Parsers¶

Warning

This step is optional and is required only if the related API does not return JSON format.

Some API does not follow any standard and it can be complex to deal with its content. Thus, you might need to build some parsers to make the response stick to the model you described for the API

Parser structure¶

Parsers are build on the model previously described for your API. An abstract class is available to give you the main lines to build your parser:

Base with abstract classes for all parsers.

class dabeplech.parsers.base.BaseListParser(content_response)[source]¶

Bases: abc.ABC

Base structure for parsers.

__init__(content_response)[source]¶

Instantiate your parser on the response.

Parameters: content_response – content response from the API

model¶: alias of pydantic.main.BaseModel

abstract parse()[source]¶: Perform parsing of the content_response.

property validated_model¶

Retrieve entry validated with the model.

Returns: Validated entry.
Return type: BaseModel

class dabeplech.parsers.base.BaseParser(content_response)[source]¶

Bases: abc.ABC

Base structure for parsers.

__init__(content_response)[source]¶

Instantiate your parser on the response.

Parameters: content_response – content response from the API

model¶: alias of pydantic.main.BaseModel

abstract parse()[source]¶: Perform parsing of the content_response.

property validated_entry¶

Retrieve entry validated with the model.

Returns: Validated entry.
Return type: BaseModel

Note

We are aware that some API needs more specific and complex parsing, but the idea is to be perform parsing with the parse method and obtain the validated data with validated_entry property.

Test your parser¶

You can add your unit tests for your parser within /tests/dabeplech/parsers directory. You can have a look at the tests for kegg to help you build your own tests.