type stringclasses 5
values | name stringlengths 1 55 | qualified_name stringlengths 5 147 | docstring stringlengths 15 4.52k ⌀ | filepath stringclasses 206
values | is_public bool 2
classes | is_private bool 2
classes | line_start int64 0 1.99k ⌀ | line_end int64 0 2.01k ⌀ | annotation stringclasses 14
values | returns stringclasses 308
values | value stringclasses 152
values | parameters listlengths 0 117 ⌀ | bases listlengths 0 3 ⌀ | parent_class stringclasses 376
values | api_element_summary stringlengths 199 33.8k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
function | least | fenic.api.functions.builtin.least | Returns the least value from the given columns for each row.
This function mimics the behavior of SQL's LEAST function. It evaluates the input columns
in order and returns the least value encountered. If all values are null, returns null.
All arguments must be of the same primitive type (e.g., StringType, BooleanType... | null | true | false | 836 | 866 | null | Column | null | [
"cols"
] | null | null | Type: function
Member Name: least
Qualified Name: fenic.api.functions.builtin.least
Docstring: Returns the least value from the given columns for each row.
This function mimics the behavior of SQL's LEAST function. It evaluates the input columns
in order and returns the least value encountered. If all values are null,... |
attribute | array_size | fenic.api.functions.builtin.array_size | null | null | true | false | 876 | 876 | null | null | _arr_ns.size | null | null | null | Type: attribute
Member Name: array_size
Qualified Name: fenic.api.functions.builtin.array_size
Docstring: none
Value: _arr_ns.size
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | array_contains | fenic.api.functions.builtin.array_contains | null | null | true | false | 877 | 877 | null | null | _arr_ns.contains | null | null | null | Type: attribute
Member Name: array_contains
Qualified Name: fenic.api.functions.builtin.array_contains
Docstring: none
Value: _arr_ns.contains
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
module | json | fenic.api.functions.json | JSON functions. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/functions/json.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: json
Qualified Name: fenic.api.functions.json
Docstring: JSON functions.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
function | jq | fenic.api.functions.json.jq | Applies a JQ query to a column containing JSON-formatted strings.
Args:
column (ColumnOrName): Input column of type `JsonType`.
query (str): A [JQ](https://jqlang.org/) expression used to extract or transform values.
Returns:
Column: A column containing the result of applying the JQ query to each row's JS... | null | true | false | 12 | 46 | null | Column | null | [
"column",
"query"
] | null | null | Type: function
Member Name: jq
Qualified Name: fenic.api.functions.json.jq
Docstring: Applies a JQ query to a column containing JSON-formatted strings.
Args:
column (ColumnOrName): Input column of type `JsonType`.
query (str): A [JQ](https://jqlang.org/) expression used to extract or transform values.
Returns... |
function | get_type | fenic.api.functions.json.get_type | Get the JSON type of each value.
Args:
column (ColumnOrName): Input column of type `JsonType`.
Returns:
Column: A column of strings indicating the JSON type
("string", "number", "boolean", "array", "object", "null").
Example: Get JSON types
```python
df.select(json.get_type(col("json_data... | null | true | false | 49 | 73 | null | Column | null | [
"column"
] | null | null | Type: function
Member Name: get_type
Qualified Name: fenic.api.functions.json.get_type
Docstring: Get the JSON type of each value.
Args:
column (ColumnOrName): Input column of type `JsonType`.
Returns:
Column: A column of strings indicating the JSON type
("string", "number", "boolean", "array", "o... |
function | contains | fenic.api.functions.json.contains | Check if a JSON value contains the specified value using recursive deep search.
Args:
column (ColumnOrName): Input column of type `JsonType`.
value (str): Valid JSON string to search for.
Returns:
Column: A column of booleans indicating whether the JSON contains the value.
Matching Rules:
- **Objects... | null | true | false | 76 | 127 | null | Column | null | [
"column",
"value"
] | null | null | Type: function
Member Name: contains
Qualified Name: fenic.api.functions.json.contains
Docstring: Check if a JSON value contains the specified value using recursive deep search.
Args:
column (ColumnOrName): Input column of type `JsonType`.
value (str): Valid JSON string to search for.
