _clean_name,
io_manager_key: Optional[str] = None,
connection_to_io_manager_key_fn: Optional[Callable[[str], Optional[str]]] = None,
connection_filter: Optional[Callable[[AirbyteConnectionMetadata], bool]] = None,
connection_directories: Optional[Sequence[str]] = None,
connection_to_asset_key_fn: Optional[
Callable[[AirbyteConnectionMetadata, str], AssetKey]
] = None,
connection_to_freshness_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[FreshnessPolicy]]
] = None,
connection_to_auto_materialize_policy_fn: Optional[
Callable[[AirbyteConnectionMetadata], Optional[AutoMaterializePolicy]]
] = None,
) -> CacheableAssetsDefinition:
"""Loads an Airbyte project into a set of Dagster assets.
Point to the root folder of an Airbyte project synced using the Octavia CLI. For
more information, see https://github.com/airbytehq/airbyte/tree/master/octavia-cli#octavia-import-all.
Args:
project_dir (str): The path to the root of your Airbyte project, containing sources, destinations,
and connections folders.
workspace_id (Optional[str]): The ID of the Airbyte workspace to load connections from. Only
required if multiple workspace state YAMLfiles exist in the project.
key_prefix (Optional[CoercibleToAssetKeyPrefix]): A prefix for the asset keys created.
create_assets_for_normalization_tables (bool): If True, assets will be created for tables
created by Airbyte's normalization feature. If False, only the destination tables
will be created. Defaults to True.
connection_to_group_fn (Optional[Callable[[str], Optional[str]]]): Function which returns an asset
group name for a given Airbyte connection name. If None, no groups will be created. Defaults
to a basic sanitization function.
io_manager_key (Optional[str]): The I/O manager key to use for all assets. Defaults to "io_manager".
Use this if all assets should be loaded from the same source, otherwise use connection_to_io_manager_key_fn.
connection_to_io_manager_key_fn (Optional[Callable[[str], Optional[str]]]): Function which returns an
I/O manager key for a given Airbyte connection name. When other ops are downstream of the loaded assets,
the IOManager specified determines how the inputs to those ops are loaded. Defaults to "io_manager".
connection_filter (Optional[Callable[[AirbyteConnectionMetadata], bool]]): Optional function which
takes in connection metadata and returns False if the connection should be excluded from the output assets.
connection_directories (Optional[List[str]]): Optional list of connection directories to load assets from.
If omitted, all connections in the Airbyte project are loaded. May be faster than connection_filter
if the project has many connections or if the connection yaml files are large.
connection_to_asset_key_fn (Optional[Callable[[AirbyteConnectionMetadata, str], AssetKey]]): Optional function which
takes in connection metadata and table name and returns an asset key for the table. If None, the default asset
key is based on the table name. Any asset key prefix will be applied to the output of this function.
connection_to_freshness_policy_fn (Optional[Callable[[AirbyteConnectionMetadata], Optional[FreshnessPolicy]]]):
Optional function which takes in connection metadata and returns a freshness policy for the connection's assets.
If None, no freshness policies will be applied to the assets.
connection_to_auto_materialize_policy_fn (Optional[Callable[[AirbyteConnectionMetadata], Optional[AutoMaterializePolicy]]]):
Optional function which takes in connection metadata and returns an auto materialization policy for the connection's assets.
If None, no auto materialization policies will be applied to the assets.
**Examples:**
Loading all Airbyte connections as assets:
.. code-block:: python
from dagster_airbyte import load_assets_from_airbyte_project
airbyte_assets = load_assets_from_airbyte_project(
project_dir="path/to/airbyte/project",
)
Filtering the set of loaded connections:
.. code-block:: python
from dagster_airbyte import load_assets_from_airbyte_project
airbyte_assets = load_assets_from_airbyte_project(
project_dir="path/to/airbyte/project",
connection_filter=lambda meta: "snowflake" in meta.name,
)
"""
if isinstance(key_prefix, str):
key_prefix = [key_prefix]
key_prefix = check.list_param(key_prefix or [], "key_prefix", of_type=str)
check.invariant(
not io_manager_key or not connection_to_io_manager_key_fn,
"Cannot specify both io_manager_key and connection_to_io_manager_key_fn",
)
if not connection_to_io_manager_key_fn:
connection_to_io_manager_key_fn = lambda _: io_manager_key
return AirbyteYAMLCacheableAssetsDefinition(
project_dir=project_dir,
workspace_id=workspace_id,
key_prefix=key_prefix,
create_assets_for_normalization_tables=create_assets_for_normalization_tables,
connection_to_group_fn=connection_to_group_fn,
connection_to_io_manager_key_fn=connection_to_io_manager_key_fn,
connection_filter=connection_filter,
connection_directories=connection_directories,
connection_to_asset_key_fn=connection_to_asset_key_fn,
connection_to_freshness_policy_fn=connection_to_freshness_policy_fn,
connection_to_auto_materialize_policy_fn=connection_to_auto_materialize_policy_fn,
)