Programming language: Rust
License: Apache License 2.0
Tags: Geospatial    
Latest version: v2.0.0

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Rust Reverse Geocoder

A fast reverse geocoder in Rust. Inspired by Python reverse-geocoder.



rrgeo takes a latitude and longitude as input and returns the closest city, country, latitude, and longitude, using a k-d tree to efficiently find the nearest neighbour based on a known list of locations. This can be useful if you need to reverse geocode a large number of coordinates quickly, or just need the rough location of coordinates but don't want the expense or complication of an online reverse geocoder.

This crate is implemented as a library, an Actix REST API, a Warp REST API, and as a command-line utility, thanks to Cargo workspaces.


Command line search

Example usage:

> cargo run -p rrgeo-cmd --release 40 -73
71 ms to load cities.csv
3 ms to build the KdTree
(40.72788, -73.09761): West Sayville New York Suffolk County US

Actix Web Server

Example usage:

cargo run -p rrgeo-actix --release

Navigate to the local web server.

Warp Web Server

Example usage:

cargo run -p rrgeo-warp --release

Navigate to the local web server.


Benchmarked on Intel Core i7 4790K at 4.00GHz.

The core library (measured with criterion):

> cargo bench
Benchmarking search: Warming up for 3.0000 s
Warning: Unable to complete 100 samples in 5.0s. You may wish to increase target time to 11.7s or reduce sample count to 40.
search                  time:   [2.3144 ms 2.3440 ms 2.3760 ms]
                        change: [-3.7824% -1.2338% +1.6347%] (p = 0.36 > 0.05)
                        No change in performance detected.
Found 6 outliers among 100 measurements (6.00%)
  2 (2.00%) high mild
  4 (4.00%) high severe

Served via Actix Web:

> cargo run --release --bin rrgeo-actix
> oha http://localhost:3000/\?lat\=40\&long\=\-73 -z 5sec
  Success rate: 1.0000
  Total:        5.0166 secs
  Slowest:      0.0531 secs
  Fastest:      0.0023 secs
  Average:      0.0166 secs
  Requests/sec: 2985.8853

  Total data:   1.47 MiB
  Size/request: 103.00 B
  Size/sec:     300.34 KiB

Response time histogram:
  0.004 [606]  |■■■■
  0.009 [2031] |■■■■■■■■■■■■■■■
  0.013 [4248] |■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.017 [3815] |■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.022 [2415] |■■■■■■■■■■■■■■■■■■
  0.026 [1097] |■■■■■■■■
  0.030 [542]  |■■■■
  0.035 [130]  |
  0.039 [55]   |
  0.043 [34]   |
  0.048 [6]    |

Latency distribution:
  10% in 0.0092 secs
  25% in 0.0124 secs
  50% in 0.0158 secs
  75% in 0.0206 secs
  90% in 0.0252 secs
  95% in 0.0284 secs
  99% in 0.0347 secs

Details (average, fastest, slowest):
  DNS+dialup:   0.0043 secs, 0.0008 secs, 0.0099 secs
  DNS-lookup:   0.0000 secs, 0.0000 secs, 0.0001 secs

Status code distribution:
  [200] 14979 responses

Served via Warp:

> cargo run --release --bin rrgeo-warp
  Success rate: 1.0000
  Total:        5.0006 secs
  Slowest:      0.2553 secs
  Fastest:      0.0113 secs
  Average:      0.1263 secs
  Requests/sec: 388.9503

  Total data:   275.42 KiB
  Size/request: 145.00 B
  Size/sec:     55.08 KiB

Response time histogram:
  0.022 [9]    |
  0.044 [10]   |
  0.067 [8]    |
  0.089 [9]    |
  0.111 [78]   |■
  0.133 [1793] |■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■
  0.155 [0]    |
  0.177 [0]    |
  0.200 [0]    |
  0.222 [0]    |
  0.244 [38]   |

Latency distribution:
  10% in 0.1229 secs
  25% in 0.1239 secs
  50% in 0.1250 secs
  75% in 0.1266 secs
  90% in 0.1277 secs
  95% in 0.1285 secs
  99% in 0.2504 secs

Details (average, fastest, slowest):
  DNS+dialup:   0.0045 secs, 0.0009 secs, 0.0097 secs
  DNS-lookup:   0.0000 secs, 0.0000 secs, 0.0001 secs

Status code distribution:
  [200] 1945 responses


Below we have comparisons between the Rust, Python and Node.js versions.

Rust Node
Load CSV 61ms 1221ms
Build KdTree 4ms 805ms
Search 1.1ms 0.5ms

Most of the performance differences appear to be in time taken to load the CSV file and create the k-d tree, but not searching the tree. Searching time resembles algorithmic complexity of k-d tree. Python version is partly implemented in C++ meaning it is not a purely Python implementation. (It might be interesting to see how a pure Python version performs.) The Node.js version is pure JavaScript, as in, not using C add-ons.

Rust --release build

     Running `target/release/web`
PT0.062677465S seconds to load cities.csv
PT0.003835230S seconds to build the KdTree
PT0.068904911S seconds to search
PT0.002596743S seconds to search
PT0.002887542S seconds to search

Rust --debug build

     Running `target/debug/web`
PT1.198010357S seconds to load cities.csv
PT0.124435778S seconds to build the KdTree
PT1.401588031S seconds to search
PT0.077837996S seconds to search
PT0.078178297S seconds to search

Python mode 1 (single threaded K-D tree)

➜  reverse-geocoder git:(master) ✗ time python mode1.py
Loading formatted geocoded file...
[{'name': 'Saint Louis Park', 'cc': 'US', 'lon': '-93.34801', 'admin1': 'Minnesota', 'admin2': 'Hennepin County', 'lat': '44.9483'}]

python mode1.py  1.60s user 0.22s system 98% cpu 1.847 total

Python mode 2 (multi threaded K-D tree)

➜  reverse-geocoder git:(master) ✗ time python mode2.py
Loading formatted geocoded file...
[{'name': 'Saint Louis Park', 'cc': 'US', 'lon': '-93.34801', 'admin1': 'Minnesota', 'admin2': 'Hennepin County', 'lat': '44.9483'}]

python mode2.py  2.82s user 0.34s system 142% cpu 2.221 total

nreverse (Node.js version)

load modules: 12.619ms
load cities.csv: 1221.833ms
create kdtree: 805.310ms
search tree: 0.758ms
search tree: 0.086ms
search tree: 0.198ms
search tree: 0.104ms
search tree: 0.031ms
total_heap_size 114mb
total_heap_size_executable 5mb
total_physical_size 112mb
total_available_size 1325mb
used_heap_size 83mb
heap_size_limit 1432mb
malloced_memory 0mb
peak_malloced_memory 4mb
does_zap_garbage 0mb


Licensed under either of

at your option.

*Note that all licence references and agreements mentioned in the rust-reverse-geocoder README section above are relevant to that project's source code only.