How to Efficiently Extract Values from Deeply Nested JSON Structures in Python?

Retrieving Nested Data from JSON Structures

When parsing complex JSON data, it can be challenging to extract specific values from deeply nested structures. This article provides a solution to this issue by outlining how to navigate nested data efficiently using Python's dictionary and list indexing syntax.

Understanding the Data Structure

Consider the following example JSON data:

<code class="python">my_json = {
    "name": "ns1:timeSeriesResponseType",
    "value": {
        "queryInfo": {
            "creationTime": 1349724919000,
            # ... other data
        }
    }
}</code>

Extracting a Specific Value

To access the "creationTime" value, use the following syntax:

<code class="python">query_info = my_json["value"]["queryInfo"]
creation_time = query_info["creationTime"]</code>

Breaking it down:

• my_json["value"] accesses the value of the "value" key in the outer dictionary (the parsed JSON data itself).
• query_info["creationTime"] accesses the value of the "creationTime" key in the "queryInfo" dictionary (which is obtained from my_json["value"]).

Therefore, creation_time will have the value 1349724919000.

Generalizing the Extraction Code

For nested data with variable levels of nesting, you can use a more general approach:

<code class="python">def get_nested_value(data, key_path):
    keys = key_path.split(".")
    value = data
    for key in keys:
        value = value[key]
    return value</code>

Usage:

<code class="python">creation_time = get_nested_value(my_json, "value.queryInfo.creationTime")</code>

This function takes a data dictionary and a key path (e.g., "value.queryInfo.creationTime") and iteratively accesses nested values until the desired value is obtained.

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