Returns:
Column: A c... |
module | session | fenic.api.session | Session module for managing query execution context and state. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/session/__init__.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: session
Qualified Name: fenic.api.session
Docstring: Session module for managing query execution context and state.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | __all__ | fenic.api.session.__all__ | null | null | false | false | 23 | 41 | null | null | ['Session', 'SessionConfig', 'SemanticConfig', 'OpenAILanguageModel', 'OpenAIEmbeddingModel', 'AnthropicLanguageModel', 'GoogleDeveloperEmbeddingModel', 'GoogleDeveloperLanguageModel', 'GoogleVertexEmbeddingModel', 'GoogleVertexLanguageModel', 'ModelConfig', 'CloudConfig', 'CloudExecutorSize', 'CohereEmbeddingModel', '... | null | null | null | Type: attribute
Member Name: __all__
Qualified Name: fenic.api.session.__all__
Docstring: none
Value: ['Session', 'SessionConfig', 'SemanticConfig', 'OpenAILanguageModel', 'OpenAIEmbeddingModel', 'AnthropicLanguageModel', 'GoogleDeveloperEmbeddingModel', 'GoogleDeveloperLanguageModel', 'GoogleVertexEmbeddingModel', 'Go... |
module | config | fenic.api.session.config | Session configuration classes for Fenic. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/session/config.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: config
Qualified Name: fenic.api.session.config
Docstring: Session configuration classes for Fenic.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
attribute | profiles_desc | fenic.api.session.config.profiles_desc | null | null | true | false | 62 | 65 | null | null | '\n Allow the same model configuration to be used with different profiles, currently used to set thinking budget/reasoning effort\n for reasoning models. To use a profile of a given model alias in a semantic operator, reference the model as `ModelAlias(name="<model_alias>", profile="<profile_name>... | null | null | null | Type: attribute
Member Name: profiles_desc
Qualified Name: fenic.api.session.config.profiles_desc
Docstring: none
Value: '\n Allow the same model configuration to be used with different profiles, currently used to set thinking budget/reasoning effort\n for reasoning models. To use a profile of a g... |
attribute | default_profiles_desc | fenic.api.session.config.default_profiles_desc | null | null | true | false | 67 | 69 | null | null | '\n If profiles are configured, which should be used by default?\n ' | null | null | null | Type: attribute
Member Name: default_profiles_desc
Qualified Name: fenic.api.session.config.default_profiles_desc
Docstring: none
Value: '\n If profiles are configured, which should be used by default?\n '
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Cla... |
attribute | GoogleEmbeddingTaskType | fenic.api.session.config.GoogleEmbeddingTaskType | null | null | true | false | 71 | 80 | null | null | Literal['SEMANTIC_SIMILARITY', 'CLASSIFICATION', 'CLUSTERING', 'RETRIEVAL_DOCUMENT', 'RETRIEVAL_QUERY', 'CODE_RETRIEVAL_QUERY', 'QUESTION_ANSWERING', 'FACT_VERIFICATION'] | null | null | null | Type: attribute
Member Name: GoogleEmbeddingTaskType
Qualified Name: fenic.api.session.config.GoogleEmbeddingTaskType
Docstring: none
Value: Literal['SEMANTIC_SIMILARITY', 'CLASSIFICATION', 'CLUSTERING', 'RETRIEVAL_DOCUMENT', 'RETRIEVAL_QUERY', 'CODE_RETRIEVAL_QUERY', 'QUESTION_ANSWERING', 'FACT_VERIFICATION']
Annotati... |
class | GoogleDeveloperEmbeddingModel | fenic.api.session.config.GoogleDeveloperEmbeddingModel | Configuration for Google Developer embedding models.
This class defines the configuration settings for Google embedding models available in Google Developer AI Studio,
including model selection and rate limiting parameters. These models are accessible using a GOOGLE_API_KEY environment variable.
Attributes:
model... | null | true | false | 83 | 171 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: GoogleDeveloperEmbeddingModel
Qualified Name: fenic.api.session.config.GoogleDeveloperEmbeddingModel
Docstring: Configuration for Google Developer embedding models.
This class defines the configuration settings for Google embedding models available in Google Developer AI Studio,
including mode... |
class | GoogleDeveloperLanguageModel | fenic.api.session.config.GoogleDeveloperLanguageModel | Configuration for Gemini models accessible through Google Developer AI Studio.
This class defines the configuration settings for Google Gemini models available in Google Developer AI Studio,
including model selection and rate limiting parameters. These models are accessible using a GOOGLE_API_KEY environment variable.... | null | true | false | 174 | 271 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: GoogleDeveloperLanguageModel
Qualified Name: fenic.api.session.config.GoogleDeveloperLanguageModel
Docstring: Configuration for Gemini models accessible through Google Developer AI Studio.
