Tony20100/langchain_full huggingface dataset:
# -> [4, 6, 8]
Parameters
others (Union[Runnable[Any, Other], Callable[[Any], Other]]) – 
name (Optional[str]) – 
Return type
RunnableSerializable[Input, Other]
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
stream(input: Input, config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[Output]¶
Default implementation of stream, which calls invoke.
Subclasses should override this method if they support streaming output.
Parameters
input (Input) – 
config (Optional[RunnableConfig]) – 
kwargs (Optional[Any]) – 
Return type
Iterator[Output]
to_json() → Union[SerializedConstructor, SerializedNotImplemented]¶
Serialize the runnable to JSON.
Return type
Union[SerializedConstructor, SerializedNotImplemented]
to_json_not_implemented() → SerializedNotImplemented¶
Return type
SerializedNotImplemented
transform(input: Iterator[Union[str, AIMessage, HumanMessage, ChatMessage, SystemMessage, FunctionMessage, ToolMessage, PromptValue]], config: Optional[RunnableConfig] = None, **kwargs: Optional[Any]) → Iterator[bytes][source]¶
Perform TTS by taking a stream of characters and streaming output bytes.
Parameters
Perform TTS by taking a stream of characters and streaming output bytes.
Parameters
input (Iterator[Union[str, AIMessage, HumanMessage, ChatMessage, SystemMessage, FunctionMessage, ToolMessage, PromptValue]]) – 
config (Optional[RunnableConfig]) – 
kwargs (Optional[Any]) – 
Return type
Iterator[bytes]
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
with_alisteners(*, on_start: Optional[AsyncListener] = None, on_end: Optional[AsyncListener] = None, on_error: Optional[AsyncListener] = None) → Runnable[Input, Output]¶
Bind asynchronous lifecycle listeners to a Runnable, returning a new Runnable.
on_start: Asynchronously called before the runnable starts running.
on_end: Asynchronously called after the runnable finishes running.
on_error: Asynchronously called if the runnable throws an error.
The Run object contains information about the run, including its id,
type, input, output, error, start_time, end_time, and any tags or metadata
added to the run.
Example:
Parameters
on_start (Optional[AsyncListener]) – 
on_end (Optional[AsyncListener]) – 
on_error (Optional[AsyncListener]) – 
Return type
Runnable[Input, Output]
with_config(config: Optional[RunnableConfig] = None, **kwargs: Any) → Runnable[Input, Output]¶
Bind config to a Runnable, returning a new Runnable.
Parameters
config (Optional[RunnableConfig]) – 
kwargs (Any) – 
Return type
output_type (Optional[Type[Output]]) – 
Return type
Runnable[Input, Output]
property InputType: Type[Input]¶
The type of input this runnable accepts specified as a type annotation.
property OutputType: Type[Output]¶
The type of output this runnable produces specified as a type annotation.
property auth: riva.client.Auth¶
Return a riva client auth object.
property config_specs: List[ConfigurableFieldSpec]¶
List configurable fields for this runnable.
property input_schema: Type[BaseModel]¶
The type of input this runnable accepts specified as a pydantic model.
property lc_attributes: Dict¶
List of attribute names that should be included in the serialized kwargs.
These attributes must be accepted by the constructor.
property lc_secrets: Dict[str, str]¶
A map of constructor argument names to secret ids.
For example,{“openai_api_key”: “OPENAI_API_KEY”}
name: str = None¶
The name of the runnable. Used for debugging and tracing.
property output_schema: Type[BaseModel]¶
The type of output this runnable produces specified as a pydantic model.
Examples using RivaTTS¶
NVIDIA Riva: ASR and TTS
langchain_community.utilities.tavily_search.TavilySearchAPIWrapper¶
class langchain_community.utilities.tavily_search.TavilySearchAPIWrapper[source]¶
Bases: BaseModel
Wrapper for Tavily Search API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param tavily_api_key: SecretStr [Required]¶
Constraints
type = string
writeOnly = True
format = password
clean_results(results: List[Dict]) → List[Dict][source]¶
Clean results from Tavily Search API.
