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|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedOpenAIModelProfile.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"reasoning_effort",
"verbosity"
] |
ResolvedOpenAIModelProfile
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedOpenAIModelProfile.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "reasoning_effort", "verbosity"]
Returns: None
Parent Class: ResolvedOpenAIModelProfile
|
class
|
ResolvedCohereModelProfile
|
fenic.core._resolved_session_config.ResolvedCohereModelProfile
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 48 | 51 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedCohereModelProfile
Qualified Name: fenic.core._resolved_session_config.ResolvedCohereModelProfile
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedCohereModelProfile.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"embedding_dimensionality",
"embedding_task_type"
] |
ResolvedCohereModelProfile
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedCohereModelProfile.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "embedding_dimensionality", "embedding_task_type"]
Returns: None
Parent Class: ResolvedCohereModelProfile
|
class
|
ResolvedOpenAIModelConfig
|
fenic.core._resolved_session_config.ResolvedOpenAIModelConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 53 | 60 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedOpenAIModelConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedOpenAIModelConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedOpenAIModelConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"model_name",
"rpm",
"tpm",
"model_provider",
"profiles",
"default_profile"
] |
ResolvedOpenAIModelConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedOpenAIModelConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_name", "rpm", "tpm", "model_provider", "profiles", "default_profile"]
Returns: None
Parent Class: ResolvedOpenAIModelConfig
|
class
|
ResolvedAnthropicModelConfig
|
fenic.core._resolved_session_config.ResolvedAnthropicModelConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 63 | 71 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedAnthropicModelConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedAnthropicModelConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedAnthropicModelConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"model_name",
"rpm",
"input_tpm",
"output_tpm",
"model_provider",
"profiles",
"default_profile"
] |
ResolvedAnthropicModelConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedAnthropicModelConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_name", "rpm", "input_tpm", "output_tpm", "model_provider", "profiles", "default_profile"]
Returns: None
Parent Class: ResolvedAnthropicModelConfig
|
class
|
ResolvedGoogleModelConfig
|
fenic.core._resolved_session_config.ResolvedGoogleModelConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 73 | 80 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedGoogleModelConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedGoogleModelConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedGoogleModelConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"model_name",
"model_provider",
"rpm",
"tpm",
"profiles",
"default_profile"
] |
ResolvedGoogleModelConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedGoogleModelConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_name", "model_provider", "rpm", "tpm", "profiles", "default_profile"]
Returns: None
Parent Class: ResolvedGoogleModelConfig
|
class
|
ResolvedCohereModelConfig
|
fenic.core._resolved_session_config.ResolvedCohereModelConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 82 | 89 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedCohereModelConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedCohereModelConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedCohereModelConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"model_name",
"rpm",
"tpm",
"model_provider",
"profiles",
"default_profile"
] |
ResolvedCohereModelConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedCohereModelConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_name", "rpm", "tpm", "model_provider", "profiles", "default_profile"]
Returns: None
Parent Class: ResolvedCohereModelConfig
|
attribute
|
ResolvedModelConfig
|
fenic.core._resolved_session_config.ResolvedModelConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 91 | 91 | null | null | null | null |
Union[ResolvedOpenAIModelConfig, ResolvedAnthropicModelConfig, ResolvedGoogleModelConfig, ResolvedCohereModelConfig]
| null |
Type: attribute
Member Name: ResolvedModelConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedModelConfig
Docstring: none
Value: Union[ResolvedOpenAIModelConfig, ResolvedAnthropicModelConfig, ResolvedGoogleModelConfig, ResolvedCohereModelConfig]
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
class
|
ResolvedSemanticConfig
|
fenic.core._resolved_session_config.ResolvedSemanticConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 96 | 99 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedSemanticConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedSemanticConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedSemanticConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"language_models",
"embedding_models"
] |
ResolvedSemanticConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedSemanticConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "language_models", "embedding_models"]
Returns: None
Parent Class: ResolvedSemanticConfig
|
class
|
ResolvedLanguageModelConfig
|
fenic.core._resolved_session_config.ResolvedLanguageModelConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 101 | 104 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedLanguageModelConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedLanguageModelConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedLanguageModelConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"model_configs",
"default_model"
] |
ResolvedLanguageModelConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedLanguageModelConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_configs", "default_model"]
Returns: None
Parent Class: ResolvedLanguageModelConfig
|
class
|
ResolvedEmbeddingModelConfig
|
fenic.core._resolved_session_config.ResolvedEmbeddingModelConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 106 | 109 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedEmbeddingModelConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedEmbeddingModelConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedEmbeddingModelConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"model_configs",
"default_model"
] |
ResolvedEmbeddingModelConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedEmbeddingModelConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "model_configs", "default_model"]
Returns: None
Parent Class: ResolvedEmbeddingModelConfig
|
class
|
ResolvedCloudConfig
|
fenic.core._resolved_session_config.ResolvedCloudConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 111 | 113 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedCloudConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedCloudConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedCloudConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"size"
] |
ResolvedCloudConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedCloudConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "size"]
Returns: None
Parent Class: ResolvedCloudConfig
|
class
|
ResolvedSessionConfig
|
fenic.core._resolved_session_config.ResolvedSessionConfig
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 116 | 121 | null | null | null | null | null |
[] |
Type: class
Member Name: ResolvedSessionConfig
Qualified Name: fenic.core._resolved_session_config.ResolvedSessionConfig
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._resolved_session_config.ResolvedSessionConfig.__init__
| null |
site-packages/fenic/core/_resolved_session_config.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"app_name",
"db_path",
"semantic",
"cloud"
] |
ResolvedSessionConfig
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._resolved_session_config.ResolvedSessionConfig.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "app_name", "db_path", "semantic", "cloud"]
Returns: None
Parent Class: ResolvedSessionConfig
|
module
|
_utils
|
fenic.core._utils
| null |
site-packages/fenic/core/_utils/__init__.py
| false | true | null | null | null | null | null | null | null | null |
Type: module
Member Name: _utils
Qualified Name: fenic.core._utils
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none
|
module
|
misc
|
fenic.core._utils.misc
| null |
site-packages/fenic/core/_utils/misc.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: misc
Qualified Name: fenic.core._utils.misc
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
function
|
get_content_hash
|
fenic.core._utils.misc.get_content_hash
|
Generate a short, consistent hash for a string.
This uses UUIDv5 (namespaced UUID) to generate a deterministic hash
of the content string, and returns the first 8 characters for brevity.
Args:
content: The input string to hash.
Returns:
A short string representing the hash of the input.
Example:
>>> get_content_hash("hello")
'aaf4c61d' # (your output will vary depending on namespace and content)
|
site-packages/fenic/core/_utils/misc.py
| true | false | 4 | 20 | null |
str
|
[
"content"
] | null | null | null |
Type: function
Member Name: get_content_hash
Qualified Name: fenic.core._utils.misc.get_content_hash
Docstring: Generate a short, consistent hash for a string.
This uses UUIDv5 (namespaced UUID) to generate a deterministic hash
of the content string, and returns the first 8 characters for brevity.
Args:
content: The input string to hash.
Returns:
A short string representing the hash of the input.
Example:
>>> get_content_hash("hello")
'aaf4c61d' # (your output will vary depending on namespace and content)
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["content"]
Returns: str
Parent Class: none
|
function
|
generate_unique_arrow_view_name
|
fenic.core._utils.misc.generate_unique_arrow_view_name
|
Generate a unique temporary view name for an Arrow table.
This is useful for assigning a one-off name to a view or table when
working with in-memory or temporary datasets.
Returns:
A string representing a unique temporary view name.