This class defines the configuration settings for Google Gemini models available in Google Developer AI S... |
class | GoogleVertexEmbeddingModel | fenic.api.session.config.GoogleVertexEmbeddingModel | Configuration for Google Vertex AI embedding models.
This class defines the configuration settings for Google embedding models available in Google Vertex AI,
including model selection and rate limiting parameters. These models are accessible using Google Cloud credentials.
Attributes:
model_name: The name of the ... | null | true | false | 274 | 362 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: GoogleVertexEmbeddingModel
Qualified Name: fenic.api.session.config.GoogleVertexEmbeddingModel
Docstring: Configuration for Google Vertex AI embedding models.
This class defines the configuration settings for Google embedding models available in Google Vertex AI,
including model selection and ... |
class | GoogleVertexLanguageModel | fenic.api.session.config.GoogleVertexLanguageModel | Configuration for Google Vertex AI models.
This class defines the configuration settings for Google Gemini models available in Google Vertex AI,
including model selection and rate limiting parameters. These models are accessible using Google Cloud credentials.
Attributes:
model_name: The name of the Google Vertex... | null | true | false | 365 | 462 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: GoogleVertexLanguageModel
Qualified Name: fenic.api.session.config.GoogleVertexLanguageModel
Docstring: Configuration for Google Vertex AI models.
This class defines the configuration settings for Google Gemini models available in Google Vertex AI,
including model selection and rate limiting p... |
class | OpenAILanguageModel | fenic.api.session.config.OpenAILanguageModel | Configuration for OpenAI language models.
This class defines the configuration settings for OpenAI language models,
including model selection and rate limiting parameters.
Attributes:
model_name: The name of the OpenAI model to use.
rpm: Requests per minute limit; must be greater than 0.
tpm: Tokens per m... | null | true | false | 465 | 595 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: OpenAILanguageModel
Qualified Name: fenic.api.session.config.OpenAILanguageModel
Docstring: Configuration for OpenAI language models.
This class defines the configuration settings for OpenAI language models,
including model selection and rate limiting parameters.
Attributes:
model_name: T... |
class | OpenAIEmbeddingModel | fenic.api.session.config.OpenAIEmbeddingModel | Configuration for OpenAI embedding models.
This class defines the configuration settings for OpenAI embedding models,
including model selection and rate limiting parameters.
Attributes:
model_name: The name of the OpenAI embedding model to use.
rpm: Requests per minute limit; must be greater than 0.
tpm: ... | null | true | false | 598 | 627 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: OpenAIEmbeddingModel
Qualified Name: fenic.api.session.config.OpenAIEmbeddingModel
Docstring: Configuration for OpenAI embedding models.
This class defines the configuration settings for OpenAI embedding models,
including model selection and rate limiting parameters.
Attributes:
model_nam... |
class | AnthropicLanguageModel | fenic.api.session.config.AnthropicLanguageModel | Configuration for Anthropic language models.
This class defines the configuration settings for Anthropic language models,
including model selection and separate rate limiting parameters for input and output tokens.
Attributes:
model_name: The name of the Anthropic model to use.
rpm: Requests per minute limit;... | null | true | false | 630 | 760 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: AnthropicLanguageModel
Qualified Name: fenic.api.session.config.AnthropicLanguageModel
Docstring: Configuration for Anthropic language models.
This class defines the configuration settings for Anthropic language models,
including model selection and separate rate limiting parameters for input ... |
attribute | ParsingEngine | fenic.api.session.config.ParsingEngine | null | null | true | false | 762 | 762 | null | null | Literal['mistral-ocr', 'cloudflare-ai', 'pdf-text', 'native'] | null | null | null | Type: attribute
Member Name: ParsingEngine
Qualified Name: fenic.api.session.config.ParsingEngine
Docstring: none
Value: Literal['mistral-ocr', 'cloudflare-ai', 'pdf-text', 'native']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | OpenRouterLanguageModel | fenic.api.session.config.OpenRouterLanguageModel | Configuration for OpenRouter language models.
