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manifest.py
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manifest.py
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import enum
from collections import defaultdict
from dataclasses import dataclass, field, replace
from itertools import chain
from multiprocessing.synchronize import Lock
from typing import (
Any,
Callable,
ClassVar,
DefaultDict,
Dict,
Generic,
List,
Mapping,
MutableMapping,
Optional,
Set,
Tuple,
TypeVar,
Union,
)
from typing_extensions import Protocol
import dbt_common.exceptions
import dbt_common.utils
from dbt import deprecations, tracking
from dbt.adapters.exceptions import (
DuplicateMacroInPackageError,
DuplicateMaterializationNameError,
)
from dbt.adapters.factory import get_adapter_package_names
# to preserve import paths
from dbt.artifacts.resources import BaseResource, DeferRelation, NodeVersion, RefArgs
from dbt.artifacts.resources.v1.config import NodeConfig
from dbt.artifacts.schemas.manifest import ManifestMetadata, UniqueID, WritableManifest
from dbt.clients.jinja_static import statically_parse_ref_or_source
from dbt.contracts.files import (
AnySourceFile,
FileHash,
FixtureSourceFile,
SchemaSourceFile,
SourceFile,
)
from dbt.contracts.graph.nodes import (
RESOURCE_CLASS_TO_NODE_CLASS,
BaseNode,
Documentation,
Exposure,
GenericTestNode,
GraphMemberNode,
Group,
Macro,
ManifestNode,
Metric,
ModelNode,
SavedQuery,
SeedNode,
SemanticModel,
SingularTestNode,
SnapshotNode,
SourceDefinition,
UnitTestDefinition,
UnitTestFileFixture,
UnpatchedSourceDefinition,
)
from dbt.contracts.graph.unparsed import SourcePatch, UnparsedVersion
from dbt.contracts.util import SourceKey
from dbt.events.types import UnpinnedRefNewVersionAvailable
from dbt.exceptions import (
AmbiguousResourceNameRefError,
CompilationError,
DuplicateResourceNameError,
)
from dbt.flags import get_flags
from dbt.mp_context import get_mp_context
from dbt.node_types import (
REFABLE_NODE_TYPES,
VERSIONED_NODE_TYPES,
AccessType,
NodeType,
)
from dbt_common.dataclass_schema import dbtClassMixin
from dbt_common.events.contextvars import get_node_info
from dbt_common.events.functions import fire_event
from dbt_common.helper_types import PathSet
PackageName = str
DocName = str
RefName = str
def find_unique_id_for_package(storage, key, package: Optional[PackageName]) -> Optional[UniqueID]:
if key not in storage:
return None
pkg_dct: Mapping[PackageName, UniqueID] = storage[key]
if package is None:
if not pkg_dct:
return None
else:
return next(iter(pkg_dct.values()))
elif package in pkg_dct:
return pkg_dct[package]
else:
return None
class DocLookup(dbtClassMixin):
def __init__(self, manifest: "Manifest") -> None:
self.storage: Dict[str, Dict[PackageName, UniqueID]] = {}
self.populate(manifest)
def get_unique_id(self, key, package: Optional[PackageName]):
return find_unique_id_for_package(self.storage, key, package)
def find(self, key, package: Optional[PackageName], manifest: "Manifest"):
unique_id = self.get_unique_id(key, package)
if unique_id is not None:
return self.perform_lookup(unique_id, manifest)
return None
def add_doc(self, doc: Documentation):
if doc.name not in self.storage:
self.storage[doc.name] = {}
self.storage[doc.name][doc.package_name] = doc.unique_id
def populate(self, manifest):
for doc in manifest.docs.values():
self.add_doc(doc)
def perform_lookup(self, unique_id: UniqueID, manifest) -> Documentation:
if unique_id not in manifest.docs:
