Empire State Run Up
Hello. I wrote an application to analyse the results of the 'Empire State Run Up', 2013 edition, after I ran the race.
Here you will find my code.
If you just want to install it
See the previous section called 'Packaging', and then install it on your virtual environment:
uv build
uv pip install dist/empirestaterunup-2025.1.2-py3-none-any.whl
There are 4 scripts that you can run:
- esru_numbers
- esru_outlier
- esru_browser
- esru_plot
If you have uvx, you can run any of them like this:
uvx --from EmpireStateRunUp esru_numbers
uvx --from EmpireStateRunUp esru_outlier
uvx --from EmpireStateRunUp esru_browser
uvx --from EmpireStateRunUp esru_plot
If you want to learn more about these programs, please grab a cup of coffe and read the TUTORIAL
If you are a developer
Running the code in developer mode
uv pip install --editable .
uv sync --dev
Modifying the layout without restarting the apps
For example, playing with the 'esru_outlier' application:
. ~/virtualenv/EmpireStateRunUp/bin/activate
pip install textual-dev
# On another terminal: . ~/virtualenv/EmpireStateRunUp/bin/activate && textual console
textual run --dev empirestaterunup.apps:run_outlier
Packaging
uv build
Installation from PiPy
For your user:
uv pip install EmpireStateRunUp
Country codes
I used the files generated by the ISO-3166-Countries-with-Regional-Codes for the flag lookup, using Regional indicator symbol.
Notes: Data from the 2025 race is full of errors. Whoever entered the data decided than things like not populating the country of origin was correct:
{"name": "Alessandro Manrique", "bib": "377", "age": 20, "country": "US", "locality": "Mexico", "gender": "M", "state": "Wisconsin", "racer_has_finished": true, "split_data": [{"name": "Full Course", "number": 1, "time_ms": 1077000, "distanc e_m": 320, "time_with_penalties_ms": 1077000, "gun_time_ms": {"timeInMillis": 2769000, "timeUnit": "m"}, "interval_full": true}, {"name": "20th Floor", "number": 2, "time_ms": 209000, "distance_m": 61, "time_with_penalties_ms": 209000, "gun_ time_ms": {"timeInMillis": 1900000, "timeUnit": "m"}, "interval_full": false}, {"name": "65th Floor", "number": 3, "time_ms": 785000, "distance_m": 229, "time_with_penalties_ms": 785000, "gun_time_ms": {"timeInMillis": 2476000, "timeUnit": " m"}, "interval_full": false}]}
I did not want to spend an long time fixing this, so first extracted all localities with some jq magic:
jq -r '[.locality | ascii_downcase]|.[]' empirestaterunup/results-2025.jsonl|sort -u
albany
albuquerque
alexandria
altamonte
ames
angier
armonk
astoria
athens
aventura
albany
albuquerque
alexandria
altamonte
ames
angier
armonk
astoria
athens
aventura
...
Next, using an AI LLM, I tried to use a reverse lookup of the country 2 letter ISO code with the locality, all in lowercase. Then wrote a small script to "fix" the country from the original dowloaded race results. For ambiguous locations I assumed the country was US, as the majority of racers from 2023-2024 where from this country.
[berkeley]
alpha-2 = "US"
[berlin]
alpha-2 = "DE"
[bethel]
alpha-2 = "US"
[bilbao]
alpha-2 = "ES"
Tutorial
Make sure you check the tutorial. It explains how this project got started, as well showcases features of the applications.
Running in server mode
The applications now support running in web server mode. To enable:
(EmpireStateRunUp) [josevnz@dmaf5 EmpireStateRunUp]$ esru_server --help
usage: esru_server [-h] --application {esru_numbers,esru_outlier,esru_browser} [--port PORT] [--debug] [results ...]
Browse user results
positional arguments:
results Race results.
options:
-h, --help show this help message and exit
--application {esru_numbers,esru_outlier,esru_browser}
Applications that can run in server mode: ['esru_numbers', 'esru_outlier', 'esru_browser']
--port PORT Default port (8000)
--debug Enable debug mode
esru_server --application esru_numbers
# Or if you have an external results file:
sru_server --application esru_browser empirestaterunup/results-2023.jsonl
Getting latest race results
I used athlinks-races to parse the race results. This is an example of a scrapping session:
uvx --from athlinks_races athlinks_races_cli --metadata_rpt /home/josevnz/EmpireStateBuildingRunUp/empirestaterunup/metadata-2025.json --athletes_rpt /home/josevnz/EmpireStateBuildingRunUp/empirestaterunup/results-2025.jsonl --format jsonlines --race_url https://www.athlinks.com/event/382111/results/Event/1124263/Results
uvx --from athlinks_races athlinks_races_cli --metadata_rpt /home/josevnz/EmpireStateBuildingRunUp/empirestaterunup/metadata-2024.json --athletes_rpt /home/josevnz/EmpireStateBuildingRunUp/empirestaterunup/results-2024.jsonl --format jsonlines --race_url https://www.athlinks.com/event/382111/results/Event/1093108/Results
uvx --from athlinks_races athlinks_races_cli --metadata_rpt /home/josevnz/EmpireStateBuildingRunUp/empirestaterunup/metadata-2023.json --athletes_rpt /home/josevnz/EmpireStateBuildingRunUp/empirestaterunup/results-2023.jsonl --format jsonlines --race_url https://www.athlinks.com/event/382111/results/Event/1062909/Results
Metadata
Release files for EmpireStateRunUp 2025.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| empirestaterunup-2025.1.2.tar.gz | 994.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| empirestaterunup-2025.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 2.0 MB
Release files / empirestaterunup-2025.1.2.tar.gz
| Download URL | empirestaterunup-2025.1.2.tar.gz |
|---|---|
| Size | 994.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
394e470e5a6e3ed541d845cb7e39cbd4b0e8d9167ad4c442ed9b3b0bb0091e39
|
|
BLAKE2b-256 checksum How to use checksums |
5ad286c3d08514a24269fd29730b421fa84fc6f376843ad57ec6c72ab81c2572
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 26, 2026.
Transparency logRelease files / empirestaterunup-2025.1.2-py3-none-any.whl
| Download URL | empirestaterunup-2025.1.2-py3-none-any.whl |
|---|---|
| Size | 994.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
73269037fd36fe02270623dd2a19e99e8c317d259c2f994533350a14562f7fe5
|
|
BLAKE2b-256 checksum How to use checksums |
b33fe223e76dbd4498c7aea1dfd425638f308b3cfbc0d66b4eaa2de92b2a5231
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 26, 2026.
Transparency log