Example:
>>> generate_unique_arrow_view_name()
'temp_arrow_view_1a2b3c4d5e6f...'
|
site-packages/fenic/core/_utils/misc.py
| true | false | 23 | 36 | null |
str
|
[] | null | null | null |
Type: function
Member Name: generate_unique_arrow_view_name
Qualified Name: fenic.core._utils.misc.generate_unique_arrow_view_name
Docstring: Generate a unique temporary view name for an Arrow table.
This is useful for assigning a one-off name to a view or table when
working with in-memory or temporary datasets.
Returns:
A string representing a unique temporary view name.
Example:
>>> generate_unique_arrow_view_name()
'temp_arrow_view_1a2b3c4d5e6f...'
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: []
Returns: str
Parent Class: none
|
module
|
json_schema_utils
|
fenic.core._utils.json_schema_utils
| null |
site-packages/fenic/core/_utils/json_schema_utils.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: json_schema_utils
Qualified Name: fenic.core._utils.json_schema_utils
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
function
|
unwrap_optional_union
|
fenic.core._utils.json_schema_utils.unwrap_optional_union
|
If node is an anyOf/oneOf with a null branch, return the first non-null branch.
Otherwise return node unchanged.
|
site-packages/fenic/core/_utils/json_schema_utils.py
| true | false | 7 | 18 | null |
Dict[str, Any]
|
[
"node"
] | null | null | null |
Type: function
Member Name: unwrap_optional_union
Qualified Name: fenic.core._utils.json_schema_utils.unwrap_optional_union
Docstring: If node is an anyOf/oneOf with a null branch, return the first non-null branch.
Otherwise return node unchanged.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["node"]
Returns: Dict[str, Any]
Parent Class: none
|
function
|
to_strict_json_schema
|
fenic.core._utils.json_schema_utils.to_strict_json_schema
|
Return a strict JSON Schema suitable for a Model Provider.
All Model Providers have different requirements for supported features and formats of JSON schemas.
This function is a best-effort attempt to generate a JSON schema that is strict enough for the most inflexible model provider:
OpenAI. Other model provider implementations may need to apply additional transformations to the schema before passing it to the model provider.
Rules (adapted from OpenAI's internal logic):
- Set additionalProperties: false for all objects (when not present)
- Set required to all keys in properties
- Recurse into properties, items, anyOf, allOf (flatten allOf of length 1)
- Strip default when it's None
- If a node has $ref alongside other keys, inline the ref target and re-ensure strictness
This function deep-copies the input once and then mutates the copy in-place. This performs
all the operations that would have been performed if a Pydantic Model were to be passed to the
LLM Model Provider.
|
site-packages/fenic/core/_utils/json_schema_utils.py
| true | false | 20 | 123 | null |
Dict[str, Any]
|
[
"schema"
] | null | null | null |
Type: function
Member Name: to_strict_json_schema
Qualified Name: fenic.core._utils.json_schema_utils.to_strict_json_schema
Docstring: Return a strict JSON Schema suitable for a Model Provider.
All Model Providers have different requirements for supported features and formats of JSON schemas.
This function is a best-effort attempt to generate a JSON schema that is strict enough for the most inflexible model provider:
OpenAI. Other model provider implementations may need to apply additional transformations to the schema before passing it to the model provider.
Rules (adapted from OpenAI's internal logic):
- Set additionalProperties: false for all objects (when not present)
- Set required to all keys in properties
- Recurse into properties, items, anyOf, allOf (flatten allOf of length 1)
- Strip default when it's None
- If a node has $ref alongside other keys, inline the ref target and re-ensure strictness
This function deep-copies the input once and then mutates the copy in-place. This performs
all the operations that would have been performed if a Pydantic Model were to be passed to the
LLM Model Provider.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["schema"]
Returns: Dict[str, Any]
Parent Class: none
|
module
|
type_inference
|
fenic.core._utils.type_inference
| null |
site-packages/fenic/core/_utils/type_inference.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: type_inference
Qualified Name: fenic.core._utils.type_inference
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
class
|
TypeInferenceError
|
fenic.core._utils.type_inference.TypeInferenceError
| null |
site-packages/fenic/core/_utils/type_inference.py
| true | false | 22 | 26 | null | null | null | null | null |
[
"ValueError"
] |
Type: class
Member Name: TypeInferenceError
Qualified Name: fenic.core._utils.type_inference.TypeInferenceError
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core._utils.type_inference.TypeInferenceError.__init__
| null |
site-packages/fenic/core/_utils/type_inference.py
| true | false | 23 | 26 | null | null |
[
"self",
"message",
"path"
] |
TypeInferenceError
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core._utils.type_inference.TypeInferenceError.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "message", "path"]
Returns: none
Parent Class: TypeInferenceError
|
function
|
infer_pytype_from_dtype
|
fenic.core._utils.type_inference.infer_pytype_from_dtype
| null |
site-packages/fenic/core/_utils/type_inference.py
| true | false | 28 | 48 | null |
type
|
[
"dtype"
] | null | null | null |
Type: function
Member Name: infer_pytype_from_dtype
Qualified Name: fenic.core._utils.type_inference.infer_pytype_from_dtype
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["dtype"]
Returns: type
Parent Class: none
|
function
|
infer_dtype_from_pyobj
|
fenic.core._utils.type_inference.infer_dtype_from_pyobj
| null |
site-packages/fenic/core/_utils/type_inference.py
| true | false | 50 | 86 | null |
DataType
|
[
"value",
"path"
] | null | null | null |
Type: function
Member Name: infer_dtype_from_pyobj
Qualified Name: fenic.core._utils.type_inference.infer_dtype_from_pyobj
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["value", "path"]
Returns: DataType
Parent Class: none
|
function
|
_find_common_supertype
|
fenic.core._utils.type_inference._find_common_supertype
| null |
site-packages/fenic/core/_utils/type_inference.py
| false | true | 89 | 126 | null |
DataType
|
[
"type1",
"type2",
"path"
] | null | null | null |
Type: function
Member Name: _find_common_supertype
Qualified Name: fenic.core._utils.type_inference._find_common_supertype
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["type1", "type2", "path"]
Returns: DataType
Parent Class: none
|
module
|
structured_outputs
|
fenic.core._utils.structured_outputs
| null |
site-packages/fenic/core/_utils/structured_outputs.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: structured_outputs
Qualified Name: fenic.core._utils.structured_outputs
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
logger
|
fenic.core._utils.structured_outputs.logger
| null |
site-packages/fenic/core/_utils/structured_outputs.py
| true | false | 16 | 16 | null | null | null | null |
logging.getLogger(__name__)
| null |
Type: attribute
Member Name: logger
Qualified Name: fenic.core._utils.structured_outputs.logger
Docstring: none
Value: logging.getLogger(__name__)
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
class
|
OutputFormatValidationError
|
fenic.core._utils.structured_outputs.OutputFormatValidationError
|
Error raised when a semantic operation schema is invalid.
|
site-packages/fenic/core/_utils/structured_outputs.py
| true | false | 18 | 19 | null | null | null | null | null |
[
"Exception"
] |
Type: class
Member Name: OutputFormatValidationError
Qualified Name: fenic.core._utils.structured_outputs.OutputFormatValidationError
Docstring: Error raised when a semantic operation schema is invalid.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
function
|
validate_output_format
|
fenic.core._utils.structured_outputs.validate_output_format
|
Check a Pydantic model type to ensure it is valid schema for semantic operations.
This function validates schemas used by semantic operations like extract, map, etc.
to ensure they have proper field descriptions and supported types.