Parameters
results (List[Dict]) – 
Return type
List[Dict]
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
raw_results(query: str, max_results: Optional[int] = 5, search_depth: Optional[str] = 'advanced', include_domains: Optional[List[str]] = [], exclude_domains: Optional[List[str]] = [], include_answer: Optional[bool] = False, include_raw_content: Optional[bool] = False, include_images: Optional[bool] = False) → Dict[source]¶
Parameters
query (str) – 
max_results (Optional[int]) – 
search_depth (Optional[str]) – 
include_domains (Optional[List[str]]) – 
exclude_domains (Optional[List[str]]) – 
include_answer (Optional[bool]) – 
include_raw_content (Optional[bool]) – 
include_images (Optional[bool]) – 
Return type
Dict
async raw_results_async(query: str, max_results: Optional[int] = 5, search_depth: Optional[str] = 'advanced', include_domains: Optional[List[str]] = [], exclude_domains: Optional[List[str]] = [], include_answer: Optional[bool] = False, include_raw_content: Optional[bool] = False, include_images: Optional[bool] = False) → Dict[source]¶
Get results from the Tavily Search API asynchronously.
Parameters
query (str) – 
max_results (Optional[int]) – 
search_depth (Optional[str]) – 
include_domains (Optional[List[str]]) –
search_depth (Optional[str]) – 
include_domains (Optional[List[str]]) – 
exclude_domains (Optional[List[str]]) – 
include_answer (Optional[bool]) – 
include_raw_content (Optional[bool]) – 
include_images (Optional[bool]) – 
Return type
Dict
results(query: str, max_results: Optional[int] = 5, search_depth: Optional[str] = 'advanced', include_domains: Optional[List[str]] = [], exclude_domains: Optional[List[str]] = [], include_answer: Optional[bool] = False, include_raw_content: Optional[bool] = False, include_images: Optional[bool] = False) → List[Dict][source]¶
Run query through Tavily Search and return metadata.
Parameters
query (str) – The query to search for.
max_results (Optional[int]) – The maximum number of results to return.
search_depth (Optional[str]) – The depth of the search. Can be “basic” or “advanced”.
include_domains (Optional[List[str]]) – A list of domains to include in the search.
exclude_domains (Optional[List[str]]) – A list of domains to exclude from the search.
include_answer (Optional[bool]) – Whether to include the answer in the results.
include_raw_content (Optional[bool]) – Whether to include the raw content in the results.
include_images (Optional[bool]) – Whether to include images in the results.
Returns
The query that was searched for.
follow_up_questions: A list of follow up questions.
response_time: The response time of the query.
answer: The answer to the query.
images: A list of images.
results: A list of dictionaries containing the results:
title: The title of the result.
url: The url of the result.
content: The content of the result.
url: The url of the result.
content: The content of the result.
score: The score of the result.
raw_content: The raw content of the result.
Return type
query
async results_async(query: str, max_results: Optional[int] = 5, search_depth: Optional[str] = 'advanced', include_domains: Optional[List[str]] = [], exclude_domains: Optional[List[str]] = [], include_answer: Optional[bool] = False, include_raw_content: Optional[bool] = False, include_images: Optional[bool] = False) → List[Dict][source]¶
Parameters
query (str) – 
max_results (Optional[int]) – 
search_depth (Optional[str]) – 
include_domains (Optional[List[str]]) – 
exclude_domains (Optional[List[str]]) – 
include_answer (Optional[bool]) – 
include_raw_content (Optional[bool]) – 
include_images (Optional[bool]) – 
Return type
List[Dict]
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) –
param lr: str = 'lang_en'¶
param serp_api_key: Optional[str] = None¶
param top_k_results: int = 10¶
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to exclude from new model, as with values this takes precedence over include
update (Optional[DictStrAny]) – values to change/add in the new model. Note: the data is not validated before creating
the new model: you should trust this data
deep (bool) – set to True to make a deep copy of the model
self (Model) – 
Returns
new model instance
Return type
Model
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
exclude (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – 
by_alias (bool) – 
skip_defaults (Optional[bool]) – 
exclude_unset (bool) – 
exclude_defaults (bool) – 
exclude_none (bool) – 
encoder (Optional[Callable[[Any], Any]]) – 
models_as_dict (bool) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
path (Union[str, Path]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod parse_obj(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
run(query: str) → str[source]¶
Run query through GoogleSearchScholar and parse result
Parameters
query (str) – 
Return type
str
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) –
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using GoogleScholarAPIWrapper¶
Google
Google Scholar
langchain_community.utilities.nvidia_riva.RivaAudioEncoding¶
class langchain_community.utilities.nvidia_riva.RivaAudioEncoding(value)[source]¶
An enum of the possible choices for Riva audio encoding.