raise dbt_common.exceptions.DbtInternalError(
f"Doc {unique_id} found in cache but not found in manifest"
)
return manifest.docs[unique_id]
class SourceLookup(dbtClassMixin):
def __init__(self, manifest: "Manifest") -> None:
self.storage: Dict[str, Dict[PackageName, UniqueID]] = {}
self.populate(manifest)
def get_unique_id(self, search_name, package: Optional[PackageName]):
return find_unique_id_for_package(self.storage, search_name, package)
def find(self, search_name, package: Optional[PackageName], manifest: "Manifest"):
unique_id = self.get_unique_id(search_name, package)
if unique_id is not None:
return self.perform_lookup(unique_id, manifest)
return None
def add_source(self, source: SourceDefinition):
if source.search_name not in self.storage:
self.storage[source.search_name] = {}
self.storage[source.search_name][source.package_name] = source.unique_id
def populate(self, manifest):
for source in manifest.sources.values():
if hasattr(source, "source_name"):
self.add_source(source)
def perform_lookup(self, unique_id: UniqueID, manifest: "Manifest") -> SourceDefinition:
if unique_id not in manifest.sources:
raise dbt_common.exceptions.DbtInternalError(
f"Source {unique_id} found in cache but not found in manifest"
)
return manifest.sources[unique_id]
class RefableLookup(dbtClassMixin):
# model, seed, snapshot
_lookup_types: ClassVar[set] = set(REFABLE_NODE_TYPES)
_versioned_types: ClassVar[set] = set(VERSIONED_NODE_TYPES)
def __init__(self, manifest: "Manifest") -> None:
self.storage: Dict[str, Dict[PackageName, UniqueID]] = {}
self.populate(manifest)
def get_unique_id(
self,
key: str,
package: Optional[PackageName],
version: Optional[NodeVersion],
node: Optional[GraphMemberNode] = None,
):
if version:
key = f"{key}.v{version}"
unique_ids = self._find_unique_ids_for_package(key, package)
if len(unique_ids) > 1:
raise AmbiguousResourceNameRefError(key, unique_ids, node)
else:
return unique_ids[0] if unique_ids else None
def find(
self,
key: str,
package: Optional[PackageName],
version: Optional[NodeVersion],
manifest: "Manifest",
source_node: Optional[GraphMemberNode] = None,
):
unique_id = self.get_unique_id(key, package, version, source_node)
if unique_id is not None:
node = self.perform_lookup(unique_id, manifest)
# If this is an unpinned ref (no 'version' arg was passed),
# AND this is a versioned node,
# AND this ref is being resolved at runtime -- get_node_info != {}
# Only ModelNodes can be versioned.
if (
isinstance(node, ModelNode)
and version is None
and node.is_versioned
and get_node_info()
):
# Check to see if newer versions are available, and log an "FYI" if so
max_version: UnparsedVersion = max(
[
UnparsedVersion(v.version)
for v in manifest.nodes.values()
if isinstance(v, ModelNode)
and v.name == node.name
and v.version is not None
]
)
assert node.latest_version is not None # for mypy, whenever i may find it
if max_version > UnparsedVersion(node.latest_version):
fire_event(
UnpinnedRefNewVersionAvailable(
node_info=get_node_info(),
ref_node_name=node.name,
ref_node_package=node.package_name,
ref_node_version=str(node.version),
ref_max_version=str(max_version.v),
)
)
return node
return None
def add_node(self, node: ManifestNode):
if node.resource_type in self._lookup_types:
if node.name not in self.storage:
self.storage[node.name] = {}
if node.is_versioned:
if node.search_name not in self.storage:
self.storage[node.search_name] = {}
self.storage[node.search_name][node.package_name] = node.unique_id