Args:
model: The Pydantic model class to validate
Raises:
SemanticSchemaValidationError: If the schema is invalid
|
site-packages/fenic/core/_utils/structured_outputs.py
| true | false | 22 | 49 | null |
None
|
[
"model"
] | null | null | null |
Type: function
Member Name: validate_output_format
Qualified Name: fenic.core._utils.structured_outputs.validate_output_format
Docstring: Check a Pydantic model type to ensure it is valid schema for semantic operations.
This function validates schemas used by semantic operations like extract, map, etc.
to ensure they have proper field descriptions and supported types.
Args:
model: The Pydantic model class to validate
Raises:
SemanticSchemaValidationError: If the schema is invalid
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["model"]
Returns: None
Parent Class: none
|
function
|
_validate_semantic_field_type
|
fenic.core._utils.structured_outputs._validate_semantic_field_type
|
Recursively validate field types for semantic operations.
|
site-packages/fenic/core/_utils/structured_outputs.py
| false | true | 52 | 95 | null |
None
|
[
"annotation",
"field_name"
] | null | null | null |
Type: function
Member Name: _validate_semantic_field_type
Qualified Name: fenic.core._utils.structured_outputs._validate_semantic_field_type
Docstring: Recursively validate field types for semantic operations.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["annotation", "field_name"]
Returns: None
Parent Class: none
|
function
|
convert_pydantic_model_to_key_descriptions
|
fenic.core._utils.structured_outputs.convert_pydantic_model_to_key_descriptions
|
Extract keys, types, and descriptions from a Pydantic model, including nested models and lists.
This function is used by structured semantic operations (extract, map, etc.) to convert
Pydantic schema models into human-readable field descriptions for LLM prompts.
Args:
schema (Type[BaseModel]): The Pydantic model class.
Returns:
str: Formatted string of model keys and descriptions.
|
site-packages/fenic/core/_utils/structured_outputs.py
| true | false | 98 | 185 | null |
str
|
[
"schema"
] | null | null | null |
Type: function
Member Name: convert_pydantic_model_to_key_descriptions
Qualified Name: fenic.core._utils.structured_outputs.convert_pydantic_model_to_key_descriptions
Docstring: Extract keys, types, and descriptions from a Pydantic model, including nested models and lists.
This function is used by structured semantic operations (extract, map, etc.) to convert
Pydantic schema models into human-readable field descriptions for LLM prompts.
Args:
schema (Type[BaseModel]): The Pydantic model class.
Returns:
str: Formatted string of model keys and descriptions.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["schema"]
Returns: str
Parent Class: none
|
module
|
schema
|
fenic.core._utils.schema
|
Utilities for converting between different schema representations.
|
site-packages/fenic/core/_utils/schema.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: schema
Qualified Name: fenic.core._utils.schema
Docstring: Utilities for converting between different schema representations.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
function
|
convert_polars_schema_to_custom_schema
|
fenic.core._utils.schema.convert_polars_schema_to_custom_schema
|
Convert a Polars schema to a fenic Schema.
Args:
polars_schema: The Polars schema to convert
Returns:
The corresponding fenic Schema with equivalent column fields
Example:
>>> custom_schema = convert_polars_schema_to_custom_schema(df.schema)
|
site-packages/fenic/core/_utils/schema.py
| true | false | 28 | 50 | null |
Schema
|
[
"polars_schema"
] | null | null | null |
Type: function
Member Name: convert_polars_schema_to_custom_schema
Qualified Name: fenic.core._utils.schema.convert_polars_schema_to_custom_schema
Docstring: Convert a Polars schema to a fenic Schema.
Args:
polars_schema: The Polars schema to convert
Returns:
The corresponding fenic Schema with equivalent column fields
Example:
>>> custom_schema = convert_polars_schema_to_custom_schema(df.schema)
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["polars_schema"]
Returns: Schema
Parent Class: none
|
function
|
convert_custom_schema_to_polars_schema
|
fenic.core._utils.schema.convert_custom_schema_to_polars_schema
|
Convert a fenic Schema to a Polars schema.
Args:
custom_schema: The fenic Schema to convert
Returns:
The corresponding Polars schema with equivalent fields
Example:
>>> polars_schema = convert_custom_schema_to_polars_schema(custom_schema)
|
site-packages/fenic/core/_utils/schema.py
| true | false | 53 | 72 | null |
pl.Schema
|
[
"custom_schema"
] | null | null | null |
Type: function
Member Name: convert_custom_schema_to_polars_schema
Qualified Name: fenic.core._utils.schema.convert_custom_schema_to_polars_schema
Docstring: Convert a fenic Schema to a Polars schema.
Args:
custom_schema: The fenic Schema to convert
Returns:
The corresponding Polars schema with equivalent fields
Example:
>>> polars_schema = convert_custom_schema_to_polars_schema(custom_schema)
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["custom_schema"]
Returns: pl.Schema
Parent Class: none
|
function
|
convert_pydantic_type_to_custom_struct_type
|
fenic.core._utils.schema.convert_pydantic_type_to_custom_struct_type
|
Convert a Pydantic model to a custom StructType.
Args:
model: The Pydantic model to convert (either an instance or a class)
Returns:
The corresponding custom StructType
Raises:
ValueError: If the model is not a Pydantic model
Example:
>>> struct_type = convert_pydantic_type_to_custom_struct_type(model)
|
site-packages/fenic/core/_utils/schema.py
| true | false | 75 | 131 | null |
StructType
|
[
"model"
] | null | null | null |
Type: function
Member Name: convert_pydantic_type_to_custom_struct_type
Qualified Name: fenic.core._utils.schema.convert_pydantic_type_to_custom_struct_type
Docstring: Convert a Pydantic model to a custom StructType.
Args:
model: The Pydantic model to convert (either an instance or a class)
Returns:
The corresponding custom StructType
Raises:
ValueError: If the model is not a Pydantic model
Example:
>>> struct_type = convert_pydantic_type_to_custom_struct_type(model)
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["model"]
Returns: StructType
Parent Class: none
|
function
|
convert_custom_dtype_to_polars
|
fenic.core._utils.schema.convert_custom_dtype_to_polars
|
Convert custom data type to the Polars data type.
Args:
custom_dtype: Custom data type
Returns:
pl.DataType: Corresponding Polars data type
Raises:
ValueError: If the custom data type is not supported
|
site-packages/fenic/core/_utils/schema.py
| true | false | 133 | 181 | null |
pl.DataType
|
[
"custom_dtype"
] | null | null | null |
Type: function
Member Name: convert_custom_dtype_to_polars
Qualified Name: fenic.core._utils.schema.convert_custom_dtype_to_polars
Docstring: Convert custom data type to the Polars data type.
Args:
custom_dtype: Custom data type
Returns:
pl.DataType: Corresponding Polars data type
Raises:
ValueError: If the custom data type is not supported
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["custom_dtype"]
Returns: pl.DataType
Parent Class: none
|
function
|
_convert_pytype_to_custom_dtype
|
fenic.core._utils.schema._convert_pytype_to_custom_dtype
|
Convert a basic Python type to a PrimitiveType.
|
site-packages/fenic/core/_utils/schema.py
| false | true | 184 | 197 | null |
_PrimitiveType
|
[
"py_type"
] | null | null | null |
Type: function
Member Name: _convert_pytype_to_custom_dtype
Qualified Name: fenic.core._utils.schema._convert_pytype_to_custom_dtype
Docstring: Convert a basic Python type to a PrimitiveType.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["py_type"]
Returns: _PrimitiveType
Parent Class: none
|
function
|
_convert_polars_dtype_to_custom_dtype
|
fenic.core._utils.schema._convert_polars_dtype_to_custom_dtype
|
Convert Polars data type to the custom PrimitiveType enum or complex type.
