How to Index a List of Records by Unique ID in Python

Build a dictionary that maps each record's unique id to the record itself from a list of dictionaries.

Easy Python 3.9+ Aug 9, 2026 Dictionaries & sets 15 views 0 copies

dictionary index records lookup list

Python code

15 lines

Python 3.9+

from typing import List, Dict, Any

def index_by_id(records: List[Dict[str, Any]], id_field: str = "id") -> Dict[Any, Dict[str, Any]]:
    """Build a dictionary mapping each record's unique id to the record itself."""
    return {record[id_field]: record for record in records}

if __name__ == "__main__":
    sample_records = [
        {"id": 101, "name": "Alice", "score": 92},
        {"id": 102, "name": "Bob", "score": 87},
        {"id": 103, "name": "Carol", "score": 95},
    ]
    indexed = index_by_id(sample_records)
    for key in sorted(indexed):
        print(f"{key}: {indexed[key]}")

Output

stdout

101: {'id': 101, 'name': 'Alice', 'score': 92}
102: {'id': 102, 'name': 'Bob', 'score': 87}
103: {'id': 103, 'name': 'Carol', 'score': 95}

How it works

The dictionary comprehension {record[id_field]: record for record in records} iterates over each record and uses its id field as the key, assigning the entire record as the value. This creates a direct mapping from id to record, allowing O(1) lookups instead of scanning the list every time. The id_field parameter defaults to "id" but can be changed to any field name in the records. Assuming ids are unique, this index is lossless — no records are overwritten. For non-unique ids, later records silently overwrite earlier ones, so validate uniqueness if needed.

Common mistakes

Assuming ids are unique — duplicates silently overwrite earlier records.
Forgetting to handle missing id keys with a KeyError.
Using the record itself as value, which may be too heavy for large datasets.
Not sorting keys when printing if deterministic order is required.

Variations

Use `defaultdict(list)` to group records by id when ids are not unique.
Use `dict.fromkeys` with a comprehension to initialize an index with default values.

Real-world use cases

Lookup customer records by customer_id in a user-facing API endpoint.
Build an in-memory index of database rows for quick joins between two datasets.
Maintain a cache of configuration items keyed by their unique config id.

How to Index a List of Records by Unique ID in Python

Python code

Output

How it works

Common mistakes

Variations

Real-world use cases

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Python code

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Common mistakes

Variations

Real-world use cases

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