JMESPath is a query language for JSON.

Overview

JMESPath

https://travis-ci.org/jmespath/jmespath.py.svg?branch=develop https://codecov.io/github/jmespath/jmespath.py/coverage.svg?branch=develop

JMESPath (pronounced "james path") allows you to declaratively specify how to extract elements from a JSON document.

For example, given this document:

{"foo": {"bar": "baz"}}

The jmespath expression foo.bar will return "baz".

JMESPath also supports:

Referencing elements in a list. Given the data:

{"foo": {"bar": ["one", "two"]}}

The expression: foo.bar[0] will return "one". You can also reference all the items in a list using the * syntax:

{"foo": {"bar": [{"name": "one"}, {"name": "two"}]}}

The expression: foo.bar[*].name will return ["one", "two"]. Negative indexing is also supported (-1 refers to the last element in the list). Given the data above, the expression foo.bar[-1].name will return "two".

The * can also be used for hash types:

{"foo": {"bar": {"name": "one"}, "baz": {"name": "two"}}}

The expression: foo.*.name will return ["one", "two"].

Installation

You can install JMESPath from pypi with:

pip install jmespath

API

The jmespath.py library has two functions that operate on python data structures. You can use search and give it the jmespath expression and the data:

>>> import jmespath
>>> path = jmespath.search('foo.bar', {'foo': {'bar': 'baz'}})
'baz'

Similar to the re module, you can use the compile function to compile the JMESPath expression and use this parsed expression to perform repeated searches:

>>> import jmespath
>>> expression = jmespath.compile('foo.bar')
>>> expression.search({'foo': {'bar': 'baz'}})
'baz'
>>> expression.search({'foo': {'bar': 'other'}})
'other'

This is useful if you're going to use the same jmespath expression to search multiple documents. This avoids having to reparse the JMESPath expression each time you search a new document.

Options

You can provide an instance of jmespath.Options to control how a JMESPath expression is evaluated. The most common scenario for using an Options instance is if you want to have ordered output of your dict keys. To do this you can use either of these options:

>>> import jmespath
>>> jmespath.search('{a: a, b: b}',
...                 mydata,
...                 jmespath.Options(dict_cls=collections.OrderedDict))


>>> import jmespath
>>> parsed = jmespath.compile('{a: a, b: b}')
>>> parsed.search(mydata,
...               jmespath.Options(dict_cls=collections.OrderedDict))

Custom Functions

The JMESPath language has numerous built-in functions, but it is also possible to add your own custom functions. Keep in mind that custom function support in jmespath.py is experimental and the API may change based on feedback.

If you have a custom function that you've found useful, consider submitting it to jmespath.site and propose that it be added to the JMESPath language. You can submit proposals here.

To create custom functions:

  • Create a subclass of jmespath.functions.Functions.
  • Create a method with the name _func_<your function name>.
  • Apply the jmespath.functions.signature decorator that indicates the expected types of the function arguments.
  • Provide an instance of your subclass in a jmespath.Options object.

Below are a few examples:

import jmespath
from jmespath import functions

# 1. Create a subclass of functions.Functions.
#    The function.Functions base class has logic
#    that introspects all of its methods and automatically
#    registers your custom functions in its function table.
class CustomFunctions(functions.Functions):

    # 2 and 3.  Create a function that starts with _func_
    # and decorate it with @signature which indicates its
    # expected types.
    # In this example, we're creating a jmespath function
    # called "unique_letters" that accepts a single argument
    # with an expected type "string".
    @functions.signature({'types': ['string']})
    def _func_unique_letters(self, s):
        # Given a string s, return a sorted
        # string of unique letters: 'ccbbadd' ->  'abcd'
        return ''.join(sorted(set(s)))

    # Here's another example.  This is creating
    # a jmespath function called "my_add" that expects
    # two arguments, both of which should be of type number.
    @functions.signature({'types': ['number']}, {'types': ['number']})
    def _func_my_add(self, x, y):
        return x + y

# 4. Provide an instance of your subclass in a Options object.
options = jmespath.Options(custom_functions=CustomFunctions())

# Provide this value to jmespath.search:
# This will print 3
print(
    jmespath.search(
        'my_add(`1`, `2`)', {}, options=options)
)

# This will print "abcd"
print(
    jmespath.search(
        'foo.bar | unique_letters(@)',
        {'foo': {'bar': 'ccbbadd'}},
        options=options)
)

Again, if you come up with useful functions that you think make sense in the JMESPath language (and make sense to implement in all JMESPath libraries, not just python), please let us know at jmespath.site.

Specification

If you'd like to learn more about the JMESPath language, you can check out the JMESPath tutorial. Also check out the JMESPath examples page for examples of more complex jmespath queries.

The grammar is specified using ABNF, as described in RFC4234. You can find the most up to date grammar for JMESPath here.

You can read the full JMESPath specification here.