Args:
polars_dtype: Polars data type
Returns:
Union[PrimitiveType, ArrayType, StructType]: Corresponding custom data type
Raises:
ValueError: If the Polars data type is not supported
|
site-packages/fenic/core/_utils/schema.py
| false | true | 200 | 250 | null |
DataType
|
[
"polars_dtype"
] | null | null | null |
Type: function
Member Name: _convert_polars_dtype_to_custom_dtype
Qualified Name: fenic.core._utils.schema._convert_polars_dtype_to_custom_dtype
Docstring: Convert Polars data type to the custom PrimitiveType enum or complex type.
Args:
polars_dtype: Polars data type
Returns:
Union[PrimitiveType, ArrayType, StructType]: Corresponding custom data type
Raises:
ValueError: If the Polars data type is not supported
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["polars_dtype"]
Returns: DataType
Parent Class: none
|
function
|
_unwrap_optional_type
|
fenic.core._utils.schema._unwrap_optional_type
|
Unwrap Optional type and return (actual_type, is_optional).
|
site-packages/fenic/core/_utils/schema.py
| false | true | 252 | 268 | null |
type
|
[
"annotation"
] | null | null | null |
Type: function
Member Name: _unwrap_optional_type
Qualified Name: fenic.core._utils.schema._unwrap_optional_type
Docstring: Unwrap Optional type and return (actual_type, is_optional).
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["annotation"]
Returns: type
Parent Class: none
|
module
|
types
|
fenic.core.types
|
Schema module for defining and manipulating DataFrame schemas.
|
site-packages/fenic/core/types/__init__.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: types
Qualified Name: fenic.core.types
Docstring: Schema module for defining and manipulating DataFrame schemas.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
__all__
|
fenic.core.types.__all__
| null |
site-packages/fenic/core/types/__init__.py
| false | false | 47 | 84 | null | null | null | null |
['ArrayType', 'BooleanType', 'BranchSide', 'ClassDefinition', 'ClassifyExample', 'ClassifyExampleCollection', 'ColumnField', 'DataType', 'DataLike', 'DataLikeType', 'QueryResult', 'DocumentPathType', 'DoubleType', 'EmbeddingType', 'FloatType', 'HtmlType', 'IntegerType', 'JoinExample', 'JoinExampleCollection', 'JsonType', 'MapExample', 'MapExampleCollection', 'MarkdownType', 'PredicateExample', 'PredicateExampleCollection', 'QueryResult', 'Schema', 'SemanticSimilarityMetric', 'StringType', 'StructField', 'StructType', 'KeyPoints', 'Paragraph', 'TranscriptType', 'FuzzySimilarityMethod', 'DatasetMetadata']
| null |
Type: attribute
Member Name: __all__
Qualified Name: fenic.core.types.__all__
Docstring: none
Value: ['ArrayType', 'BooleanType', 'BranchSide', 'ClassDefinition', 'ClassifyExample', 'ClassifyExampleCollection', 'ColumnField', 'DataType', 'DataLike', 'DataLikeType', 'QueryResult', 'DocumentPathType', 'DoubleType', 'EmbeddingType', 'FloatType', 'HtmlType', 'IntegerType', 'JoinExample', 'JoinExampleCollection', 'JsonType', 'MapExample', 'MapExampleCollection', 'MarkdownType', 'PredicateExample', 'PredicateExampleCollection', 'QueryResult', 'Schema', 'SemanticSimilarityMetric', 'StringType', 'StructField', 'StructType', 'KeyPoints', 'Paragraph', 'TranscriptType', 'FuzzySimilarityMethod', 'DatasetMetadata']
Annotation: none
is Public? : false
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
module
|
query_result
|
fenic.core.types.query_result
|
QueryResult class and related types.
|
site-packages/fenic/core/types/query_result.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: query_result
Qualified Name: fenic.core.types.query_result
Docstring: QueryResult class and related types.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
DataLikeType
|
fenic.core.types.query_result.DataLikeType
|
String literal type for specifying data output formats.
Valid values:
- "polars": Native Polars DataFrame format
- "pandas": Pandas DataFrame with PyArrow extension arrays
- "pydict": Python dictionary with column names as keys, lists as values
- "pylist": Python list of dictionaries, each representing one row
- "arrow": Apache Arrow Table format
Used as input parameter for methods that can return data in multiple formats.
|
site-packages/fenic/core/types/query_result.py
| true | false | 13 | 13 | null | null | null | null |
Literal['polars', 'pandas', 'pydict', 'pylist', 'arrow']
| null |
Type: attribute
Member Name: DataLikeType
Qualified Name: fenic.core.types.query_result.DataLikeType
Docstring: String literal type for specifying data output formats.
Valid values:
- "polars": Native Polars DataFrame format
- "pandas": Pandas DataFrame with PyArrow extension arrays
- "pydict": Python dictionary with column names as keys, lists as values
- "pylist": Python list of dictionaries, each representing one row
- "arrow": Apache Arrow Table format
Used as input parameter for methods that can return data in multiple formats.
Value: Literal['polars', 'pandas', 'pydict', 'pylist', 'arrow']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
DataLike
|
fenic.core.types.query_result.DataLike
|
Union type representing any supported data format for both input and output operations.
This type encompasses all possible data structures that can be:
1. Used as input when creating DataFrames
2. Returned as output from query results
Supported formats:
- pl.DataFrame: Native Polars DataFrame with efficient columnar storage
- pd.DataFrame: Pandas DataFrame, optionally with PyArrow extension arrays
- Dict[str, List[Any]]: Column-oriented dictionary where:
* Keys are column names (str)
* Values are lists containing all values for that column
- List[Dict[str, Any]]: Row-oriented list where:
* Each element is a dictionary representing one row
* Dictionary keys are column names, values are cell values
- pa.Table: Apache Arrow Table with columnar memory layout
Usage:
- Input: Used in create_dataframe() to accept data in various formats
- Output: Used in QueryResult.data to return results in requested format
The specific type returned depends on the DataLikeType format specified
when collecting query results.
|
site-packages/fenic/core/types/query_result.py
| true | false | 28 | 34 | null | null | null | null |
Union[pl.DataFrame, pd.DataFrame, Dict[str, List[Any]], List[Dict[str, Any]], pa.Table]
| null |
Type: attribute
Member Name: DataLike
Qualified Name: fenic.core.types.query_result.DataLike
Docstring: Union type representing any supported data format for both input and output operations.
This type encompasses all possible data structures that can be:
1. Used as input when creating DataFrames
2. Returned as output from query results
Supported formats:
- pl.DataFrame: Native Polars DataFrame with efficient columnar storage
- pd.DataFrame: Pandas DataFrame, optionally with PyArrow extension arrays
- Dict[str, List[Any]]: Column-oriented dictionary where:
* Keys are column names (str)
* Values are lists containing all values for that column
- List[Dict[str, Any]]: Row-oriented list where:
* Each element is a dictionary representing one row
* Dictionary keys are column names, values are cell values
- pa.Table: Apache Arrow Table with columnar memory layout
Usage:
- Input: Used in create_dataframe() to accept data in various formats
- Output: Used in QueryResult.data to return results in requested format
The specific type returned depends on the DataLikeType format specified
when collecting query results.
Value: Union[pl.DataFrame, pd.DataFrame, Dict[str, List[Any]], List[Dict[str, Any]], pa.Table]
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
class
|
QueryResult
|
fenic.core.types.query_result.QueryResult
|
Container for query execution results and associated metadata.
This dataclass bundles together the materialized data from a query execution
along with metrics about the execution process. It provides a unified interface
for accessing both the computed results and performance information.
Attributes:
data (DataLike): The materialized query results in the requested format.
Can be any of the supported data types (Polars/Pandas DataFrame,
Arrow Table, or Python dict/list structures).
metrics (QueryMetrics): Execution metadata including timing information,
memory usage, rows processed, and other performance metrics collected
during query execution.