This class defines the configuration settings for OpenRouter language models,
including model selection and rate limiting parameters. When fetching available models from OpenRouter, results
will be filtered to only include models from providers that are not in the user’s i... | null | true | false | 764 | 939 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: OpenRouterLanguageModel
Qualified Name: fenic.api.session.config.OpenRouterLanguageModel
Docstring: Configuration for OpenRouter language models.
This class defines the configuration settings for OpenRouter language models,
including model selection and rate limiting parameters. When fetching ... |
attribute | CohereEmbeddingTaskType | fenic.api.session.config.CohereEmbeddingTaskType | null | null | true | false | 942 | 947 | null | null | Literal['search_document', 'search_query', 'classification', 'clustering'] | null | null | null | Type: attribute
Member Name: CohereEmbeddingTaskType
Qualified Name: fenic.api.session.config.CohereEmbeddingTaskType
Docstring: none
Value: Literal['search_document', 'search_query', 'classification', 'clustering']
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | CohereEmbeddingModel | fenic.api.session.config.CohereEmbeddingModel | Configuration for Cohere embedding models.
This class defines the configuration settings for Cohere embedding models,
including model selection and rate limiting parameters.
Attributes:
model_name: The name of the Cohere model to use.
rpm: Requests per minute limit for the model.
tpm: Tokens per minute li... | null | true | false | 950 | 1,030 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: CohereEmbeddingModel
Qualified Name: fenic.api.session.config.CohereEmbeddingModel
Docstring: Configuration for Cohere embedding models.
This class defines the configuration settings for Cohere embedding models,
including model selection and rate limiting parameters.
Attributes:
model_nam... |
attribute | EmbeddingModel | fenic.api.session.config.EmbeddingModel | null | null | true | false | 1,033 | 1,038 | null | null | Union[OpenAIEmbeddingModel, GoogleVertexEmbeddingModel, GoogleDeveloperEmbeddingModel, CohereEmbeddingModel] | null | null | null | Type: attribute
Member Name: EmbeddingModel
Qualified Name: fenic.api.session.config.EmbeddingModel
Docstring: none
Value: Union[OpenAIEmbeddingModel, GoogleVertexEmbeddingModel, GoogleDeveloperEmbeddingModel, CohereEmbeddingModel]
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Pa... |
attribute | LanguageModel | fenic.api.session.config.LanguageModel | null | null | true | false | 1,039 | 1,045 | null | null | Union[OpenAILanguageModel, AnthropicLanguageModel, GoogleDeveloperLanguageModel, GoogleVertexLanguageModel, OpenRouterLanguageModel] | null | null | null | Type: attribute
Member Name: LanguageModel
Qualified Name: fenic.api.session.config.LanguageModel
Docstring: none
Value: Union[OpenAILanguageModel, AnthropicLanguageModel, GoogleDeveloperLanguageModel, GoogleVertexLanguageModel, OpenRouterLanguageModel]
Annotation: none
is Public? : true
is Private? : false
Parameters:... |
attribute | ModelConfig | fenic.api.session.config.ModelConfig | null | null | true | false | 1,046 | 1,046 | null | null | Union[EmbeddingModel, LanguageModel] | null | null | null | Type: attribute
Member Name: ModelConfig
Qualified Name: fenic.api.session.config.ModelConfig
Docstring: none
Value: Union[EmbeddingModel, LanguageModel]
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | SemanticConfig | fenic.api.session.config.SemanticConfig | Configuration for semantic language and embedding models.
This class defines the configuration for both language models and optional
embedding models used in semantic operations. It ensures that all configured
models are valid and supported by their respective providers.
Attributes:
language_models: Mapping of mo... | null | true | false | 1,049 | 1,341 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: SemanticConfig
Qualified Name: fenic.api.session.config.SemanticConfig
Docstring: Configuration for semantic language and embedding models.
This class defines the configuration for both language models and optional
embedding models used in semantic operations. It ensures that all configured
mo... |
method | model_post_init | fenic.api.session.config.SemanticConfig.model_post_init | Post initialization hook to set defaults.
This hook runs after the model is initialized and validated.
It sets the default language and embedding models if they are not set
and there is only one model available. For Google models that support
thinking_level, it auto-creates "low" and "high" profiles if no profiles
are... | null | true | false | 1,153 | 1,207 | null | None | null | [
"self",
"__context"
] | null | SemanticConfig | Type: method
Member Name: model_post_init
Qualified Name: fenic.api.session.config.SemanticConfig.model_post_init
Docstring: Post initialization hook to set defaults.