if node.is_latest_version: # type: ignore
self.storage[node.name][node.package_name] = node.unique_id
else:
self.storage[node.name][node.package_name] = node.unique_id
def populate(self, manifest):
for node in manifest.nodes.values():
self.add_node(node)
def perform_lookup(self, unique_id: UniqueID, manifest) -> ManifestNode:
if unique_id in manifest.nodes:
node = manifest.nodes[unique_id]
else:
raise dbt_common.exceptions.DbtInternalError(
f"Node {unique_id} found in cache but not found in manifest"
)
return node
def _find_unique_ids_for_package(self, key, package: Optional[PackageName]) -> List[str]:
if key not in self.storage:
return []
pkg_dct: Mapping[PackageName, UniqueID] = self.storage[key]
if package is None:
if not pkg_dct:
return []
else:
return list(pkg_dct.values())
elif package in pkg_dct:
return [pkg_dct[package]]
else:
return []
class MetricLookup(dbtClassMixin):
def __init__(self, manifest: "Manifest") -> None:
self.storage: Dict[str, Dict[PackageName, UniqueID]] = {}
self.populate(manifest)
def get_unique_id(self, search_name, package: Optional[PackageName]):
return find_unique_id_for_package(self.storage, search_name, package)
def find(self, search_name, package: Optional[PackageName], manifest: "Manifest"):
unique_id = self.get_unique_id(search_name, package)
if unique_id is not None:
return self.perform_lookup(unique_id, manifest)
return None
def add_metric(self, metric: Metric):
if metric.search_name not in self.storage:
self.storage[metric.search_name] = {}
self.storage[metric.search_name][metric.package_name] = metric.unique_id
def populate(self, manifest):
for metric in manifest.metrics.values():
if hasattr(metric, "name"):
self.add_metric(metric)
def perform_lookup(self, unique_id: UniqueID, manifest: "Manifest") -> Metric:
if unique_id not in manifest.metrics:
raise dbt_common.exceptions.DbtInternalError(
f"Metric {unique_id} found in cache but not found in manifest"
)
return manifest.metrics[unique_id]
class SavedQueryLookup(dbtClassMixin):
"""Lookup utility for finding SavedQuery nodes"""
def __init__(self, manifest: "Manifest") -> None:
self.storage: Dict[str, Dict[PackageName, UniqueID]] = {}
self.populate(manifest)
def get_unique_id(self, search_name, package: Optional[PackageName]):
return find_unique_id_for_package(self.storage, search_name, package)
def find(self, search_name, package: Optional[PackageName], manifest: "Manifest"):
unique_id = self.get_unique_id(search_name, package)
if unique_id is not None:
return self.perform_lookup(unique_id, manifest)
return None
def add_saved_query(self, saved_query: SavedQuery):
if saved_query.search_name not in self.storage:
self.storage[saved_query.search_name] = {}
self.storage[saved_query.search_name][saved_query.package_name] = saved_query.unique_id
def populate(self, manifest):
for saved_query in manifest.saved_queries.values():
if hasattr(saved_query, "name"):
self.add_saved_query(saved_query)
def perform_lookup(self, unique_id: UniqueID, manifest: "Manifest") -> SavedQuery:
if unique_id not in manifest.saved_queries:
raise dbt_common.exceptions.DbtInternalError(
f"SavedQUery {unique_id} found in cache but not found in manifest"
)
return manifest.saved_queries[unique_id]
class SemanticModelByMeasureLookup(dbtClassMixin):
"""Lookup utility for finding SemanticModel by measure
This is possible because measure names are supposed to be unique across
the semantic models in a manifest.
