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How to Merge JSON Files in Python Without Overwriting Keys

Timesofasi — Fri, 30 Oct 2026 13:07:29 GMT

Merging JSON files sounds easy until you lose data. A plain dict.update() overwrites whole nested objects, and arrays are replaced instead of combined. Here is how to do it properly in Python.

The problem: shallow merge loses data

Say you have two config files.

a.json

{
  "name": "app",
  "settings": { "theme": "dark", "lang": "en" }
}

b.json

{
  "settings": { "theme": "light" },
  "debug": true
}

A shallow merge replaces the whole settings object:

import json

with open("a.json") as f1, open("b.json") as f2:
    a = json.load(f1)
    b = json.load(f2)

result = {**a, **b}   # or: a | b  (Python 3.9+)
print(json.dumps(result, indent=2))

{
  "name": "app",
  "settings": { "theme": "light" },
  "debug": true
}

Notice that "lang": "en" is gone. That is the classic shallow merge bug.

Deep merge: keep nested keys

A deep merge walks into nested objects and merges them recursively:

def deep_merge(a, b):
    result = dict(a)
    for key, value in b.items():
        if key in result and isinstance(result[key], dict) and isinstance(value, dict):
            result[key] = deep_merge(result[key], value)
        else:
            result[key] = value
    return result

merged = deep_merge(a, b)
print(json.dumps(merged, indent=2))

{
  "name": "app",
  "settings": { "theme": "light", "lang": "en" },
  "debug": true
}

Now lang is kept, and theme is updated by the second file. If both files define the same key, the last file wins. Decide this on purpose, since it is the most common source of surprises.

Merging many files at once

import json
from functools import reduce
from pathlib import Path

files = sorted(Path("configs").glob("*.json"))
data = [json.loads(p.read_text()) for p in files]

merged = reduce(deep_merge, data, {})
Path("merged.json").write_text(json.dumps(merged, indent=2))

Sorting the files makes the result predictable, because the order decides who wins on conflicts.

Merging arrays of objects by ID

Merging two lists usually should not create duplicates. If your objects have an id, merge them by it:

def merge_by_id(a, b, key="id"):
    merged = {item[key]: item for item in a}
    for item in b:
        merged[item[key]] = deep_merge(merged.get(item[key], {}), item)
    return list(merged.values())

users_a = [{"id": 1, "name": "Asha"}, {"id": 2, "name": "Ravi"}]
users_b = [{"id": 2, "email": "ravi@example.com"}, {"id": 3, "name": "Meena"}]

print(merge_by_id(users_a, users_b))
# [{'id': 1, 'name': 'Asha'},
#  {'id': 2, 'name': 'Ravi', 'email': 'ravi@example.com'},
#  {'id': 3, 'name': 'Meena'}]

Edge cases to watch for

Type conflicts: one file has an object and the other has a string for the same key. Decide which wins.
Arrays without IDs: you either replace them, concatenate them, or de-duplicate them. Pick one rule.
null values: decide whether null should overwrite a real value.
Large files: json.load reads everything into memory. For very large files, use a streaming parser such as ijson.
Invalid JSON: wrap json.load in try/except json.JSONDecodeError so one bad file gives a clear error.

Don't want to write code?

If you just need a quick result, I built a free browser tool for this: JoinJSON. You can paste JSON, upload files, or load from a URL, then merge them and download the result.

More guides:

What edge case has bitten you when merging JSON? Tell me in the comments.

Top Machine Learning Projects for Students to Boost Their Skills

Timesofasi — Sun, 22 Sep 2024 15:56:58 GMT

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Machine Learning Project With Source Code

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