Example: Access query results and metrics
```python
# Execute query and get results with metrics
result = df.filter(col("age") > 25).collect("pandas")
pandas_df = result.data # Access the Pandas DataFrame
print(result.metrics.execution_time) # Access execution metrics
print(result.metrics.rows_processed) # Access row count
```
Example: Work with different data formats
```python
# Get results in different formats
polars_result = df.collect("polars")
arrow_result = df.collect("arrow")
dict_result = df.collect("pydict")
# All contain the same data, different formats
print(type(polars_result.data)) # <class 'polars.DataFrame'>
print(type(arrow_result.data)) # <class 'pyarrow.lib.Table'>
print(type(dict_result.data)) # <class 'dict'>
```
Note:
The actual type of the `data` attribute depends on the format requested
during collection. Use type checking or isinstance() if you need to
handle the data differently based on its format.
|
site-packages/fenic/core/types/query_result.py
| true | false | 61 | 106 | null | null | null | null | null |
[] |
Type: class
Member Name: QueryResult
Qualified Name: fenic.core.types.query_result.QueryResult
Docstring: Container for query execution results and associated metadata.
This dataclass bundles together the materialized data from a query execution
along with metrics about the execution process. It provides a unified interface
for accessing both the computed results and performance information.
Attributes:
data (DataLike): The materialized query results in the requested format.
Can be any of the supported data types (Polars/Pandas DataFrame,
Arrow Table, or Python dict/list structures).
metrics (QueryMetrics): Execution metadata including timing information,
memory usage, rows processed, and other performance metrics collected
during query execution.
Example: Access query results and metrics
```python
# Execute query and get results with metrics
result = df.filter(col("age") > 25).collect("pandas")
pandas_df = result.data # Access the Pandas DataFrame
print(result.metrics.execution_time) # Access execution metrics
print(result.metrics.rows_processed) # Access row count
```
Example: Work with different data formats
```python
# Get results in different formats
polars_result = df.collect("polars")
arrow_result = df.collect("arrow")
dict_result = df.collect("pydict")
# All contain the same data, different formats
print(type(polars_result.data)) # <class 'polars.DataFrame'>
print(type(arrow_result.data)) # <class 'pyarrow.lib.Table'>
print(type(dict_result.data)) # <class 'dict'>
```
Note:
The actual type of the `data` attribute depends on the format requested
during collection. Use type checking or isinstance() if you need to
handle the data differently based on its format.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__init__
|
fenic.core.types.query_result.QueryResult.__init__
| null |
site-packages/fenic/core/types/query_result.py
| true | false | 0 | 0 | null |
None
|
[
"self",
"data",
"metrics"
] |
QueryResult
| null | null |
Type: method
Member Name: __init__
Qualified Name: fenic.core.types.query_result.QueryResult.__init__
Docstring: none
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "data", "metrics"]
Returns: None
Parent Class: QueryResult
|
module
|
enums
|
fenic.core.types.enums
|
Enums used in the DataFrame API.
|
site-packages/fenic/core/types/enums.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: enums
Qualified Name: fenic.core.types.enums
Docstring: Enums used in the DataFrame API.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
SemanticSimilarityMetric
|
fenic.core.types.enums.SemanticSimilarityMetric
|
Type alias representing supported semantic similarity metrics.
Valid values:
- "cosine": Cosine similarity, measures the cosine of the angle between two vectors.
- "l2": Euclidean (L2) distance, measures the straight-line distance between two vectors.
- "dot": Dot product similarity, the raw inner product of two vectors.
These metrics are commonly used for comparing embedding vectors in semantic search
and other similarity-based applications.
|
site-packages/fenic/core/types/enums.py
| true | false | 6 | 6 | null | null | null | null |
Literal['cosine', 'l2', 'dot']
| null |
Type: attribute
Member Name: SemanticSimilarityMetric
Qualified Name: fenic.core.types.enums.SemanticSimilarityMetric
Docstring: Type alias representing supported semantic similarity metrics.
Valid values:
- "cosine": Cosine similarity, measures the cosine of the angle between two vectors.
- "l2": Euclidean (L2) distance, measures the straight-line distance between two vectors.
- "dot": Dot product similarity, the raw inner product of two vectors.
These metrics are commonly used for comparing embedding vectors in semantic search
and other similarity-based applications.
Value: Literal['cosine', 'l2', 'dot']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
BranchSide
|
fenic.core.types.enums.BranchSide
|
Type alias representing the side of a branch in a lineage graph.
Valid values:
- "left": The left branch of a join.
- "right": The right branch of a join.
|
site-packages/fenic/core/types/enums.py
| true | false | 21 | 21 | null | null | null | null |
Literal['left', 'right']
| null |
Type: attribute
Member Name: BranchSide
Qualified Name: fenic.core.types.enums.BranchSide
Docstring: Type alias representing the side of a branch in a lineage graph.
Valid values:
- "left": The left branch of a join.
- "right": The right branch of a join.
Value: Literal['left', 'right']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
TranscriptFormatType
|
fenic.core.types.enums.TranscriptFormatType
|
Type alias representing supported transcript formats.
Valid values:
- "srt": SubRip Subtitle format with indexed entries and timestamp ranges
- "generic": Conversation transcript format with speaker names and timestamps
- "webvtt": Web Video Text Tracks format with speaker names and timestamps
All formats are parsed into a unified schema with fields: index, speaker,
start_time, end_time, duration, content, format.
|
site-packages/fenic/core/types/enums.py
| true | false | 31 | 31 | null | null | null | null |
Literal['srt', 'generic', 'webvtt']
| null |
Type: attribute
Member Name: TranscriptFormatType
Qualified Name: fenic.core.types.enums.TranscriptFormatType
Docstring: Type alias representing supported transcript formats.
Valid values:
- "srt": SubRip Subtitle format with indexed entries and timestamp ranges
- "generic": Conversation transcript format with speaker names and timestamps
- "webvtt": Web Video Text Tracks format with speaker names and timestamps
All formats are parsed into a unified schema with fields: index, speaker,
start_time, end_time, duration, content, format.
Value: Literal['srt', 'generic', 'webvtt']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
JoinType
|
fenic.core.types.enums.JoinType
|
Type alias representing supported join types.
Valid values:
- "inner": Inner join, returns only rows that have matching values in both tables.
- "outer": Outer join, returns all rows from both tables, filling missing values with nulls.
- "left": Left join, returns all rows from the left table and matching rows from the right table.
- "right": Right join, returns all rows from the right table and matching rows from the left table.
- "cross": Cross join, returns the Cartesian product of the two tables.
|
site-packages/fenic/core/types/enums.py
| true | false | 45 | 45 | null | null | null | null |
Literal['inner', 'full', 'left', 'right', 'cross']
| null |
Type: attribute
Member Name: JoinType
Qualified Name: fenic.core.types.enums.JoinType
Docstring: Type alias representing supported join types.
Valid values:
- "inner": Inner join, returns only rows that have matching values in both tables.
- "outer": Outer join, returns all rows from both tables, filling missing values with nulls.
- "left": Left join, returns all rows from the left table and matching rows from the right table.
- "right": Right join, returns all rows from the right table and matching rows from the left table.
- "cross": Cross join, returns the Cartesian product of the two tables.
Value: Literal['inner', 'full', 'left', 'right', 'cross']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
FuzzySimilarityMethod
|
fenic.core.types.enums.FuzzySimilarityMethod
|
Type alias representing the supported fuzzy string similarity algorithms.
These algorithms quantify the similarity or difference between two strings using various distance or similarity metrics:
- "indel":
Computes the Indel (Insertion-Deletion) distance, which counts only insertions and deletions needed to transform one string into another, excluding substitutions. This is equivalent to the Longest Common Subsequence (LCS) problem. Useful when character substitutions should not be considered as valid operations (e.g., DNA sequence alignment where only insertions/deletions occur).
