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{
"cells": [
{
"cell_type": "code",
"execution_count": 10,
"id": "b7d2515e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Successfully loaded in libraries\n"
]
}
],
"source": [
"import fastf1\n",
"import pandas as pd\n",
"from urllib.request import urlopen\n",
"from pprint import pprint\n",
"from utils.parser_utils import parse_event_info, parse_season_calendar\n",
"import json\n",
"print(\"Successfully loaded in libraries\")"
]
},
{
"cell_type": "markdown",
"id": "81c06a3f",
"metadata": {},
"source": [
"# FastF1"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "352270a0",
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"core INFO \tLoading data for Japanese Grand Prix - Race [v3.5.3]\n",
"req INFO \tUsing cached data for session_info\n",
"req INFO \tUsing cached data for driver_info\n",
"req INFO \tUsing cached data for session_status_data\n",
"req INFO \tUsing cached data for lap_count\n",
"req INFO \tUsing cached data for track_status_data\n",
"req INFO \tUsing cached data for _extended_timing_data\n",
"req INFO \tUsing cached data for timing_app_data\n",
"core INFO \tProcessing timing data...\n",
"req INFO \tUsing cached data for weather_data\n",
"req INFO \tUsing cached data for race_control_messages\n",
"core INFO \tFinished loading data for 20 drivers: ['1', '4', '81', '16', '63', '12', '44', '6', '23', '87', '14', '22', '10', '55', '7', '27', '30', '31', '5', '18']\n",
"data WARNING \tFailed to generate marker distance information: telemetry data has not been loaded\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"CircuitInfo(corners= X Y Number Letter Angle Distance\n",
"0 5954.595977 -6043.797284 1 -359.859187 NaN\n",
"1 5411.746105 -6985.870033 2 -81.205284 NaN\n",
"2 3770.348048 -5370.929541 3 -131.304090 NaN\n",
"3 2554.616588 -4969.478669 4 -304.343564 NaN\n",
"4 1863.122660 -3634.685488 5 -131.398389 NaN\n",
"5 343.857125 -3137.336941 6 -311.879680 NaN\n",
"6 -615.746076 -519.819724 7 -106.459045 NaN\n",
"7 -3936.654450 -2323.145349 8 -57.888888 NaN\n",
"8 -5453.049412 -2538.215879 9 -110.431844 NaN\n",
"9 -6229.209841 449.908978 10 -1.787031 NaN\n",
"10 -5964.645828 1876.742727 11 -126.423013 NaN\n",
"11 -7552.525448 119.000613 12 -237.277364 NaN\n",
"12 -12335.806433 3018.433431 13 -125.951757 NaN\n",
"13 -13731.830146 2733.425582 14 -201.694648 NaN\n",
"14 -4974.205293 -1679.808731 15 -254.712390 NaN\n",
"15 -1819.327067 517.589808 16 -293.925016 NaN\n",
"16 -1184.012753 429.700268 17 -50.270393 NaN\n",
"17 332.706500 616.534453 18 -291.606210 NaN,\n",
" marshal_lights= X Y Number Letter Angle Distance\n",
"0 1690.855950 -638.228799 1 -319.688225 NaN\n",
"1 5783.596809 -5462.065134 2 -326.487422 NaN\n",
"2 4811.098103 -6861.098123 3 -135.071247 NaN\n",
"3 3613.521255 -5257.354862 4 -300.361781 NaN\n",
"4 1815.810860 -3592.898831 5 -297.867821 NaN\n",
"5 198.335929 -2984.219502 6 -140.707699 NaN\n",
"6 298.955074 -1117.388942 7 -335.948534 NaN\n",
"7 -1697.196338 -420.240677 8 -260.369093 NaN\n",
"8 -4279.213479 -2448.991996 9 -80.383553 NaN\n",
"9 -5705.360349 -2278.848846 10 -161.756206 NaN\n",
"10 -6223.720506 612.148266 11 -2.135760 NaN\n",
"11 -6037.625361 1929.727809 12 -295.371985 NaN\n",
"12 -7620.649284 74.874949 13 -58.450233 NaN\n",
"13 -10755.257143 583.334425 14 -126.874237 NaN\n",
"14 -12499.786963 3090.369959 15 -289.937350 NaN\n",
"15 -13787.721653 2369.387645 16 -170.487671 NaN\n",
"16 -12375.140308 938.000955 17 -122.280757 NaN\n",
"17 -10189.779019 -164.943254 18 -109.977438 NaN\n",
"18 -7499.143789 -1076.181403 19 -109.130546 NaN\n",
"19 -4733.288295 -1590.501071 20 -68.544674 NaN\n",
"20 -1984.075069 530.759537 21 -258.330855 NaN\n",
"21 -86.348618 755.041276 22 -284.607743 NaN,\n",
" marshal_sectors= X Y Number Letter Angle Distance\n",
"0 1749.509891 -706.732882 1 -319.461645 NaN\n",
"1 5890.822450 -5655.136054 2 -343.938801 NaN\n",
"2 4982.553266 -6958.944675 3 -107.988939 NaN\n",
"3 3770.348048 -5370.929541 4 -131.463504 NaN\n",
"4 1886.764195 -3655.599156 5 -311.621063 NaN\n",
"5 353.981975 -3146.309291 6 -311.728322 NaN\n",
"6 344.825980 -1220.364548 7 -337.684641 NaN\n",
"7 -1536.171947 -402.081185 8 -268.084725 NaN\n",
"8 -4239.222910 -2442.075986 9 -80.307903 NaN\n",
"9 -5607.722824 -2440.304958 10 -137.786652 NaN\n",
"10 -6229.209841 449.908978 11 -2.314662 NaN\n",
"11 -6082.609487 1931.331580 12 -271.786528 NaN\n",
"12 -7563.880972 111.645273 13 -237.193746 NaN\n",
"13 -10809.400279 623.878159 14 -306.809173 NaN\n",
"14 -12457.333265 3075.178205 15 -289.922395 NaN\n",
"15 -13782.934850 2342.759685 16 -169.348189 NaN\n",
"16 -12386.562623 945.247835 17 -122.394556 NaN\n",
"17 -10177.060736 -169.562715 18 -109.850944 NaN\n",
"18 -7417.936277 -1103.488715 19 -108.299236 NaN\n",
"19 -4779.517092 -1608.478900 20 -68.926520 NaN\n",
"20 -1948.165854 534.110177 21 -85.058804 NaN\n",
"21 53.048886 717.912969 22 -289.674903 NaN,\n",
" rotation=49.0)\n"
]
}
],
"source": [
"session = fastf1.get_session(2025, 3, \"R\")\n",
"session.load(telemetry=False)\n",
"circuit_info = session.get_circuit_info()\n",
"pprint(circuit_info)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "hackaton",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.9"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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