This hook runs after the model is initialized and validated.
It sets the default language and embedding models if they are not set
and there is only one... |
method | validate_models | fenic.api.session.config.SemanticConfig.validate_models | Validates that the selected models are supported by the system.
This validator checks that both the language model and embedding model (if provided)
are valid and supported by their respective providers.
Returns:
The validated SemanticConfig instance.
Raises:
ConfigurationError: If any of the models are not ... | null | true | false | 1,209 | 1,341 | null | SemanticConfig | null | [
"self"
] | null | SemanticConfig | Type: method
Member Name: validate_models
Qualified Name: fenic.api.session.config.SemanticConfig.validate_models
Docstring: Validates that the selected models are supported by the system.
This validator checks that both the language model and embedding model (if provided)
are valid and supported by their respective p... |
class | CloudExecutorSize | fenic.api.session.config.CloudExecutorSize | Enum defining available cloud executor sizes.
This enum represents the different size options available for cloud-based
execution environments.
Attributes:
SMALL: Small instance size.
MEDIUM: Medium instance size.
LARGE: Large instance size.
XLARGE: Extra large instance size. | null | true | false | 1,344 | 1,360 | null | null | null | null | [
"str",
"Enum"
] | null | Type: class
Member Name: CloudExecutorSize
Qualified Name: fenic.api.session.config.CloudExecutorSize
Docstring: Enum defining available cloud executor sizes.
This enum represents the different size options available for cloud-based
execution environments.
Attributes:
SMALL: Small instance size.
MEDIUM: Mediu... |
class | CloudConfig | fenic.api.session.config.CloudConfig | Configuration for cloud-based execution.
This class defines settings for running operations in a cloud environment,
allowing for scalable and distributed processing of language model operations.
Attributes:
size: Size of the cloud executor instance.
If None, the default size will be used.
Example:
Co... | null | true | false | 1,363 | 1,387 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: CloudConfig
Qualified Name: fenic.api.session.config.CloudConfig
Docstring: Configuration for cloud-based execution.
This class defines settings for running operations in a cloud environment,
allowing for scalable and distributed processing of language model operations.
Attributes:
size: ... |
class | LLMResponseCacheConfig | fenic.api.session.config.LLMResponseCacheConfig | Configuration for LLM response caching.
LLM response caching stores the results of language model API calls to reduce
costs and improve performance for repeated queries. This is distinct from
DataFrame caching (the `.cache()` operator).
Attributes:
enabled: Whether caching is enabled (default: True).
backend:... | null | true | false | 1,390 | 1,507 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: LLMResponseCacheConfig
Qualified Name: fenic.api.session.config.LLMResponseCacheConfig
Docstring: Configuration for LLM response caching.
LLM response caching stores the results of language model API calls to reduce
costs and improve performance for repeated queries. This is distinct from
Data... |
method | validate_ttl | fenic.api.session.config.LLMResponseCacheConfig.validate_ttl | Validate TTL duration string format.
Format: <number><unit> where unit is s/m/h/d
Examples: "30s", "15m", "2h", "7d"
Args:
v: TTL duration string to validate.
Returns:
The validated TTL string.
Raises:
ValueError: If format is invalid or value is out of range. | null | true | false | 1,448 | 1,486 | null | str | null | [
"cls",
"v"
] | null | LLMResponseCacheConfig | Type: method
Member Name: validate_ttl
Qualified Name: fenic.api.session.config.LLMResponseCacheConfig.validate_ttl
Docstring: Validate TTL duration string format.
Format: <number><unit> where unit is s/m/h/d
Examples: "30s", "15m", "2h", "7d"
Args:
v: TTL duration string to validate.
Returns:
The validated ... |
method | ttl_seconds | fenic.api.session.config.LLMResponseCacheConfig.ttl_seconds | Convert TTL string to seconds.
Returns:
TTL duration in seconds.
Raises:
ValueError: If TTL format is invalid. | null | true | false | 1,488 | 1,507 | null | int | null | [
"self"
] | null | LLMResponseCacheConfig | Type: method
Member Name: ttl_seconds
Qualified Name: fenic.api.session.config.LLMResponseCacheConfig.ttl_seconds
Docstring: Convert TTL string to seconds.
Returns:
TTL duration in seconds.
Raises:
ValueError: If TTL format is invalid.