Testing

In addition to the unit tests for the jmespath modules, there is a tests/compliance directory that contains .json files with test cases. This allows other implementations to verify they are producing the correct output. Each json file is grouped by feature.

Discuss

Join us on our Gitter channel if you want to chat or if you have any questions.

A simple USI Shogi Engine written in python using python-shogi.

Revengeshogi My attempt at creating a USI Shogi Engine in python using python-shogi. Current State of Engine Currently only generating random moves us

1 Jan 06, 2022
A python package to import files from an adjacent folder

EasyImports About EasyImports is a python package that allows users to easily access and import files from sister folders: f.ex: - Project - Folde

1 Jun 22, 2022
100 numpy exercises (with solutions)

100 numpy exercises This is a collection of numpy exercises from numpy mailing list, stack overflow, and numpy documentation. I've also created some p

Nicolas P. Rougier 9.5k Dec 30, 2022
Explain yourself! Interrogate a codebase for docstring coverage.

interrogate: explain yourself Interrogate a codebase for docstring coverage. Why Do I Need This? interrogate checks your code base for missing docstri

Lynn Root 435 Dec 29, 2022
Generate a backend and frontend stack using Python and json-ld, including interactive API documentation.

d4 - Base Project Generator Generate a backend and frontend stack using Python and json-ld, including interactive API documentation. d4? What is d4 fo

Markus Leist 3 May 03, 2022
Lightweight, configurable Sphinx theme. Now the Sphinx default!

What is Alabaster? Alabaster is a visually (c)lean, responsive, configurable theme for the Sphinx documentation system. It is Python 2+3 compatible. I

Jeff Forcier 670 Dec 19, 2022
Soccerdata - Efficiently scrape soccer data from various sources

SoccerData is a collection of wrappers over soccer data from Club Elo, ESPN, FBr

Pieter Robberechts 195 Jan 04, 2023
Explorative Data Analysis Guidelines

Explorative Data Analysis Get data into a usable format! Find out if the following predictive modeling phase will be successful! Combine everything in

Florian Rohrer 18 Dec 26, 2022
VSCode extension that generates docstrings for python files

VSCode Python Docstring Generator Visual Studio Code extension to quickly generate docstrings for python functions. Features Quickly generate a docstr

Nils Werner 506 Jan 03, 2023
An MkDocs plugin to export content pages as PDF files

MkDocs PDF Export Plugin An MkDocs plugin to export content pages as PDF files The pdf-export plugin will export all markdown pages in your MkDocs rep

Terry Zhao 266 Dec 13, 2022
Hasköy is an open-source variable sans-serif typeface family

Hasköy Hasköy is an open-source variable sans-serif typeface family. Designed with powerful opentype features and each weight includes latin-extended

67 Jan 04, 2023
Version bêta d'un système pour suivre les prix des livres chez Books to Scrape,

Version bêta d'un système pour suivre les prix des livres chez Books to Scrape, un revendeur de livres en ligne. En pratique, dans cette version bêta, le programme n'effectuera pas une véritable surv

Mouhamed Dia 1 Jan 06, 2022
Pydantic model generator for easy conversion of JSON, OpenAPI, JSON Schema, and YAML data sources.

datamodel-code-generator This code generator creates pydantic model from an openapi file and others. Help See documentation for more details. Supporte

Koudai Aono 1.3k Dec 29, 2022
Docov - Light-weight, recursive docstring coverage analysis for python modules

docov Light-weight, recursive docstring coverage analysis for python modules. Ov

Richard D. Paul 3 Feb 04, 2022
Sane and flexible OpenAPI 3 schema generation for Django REST framework.

drf-spectacular Sane and flexible OpenAPI 3.0 schema generation for Django REST framework. This project has 3 goals: Extract as much schema informatio

T. Franzel 1.4k Jan 08, 2023
Credit EDA Case Study Using Python

This case study aims to identify patterns which indicate if a client has difficulty paying their installments which may be used for taking actions such as denying the loan, reducing the amount of loa

Purvi Padliya 1 Jan 14, 2022
Minimal reproducible example for `mkdocstrings` Python handler issue

Minimal reproducible example for `mkdocstrings` Python handler issue

Hayden Richards 0 Feb 17, 2022
A Python package develop for transportation spatio-temporal big data processing, analysis and visualization.

English 中文版 TransBigData Introduction TransBigData is a Python package developed for transportation spatio-temporal big data processing, analysis and

Qing Yu 251 Jan 03, 2023
The project that powers MDN.

Kuma Kuma is the platform that powers MDN (developer.mozilla.org) Development Code: https://github.com/mdn/kuma Issues: P1 Bugs (to be fixed ASAP) P2

MDN Web Docs 1.9k Dec 26, 2022
PowerApps-docstring is a console based, pipeline ready application that automatically generates user and technical documentation for Power Apps.

powerapps-docstring PowerApps-docstring is a console based, pipeline ready application that automatically generates user and technical documentation f

Sebastian Muthwill 30 Nov 23, 2022