PoolingClient

The PoolingClient object used for fetching information through different API calls, each with different parameters.

egytech_api.core.PoolingClient(pydantic.BaseModel)

Attributes

Name	Type	Description
queries	list[ParticipantsQueryParams]	The list of queries to-be-executed.

Note: There is nothing to guarantee that the fetched participants via this object don't have duplicates. It's up to you to use this data and infer from it at your own risk.

Example:

Query 1: Participants whose companies work on B2B solutions and have a cs degree.

Query 2: Females who work in front-end and have a cs degree.

Among these 2 queries, a female could fulfill both sets of criteria. The wrapper doesn't currently implement safeguards to prevent duplicates in query results.

Methods

get_df()

Returns a pandas.DataFrame instance of the aggregated participant data from the queries.

Parameters

No parameters

Returns

Type	Description
pandas.DataFrame	A pandas.DataFrame instance containing the fetched data as one row per fetched participant.

save_csv(filename: str)

Parameters

Name	Type	Description	Example
filename	str	The name of the .csv file to dump the fetched participant data in (without extension). No extension is needed explicitly as it's added during the file-saving process.	"my_awesome_data"

Returns

None

This method is simply a placeholder for the pandas.DataFrame.to_csv() method. It simply saves the generated pandas.DataFrame instance to a .csv file and excludes the index. You can customize your own function parameters for this by simply calling the get_df() method, and manipulating the resulting pandas.DataFrame as you want.

save_excel(filename: str)

Parameters

Name	Type	Description	Example
filename	str	The name of the .xlsx file to dump the fetched participant data in (without extension). No extension is needed explicitly as it's added during the file-saving process.	"my_awesome_data"

Returns

None

This method is simply a placeholder for the pandas.DataFrame.to_excel() method. It simply saves the generated pandas.DataFrame instance to a .xlsx file and excludes the index. You can customize your own function parameters for this by simply calling the get_df() method, and manipulating the resulting pandas.DataFrame as you want.

This function uses "xlsxwriter" as the excel writer engine by default. Customization is available by calling to_excel() on a pandas.DataFrame instance instead.