Value: none
Annotation: none
is Public? : true
is Private? : false
Paramet... |
class | AdaptiveTokenEstimationConfig | fenic.api.session.config.AdaptiveTokenEstimationConfig | Tunes adaptive output-token reservation for rate limiting.
Output-token reservations are learned from observed usage and clamped to the
request's max_completion_tokens ceiling, then corrected after each response
(settlement). Enabled by default.
Setting ``enabled=False`` disables adaptive *estimation* — reservations ... | null | true | false | 1,510 | 1,537 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: AdaptiveTokenEstimationConfig
Qualified Name: fenic.api.session.config.AdaptiveTokenEstimationConfig
Docstring: Tunes adaptive output-token reservation for rate limiting.
Output-token reservations are learned from observed usage and clamped to the
request's max_completion_tokens ceiling, then ... |
class | SessionConfig | fenic.api.session.config.SessionConfig | Configuration for a user session.
This class defines the complete configuration for a user session, including
application settings, model configurations, and optional cloud settings.
It serves as the central configuration object for all language model operations.
Attributes:
app_name: Name of the application usin... | null | true | false | 1,540 | 1,795 | null | null | null | null | [
"BaseModel"
] | null | Type: class
Member Name: SessionConfig
Qualified Name: fenic.api.session.config.SessionConfig
Docstring: Configuration for a user session.
This class defines the complete configuration for a user session, including
application settings, model configurations, and optional cloud settings.
It serves as the central config... |
method | to_json | fenic.api.session.config.SessionConfig.to_json | Export the session config to a JSON string. | null | true | false | 1,611 | 1,613 | null | str | null | [
"self"
] | null | SessionConfig | Type: method
Member Name: to_json
Qualified Name: fenic.api.session.config.SessionConfig.to_json
Docstring: Export the session config to a JSON string.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self"]
Returns: str
Parent Class: SessionConfig |
method | _to_resolved_config | fenic.api.session.config.SessionConfig._to_resolved_config | null | null | false | true | 1,615 | 1,795 | null | ResolvedSessionConfig | null | [
"self"
] | null | SessionConfig | Type: method
Member Name: _to_resolved_config
Qualified Name: fenic.api.session.config.SessionConfig._to_resolved_config
Docstring: none
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["self"]
Returns: ResolvedSessionConfig
Parent Class: SessionConfig |
function | _validate_language_profile | fenic.api.session.config._validate_language_profile | Validate the language profile against the language model. | null | false | true | 1,798 | 1,883 | null | None | null | [
"language_model",
"model_alias",
"completion_model_params",
"profile",
"profile_alias"
] | null | null | Type: function
Member Name: _validate_language_profile
Qualified Name: fenic.api.session.config._validate_language_profile
Docstring: Validate the language profile against the language model.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["language_model", "model_alias", "completion_mod... |
function | _validate_embedding_profile | fenic.api.session.config._validate_embedding_profile | Validate Embedding profile against embedding model parameters. | null | false | true | 1,886 | 1,904 | null | null | null | [
"embedding_model_parameters",
"model_alias",
"profile_alias",
"profile"
] | null | null | Type: function
Member Name: _validate_embedding_profile
Qualified Name: fenic.api.session.config._validate_embedding_profile
Docstring: Validate Embedding profile against embedding model parameters.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["embedding_model_parameters", "model_alia... |
function | _get_model_provider_for_model_config | fenic.api.session.config._get_model_provider_for_model_config | Determine the ModelProvider for the given model configuration. | null | false | true | 1,907 | 1,922 | null | ModelProvider | null | [
"model_config"
] | null | null | Type: function
Member Name: _get_model_provider_for_model_config
Qualified Name: fenic.api.session.config._get_model_provider_for_model_config
Docstring: Determine the ModelProvider for the given model configuration.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["model_config"]
Returns... |
module | session | fenic.api.session.session | Main session class for interacting with the DataFrame API. | /private/var/folders/w2/dyfkx_354cqghs4b74vb_x380000gn/T/fenic-clone-0.11.0-a2lcuovw/fenic/src/fenic/api/session/session.py | true | false | null | null | null | null | null | null | null | null | Type: module
Member Name: session
Qualified Name: fenic.api.session.session
Docstring: Main session class for interacting with the DataFrame API.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: none
Returns: none
Parent Class: none |
class | Session | fenic.api.session.session.Session | The entry point to programming with the DataFrame API. Similar to PySpark's SparkSession.
