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Pure Python distance engine — Haversine great-circle distance, bearing, midpoint, travel time estimates, and unit conversions. Zero dependencies.

Project description

distancefyi

PyPI Python License: MIT

Pure Python distance engine for developers. Compute Haversine great-circle distances, initial bearings with 16-point compass directions, geographic midpoints, great circle arcs, antipodal points, and realistic travel time estimates -- all with zero dependencies.

Explore distances between world cities at distancefyi.com -- distance calculator, city-to-city routes, and travel time estimates.

distancefyi CLI demo

Table of Contents

Install

pip install distancefyi              # Core engine (zero deps)
pip install "distancefyi[cli]"       # + Command-line interface
pip install "distancefyi[mcp]"       # + MCP server for AI assistants
pip install "distancefyi[api]"       # + HTTP client for distancefyi.com API
pip install "distancefyi[all]"       # Everything

Quick Start

from distancefyi import haversine_distance, bearing, midpoint, compute_distance

# Seoul to Tokyo
haversine_distance(37.5665, 126.978, 35.6762, 139.6503)  # 1159 km
bearing(37.5665, 126.978, 35.6762, 139.6503)              # 108.6 degrees
midpoint(37.5665, 126.978, 35.6762, 139.6503)             # (36.82..., 133.36...)

# Full computation with travel times
result = compute_distance(37.5665, 126.978, 35.6762, 139.6503)
result.distance_km          # 1159
result.distance_miles       # 720
result.compass_direction    # "ESE"
result.flight_time_minutes  # 123

Understanding Distance Calculation

The Haversine formula computes the great-circle distance between two points on a sphere. It uses the Earth's mean radius (R = 6,371 km) as a spherical approximation, which introduces a maximum error of about 0.3% compared to the true ellipsoidal distance. For most applications -- route planning, city-to-city comparisons, flight distance estimation -- this is more than sufficient.

Distance Unit Abbreviation Relative to 1 km Common Use
Kilometer km 1.0 Worldwide standard
Mile (statute) mi 0.6214 US, UK road distances
Nautical mile nmi 0.5400 Aviation, maritime navigation
Meter m 1,000 Walking, urban distances
Foot ft 3,280.84 US/UK altitude, short distances
from distancefyi import haversine_distance, km_to_miles, km_to_nautical_miles

# Great-circle distance between New York and London
km = haversine_distance(40.7128, -74.0060, 51.5074, -0.1278)  # NYC to London
miles = km_to_miles(km)                # 3,459 statute miles
nm = km_to_nautical_miles(km)          # 3,005 nautical miles (used in aviation)

For sub-meter precision (surveying, geodesy), you would need Vincenty's formula on the WGS84 ellipsoid, which accounts for the Earth's equatorial bulge. The Haversine formula treats the Earth as a perfect sphere, so it slightly underestimates distances near the equator and overestimates near the poles.

Learn more: Distance Calculator · Browse Cities · Browse Countries

Navigation & Bearing

The initial bearing (forward azimuth) is the compass direction you would face when starting a journey along the great-circle route. Unlike a rhumb line (constant compass bearing), a great-circle route's bearing changes continuously along the path -- this is why flight paths on a Mercator map appear curved.

Compass Direction Abbreviation Degree Range
North N 348.75 -- 11.25
North-Northeast NNE 11.25 -- 33.75
Northeast NE 33.75 -- 56.25
East-Northeast ENE 56.25 -- 78.75
East E 78.75 -- 101.25
East-Southeast ESE 101.25 -- 123.75
Southeast SE 123.75 -- 146.25
South-Southeast SSE 146.25 -- 168.75
South S 168.75 -- 191.25
South-Southwest SSW 191.25 -- 213.75
Southwest SW 213.75 -- 236.25
West-Southwest WSW 236.25 -- 258.75
West W 258.75 -- 281.25
West-Northwest WNW 281.25 -- 303.75
Northwest NW 303.75 -- 326.25
North-Northwest NNW 326.25 -- 348.75
from distancefyi import bearing, compass_direction, great_circle_points, antipodal_point

# Initial bearing from New York to London (great-circle route)
b = bearing(40.7128, -74.0060, 51.5074, -0.1278)  # 51.2 degrees
compass_direction(b)                                 # "NE" (Northeast)

# Generate waypoints along the great-circle arc for route visualization
points = great_circle_points(40.7128, -74.0060, 51.5074, -0.1278, num_points=10)

# Antipodal point -- diametrically opposite location on Earth
lat, lon = antipodal_point(40.7128, -74.0060)  # (-40.7128, 105.994)

The 16-point compass rose divides 360 degrees into directions: N, NNE, NE, ENE, E, ESE, SE, SSE, S, SSW, SW, WSW, W, WNW, NW, NNW. Each sector spans 22.5 degrees.

Learn more: Distance Calculator · City Routes

Travel Time Estimates

Travel time estimates use realistic speed models that account for acceleration, deceleration, rest stops, and real-world conditions rather than simple distance-over-speed division.

