JSON data is frequently stored in strings. We’ll also explore how to handle custom classes. We’re going to convert JSON to dictionary and list and the other way round. In the remainder of this tutorial, we will explore this package. You can find the official documentation for the Python JSON module here. The json module provides the functionality to write custom encoders and decoders, and there is no separate installation needed. The JSON package can also convert Python objects into the JSON format. The json module can handle the conversion of JSON data from JSON format to the equivalent Python objects such as dictionary and list. The Python json module is part of the Standard Library. If you want to read more about the JSON standard, head over to the official JSON website. This is one of the primary reasons why JSON is so popular. English Spanish Īs evident here, JSON is lightweight. This post is featured in Issue #374 of P圜oder’s Weekly.United States 331002651 Washington D. append ( extract ( item, path, 0, )) return outer_arr Update append ( None ) return arr if isinstance ( obj, dict ): return extract ( obj, path, 0, ) elif isinstance ( obj, list ): outer_arr = for item in obj : outer_arr. get ( key, None )) elif isinstance ( obj, dict ): arr. append ( None ) else : for item in obj : arr. append ( None ) if ind + 1 = len ( path ): if isinstance ( obj, list ): if not obj : arr. append ( None ) else : for item in obj : extract ( item, path, ind, arr ) else : arr. append ( None ) elif isinstance ( obj, list ): if not obj : arr. get ( key ), path, ind + 1, arr ) else : arr. ''' key = path if ind + 1 < len ( path ): if isinstance ( obj, dict ): if key in obj. Path - list - list of strings that form the JSON path ''' def extract ( obj, path, ind, arr ): '''Įxtracts an element from a nested dictionaryĪlong a specified path and returns a list. Path - list - list of strings that form the path to the desired element Obj - list or dict - input dictionary or list of dictionaries If the input is a list of dictionary, a list of lists is returned. If the input is a dictionary, a list is returned. īelow is the full function (inspired/motivated from what’s discussed here): def extract_element_from_json ( obj, path ): '''Įxtracts an element from a nested dictionary orĪ list of nested dictionaries along a specified path. If any element of path is missing from the corresponding level of the nested dictionary/JSON, then this function returns a None. If obj is a single dictionary/JSON record, then this function returns a list containing the desired information, and if obj is a list of dictionaries/JSON records, then this function returns a list of lists containing the desired information. This is how both ‘Alice’ and ‘Bob’ are returned since the value of employees is a list, the nesting is split on both of its elements and each of the values for name are appended to the output list. When a list is encountered as the value of a key in path, this function splits and continues nesting on each element of the encountered list in a depth-first manner. This function nests into the record(s) in obj according to the keys specified in path to retrieve the desired information. Suppose you have the following JSON record: extract_element_from_json ( data, ) > Under the Hood This post provides a solution if one knows the path through the nested JSON to the desired information. For analyzing complex JSON data in Python, there aren’t clear, general methods for extracting information (see here for a tutorial of working with JSON data in Python). Despite being more human-readable than most alternatives, JSON objects can be quite complex. JSON is the typical format used by web services for message passing that’s also relatively human-readable.
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