- "levenshtein":
Computes the Levenshtein distance, which is the minimum number of single-character edits (insertions, deletions, or substitutions) required to transform one string into another. Suitable for general-purpose fuzzy matching where transpositions do not matter.
- "damerau_levenshtein":
An extension of Levenshtein distance that also accounts for transpositions of adjacent characters (e.g., "ab" → "ba"). This metric is more accurate for real-world typos and keyboard errors.
- "jaro":
Measures similarity based on the number and order of common characters between two strings. It is particularly effective for short strings such as names. Returns a normalized score between 0 (no similarity) and 1 (exact match).
- "jaro_winkler":
A variant of the Jaro distance that gives more weight to common prefixes. Designed to improve accuracy on strings with shared beginnings (e.g., first names, surnames).
- "hamming":
Measures the number of differing characters between two strings of equal length. Only valid when both strings are the same length. It does not support insertions or deletions—only substitutions.
Choose the method based on the type of expected variation (e.g., typos, transpositions, or structural changes).
|
site-packages/fenic/core/types/enums.py
| true | false | 58 | 58 | null | null | null | null |
Literal['indel', 'levenshtein', 'damerau_levenshtein', 'jaro_winkler', 'jaro', 'hamming']
| null |
Type: attribute
Member Name: FuzzySimilarityMethod
Qualified Name: fenic.core.types.enums.FuzzySimilarityMethod
Docstring: Type alias representing the supported fuzzy string similarity algorithms.
These algorithms quantify the similarity or difference between two strings using various distance or similarity metrics:
- "indel":
Computes the Indel (Insertion-Deletion) distance, which counts only insertions and deletions needed to transform one string into another, excluding substitutions. This is equivalent to the Longest Common Subsequence (LCS) problem. Useful when character substitutions should not be considered as valid operations (e.g., DNA sequence alignment where only insertions/deletions occur).
- "levenshtein":
Computes the Levenshtein distance, which is the minimum number of single-character edits (insertions, deletions, or substitutions) required to transform one string into another. Suitable for general-purpose fuzzy matching where transpositions do not matter.
- "damerau_levenshtein":
An extension of Levenshtein distance that also accounts for transpositions of adjacent characters (e.g., "ab" → "ba"). This metric is more accurate for real-world typos and keyboard errors.
- "jaro":
Measures similarity based on the number and order of common characters between two strings. It is particularly effective for short strings such as names. Returns a normalized score between 0 (no similarity) and 1 (exact match).
- "jaro_winkler":
A variant of the Jaro distance that gives more weight to common prefixes. Designed to improve accuracy on strings with shared beginnings (e.g., first names, surnames).
- "hamming":
Measures the number of differing characters between two strings of equal length. Only valid when both strings are the same length. It does not support insertions or deletions—only substitutions.
Choose the method based on the type of expected variation (e.g., typos, transpositions, or structural changes).
Value: Literal['indel', 'levenshtein', 'damerau_levenshtein', 'jaro_winkler', 'jaro', 'hamming']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
StringCasingType
|
fenic.core.types.enums.StringCasingType
|
Type alias representing the type of string casing.
Valid values:
- "lower": Convert to lowercase.
- "upper": Convert to uppercase.
- "title": Convert to title case.
|
site-packages/fenic/core/types/enums.py
| true | false | 80 | 80 | null | null | null | null |
Literal['lower', 'upper', 'title']
| null |
Type: attribute
Member Name: StringCasingType
Qualified Name: fenic.core.types.enums.StringCasingType
Docstring: Type alias representing the type of string casing.
Valid values:
- "lower": Convert to lowercase.
- "upper": Convert to uppercase.
- "title": Convert to title case.
Value: Literal['lower', 'upper', 'title']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
attribute
|
StripCharsSide
|
fenic.core.types.enums.StripCharsSide
|
Type alias representing the side of a string to strip characters from.
Valid values:
- "left": Strip characters from the left side.
- "right": Strip characters from the right side.
- "both": Strip characters from both sides.
|
site-packages/fenic/core/types/enums.py
| true | false | 91 | 91 | null | null | null | null |
Literal['left', 'right', 'both']
| null |
Type: attribute
Member Name: StripCharsSide
Qualified Name: fenic.core.types.enums.StripCharsSide
Docstring: Type alias representing the side of a string to strip characters from.
Valid values:
- "left": Strip characters from the left side.
- "right": Strip characters from the right side.
- "both": Strip characters from both sides.
Value: Literal['left', 'right', 'both']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
module
|
semantic
|
fenic.core.types.semantic
|
Types used to configure model selection for semantic functions.
|
site-packages/fenic/core/types/semantic.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: semantic
Qualified Name: fenic.core.types.semantic
Docstring: Types used to configure model selection for semantic functions.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
class
|
ModelAlias
|
fenic.core.types.semantic.ModelAlias
|
A combination of a model name and a required profile for that model.
Model aliases are used to select a specific model to use in a semantic operation.
Both the model name and profile must be specified when creating a ModelAlias.
Attributes:
name: The name of the model.
profile: The name of a profile configuration to use for the model.
Example:
```python
model_alias = ModelAlias(name="o4-mini", profile="low")
```
|
site-packages/fenic/core/types/semantic.py
| true | false | 11 | 28 | null | null | null | null | null |
[
"BaseModel"
] |
Type: class
Member Name: ModelAlias
Qualified Name: fenic.core.types.semantic.ModelAlias
Docstring: A combination of a model name and a required profile for that model.
Model aliases are used to select a specific model to use in a semantic operation.
Both the model name and profile must be specified when creating a ModelAlias.
Attributes:
name: The name of the model.
profile: The name of a profile configuration to use for the model.
Example:
```python
model_alias = ModelAlias(name="o4-mini", profile="low")
```
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
function
|
_resolve_model_alias
|
fenic.core.types.semantic._resolve_model_alias
|
Convert a model alias from the API layer to the expression layer format.
Args:
model_alias: Either a string, a ModelAlias, or None
Returns:
A ResolvedModelAlias with optional profile, or None
|
site-packages/fenic/core/types/semantic.py
| false | true | 30 | 46 | null |
Optional[ResolvedModelAlias]
|
[
"model_alias"
] | null | null | null |
Type: function
Member Name: _resolve_model_alias
Qualified Name: fenic.core.types.semantic._resolve_model_alias
Docstring: Convert a model alias from the API layer to the expression layer format.
Args:
model_alias: Either a string, a ModelAlias, or None
Returns:
A ResolvedModelAlias with optional profile, or None
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["model_alias"]
Returns: Optional[ResolvedModelAlias]
Parent Class: none
|
module
|
classify
|
fenic.core.types.classify
|
Definition of a ClassDefinition class with optional description for semantic.classify.
|
site-packages/fenic/core/types/classify.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: classify
Qualified Name: fenic.core.types.classify
Docstring: Definition of a ClassDefinition class with optional description for semantic.classify.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
class
|
ClassDefinition
|
fenic.core.types.classify.ClassDefinition
|
Definition of a classification class with optional description.
Used to define the available classes for semantic classification operations.
The description helps the LLM understand what each class represents.
|
site-packages/fenic/core/types/classify.py
| true | false | 6 | 14 | null | null | null | null | null |
[
"BaseModel"
] |
Type: class
Member Name: ClassDefinition
Qualified Name: fenic.core.types.classify.ClassDefinition
Docstring: Definition of a classification class with optional description.
Used to define the available classes for semantic classification operations.
