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jsonpath-ngvsjsonlite

Apache-2.0 63 5 600
34.5 million (month) Feb 09 2022 1.7.0(16 days ago)
377 2 117 MIT
Dec 03 2013 1.4 million (month) 1.8.9(10 months ago)

jsonpath-ng is a Python library for parsing and querying JSON data.
It is a powerful tool for extracting and manipulating data from JSON structures,

The library uses a syntax similar to XPath, which is a well-known language for querying and manipulating XML data, to query and extract data from JSON structures. This makes it familiar and intuitive for many developers who have worked with XML in the past. JSONPath implementation in Python.

JSONPath is a JSON query path language inspired by XPath (path language for querying XML/HTML). For more see the initial syntax proposal.

jsonpath-ng is implemented in pure Python and can be easily extended with additional python functions if needed. Most commonly used JSONPath feature in web scraping is the recursive key lookup ($..key) which is a convenient way to find specific data fields in large datasets.

A reasonably fast JSON parser and generator, optimized for statistical data and the web. Offers simple, flexible tools for working with JSON in R, and is particularly powerful for building pipelines and interacting with a web API.

In addition to converting JSON data from/to R objects, 'jsonlite' contains functions to stream, validate, and prettify JSON data. The unit tests included with the package verify that all edge cases are encoded and decoded consistently for use with dynamic data in systems and applications.

Example Use


from jsonpath_ng import jsonpath, parse

# A robust parser, not just a regex. (Makes powerful extensions possible; see below)
jsonpath_expr = parse('foo[*].baz')

# Extracting values is easy
[match.value for match in jsonpath_expr.find({'foo': [{'baz': 1}, {'baz': 2}]})]
[1, 2]

# Matches remember where they came from
[str(match.full_path) for match in jsonpath_expr.find({'foo': [{'baz': 1}, {'baz': 2}]})]
['foo.[0].baz', 'foo.[1].baz']

# And this can be useful for automatically providing ids for bits of data that do not have them (currently a global switch)
jsonpath.auto_id_field = 'id'
[match.value for match in parse('foo[*].id').find({'foo': [{'id': 'bizzle'}, {'baz': 3}]})]
['foo.bizzle', 'foo.[1]']

# A handy extension: named operators like `parent`
[match.value for match in parse('a.*.b.`parent`.c').find({'a': {'x': {'b': 1, 'c': 'number one'}, 'y': {'b': 2, 'c': 'number two'}}})]
['number two', 'number one']

# You can also build expressions directly quite easily
from jsonpath_ng.jsonpath import Fields
from jsonpath_ng.jsonpath import Slice

jsonpath_expr_direct = Fields('foo').child(Slice('*')).child(Fields('baz'))  # This is equivalent
library("jsonlite")

json <- '["Mario", "Peach", null, "Bowser"]'

# load json to dataframe/array/matrix (determined automatically)
fromJSON(json)

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