There are other libraries that implement similar functionality to that of json-enhanced, but all of them use their own syntax for querying data, whereas json-enhanced uses a purely Python syntax, based on Django's ORM.
Let's see a quick usage comparison between the different related packages.
Perhaps the most used library to cover this type of needs. Following the example concerning authors and books, published on its web site:
data = {
"store": {
"book": [
{
"category": "reference",
"author": "Nigel Rees",
"title": "Sayings of the Century",
"price": 8.95
},
{
"category": "fiction",
"author": "Evelyn Waugh",
"title": "Sword of Honour",
"price": 12.99
},
{
"category": "fiction",
"author": "Herman Melville",
"title": "Moby Dick",
"isbn": "0-553-21311-3",
"price": 8.99
},
{
"category": "fiction",
"author": "J. R. R. Tolkien",
"title": "The Lord of the Rings",
"isbn": "0-395-19395-8",
"price": 22.99
}
],
"bicycle": {
"color": "red",
"price": 19.95
}
}
}
from jsonpath_ng.ext import parse
# retrieving the authors of all books in the store
query_all_book_authors = parse("$.store.book[*].author")
[match.value for match in query_all_book_authors.find(data)]
['Nigel Rees', 'Evelyn Waugh', 'Herman Melville', 'J. R. R. Tolkien']
# getting the json path of the first author
str(query_all_book_authors.find(data)[0].full_path)
'store.book.[0].author'
# filter all books with isbn number
query_isbn_books = parse("$..book[?(@.isbn)]")
[match.value for match in query_isbn_books.find(data)]
[{'category': 'fiction',
'author': 'Herman Melville',
'title': 'Moby Dick',
'isbn': '0-553-21311-3',
'price': 8.99},
{'category': 'fiction',
'author': 'J. R. R. Tolkien',
'title': 'The Lord of the Rings',
'isbn': '0-395-19395-8',
'price': 22.99}] import jsonutils as js
data = js.JSONObject(data) # load previous data as a JSONNode instance
# retrieving the authors of all books in the store
data.store.book.query(author=js.All) # just one statement
<QuerySet ['Nigel Rees', 'Evelyn Waugh', 'Herman Melville', 'J. R. R. Tolkien']>
# getting the json path of the first author
data.store.book.query(author=js.All).first().jsonpath
store/book/0/author/
# or if we want a python path expression
data.store.book.query(author=js.All).first().jsonpath.expr
'["store"]["book"][0]["author"]'
# filter all books with isbn number
data.store.book.query(isbn__isnull=False, include_parent_=True)
<QuerySet [{'category': 'fiction', 'author': 'Herman Melville', 'title': 'Moby Dick', 'isbn': '0-553-21311-3', 'price': 8.99}, {'category': 'fiction', 'author': 'J. R. R. Tolkien', 'title': 'The Lord of the Rings', 'isbn': '0-395-19395-8', 'price': 22.99}]>This library is currently out of maintenance. Its syntax is very similar to that of jsonpath-ng. Let's compare its functionality following the example of json above.
from objectpath import Tree
tree = Tree(data) # loading the data above
# retrieving books with price greater than 12
list(tree.execute("$.store.book[@.price > 12]"))
[{'category': 'fiction',
'author': 'Evelyn Waugh',
'title': 'Sword of Honour',
'price': 12.99},
{'category': 'fiction',
'author': 'J. R. R. Tolkien',
'title': 'The Lord of the Rings',
'isbn': '0-395-19395-8',
'price': 22.99}]import jsonutils as js
data = js.JSONObject(data)
# retrieving books with price greater than 12
data.store.book.query(price__gt=12) # without including parent nodes
<QuerySet [12.99, 22.99]>
# getting the last element's parent
data.store.book.query(price__gt=12).last().parent
{'category': 'fiction',
'author': 'J. R. R. Tolkien',
'title': 'The Lord of the Rings',
'isbn': '0-395-19395-8',
'price': 22.99}The pandas library offers very user-friendly tools for querying structured data. The main problem is that it can only properly read data that has a defined structure (which can be converted to a dataframe). In the case we are concerned with, we could proceed as follows:
import pandas as pd
df = pd.json_normalize(data, ["store", ["book"]])
df
category author title price isbn
0 reference Nigel Rees Sayings of the Century 8.95 NaN
1 fiction Evelyn Waugh Sword of Honour 12.99 NaN
2 fiction Herman Melville Moby Dick 8.99 0-553-21311-3
3 fiction J. R. R. Tolkien The Lord of the Rings 22.99 0-395-19395-8
# filter books with no isbn
df.query("isbn.isna()")
category author title price isbn
0 reference Nigel Rees Sayings of the Century 8.95 NaN
1 fiction Evelyn Waugh Sword of Honour 12.99 NaN
# filter books whose title contains the string "the" and has a valid ISBN
df.query("title.str.contains('the') & isbn.isna() == False")
category author title price isbn
3 fiction J. R. R. Tolkien The Lord of the Rings 22.99 0-395-19395-8import jsonutils as js
data = js.JSONObject(data) # load the data into JSONNode instance
# filter books with no isbn
data.store.book.annotate(isbn=None).query(isbn__isnull=True, include_parent_=True)
<QuerySet [{'category': 'reference', 'author': 'Nigel Rees', 'title': 'Sayings of the Century', 'price': 8.95, 'isbn': None}, {'category': 'fiction', 'author': 'Evelyn Waugh', 'title': 'Sword of Honour', 'price': 12.99, 'isbn': None}]>
# filter books whose title contains the string "the" and has a valid ISBN
data.store.book.query(title__contains="the", isbn__isnull=False)
<QuerySet [{'category': 'fiction', 'author': 'J. R. R. Tolkien', 'title': 'The Lord of the Rings', 'isbn': '0-395-19395-8', 'price': 22.99}]>