The list of types exposed by the Riva GRPC Protobuf files can be found
with the following commands:
`python
import riva.client
print(riva.client.AudioEncoding.keys())  # noqa: T201
`
ALAW = 'ALAW'¶
ENCODING_UNSPECIFIED = 'ENCODING_UNSPECIFIED'¶
FLAC = 'FLAC'¶
LINEAR_PCM = 'LINEAR_PCM'¶
MULAW = 'MULAW'¶
OGGOPUS = 'OGGOPUS'¶
riva_pb2¶
Returns the Riva API object for the encoding.
Examples using RivaAudioEncoding¶
NVIDIA Riva: ASR and TTS
langchain_community.utilities.spark_sql.SparkSQL¶
class langchain_community.utilities.spark_sql.SparkSQL(spark_session: Optional[SparkSession] = None, catalog: Optional[str] = None, schema: Optional[str] = None, ignore_tables: Optional[List[str]] = None, include_tables: Optional[List[str]] = None, sample_rows_in_table_info: int = 3)[source]¶
SparkSQL is a utility class for interacting with Spark SQL.
Initialize a SparkSQL object.
Parameters
spark_session (Optional[SparkSession]) – A SparkSession object.
If not provided, one will be created.
catalog (Optional[str]) – The catalog to use.
If not provided, the default catalog will be used.
schema (Optional[str]) – The schema to use.
If not provided, the default schema will be used.
ignore_tables (Optional[List[str]]) – A list of tables to ignore.
If not provided, all tables will be used.
include_tables (Optional[List[str]]) – A list of tables to include.
If not provided, all tables will be used.
sample_rows_in_table_info (int) – The number of rows to include in the table info.
Defaults to 3.
Methods
__init__([spark_session, catalog, schema, ...])
Initialize a SparkSQL object.
from_uri(database_uri[, engine_args])
Creating a remote Spark Session via Spark connect.
get_table_info([table_names])
get_table_info_no_throw([table_names])
Get information about specified tables.
get_usable_table_names()
Get names of tables available.
run(command[, fetch])
run_no_throw(command[, fetch])
Execute a SQL command and return a string representing the results.
Execute a SQL command and return a string representing the results.
__init__(spark_session: Optional[SparkSession] = None, catalog: Optional[str] = None, schema: Optional[str] = None, ignore_tables: Optional[List[str]] = None, include_tables: Optional[List[str]] = None, sample_rows_in_table_info: int = 3)[source]¶
Initialize a SparkSQL object.
Parameters
spark_session (Optional[SparkSession]) – A SparkSession object.
If not provided, one will be created.
catalog (Optional[str]) – The catalog to use.
If not provided, the default catalog will be used.
schema (Optional[str]) – The schema to use.
If not provided, the default schema will be used.
ignore_tables (Optional[List[str]]) – A list of tables to ignore.
If not provided, all tables will be used.
include_tables (Optional[List[str]]) – A list of tables to include.
If not provided, all tables will be used.
sample_rows_in_table_info (int) – The number of rows to include in the table info.
Defaults to 3.
classmethod from_uri(database_uri: str, engine_args: Optional[dict] = None, **kwargs: Any) → SparkSQL[source]¶
Creating a remote Spark Session via Spark connect.
For example: SparkSQL.from_uri(“sc://localhost:15002”)
Parameters
database_uri (str) – 
engine_args (Optional[dict]) – 
kwargs (Any) – 
Return type
SparkSQL
get_table_info(table_names: Optional[List[str]] = None) → str[source]¶
Parameters
table_names (Optional[List[str]]) – 
Return type
str
get_table_info_no_throw(table_names: Optional[List[str]] = None) → str[source]¶
Get information about specified tables.
Get information about specified tables.
Follows best practices as specified in: Rajkumar et al, 2022
(https://arxiv.org/abs/2204.00498)
If sample_rows_in_table_info, the specified number of sample rows will be
appended to each table description. This can increase performance as
demonstrated in the paper.
Parameters
table_names (Optional[List[str]]) – 
Return type
str
get_usable_table_names() → Iterable[str][source]¶
Get names of tables available.
Return type
Iterable[str]
run(command: str, fetch: str = 'all') → str[source]¶
Parameters
command (str) – 
fetch (str) – 
Return type
str
run_no_throw(command: str, fetch: str = 'all') → str[source]¶
Execute a SQL command and return a string representing the results.
If the statement returns rows, a string of the results is returned.
If the statement returns no rows, an empty string is returned.
If the statement throws an error, the error message is returned.