"""
def __init__(self, manifest: "Manifest") -> None:
self.storage: DefaultDict[str, Dict[PackageName, UniqueID]] = defaultdict(dict)
self.populate(manifest)
def get_unique_id(self, search_name: str, package: Optional[PackageName]):
return find_unique_id_for_package(self.storage, search_name, package)
def find(
self, search_name: str, package: Optional[PackageName], manifest: "Manifest"
) -> Optional[SemanticModel]:
"""Tries to find a SemanticModel based on a measure name"""
unique_id = self.get_unique_id(search_name, package)
if unique_id is not None:
return self.perform_lookup(unique_id, manifest)
return None
def add(self, semantic_model: SemanticModel):
"""Sets all measures for a SemanticModel as paths to the SemanticModel's `unique_id`"""
for measure in semantic_model.measures:
self.storage[measure.name][semantic_model.package_name] = semantic_model.unique_id
def populate(self, manifest: "Manifest"):
"""Populate storage with all the measure + package paths to the Manifest's SemanticModels"""
for semantic_model in manifest.semantic_models.values():
self.add(semantic_model=semantic_model)
for disabled in manifest.disabled.values():
for node in disabled:
if isinstance(node, SemanticModel):
self.add(semantic_model=node)
def perform_lookup(self, unique_id: UniqueID, manifest: "Manifest") -> SemanticModel:
"""Tries to get a SemanticModel from the Manifest"""
enabled_semantic_model: Optional[SemanticModel] = manifest.semantic_models.get(unique_id)
disabled_semantic_model: Optional[List] = manifest.disabled.get(unique_id)
if isinstance(enabled_semantic_model, SemanticModel):
return enabled_semantic_model
elif disabled_semantic_model is not None and isinstance(
disabled_semantic_model[0], SemanticModel
):
return disabled_semantic_model[0]
else:
raise dbt_common.exceptions.DbtInternalError(
f"Semantic model `{unique_id}` found in cache but not found in manifest"
)
# This handles both models/seeds/snapshots and sources/metrics/exposures/semantic_models
class DisabledLookup(dbtClassMixin):
def __init__(self, manifest: "Manifest") -> None:
self.storage: Dict[str, Dict[PackageName, List[Any]]] = {}
self.populate(manifest)
def populate(self, manifest: "Manifest"):
for node in list(chain.from_iterable(manifest.disabled.values())):
self.add_node(node)
def add_node(self, node: GraphMemberNode) -> None:
if node.search_name not in self.storage:
self.storage[node.search_name] = {}
if node.package_name not in self.storage[node.search_name]:
self.storage[node.search_name][node.package_name] = []
self.storage[node.search_name][node.package_name].append(node)
# This should return a list of disabled nodes. It's different from
# the other Lookup functions in that it returns full nodes, not just unique_ids
def find(
self,
search_name,
package: Optional[PackageName],
version: Optional[NodeVersion] = None,
resource_types: Optional[List[NodeType]] = None,
) -> Optional[List[Any]]:
if version:
search_name = f"{search_name}.v{version}"
if search_name not in self.storage:
return None
pkg_dct: Mapping[PackageName, List[Any]] = self.storage[search_name]
nodes = []
if package is None:
if not pkg_dct:
return None
else:
nodes = next(iter(pkg_dct.values()))
elif package in pkg_dct:
nodes = pkg_dct[package]
else:
return None
if resource_types is None:
return nodes
else:
new_nodes = []
for node in nodes:
if node.resource_type in resource_types:
new_nodes.append(node)
if not new_nodes:
return None
else:
return new_nodes
class AnalysisLookup(RefableLookup):
_lookup_types: ClassVar[set] = set([NodeType.Analysis])
_versioned_types: ClassVar[set] = set()
class SingularTestLookup(dbtClassMixin):
def __init__(self, manifest: "Manifest") -> None:
self.storage: Dict[str, Dict[PackageName, UniqueID]] = {}
self.populate(manifest)
def get_unique_id(self, search_name, package: Optional[PackageName]) -> Optional[UniqueID]:
return find_unique_id_for_package(self.storage, search_name, package)
def find(
self, search_name, package: Optional[PackageName], manifest: "Manifest"
) -> Optional[SingularTestNode]:
unique_id = self.get_unique_id(search_name, package)
if unique_id is not None:
return self.perform_lookup(unique_id, manifest)
return None
def add_singular_test(self, source: SingularTestNode) -> None:
if source.search_name not in self.storage:
self.storage[source.search_name] = {}
self.storage[source.search_name][source.package_name] = source.unique_id
def populate(self, manifest: "Manifest") -> None:
for node in manifest.nodes.values():
if isinstance(node, SingularTestNode):
self.add_singular_test(node)
def perform_lookup(self, unique_id: UniqueID, manifest: "Manifest") -> SingularTestNode:
if unique_id not in manifest.nodes:
raise dbt_common.exceptions.DbtInternalError(
f"Singular test {unique_id} found in cache but not found in manifest"
)
node = manifest.nodes[unique_id]
assert isinstance(node, SingularTestNode)
return node
def _packages_to_search(
current_project: str,
node_package: str,
target_package: Optional[str] = None,
) -> List[Optional[str]]:
if target_package is not None:
return [target_package]
elif current_project == node_package:
return [current_project, None]
else:
return [current_project, node_package, None]
def _sort_values(dct):
"""Given a dictionary, sort each value. This makes output deterministic,
which helps for tests.