The description helps the LLM understand what each class represents.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
module
|
summarize
|
fenic.core.types.summarize
|
Summary structures for different formats of summaries.
|
site-packages/fenic/core/types/summarize.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: summarize
Qualified Name: fenic.core.types.summarize
Docstring: Summary structures for different formats of summaries.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
class
|
KeyPoints
|
fenic.core.types.summarize.KeyPoints
|
Summary as a concise bulleted list.
Each bullet should capture a distinct and essential idea, with a maximum number of points specified.
Attributes:
max_points: The maximum number of key points to include in the summary.
|
site-packages/fenic/core/types/summarize.py
| true | false | 6 | 27 | null | null | null | null | null |
[
"BaseModel"
] |
Type: class
Member Name: KeyPoints
Qualified Name: fenic.core.types.summarize.KeyPoints
Docstring: Summary as a concise bulleted list.
Each bullet should capture a distinct and essential idea, with a maximum number of points specified.
Attributes:
max_points: The maximum number of key points to include in the summary.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__str__
|
fenic.core.types.summarize.KeyPoints.__str__
|
Return a description of the summary format for KeyPoints.
|
site-packages/fenic/core/types/summarize.py
| true | false | 17 | 23 | null | null |
[
"self"
] |
KeyPoints
| null | null |
Type: method
Member Name: __str__
Qualified Name: fenic.core.types.summarize.KeyPoints.__str__
Docstring: Return a description of the summary format for KeyPoints.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: KeyPoints
|
method
|
max_tokens
|
fenic.core.types.summarize.KeyPoints.max_tokens
|
Calculate the maximum number of tokens for the summary based on the number of key points.
|
site-packages/fenic/core/types/summarize.py
| true | false | 25 | 27 | null |
int
|
[
"self"
] |
KeyPoints
| null | null |
Type: method
Member Name: max_tokens
Qualified Name: fenic.core.types.summarize.KeyPoints.max_tokens
Docstring: Calculate the maximum number of tokens for the summary based on the number of key points.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: int
Parent Class: KeyPoints
|
class
|
Paragraph
|
fenic.core.types.summarize.Paragraph
|
Summary as a cohesive narrative.
The summary should flow naturally and not exceed a specified maximum word count.
Attributes:
max_words: The maximum number of words allowed in the summary.
|
site-packages/fenic/core/types/summarize.py
| true | false | 29 | 48 | null | null | null | null | null |
[
"BaseModel"
] |
Type: class
Member Name: Paragraph
Qualified Name: fenic.core.types.summarize.Paragraph
Docstring: Summary as a cohesive narrative.
The summary should flow naturally and not exceed a specified maximum word count.
Attributes:
max_words: The maximum number of words allowed in the summary.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__str__
|
fenic.core.types.summarize.Paragraph.__str__
|
Return a description of the summary format for Paragraph.
|
site-packages/fenic/core/types/summarize.py
| true | false | 40 | 44 | null | null |
[
"self"
] |
Paragraph
| null | null |
Type: method
Member Name: __str__
Qualified Name: fenic.core.types.summarize.Paragraph.__str__
Docstring: Return a description of the summary format for Paragraph.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: Paragraph
|
method
|
max_tokens
|
fenic.core.types.summarize.Paragraph.max_tokens
|
Calculate the maximum number of tokens for the summary based on the number of words.
|
site-packages/fenic/core/types/summarize.py
| true | false | 46 | 48 | null |
int
|
[
"self"
] |
Paragraph
| null | null |
Type: method
Member Name: max_tokens
Qualified Name: fenic.core.types.summarize.Paragraph.max_tokens
Docstring: Calculate the maximum number of tokens for the summary based on the number of words.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: int
Parent Class: Paragraph
|
module
|
datatypes
|
fenic.core.types.datatypes
|
Core data type definitions for the DataFrame API.
This module defines the type system used throughout the DataFrame API. It includes:
- Base classes for all data types
- Primitive types (string, integer, float, etc.)
- Composite types (arrays, structs)
- Specialized types (embeddings, markdown, etc.)
|
site-packages/fenic/core/types/datatypes.py
| true | false | null | null | null | null | null | null | null | null |
Type: module
Member Name: datatypes
Qualified Name: fenic.core.types.datatypes
Docstring: Core data type definitions for the DataFrame API.
This module defines the type system used throughout the DataFrame API. It includes:
- Base classes for all data types
- Primitive types (string, integer, float, etc.)
- Composite types (arrays, structs)
- Specialized types (embeddings, markdown, etc.)
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
class
|
DataType
|
fenic.core.types.datatypes.DataType
|
Base class for all data types.
You won't instantiate this class directly. Instead, use one of the
concrete types like `StringType`, `ArrayType`, or `StructType`.
Used for casting, type validation, and schema inference in the DataFrame API.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 19 | 67 | null | null | null | null | null |
[
"ABC"
] |
Type: class
Member Name: DataType
Qualified Name: fenic.core.types.datatypes.DataType
Docstring: Base class for all data types.
You won't instantiate this class directly. Instead, use one of the
concrete types like `StringType`, `ArrayType`, or `StructType`.
Used for casting, type validation, and schema inference in the DataFrame API.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
method
|
__str__
|
fenic.core.types.datatypes.DataType.__str__
|
Return a string representation of the data type.
Returns:
A string describing the data type.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 28 | 35 | null |
str
|
[
"self"
] |
DataType
| null | null |
Type: method
Member Name: __str__
Qualified Name: fenic.core.types.datatypes.DataType.__str__
Docstring: Return a string representation of the data type.
Returns:
A string describing the data type.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: DataType
|
method
|
__eq__
|
fenic.core.types.datatypes.DataType.__eq__
|
Compare this data type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the objects are equal, False otherwise.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 37 | 47 | null |
bool
|
[
"self",
"other"
] |
DataType
| null | null |
Type: method
Member Name: __eq__
Qualified Name: fenic.core.types.datatypes.DataType.__eq__
Docstring: Compare this data type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the objects are equal, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: bool
Parent Class: DataType
|
method
|
__ne__
|
fenic.core.types.datatypes.DataType.__ne__
|
Compare this data type with another object for inequality.
Args:
other: The object to compare with.
Returns:
True if the objects are not equal, False otherwise.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 49 | 58 | null |
bool
|
[
"self",
"other"
] |
DataType
| null | null |
Type: method
Member Name: __ne__
Qualified Name: fenic.core.types.datatypes.DataType.__ne__
Docstring: Compare this data type with another object for inequality.
Args:
other: The object to compare with.
Returns:
True if the objects are not equal, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: bool
Parent Class: DataType
|
method
|
__hash__
|
fenic.core.types.datatypes.DataType.__hash__
|
Return a hash value for this data type.
Returns:
An integer hash value.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 60 | 67 | null | null |
[
"self"
] |
DataType
| null | null |
Type: method
Member Name: __hash__
Qualified Name: fenic.core.types.datatypes.DataType.__hash__
Docstring: Return a hash value for this data type.
Returns:
An integer hash value.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: none
Parent Class: DataType
|
class
|
_PrimitiveType
|
fenic.core.types.datatypes._PrimitiveType
|
Marker class for all primitive type.
|
site-packages/fenic/core/types/datatypes.py
| false | true | 70 | 73 | null | null | null | null | null |
[
"DataType"
] |
Type: class
Member Name: _PrimitiveType
Qualified Name: fenic.core.types.datatypes._PrimitiveType
Docstring: Marker class for all primitive type.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none
|
class
|
_LogicalType
|
fenic.core.types.datatypes._LogicalType
|
Marker class for all logical types.
|
site-packages/fenic/core/types/datatypes.py
| false | true | 76 | 79 | null | null | null | null | null |
[
"DataType"
] |
Type: class
Member Name: _LogicalType
Qualified Name: fenic.core.types.datatypes._LogicalType
Docstring: Marker class for all logical types.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none
|
class
|
_StringType
|
fenic.core.types.datatypes._StringType
| null |
site-packages/fenic/core/types/datatypes.py
| false | true | 85 | 104 | null | null | null | null | null |
[
"_PrimitiveType"
] |
Type: class
Member Name: _StringType
Qualified Name: fenic.core.types.datatypes._StringType
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none
|
method
|
__str__
|
fenic.core.types.datatypes._StringType.__str__
|
Return a string representation of the string type.
