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For a string containing JSON, use json.loads(json_text). When the JSON’s top-level value is an object, Python returns a dict; other top-level values decode to their corresponding Python types. The Python Software Foundation’s json documentation describes loads as deserializing a JSON document from a string, bytes, or bytearray into a Python object.
Convert JSON text with json.loads
json is part of Python’s standard library, so no third-party package is needed. Import it and pass the JSON string to loads:
import json
json_text = '{"name": "Ada", "active": true, "scores": [10, 12]}'
data = json.loads(json_text)
print(data["name"]) # Ada
print(type(data)) # <class 'dict'>JSON syntax differs from Python syntax: JSON strings and object keys use double quotes, and its literals are true, false, and null. The decoder maps those literals to Python’s True, False, and None.
Check the top-level value before treating it as a dictionary
json.loads returns a Python value based on the JSON value at the document’s top level. An object becomes a dict, but JSON permits other top-level values too.
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| Top-level JSON value | Python result |
|---|---|
Object, such as {"name": "Ada"} |
dict |
Array, such as [1, 2] |
list |
| String | str |
| Integer | int |
| Real number | float |
true or false |
True or False |
null |
None |
If the input’s top-level value might vary, inspect it before accessing dictionary keys:
data = json.loads(json_text)
if isinstance(data, dict):
print(data.get("name"))
else:
print("Expected a JSON object")Four other useful forms of the standard decoder
These options customize or make explicit how Python’s built-in JSON decoder works. For ordinary JSON text, json.loads remains the simplest choice.
1. Call JSONDecoder().decode explicitly
Use the decoder object when you want to work with the standard JSONDecoder class directly:
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decoder = json.JSONDecoder()
data = decoder.decode(json_text)2. Transform decoded objects with object_hook
object_hook is called for each decoded JSON object. It receives a dictionary and may return a replacement, which is useful when objects follow a known tagged structure:
def object_hook(obj):
if obj.get("__type__") == "point":
return (obj["x"], obj["y"])
return obj
data = json.loads(json_text, object_hook=object_hook)In this example, an object tagged with "__type__": "point" becomes a tuple. Other objects remain dictionaries.
3. Handle object members as ordered pairs with object_pairs_hook
Use object_pairs_hook when your code needs each object’s members as an ordered list of pairs, or when you want to build a different representation from those pairs:
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data = json.loads(json_text, object_pairs_hook=dict)If both object_hook and object_pairs_hook are supplied, object_pairs_hook takes priority.
4. Choose how JSON numbers are parsed
The parse_float and parse_int hooks receive the textual form of a JSON number. For example, to decode decimal values as Decimal rather than the default floating-point type:
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from decimal import Decimal
data = json.loads(json_text, parse_float=Decimal)Use a numeric hook when your application requires a particular numeric type or conversion policy; otherwise, the defaults are appropriate.
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Use json.load for a file, not a string
When the JSON comes from an open, readable file object, use json.load(file). The distinction is the input: loads takes JSON text, while load reads from a file-like object.
with open("data.json", encoding="utf-8") as file:
data = json.load(file)Handle invalid JSON and Python-looking text
Catch decoding errors when input may be malformed
Malformed JSON raises json.JSONDecodeError. Its location details can help identify where decoding failed:
try:
data = json.loads(json_text)
except json.JSONDecodeError as error:
print(f"Invalid JSON at line {error.lineno}, column {error.colno}: {error.msg}")Do not mistake a Python dictionary representation for JSON
A string such as {'name': 'Ada'} uses single quotes, so it is Python-like text rather than valid standard JSON. Correct the producer or input format so it supplies valid JSON, then decode it with json.loads. Do not use eval to convert input: it executes Python expressions and is not a JSON parser.
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Account for non-standard numeric constants
Python’s JSON decoder accepts NaN, Infinity, and -Infinity by default, although these are outside the JSON specification. If strict conformance matters, account for this behavior rather than assuming every accepted input is standard JSON.
For unusually large or untrusted integer input, note that Python 3.11 changed the default integer parsing path to use the interpreter’s integer-string length limitation as a denial-of-service mitigation, as described in the official documentation.
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