Example: Create a session with default configuration
```python
session = Session.get_or_create(SessionConfig(app_name="my_app"))
```
Example: Create a session with cloud configuration
```python
config = Sessi... | null | true | false | 33 | 351 | null | null | null | null | [] | null | Type: class
Member Name: Session
Qualified Name: fenic.api.session.session.Session
Docstring: The entry point to programming with the DataFrame API. Similar to PySpark's SparkSession.
Example: Create a session with default configuration
```python
session = Session.get_or_create(SessionConfig(app_name="my_app")... |
method | __new__ | fenic.api.session.session.Session.__new__ | Create a new Session instance. | null | true | false | 56 | 62 | null | null | null | [
"cls"
] | null | Session | Type: method
Member Name: __new__
Qualified Name: fenic.api.session.session.Session.__new__
Docstring: Create a new Session instance.
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["cls"]
Returns: none
Parent Class: Session |
method | get_or_create | fenic.api.session.session.Session.get_or_create | Gets an existing Session or creates a new one with the configured settings.
Returns:
A Session instance configured with the provided settings | null | true | false | 64 | 91 | null | Session | null | [
"cls",
"config"
] | null | Session | Type: method
Member Name: get_or_create
Qualified Name: fenic.api.session.session.Session.get_or_create
Docstring: Gets an existing Session or creates a new one with the configured settings.
Returns:
A Session instance configured with the provided settings
Value: none
Annotation: none
is Public? : true
is Private?... |
method | _create_local_session | fenic.api.session.session.Session._create_local_session | Get or create a local session. | null | false | true | 93 | 103 | null | Session | null | [
"cls",
"session_state"
] | null | Session | Type: method
Member Name: _create_local_session
Qualified Name: fenic.api.session.session.Session._create_local_session
Docstring: Get or create a local session.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["cls", "session_state"]
Returns: Session
Parent Class: Session |
method | _create_cloud_session | fenic.api.session.session.Session._create_cloud_session | Create a cloud session. | null | false | true | 105 | 115 | null | Session | null | [
"cls",
"session_state"
] | null | Session | Type: method
Member Name: _create_cloud_session
Qualified Name: fenic.api.session.session.Session._create_cloud_session
Docstring: Create a cloud session.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["cls", "session_state"]
Returns: Session
Parent Class: Session |
method | create_dataframe | fenic.api.session.session.Session.create_dataframe | Create a DataFrame from a variety of Python-native data formats.
Args:
data: Input data. Must be one of:
- Polars DataFrame
- Pandas DataFrame
- dict of column_name -> list of values
- list of dicts (each dict representing a row)
- pyarrow Table
schema: Optional complete... | null | true | false | 134 | 226 | null | DataFrame | null | [
"self",
"data",
"schema"
] | null | Session | Type: method
Member Name: create_dataframe
Qualified Name: fenic.api.session.session.Session.create_dataframe
Docstring: Create a DataFrame from a variety of Python-native data formats.
Args:
data: Input data. Must be one of:
- Polars DataFrame
- Pandas DataFrame
- dict of column_name -> li... |
method | table | fenic.api.session.session.Session.table | Returns the specified table as a DataFrame.
Args:
table_name: Name of the table
Returns:
Table as a DataFrame
Raises:
ValueError: If the table does not exist
Example: Load an existing table
```python
df = session.table("my_table")
``` | null | true | false | 228 | 250 | null | DataFrame | null | [
"self",
"table_name"
] | null | Session | Type: method
Member Name: table
Qualified Name: fenic.api.session.session.Session.table
Docstring: Returns the specified table as a DataFrame.
Args:
table_name: Name of the table
Returns:
Table as a DataFrame
Raises:
ValueError: If the table does not exist
Example: Load an existing table
```python
... |
method | view | fenic.api.session.session.Session.view | Returns the specified view as a DataFrame.
Args:
view_name: Name of the view
Returns:
DataFrame: Dataframe with the given view | null | true | false | 252 | 269 | null | DataFrame | null | [
"self",
"view_name"
] | null | Session | Type: method
Member Name: view
Qualified Name: fenic.api.session.session.Session.view
Docstring: Returns the specified view as a DataFrame.
Args:
view_name: Name of the view
Returns:
DataFrame: Dataframe with the given view
Value: none
Annotation: none
is Public? : true
is Private? : false
Parameters: ["self",... |
method | sql | fenic.api.session.session.Session.sql | Execute a read-only SQL query against one or more DataFrames using named placeholders.
