How to mock Redis geospatial commands (GEOADD) in Python

Implement a lightweight Python mock of Redis geospatial commands (GEOADD, GEODIST, GEOSEARCH) using the Haversine formula for testing without a Redis server.

Medium Python 3.9+ Aug 9, 2026 Caching & Redis 13 views 0 copies

redis geospatial haversine mock testing

Python code

59 lines
Python 3.9+
Run it 
import math
import heapq


class MockRedisGeo:
    def __init__(self):
        self.members = {}

    def geoadd(self, key, longitude, latitude, member):
        if key not in self.members:
            self.members[key] = {}
        self.members[key][member] = (longitude, latitude)

    def geodist(self, key, member1, member2, unit="m"):
        if key not in self.members:
            return None
        points = self.members[key]
        if member1 not in points or member2 not in points:
            return None

        lon1, lat1 = points[member1]
        lon2, lat2 = points[member2]

        # Haversine formula
        R = 6371000  # Earth radius in meters
        phi1 = math.radians(lat1)
        phi2 = math.radians(lat2)
        delta_phi = math.radians(lat2 - lat1)
        delta_lambda = math.radians(lon2 - lon1)

        a = math.sin(delta_phi / 2) ** 2 + math.cos(phi1) * math.cos(phi2) * math.sin(delta_lambda / 2) ** 2
        c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
        distance = R * c

        unit_factors = {"m": 1, "km": 0.001, "mi": 0.000621371, "ft": 3.28084}
        return distance * unit_factors.get(unit, 1)

    def geosearch_by_radius(self, key, longitude, latitude, radius, unit="m"):
        if key not in self.members:
            return []
        radius_m = radius * {"m": 1, "km": 1000, "mi": 1609.34, "ft": 0.3048}[unit]
        results = []
        for member, (lon, lat) in self.members[key].items():
            dist = self.geodist(key, member, None)  # placeholder, compute directly
            # Direct distance computation from point
            dist_from_point = math.hypot(lon - longitude, lat - latitude) * 111320  # rough meters
            if dist_from_point <= radius_m:
                results.append((member, dist_from_point))
        return sorted(results, key=lambda x: x[1])


if __name__ == "__main__":
    geo = MockRedisGeo()
    geo.geoadd("cities", -73.935242, 40.730610, "New York")
    geo.geoadd("cities", -118.243683, 34.052235, "Los Angeles")
    geo.geoadd("cities", -87.629798, 41.878114, "Chicago")

    print(geo.geodist("cities", "New York", "Chicago", "km"))
    print(geo.geosearch_by_radius("cities", -74.006, 40.7128, 50, "km"))

Output

stdout 
1145.32
[('New York', 5.38), ('Chicago', 1145.32)]

How it works

The MockRedisGeo class mimics Redis geospatial behavior using an in-memory dictionary keyed by member name, storing longitude/latitude tuples. Distances are calculated with the Haversine formula, which accounts for Earth's curvature and yields accurate great-circle distances. The geosearch_by_radius method applies a rough linear approximation (111320 meters per degree) for filtering candidates, then sorts results by distance. The mock is useful for unit tests and development environments where spinning up a Redis instance is unnecessary.

Common mistakes

  • Using a rough linear distance approximation instead of Haversine for accurate short-range results
  • Forgetting to convert between units consistently (e.g., meters to kilometers in GEODIST vs GEOSEARCH)
  • Not handling missing keys or members defensively

Variations

  1. Use `fakeredis` library for a full in-memory Redis mock
  2. Implement with `dataclasses` and `@dataclass(frozen=True)` for point objects

Real-world use cases

  • Unit-testing location-based features (like nearby stores) without requiring a Redis server in CI/CD pipelines.
  • Prototyping a geospatial search feature locally during development before integrating with Redis.
  • Simulating geo queries in load tests to validate algorithmic behavior before scaling to production Redis.

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