"""
return {k: sorted(v) for k, v in dct.items()}
def build_node_edges(nodes: List[ManifestNode]):
"""Build the forward and backward edges on the given list of ManifestNodes
and return them as two separate dictionaries, each mapping unique IDs to
lists of edges.
"""
backward_edges: Dict[str, List[str]] = {}
# pre-populate the forward edge dict for simplicity
forward_edges: Dict[str, List[str]] = {n.unique_id: [] for n in nodes}
for node in nodes:
backward_edges[node.unique_id] = node.depends_on_nodes[:]
for unique_id in backward_edges[node.unique_id]:
if unique_id in forward_edges.keys():
forward_edges[unique_id].append(node.unique_id)
return _sort_values(forward_edges), _sort_values(backward_edges)
# Build a map of children of macros and generic tests
def build_macro_edges(nodes: List[Any]):
forward_edges: Dict[str, List[str]] = {
n.unique_id: [] for n in nodes if n.unique_id.startswith("macro") or n.depends_on_macros
}
for node in nodes:
for unique_id in node.depends_on_macros:
if unique_id in forward_edges.keys():
forward_edges[unique_id].append(node.unique_id)
return _sort_values(forward_edges)
def _deepcopy(value):
return value.from_dict(value.to_dict(omit_none=True))
class Locality(enum.IntEnum):
Core = 1
Imported = 2
Root = 3
@dataclass
class MacroCandidate:
locality: Locality
macro: Macro
def __eq__(self, other: object) -> bool:
if not isinstance(other, MacroCandidate):
return NotImplemented
return self.locality == other.locality
def __lt__(self, other: object) -> bool:
if not isinstance(other, MacroCandidate):
return NotImplemented
if self.locality < other.locality:
return True
if self.locality > other.locality:
return False
return False
@dataclass
class MaterializationCandidate(MacroCandidate):
# specificity describes where in the inheritance chain this materialization candidate is
# a specificity of 0 means a materialization defined by the current adapter
# the highest the specificity describes a default materialization. the value itself depends on
# how many adapters there are in the inheritance chain
specificity: int
@classmethod
def from_macro(cls, candidate: MacroCandidate, specificity: int) -> "MaterializationCandidate":
return cls(
locality=candidate.locality,
macro=candidate.macro,
specificity=specificity,
)
def __eq__(self, other: object) -> bool:
if not isinstance(other, MaterializationCandidate):
return NotImplemented
equal = self.specificity == other.specificity and self.locality == other.locality
if equal:
raise DuplicateMaterializationNameError(self.macro, other)
return equal
def __lt__(self, other: object) -> bool:
if not isinstance(other, MaterializationCandidate):
return NotImplemented
if self.specificity > other.specificity:
return True
if self.specificity < other.specificity:
return False
if self.locality < other.locality:
return True
if self.locality > other.locality:
return False
return False
M = TypeVar("M", bound=MacroCandidate)
class CandidateList(List[M]):
def last_candidate(
self, valid_localities: Optional[List[Locality]] = None
) -> Optional[MacroCandidate]:
"""
Obtain the last (highest precedence) MacroCandidate from the CandidateList of any locality in valid_localities.