This allows you to execute ad hoc SQL queries using familiar syntax when it's more convenient than the DataFrame API.
Placeholders in the SQL string (e.g. `{df}`) should correspond to keyword arguments (e.g. `df=my_dataframe`).
For... | null | true | false | 271 | 341 | null | DataFrame | null | [
"self",
"query",
"tables"
] | null | Session | Type: method
Member Name: sql
Qualified Name: fenic.api.session.session.Session.sql
Docstring: Execute a read-only SQL query against one or more DataFrames using named placeholders.
This allows you to execute ad hoc SQL queries using familiar syntax when it's more convenient than the DataFrame API.
Placeholders in the... |
method | stop | fenic.api.session.session.Session.stop | Stops the session and closes all connections.
Args:
skip_usage_summary: Whether to skip printing the usage summary.
Unless `skip_usage_summary` is set, a summary of your session's metrics will print once you stop your session. | null | true | false | 343 | 351 | null | null | null | [
"self",
"skip_usage_summary"
] | null | Session | Type: method
Member Name: stop
Qualified Name: fenic.api.session.session.Session.stop
Docstring: Stops the session and closes all connections.
Args:
skip_usage_summary: Whether to skip printing the usage summary.
Unless `skip_usage_summary` is set, a summary of your session's metrics will print once you stop your... |
function | _normalize_data_like_to_polars | fenic.api.session.session._normalize_data_like_to_polars | Normalize supported Python-native data inputs to a Polars DataFrame.
Args:
data: Input data to normalize.
allow_empty_list: Whether an empty list is allowed.
validate_all_rows: Whether every row-oriented item must be a dict.
Returns:
A tuple of the normalized Polars DataFrame and the complete set of
... | null | false | true | 354 | 406 | null | tuple[pl.DataFrame, set[str] | None] | null | [
"data",
"allow_empty_list",
"validate_all_rows"
] | null | null | Type: function
Member Name: _normalize_data_like_to_polars
Qualified Name: fenic.api.session.session._normalize_data_like_to_polars
Docstring: Normalize supported Python-native data inputs to a Polars DataFrame.
Args:
data: Input data to normalize.
allow_empty_list: Whether an empty list is allowed.
valida... |
function | _coerce_to_schema | fenic.api.session.session._coerce_to_schema | Coerce a normalized Polars DataFrame to an explicit logical schema. | null | false | true | 409 | 442 | null | pl.DataFrame | null | [
"pl_df",
"schema",
"row_field_names"
] | null | null | Type: function
Member Name: _coerce_to_schema
Qualified Name: fenic.api.session.session._coerce_to_schema
Docstring: Coerce a normalized Polars DataFrame to an explicit logical schema.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["pl_df", "schema", "row_field_names"]
Returns: pl.DataF... |
function | _schema_only_empty_frame | fenic.api.session.session._schema_only_empty_frame | Create an empty Polars DataFrame with a schema's physical dtypes. | null | false | true | 445 | 447 | null | pl.DataFrame | null | [
"schema"
] | null | null | Type: function
Member Name: _schema_only_empty_frame
Qualified Name: fenic.api.session.session._schema_only_empty_frame
Docstring: Create an empty Polars DataFrame with a schema's physical dtypes.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["schema"]
Returns: pl.DataFrame
Parent Clas... |
function | _validate_explicit_schema | fenic.api.session.session._validate_explicit_schema | Validate the public explicit schema argument before coercion. | null | false | true | 450 | 465 | null | None | null | [
"schema"
] | null | null | Type: function
Member Name: _validate_explicit_schema
Qualified Name: fenic.api.session.session._validate_explicit_schema
Docstring: Validate the public explicit schema argument before coercion.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["schema"]
Returns: None
Parent Class: none |
function | _raise_schema_column_mismatch | fenic.api.session.session._raise_schema_column_mismatch | Raise a validation error describing a top-level schema column mismatch. | null | false | true | 468 | 479 | null | None | null | [
"expected",
"actual"
] | null | null | Type: function
Member Name: _raise_schema_column_mismatch
Qualified Name: fenic.api.session.session._raise_schema_column_mismatch
Docstring: Raise a validation error describing a top-level schema column mismatch.
Value: none
Annotation: none
is Public? : false
is Private? : true
Parameters: ["expected", "actual"]
Retur... |
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