Read from JSON files without having to keep everything in memory

pip install sleepyjson==0.0.2



In some situations, particularly in big data scenarios, it is necessary to extract information from a JSON file without needing to read the full content into memory. For an example, see the "Example" section below.

sleepyjson provides a mechanism to deal with this scenario, where the JSON file is only parsed until the necessary information is found, and only that data is kept in memory.

Although the package provides ways to handle random access to the contents of the file, random access runs in linear time on the size of the file. In fact, the whole idea of the package is to support memory-lightweight sequential processing of the JSON file.


Imagine you have a 10GB JSON file, where the top value is an array and the various items follow a predictable structure, as illustrated in the snippet below (pretend that the top level array contains millions of items and the snippets key contains large arrays with potentially long strings). Imagine as well that you want to extract the identifiers associated items that are dated from January of any year.

    "identifier": "AX1999",
    "url": "",
    "date": {
      "year": 2020,
      "month": 1,
      "day": 1
    "snippets": [
      "A happy snippet of text found in the URL",
      "Another snippet of text, this time sad",
      "Yet another",
      "And potentially many more"
  // ...

Traditionally (with the standard library json package), you would need to read the full dataset into memory.

import json

with open('data.json') as f:
  data = json.load(f)

identifiers = [
  for item in data
  if item['date']['month'] == 1

Because you're reading the full file contents into the data variable, the memory consumption for this snippet is quite high.

With sleepyjson, you can keep memory usage low and still achieve the same result:

import sleepyjson

with open('data.json') as f:
  reader = sleepyjson.Reader(f)

  identifiers = [
    for item in reader
    if item['date']['month'].value() == 1

Notice the while the memory consumption is low, time complexity is linear for most purposes. If you want to get to a value near the end of a JSON file, the file must be fully parsed until the position you need to access. Additionally, because this is a pure python implementation, parsing is slow (I may change the parsing mechanism in the future to a compiled process to accelerate this).

Comparison with json

As you can spot in the previous snippet of code, sleepyjson requires you to keep the file opened while you are moving within the JSON contents. This is because no content is moved into memory unless the code does so explicitly.

Additionally, the contents of a value must be explicitly requested with the .value() method. Note: I want to change this method to something more explicit, like materialize, to convey the meaning that we are not simply getting the value, but actually parsing and building a JSON value, which might be costly if the value is big.

The sleepyjson.Reader class takes a file-like object, but doesn't read its contents until requested to. You can move around the file using iteration and indexation.

Also, sleepyjson.Reader can read "JSON streams" in addition to regular JSON files. JSON streams are files that contain JSON values in succession. The reader can navigate within these files using the .next() method.

# Assuming file `data.json` contains
# ["an", "array"] {"an": "object"}

from sleepyjson import Reader

with open('data.json') as f:
  reader = Reader(f)

  print(reader.value())  # ['an', 'array']
  print(reader.value())  # {'an': 'object'}

Partially valid JSON

In case your information needs from the file do not require the file to be read until the end, sleepyjson parses only the necessary contents from the file, which means that the file does not need to be completely valid.

Comments, trailing commas

Even though python's json package does not accept comments nor trailing commas, some popular packages elsewhere do. To support reading this "non-standard" data format, sleepyjson understands double-slash comments and ignores trailing commas. So the following would be a valid JSON file from the point of view of this package:

  // Comment
  "powers of two": [

Simple documentation

The API surface of this package is simple, providing three classes:

  • Node
  • NodeType
  • Reader

While you can produce instances of the Node class, I recommend you only instantiate Reader directly. NodeType is an enumeration class that represents the possible JSON value types.

The Node class

This class represents a value in the JSON file. It deliberately does not contain a full representation of the value, particularly for strings, arrays and objects, because doing so would defeat the purpose of the package. It does, however, offer mechanisms to access those value, by allowing iteration over arrays and objects, and allowing (but not requiring) the construction, in memory, of its contents.

In the following examples, we assume node points to the JSON object represented below:

  "a": [0, 1.337e3],
  "b": "string",
  "c": [true, false, null]

In general, some operations are only valid for some types (namely indexing, iterating, etc.). If the corresponding methods are called on a node of an incorrect type, a ValueError is raised.

The Node.type attribute

Returns an instance of NodeType that represents the type of JSON value under this node. Possible values are:

  • NodeType.OBJECT
  • NodeType.ARRAY
  • NodeType.NUMBER
  • NodeType.STRING
  • NodeType.TRUE
  • NodeType.FALSE
  • NodeType.NULL

The Node.value method

Builds and returns the value of this node.