If valid_localities is not specified, return the last MacroCandidate of any locality.
"""
if not self:
return None
self.sort()
if valid_localities is None:
return self[-1]
for candidate in reversed(self):
if candidate.locality in valid_localities:
return candidate
return None
def last(self) -> Optional[Macro]:
last_candidate = self.last_candidate()
return last_candidate.macro if last_candidate is not None else None
def _get_locality(macro: Macro, root_project_name: str, internal_packages: Set[str]) -> Locality:
if macro.package_name == root_project_name:
return Locality.Root
elif macro.package_name in internal_packages:
return Locality.Core
else:
return Locality.Imported
class Searchable(Protocol):
resource_type: NodeType
package_name: str
@property
def search_name(self) -> str:
raise NotImplementedError("search_name not implemented")
D = TypeVar("D")
@dataclass
class Disabled(Generic[D]):
target: D
MaybeMetricNode = Optional[Union[Metric, Disabled[Metric]]]
MaybeSavedQueryNode = Optional[Union[SavedQuery, Disabled[SavedQuery]]]
MaybeDocumentation = Optional[Documentation]
MaybeParsedSource = Optional[
Union[
SourceDefinition,
Disabled[SourceDefinition],
]
]
MaybeNonSource = Optional[Union[ManifestNode, Disabled[ManifestNode]]]
T = TypeVar("T", bound=GraphMemberNode)
# This contains macro methods that are in both the Manifest
# and the MacroManifest
class MacroMethods:
# Just to make mypy happy. There must be a better way.
def __init__(self):
self.macros = []
self.metadata = {}
self._macros_by_name = {}
self._macros_by_package = {}
def find_macro_by_name(
self, name: str, root_project_name: str, package: Optional[str]
) -> Optional[Macro]:
"""Find a macro in the graph by its name and package name, or None for
any package. The root project name is used to determine priority:
- locally defined macros come first
- then imported macros
- then macros defined in the root project
"""
filter: Optional[Callable[[MacroCandidate], bool]] = None
if package is not None:
def filter(candidate: MacroCandidate) -> bool:
return package == candidate.macro.package_name
candidates: CandidateList = self._find_macros_by_name(
name=name,
root_project_name=root_project_name,
filter=filter,
)
return candidates.last()
def find_generate_macro_by_name(
self, component: str, root_project_name: str, imported_package: Optional[str] = None
) -> Optional[Macro]:
"""
The default `generate_X_name` macros are similar to regular ones, but only
includes imported packages when searching for a package.
- if package is not provided:
- if there is a `generate_{component}_name` macro in the root
project, return it
- return the `generate_{component}_name` macro from the 'dbt'
internal project
- if package is provided
- return the `generate_{component}_name` macro from the imported
package, if one exists
"""
def filter(candidate: MacroCandidate) -> bool:
if imported_package:
return (
candidate.locality == Locality.Imported
and imported_package == candidate.macro.package_name
)
else:
return candidate.locality != Locality.Imported
candidates: CandidateList = self._find_macros_by_name(
name=f"generate_{component}_name",
root_project_name=root_project_name,
filter=filter,
)
return candidates.last()
def _find_macros_by_name(
self,
name: str,
root_project_name: str,
filter: Optional[Callable[[MacroCandidate], bool]] = None,
) -> CandidateList:
"""Find macros by their name."""