Travel Mode Average Speed Includes Best For
Flight 850 km/h cruise Taxi, climb, descent, approach Distances > 300 km
Driving 80 km/h average Rest stops, speed variation 50 -- 2,000 km
Walking 5 km/h Steady pace, no stops < 30 km
Distance Band Flight Time Drive Time Walk Time
500 km ~70 min ~6 h ~4 days
1,000 km ~110 min ~12.5 h ~8 days
5,000 km ~390 min ~62.5 h ~42 days
10,000 km ~740 min ~125 h ~83 days
from distancefyi import estimate_flight_time, estimate_drive_time, estimate_walk_time

# Seoul to Tokyo distance in kilometers
km = 1159

# Realistic flight time with taxi, climb, cruise, and descent phases
estimate_flight_time(km)   # ~123 minutes (cruising at 850 km/h)

# Driving time with average highway speed and rest stops
estimate_drive_time(km)    # ~870 minutes (average 80 km/h)

# Walking time at a steady 5 km/h pace
estimate_walk_time(km)     # ~13,908 minutes

Learn more: Flight Time Calculator · City Distance Routes · Country Distances

Command-Line Interface

pip install "distancefyi[cli]"

distancefyi calc --lat1 37.5665 --lon1 126.978 --lat2 35.6762 --lon2 139.6503
distancefyi bearing --lat1 37.57 --lon1 126.98 --lat2 35.68 --lon2 139.65
distancefyi midpoint --lat1 37.57 --lon1 126.98 --lat2 35.68 --lon2 139.65
distancefyi convert 100 km mi

MCP Server (Claude, Cursor, Windsurf)

Add distance tools to any AI assistant that supports Model Context Protocol.

pip install "distancefyi[mcp]"

Add to your claude_desktop_config.json:

{
    "mcpServers": {
        "distancefyi": {
            "command": "python",
            "args": ["-m", "distancefyi.mcp_server"]
        }
    }
}

Available tools: calculate_distance, get_bearing, get_midpoint, get_flight_time, convert_distance

REST API Client

pip install "distancefyi[api]"
from distancefyi.api import DistanceFYI

with DistanceFYI() as client:
    result = client.distance("seoul", "tokyo")

Full API documentation at distancefyi.com.

API Reference

Core Distance

Function Description
haversine_distance(lat1, lon1, lat2, lon2) -> int Great-circle distance in km
compute_distance(lat1, lon1, lat2, lon2) -> DistanceResult Full computation with all metrics
bearing(lat1, lon1, lat2, lon2) -> float Initial bearing in degrees (0-360)
compass_direction(degrees) -> str 16-point compass abbreviation (e.g., "NE")
compass_direction_full(degrees) -> str Full compass name (e.g., "Northeast")

Midpoint & Great Circle

Function Description
midpoint(lat1, lon1, lat2, lon2) -> tuple[float, float] Geographic midpoint
great_circle_points(lat1, lon1, lat2, lon2, num_points) -> list Waypoints along the arc
antipodal_point(lat, lon) -> tuple[float, float] Diametrically opposite point

Travel Time

Function Description
estimate_flight_time(km) -> int Flight time in minutes
estimate_drive_time(km) -> int Drive time in minutes
estimate_walk_time(km) -> int Walk time in minutes

Unit Conversion & Formatting

Function Description
km_to_miles(km) -> float Kilometers to miles
km_to_nautical_miles(km) -> float Kilometers to nautical miles
miles_to_km(miles) -> float Miles to kilometers
format_distance(km) -> str Human-readable distance string
format_duration(minutes) -> str Human-readable duration string

Features

  • Haversine distance -- great-circle distance in km, miles, nautical miles
  • Bearing -- initial bearing with 16-point compass direction
  • Midpoint -- geographic midpoint between two coordinates
  • Great circle arc -- generate waypoints along the shortest path
  • Antipodal point -- diametrically opposite point on Earth
  • Travel time estimates -- flight, drive, walk time with realistic models
  • Unit conversion -- km, miles, nautical miles
  • Formatting -- human-readable distance and duration strings
  • CLI -- Rich terminal output with distance tables
  • MCP server -- 5 tools for AI assistants (Claude, Cursor, Windsurf)
  • REST API client -- httpx-based client for distancefyi.com API
  • Zero dependencies -- core engine uses only math from stdlib
  • Type-safe -- full type annotations, py.typed marker (PEP 561)

Learn More About Distance

FYIPedia Developer Tools

Part of the FYIPedia open-source developer tools ecosystem.

Package PyPI npm Description
colorfyi PyPI npm Color conversion, WCAG contrast, harmonies -- colorfyi.com
emojifyi PyPI npm Emoji encoding & metadata for 3,781 emojis -- emojifyi.com
symbolfyi PyPI npm Symbol encoding in 11 formats -- symbolfyi.com
unicodefyi PyPI npm Unicode lookup with 17 encodings -- unicodefyi.com
fontfyi PyPI npm Google Fonts metadata & CSS -- fontfyi.com
distancefyi PyPI npm Haversine distance & travel times -- distancefyi.com
timefyi PyPI npm Timezone ops & business hours -- timefyi.com
namefyi PyPI npm Korean romanization & Five Elements -- namefyi.com
unitfyi PyPI npm Unit conversion, 220 units -- unitfyi.com
holidayfyi PyPI npm Holiday dates & Easter calculation -- holidayfyi.com
cocktailfyi PyPI -- Cocktail ABV, calories, flavor -- cocktailfyi.com
fyipedia PyPI -- Unified CLI: fyi color info FF6B35 -- fyipedia.com
fyipedia-mcp PyPI -- Unified MCP hub for AI assistants -- fyipedia.com

License

MIT

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