Returns:
The string "StringType".
|
site-packages/fenic/core/types/datatypes.py
| true | false | 87 | 93 | null |
str
|
[
"self"
] |
_StringType
| null | null |
Type: method
Member Name: __str__
Qualified Name: fenic.core.types.datatypes._StringType.__str__
Docstring: Return a string representation of the string type.
Returns:
The string "StringType".
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: _StringType
|
method
|
__eq__
|
fenic.core.types.datatypes._StringType.__eq__
|
Compare this string type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also a string type, False otherwise.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 95 | 104 | null |
bool
|
[
"self",
"other"
] |
_StringType
| null | null |
Type: method
Member Name: __eq__
Qualified Name: fenic.core.types.datatypes._StringType.__eq__
Docstring: Compare this string type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also a string type, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: bool
Parent Class: _StringType
|
class
|
_IntegerType
|
fenic.core.types.datatypes._IntegerType
| null |
site-packages/fenic/core/types/datatypes.py
| false | true | 107 | 126 | null | null | null | null | null |
[
"_PrimitiveType"
] |
Type: class
Member Name: _IntegerType
Qualified Name: fenic.core.types.datatypes._IntegerType
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none
|
method
|
__str__
|
fenic.core.types.datatypes._IntegerType.__str__
|
Return a string representation of the integer type.
Returns:
The string "IntegerType".
|
site-packages/fenic/core/types/datatypes.py
| true | false | 109 | 115 | null |
str
|
[
"self"
] |
_IntegerType
| null | null |
Type: method
Member Name: __str__
Qualified Name: fenic.core.types.datatypes._IntegerType.__str__
Docstring: Return a string representation of the integer type.
Returns:
The string "IntegerType".
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: _IntegerType
|
method
|
__eq__
|
fenic.core.types.datatypes._IntegerType.__eq__
|
Compare this integer type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also an integer type, False otherwise.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 117 | 126 | null |
bool
|
[
"self",
"other"
] |
_IntegerType
| null | null |
Type: method
Member Name: __eq__
Qualified Name: fenic.core.types.datatypes._IntegerType.__eq__
Docstring: Compare this integer type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also an integer type, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: bool
Parent Class: _IntegerType
|
class
|
_FloatType
|
fenic.core.types.datatypes._FloatType
| null |
site-packages/fenic/core/types/datatypes.py
| false | true | 129 | 148 | null | null | null | null | null |
[
"_PrimitiveType"
] |
Type: class
Member Name: _FloatType
Qualified Name: fenic.core.types.datatypes._FloatType
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none
|
method
|
__str__
|
fenic.core.types.datatypes._FloatType.__str__
|
Return a string representation of the float type.
Returns:
The string "FloatType".
|
site-packages/fenic/core/types/datatypes.py
| true | false | 131 | 137 | null |
str
|
[
"self"
] |
_FloatType
| null | null |
Type: method
Member Name: __str__
Qualified Name: fenic.core.types.datatypes._FloatType.__str__
Docstring: Return a string representation of the float type.
Returns:
The string "FloatType".
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: _FloatType
|
method
|
__eq__
|
fenic.core.types.datatypes._FloatType.__eq__
|
Compare this float type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also a float type, False otherwise.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 139 | 148 | null |
bool
|
[
"self",
"other"
] |
_FloatType
| null | null |
Type: method
Member Name: __eq__
Qualified Name: fenic.core.types.datatypes._FloatType.__eq__
Docstring: Compare this float type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also a float type, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: bool
Parent Class: _FloatType
|
class
|
_DoubleType
|
fenic.core.types.datatypes._DoubleType
| null |
site-packages/fenic/core/types/datatypes.py
| false | true | 151 | 170 | null | null | null | null | null |
[
"_PrimitiveType"
] |
Type: class
Member Name: _DoubleType
Qualified Name: fenic.core.types.datatypes._DoubleType
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none
|
method
|
__str__
|
fenic.core.types.datatypes._DoubleType.__str__
|
Return a string representation of the double type.
Returns:
The string "DoubleType".
|
site-packages/fenic/core/types/datatypes.py
| true | false | 153 | 159 | null |
str
|
[
"self"
] |
_DoubleType
| null | null |
Type: method
Member Name: __str__
Qualified Name: fenic.core.types.datatypes._DoubleType.__str__
Docstring: Return a string representation of the double type.
Returns:
The string "DoubleType".
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: _DoubleType
|
method
|
__eq__
|
fenic.core.types.datatypes._DoubleType.__eq__
|
Compare this double type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also a double type, False otherwise.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 161 | 170 | null |
bool
|
[
"self",
"other"
] |
_DoubleType
| null | null |
Type: method
Member Name: __eq__
Qualified Name: fenic.core.types.datatypes._DoubleType.__eq__
Docstring: Compare this double type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also a double type, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: bool
Parent Class: _DoubleType
|
class
|
_BooleanType
|
fenic.core.types.datatypes._BooleanType
| null |
site-packages/fenic/core/types/datatypes.py
| false | true | 173 | 192 | null | null | null | null | null |
[
"_PrimitiveType"
] |
Type: class
Member Name: _BooleanType
Qualified Name: fenic.core.types.datatypes._BooleanType
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: none
Returns: none
Parent Class: none
|
method
|
__str__
|
fenic.core.types.datatypes._BooleanType.__str__
|
Return a string representation of the boolean type.
Returns:
The string "BooleanType".
|
site-packages/fenic/core/types/datatypes.py
| true | false | 175 | 181 | null |
str
|
[
"self"
] |
_BooleanType
| null | null |
Type: method
Member Name: __str__
Qualified Name: fenic.core.types.datatypes._BooleanType.__str__
Docstring: Return a string representation of the boolean type.
Returns:
The string "BooleanType".
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: _BooleanType
|
method
|
__eq__
|
fenic.core.types.datatypes._BooleanType.__eq__
|
Compare this boolean type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also a boolean type, False otherwise.
|
site-packages/fenic/core/types/datatypes.py
| true | false | 183 | 192 | null |
bool
|
[
"self",
"other"
] |
_BooleanType
| null | null |
Type: method
Member Name: __eq__
Qualified Name: fenic.core.types.datatypes._BooleanType.__eq__
Docstring: Compare this boolean type with another object for equality.
Args:
other: The object to compare with.
Returns:
True if the other object is also a boolean type, False otherwise.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self", "other"]
Returns: bool
Parent Class: _BooleanType
|
class
|
ArrayType
|
fenic.core.types.datatypes.ArrayType
|
A type representing a homogeneous variable-length array (list) of elements.
Attributes:
element_type: The data type of each element in the array.
Example: Create an array of strings
```python
ArrayType(StringType)
ArrayType(element_type=StringType)
```
|
site-packages/fenic/core/types/datatypes.py
| true | false | 198 | 232 | null | null | null | null | null |
[
"DataType"
] |
Type: class
Member Name: ArrayType
Qualified Name: fenic.core.types.datatypes.ArrayType
Docstring: A type representing a homogeneous variable-length array (list) of elements.
Attributes:
element_type: The data type of each element in the array.
Example: Create an array of strings
```python
ArrayType(StringType)
ArrayType(element_type=StringType)
```
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none
|
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