candidates: CandidateList = CandidateList()
macros_by_name = self.get_macros_by_name()
if name not in macros_by_name:
return candidates
packages = set(get_adapter_package_names(self.metadata.adapter_type))
for macro in macros_by_name[name]:
candidate = MacroCandidate(
locality=_get_locality(macro, root_project_name, packages),
macro=macro,
)
if filter is None or filter(candidate):
candidates.append(candidate)
return candidates
def get_macros_by_name(self) -> Dict[str, List[Macro]]:
if self._macros_by_name is None:
# The by-name mapping doesn't exist yet (perhaps because the manifest
# was deserialized), so we build it.
self._macros_by_name = self._build_macros_by_name(self.macros)
return self._macros_by_name
@staticmethod
def _build_macros_by_name(macros: Mapping[str, Macro]) -> Dict[str, List[Macro]]:
# Convert a macro dictionary keyed on unique id to a flattened version
# keyed on macro name for faster lookup by name. Since macro names are
# not necessarily unique, the dict value is a list.
macros_by_name: Dict[str, List[Macro]] = {}
for macro in macros.values():
if macro.name not in macros_by_name:
macros_by_name[macro.name] = []
macros_by_name[macro.name].append(macro)
return macros_by_name
def get_macros_by_package(self) -> Dict[str, Dict[str, Macro]]:
if self._macros_by_package is None:
# The by-package mapping doesn't exist yet (perhaps because the manifest
# was deserialized), so we build it.
self._macros_by_package = self._build_macros_by_package(self.macros)
return self._macros_by_package
@staticmethod
def _build_macros_by_package(macros: Mapping[str, Macro]) -> Dict[str, Dict[str, Macro]]:
# Convert a macro dictionary keyed on unique id to a flattened version
# keyed on package name for faster lookup by name.
macros_by_package: Dict[str, Dict[str, Macro]] = {}
for macro in macros.values():
if macro.package_name not in macros_by_package:
macros_by_package[macro.package_name] = {}
macros_by_name = macros_by_package[macro.package_name]
macros_by_name[macro.name] = macro
return macros_by_package
@dataclass
class ParsingInfo:
static_analysis_parsed_path_count: int = 0
static_analysis_path_count: int = 0
@dataclass
class ManifestStateCheck(dbtClassMixin):
vars_hash: FileHash = field(default_factory=FileHash.empty)
project_env_vars_hash: FileHash = field(default_factory=FileHash.empty)
profile_env_vars_hash: FileHash = field(default_factory=FileHash.empty)
profile_hash: FileHash = field(default_factory=FileHash.empty)
project_hashes: MutableMapping[str, FileHash] = field(default_factory=dict)
NodeClassT = TypeVar("NodeClassT", bound="BaseNode")
ResourceClassT = TypeVar("ResourceClassT", bound="BaseResource")
@dataclass
class Manifest(MacroMethods, dbtClassMixin):
"""The manifest for the full graph, after parsing and during compilation."""
# These attributes are both positional and by keyword. If an attribute
# is added it must all be added in the __reduce_ex__ method in the
# args tuple in the right position.
nodes: MutableMapping[str, ManifestNode] = field(default_factory=dict)
sources: MutableMapping[str, SourceDefinition] = field(default_factory=dict)
macros: MutableMapping[str, Macro] = field(default_factory=dict)
docs: MutableMapping[str, Documentation] = field(default_factory=dict)
exposures: MutableMapping[str, Exposure] = field(default_factory=dict)
metrics: MutableMapping[str, Metric] = field(default_factory=dict)
groups: MutableMapping[str, Group] = field(default_factory=dict)
selectors: MutableMapping[str, Any] = field(default_factory=dict)
files: MutableMapping[str, AnySourceFile] = field(default_factory=dict)
metadata: ManifestMetadata = field(default_factory=ManifestMetadata)
flat_graph: Dict[str, Any] = field(default_factory=dict)
state_check: ManifestStateCheck = field(default_factory=ManifestStateCheck)
source_patches: MutableMapping[SourceKey, SourcePatch] = field(default_factory=dict)
disabled: MutableMapping[str, List[GraphMemberNode]] = field(default_factory=dict)
env_vars: MutableMapping[str, str] = field(default_factory=dict)
semantic_models: MutableMapping[str, SemanticModel] = field(default_factory=dict)