  • If the node is a JSON true, false or null literal, it returns True, False or None respectively.
  • If the node is a number, it parses and returns the number (returns an int if no decimal and no exponent is provided, float otherwise).
  • If the node is a string, it parses the string, unescaping any escaped characters
  • If the node is an array, it returns a python list
  • If the node is an object, it returns a python dict

The inner values of arrays and objects are recursively built with the .value method as well.

The Node.__getitem__ method (node[i])

For arrays and objects, returns a Node that represents the requested item. For arrays, you can index with integers. Negative value are allowed, but this requires parsing the entire array to determine the length of the array. For objects, you can index with strings. Indexing parses the node only until the correct item is found (except for indexing arrays with a negative value). If the item is not found, an IndexError is raised (for arrays) or a KeyError is raised (for objects).

node['a'].value() # [0, 1337.0]
node['c'][0].value() # True
node['c'][-1].value() # None

node['x'] # raises KeyError

The Node.__len__ method (len(node))

For arrays and objects, returns the length of the value. Determining the length parses the result but doesn't construct the items, which means it is easy on memory.

len(node) # 3
len(node['a']) # 2
len(node['b']) # raises ValueError; you cannot determine the length of a string

The Node.__iter__ method (for i in node)

Iterates over the items in an array, or over the keys in an object. This iterates in the order the values appear in the file. Also see Node.items, to iterate over the keys and values of a JSON object.

list(node) # ['a', 'b', 'c']
[i.value() > 0 for i in node['a']] # [False, True]

The Node.items method

Iterates over the items of a JSON object. The iterator returned from this method sequentially produces pairs of type (str, Node), where the first item in the key and the second item is the node representing the value associated with that key. The iterator respects the order in the file.

The Node.__contains__ method (x in node)

This defines the in operator. x in node is True if:

  • node represents a JSON array and one of its inner values is equal to x
  • node represents a JSON object and one of its keys is equal to x
'a' in node # True
0 in node['a'] # True

The Node.is_* methods

There are several of these methods, each testing the type of value the node points to:

  • Node.is_object: Determines whether the node points to an object
  • Node.is_array: Determines whether the node points to an array
  • Node.is_string: Determines whether the node points to a string
  • Node.is_number: Determines whether the node points to a number
  • Node.is_true: Determines whether the node points to the true literal
  • Node.is_false: Determines whether the node points to the false literal
  • Node.is_boolean: Determines whether the node points to a boolean (true or false)
  • Node.is_null: Determines whether the node points to the null literal

A note on key uniqueness

sleepyjson does not make an effort to validate that keys on objects are unique. This means that iterating over the keys of an object can produce the same key more than once; however, retrieving the actual value of a JSON object preserves only one of those key-value pairs (since the returned object is actually a python dictionary).

Additionally, because retrieving an item from an object stops when the key is first found in the file, and building the python dictionary likely preserves the last value associated with the key.

As such, when a key is repeated in a JSON object, the following can happen:

  • len(node) > len(node.value())
  • node[key].value() != node.value()[key]

The Reader class

In the following examples, we assume reader to be constructed from a file whose contents are:

  "a": [1, 2, 3]
[null, false, true]

The Reader.__init__ constructor

This class constructor takes a file-like whose contents are in the JSON format. The file should contain a JSON value or a sequence of JSON values (a-la JSON streams). It can also receive multiple files.

The Reader.node attribute

Returns the node that is currently being read in the JSON stream. As a convenience, you can access the fields and methods of this node by calling them directly on the reader:

reader.node.value() # {'a': [1, 2, 3]}
reader.value() # {'a': [1, 2, 3]}

The Reader.__len__ method (len(node))

Returns the length of the current node. Equivalent to len(reader.node).

The Reader.__iter__ method (for i in node)

Iterates over the current node. Equivalent to iter(reader.node)

The Reader.__getattr__ method (node.*)

This method gets the requested attribute from reader.node, thus ensuring that the reader behaves in most ways like the node it is currently reading. Read the Node documentation to know more about this.

The Reader.__getitem__ method (node[i])

This method implements random access to the contents of the current node. Equivalent to reader.node[i]. See the documentation for the Node class.

reader['a'].value() # [1, 2, 3]
len(reader['a']) # 3

The method

Jumps to the next value on the JSON stream. Notice that if multiple files have been given in the constructor, this is the way to access the next files. There is no way to jump back to a previous value on the stream.

reader.value() # {'a': [1, 2, 3]}
reader.value() # true
reader.value() # [None, False, True]

If there are no more nodes in the current file and no more files to process, this method raises a StopIteration exception.

The Reader.jump method

Performs the .next() method a non-negative number of times.

reader.value() # {'a': [1, 2, 3]}
reader.value() # [None, False, True]