Module reference

Constructor

BEA(api_key)

The primary class in the BEApy package, handles sending requests and manipulating the results.

Raw API call

BEAAPI.send_request(params)

Base method for sending a GET request to the API.

Metadata

BEA.dataset_list()	Get a list of all availible datasets (API method getDatasetList)
BEA.parameter_list(dataset)	Get a list of availible parameters for the dataset (API method getParameterList)
BEA.parameter_values(dataset, parameter[, …])	Get a list of possible values for the parameter in a dataset (API method getParameterValues).

References

Module for sending requests to BEA API and handling errors

class beapy.api.BEAAPI(api_key)

Base class for communicating with the API, outputs raw JSON results.

This class communicates with the BEA API and handles possible errors, returning unfiltered JSON results in case of success. It stores your API key on initiation, and uses it for future requests. It serves as a base class to enable the BEA class to abstract from requests and error handling.

Parameters:api_key (str) – Your BEA API key

send_request(params)

Base method for sending a GET request to the API.

This method sends a GET request to the base url with the params + the API key + JSON format and handles error messages. If successful, returns the Results part of the response.

Parameters:params (dict) – Additional params to add to the GET request Return type:dict

exception beapy.api.BEAError(status_code, message)

Error class to handle BEA API specific errors

class beapy.BEA(api_key)

The primary class in the BEApy package, handles sending requests and manipulating the results. Needs to be initiated with your BEA API key once, it is stored for all later requests.

Parameters:api_key (str) – Your BEA API key

dataset_list()

Get a list of all availible datasets (API method getDatasetList)

Returns:A DataFrame with a description and name of availible datasets. Return type:pd.DataFrame

parameter_list(dataset)

Get a list of availible parameters for the dataset (API method getParameterList)

Usually the parameter list will also include the value of the ALL option, as well as data type, whether the parameteris is required, and whether it accepts multiple values.

Parameters:dataset (str) – The name of the dataset Returns:A DataFrame with a description and name of availible parameters, as well as some other options. Return type:pd.DataFrame

parameter_values(dataset, parameter, filtering=None)

Get a list of possible values for the parameter in a dataset (API method getParameterValues).

Optionally, filter the list based on values of other parameters (API method getParameterValuesFiltered). Be careful in this case, as the filtered method is not implemented for all datasets.

Parameters:

• dataset (str) – The name of the dataset
• parameter (str) – The name of the (target) parameter whose values you are retrieving
• filter – A dictionary of parameter-value pairs, based on which to filter the target parameter. If set to None, getParameterValues` API method is used. Otherwise, getParameterValuesFiltered is used.

Returns:

A DataFrame with a description and name (key) of availible parameters values

Return type:

pd.DataFrame