unit_tests: MutableMapping[str, UnitTestDefinition] = field(default_factory=dict)
saved_queries: MutableMapping[str, SavedQuery] = field(default_factory=dict)
fixtures: MutableMapping[str, UnitTestFileFixture] = field(default_factory=dict)
_doc_lookup: Optional[DocLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_source_lookup: Optional[SourceLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_ref_lookup: Optional[RefableLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_metric_lookup: Optional[MetricLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_saved_query_lookup: Optional[SavedQueryLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_semantic_model_by_measure_lookup: Optional[SemanticModelByMeasureLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_disabled_lookup: Optional[DisabledLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_analysis_lookup: Optional[AnalysisLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_singular_test_lookup: Optional[SingularTestLookup] = field(
default=None, metadata={"serialize": lambda x: None, "deserialize": lambda x: None}
)
_parsing_info: ParsingInfo = field(
default_factory=ParsingInfo,
metadata={"serialize": lambda x: None, "deserialize": lambda x: None},
)
_lock: Lock = field(
default_factory=get_mp_context().Lock,
metadata={"serialize": lambda x: None, "deserialize": lambda x: None},
)
_macros_by_name: Optional[Dict[str, List[Macro]]] = field(
default=None,
metadata={"serialize": lambda x: None, "deserialize": lambda x: None},
)
_macros_by_package: Optional[Dict[str, Dict[str, Macro]]] = field(
default=None,
metadata={"serialize": lambda x: None, "deserialize": lambda x: None},
)
def __pre_serialize__(self, context: Optional[Dict] = None):
# serialization won't work with anything except an empty source_patches because
# tuple keys are not supported, so ensure it's empty
self.source_patches = {}
return self
@classmethod
def __post_deserialize__(cls, obj):
obj._lock = get_mp_context().Lock()
return obj
def build_flat_graph(self):
"""This attribute is used in context.common by each node, so we want to
only build it once and avoid any concurrency issues around it.
Make sure you don't call this until you're done with building your
manifest!
"""
self.flat_graph = {
"exposures": {k: v.to_dict(omit_none=False) for k, v in self.exposures.items()},
"groups": {k: v.to_dict(omit_none=False) for k, v in self.groups.items()},
"metrics": {k: v.to_dict(omit_none=False) for k, v in self.metrics.items()},
"nodes": {k: v.to_dict(omit_none=False) for k, v in self.nodes.items()},
"sources": {k: v.to_dict(omit_none=False) for k, v in self.sources.items()},
"semantic_models": {
k: v.to_dict(omit_none=False) for k, v in self.semantic_models.items()
},
"saved_queries": {
k: v.to_dict(omit_none=False) for k, v in self.saved_queries.items()
},
}
def build_disabled_by_file_id(self):
disabled_by_file_id = {}
for node_list in self.disabled.values():
for node in node_list:
disabled_by_file_id[node.file_id] = node
return disabled_by_file_id
def _get_parent_adapter_types(self, adapter_type: str) -> List[str]:
# This is duplicated logic from core/dbt/context/providers.py
# Ideally this would instead be incorporating actual dispatch logic
from dbt.adapters.factory import get_adapter_type_names
# order matters for dispatch:
# 1. current adapter
# 2. any parent adapters (dependencies)
# 3. 'default'
return get_adapter_type_names(adapter_type) + ["default"]
def _materialization_candidates_for(
self,
project_name: str,
materialization_name: str,
adapter_type: str,
specificity: int,
) -> CandidateList:
full_name = dbt_common.utils.get_materialization_macro_name(
materialization_name=materialization_name,
adapter_type=adapter_type,
with_prefix=False,
)
return CandidateList(
MaterializationCandidate.from_macro(m, specificity)
for m in self._find_macros_by_name(full_name, project_name)
)
def find_materialization_macro_by_name(
self, project_name: str, materialization_name: str, adapter_type: str
) -> Optional[Macro]:
candidates: CandidateList = CandidateList(