Parameters
command (str) – 
fetch (str) – 
Return type
str
Examples using SparkSQL¶
Spark SQL
langchain_community.utilities.stackexchange.StackExchangeAPIWrapper¶
class langchain_community.utilities.stackexchange.StackExchangeAPIWrapper[source]¶
Bases: BaseModel
Wrapper for Stack Exchange API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param fetch_params: Dict[str, Any] [Optional]¶
Additional params to pass to StackApi.fetch.
param max_results: int = 3¶
Max number of results to include in output.
param query_type: Literal['all', 'title', 'body'] = 'all'¶
Which part of StackOverflows items to match against. One of ‘all’, ‘title’,
‘body’. Defaults to ‘all’.
param result_separator: str = '\n\n'¶
Separator between question,answer pairs.
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
Creates a new model setting __dict__ and __fields_set__ from trusted or pre-validated data.
Default values are respected, but no other validation is performed.
Behaves as if Config.extra = ‘allow’ was set since it adds all passed values
Parameters
_fields_set (Optional[SetStr]) – 
values (Any) – 
Return type
Model
copy(*, include: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, exclude: Optional[Union[AbstractSetIntStr, MappingIntStrAny]] = None, update: Optional[DictStrAny] = None, deep: bool = False) → Model¶
Duplicate a model, optionally choose which fields to include, exclude and change.
Parameters
include (Optional[Union[AbstractSetIntStr, MappingIntStrAny]]) – fields to include in new model
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
run(query: str) → str[source]¶
Run query through StackExchange API and parse results.
Parameters
query (str) – 
Return type
str
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using StackExchangeAPIWrapper¶
Stack Exchange
StackExchange
langchain_community.utilities.dataforseo_api_search.DataForSeoAPIWrapper¶
class langchain_community.utilities.dataforseo_api_search.DataForSeoAPIWrapper[source]¶
Bases: BaseModel
Wrapper around the DataForSeo API.
Create a new model by parsing and validating input data from keyword arguments.
Raises ValidationError if the input data cannot be parsed to form a valid model.
param aiosession: Optional[ClientSession] = None¶
The aiohttp session to use for the DataForSEO SERP API.
param api_login: Optional[str] = None¶
The API login to use for the DataForSEO SERP API.
param api_password: Optional[str] = None¶
The API password to use for the DataForSEO SERP API.
param default_params: dict = {'depth': 10, 'language_code': 'en', 'location_name': 'United States', 'se_name': 'google', 'se_type': 'organic'}¶
Default parameters to use for the DataForSEO SERP API.
param json_result_fields: Optional[list] = None¶
The JSON result fields.
param json_result_types: Optional[list] = None¶
The JSON result types.
param params: dict = {}¶
Additional parameters to pass to the DataForSEO SERP API.
param top_count: Optional[int] = None¶
The number of top results to return.
async aresults(url: str) → list[source]¶
Parameters
url (str) – 
Return type
list
async arun(url: str) → str[source]¶
Run request to DataForSEO SERP API and parse result async.
Parameters
url (str) – 
Return type
str
classmethod construct(_fields_set: Optional[SetStr] = None, **values: Any) → Model¶
dumps_kwargs (Any) – 
Return type
unicode
classmethod parse_file(path: Union[str, Path], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
path (Union[str, Path]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
classmethod parse_obj(obj: Any) → Model¶
Parameters
obj (Any) – 
Return type
Model
classmethod parse_raw(b: Union[str, bytes], *, content_type: unicode = None, encoding: unicode = 'utf8', proto: Protocol = None, allow_pickle: bool = False) → Model¶
Parameters
b (Union[str, bytes]) – 
content_type (unicode) – 
encoding (unicode) – 
proto (Protocol) – 
allow_pickle (bool) – 
Return type
Model
results(url: str) → list[source]¶
Parameters
url (str) – 
Return type
list
run(url: str) → str[source]¶
Run request to DataForSEO SERP API and parse result async.
Parameters
url (str) – 
Return type
str
classmethod schema(by_alias: bool = True, ref_template: unicode = '#/definitions/{model}') → DictStrAny¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
Return type
DictStrAny
classmethod schema_json(*, by_alias: bool = True, ref_template: unicode = '#/definitions/{model}', **dumps_kwargs: Any) → unicode¶
Parameters
by_alias (bool) – 
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
ref_template (unicode) – 
dumps_kwargs (Any) – 
Return type
unicode
classmethod update_forward_refs(**localns: Any) → None¶
Try to update ForwardRefs on fields based on this Model, globalns and localns.
Parameters
localns (Any) – 
Return type
None
classmethod validate(value: Any) → Model¶
Parameters
value (Any) – 
Return type
Model
Examples using DataForSeoAPIWrapper¶
DataForSEO