Started adding weather code

This commit is contained in:
2025-07-10 21:09:48 +00:00
parent 7f57befaee
commit 5ba8ae59d6
7 changed files with 197 additions and 111 deletions

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@@ -4,9 +4,11 @@ verify_ssl = true
name = "pypi"
[packages]
numpy = "*"
geopy = "*"
matplotlib = "*"
requests = "2.32"
numpy = "*"
pytz = "*"
requests = "*"
[dev-packages]

36
Pipfile.lock generated
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@@ -1,7 +1,7 @@
{
"_meta": {
"hash": {
"sha256": "e9b6a65b58f567612bd972fe4d418a525f8ce074120f1b49939a2a5e73f07ac9"
"sha256": "126729a6f98a1153aadb9df0008587107239cbb495b6d44f658c16a275f11a0a"
},
"pipfile-spec": 6,
"requires": {
@@ -18,11 +18,11 @@
"default": {
"certifi": {
"hashes": [
"sha256:2e0c7ce7cb5d8f8634ca55d2ba7e6ec2689a2fd6537d8dec1296a477a4910057",
"sha256:d747aa5a8b9bbbb1bb8c22bb13e22bd1f18e9796defa16bab421f7f7a317323b"
"sha256:c1d2ec05395148ee10cf672ffc28cd37ea0ab0d99f9cc74c43e588cbd111b079",
"sha256:d842783a14f8fdd646895ac26f719a061408834473cfc10203f6a575beb15d39"
],
"markers": "python_version >= '3.7'",
"version": "==2025.6.15"
"version": "==2025.7.9"
},
"charset-normalizer": {
"hashes": [
@@ -241,6 +241,22 @@
"markers": "python_version >= '3.9'",
"version": "==4.58.5"
},
"geographiclib": {
"hashes": [
"sha256:6b7225248e45ff7edcee32becc4e0a1504c606ac5ee163a5656d482e0cd38734",
"sha256:f7f41c85dc3e1c2d3d935ec86660dc3b2c848c83e17f9a9e51ba9d5146a15859"
],
"markers": "python_version >= '3.7'",
"version": "==2.0"
},
"geopy": {
"hashes": [
"sha256:50283d8e7ad07d89be5cb027338c6365a32044df3ae2556ad3f52f4840b3d0d1",
"sha256:ae8b4bc5c1131820f4d75fce9d4aaaca0c85189b3aa5d64c3dcaf5e3b7b882a7"
],
"index": "pypi",
"version": "==2.4.1"
},
"idna": {
"hashes": [
"sha256:12f65c9b470abda6dc35cf8e63cc574b1c52b11df2c86030af0ac09b01b13ea9",
@@ -565,9 +581,17 @@
"sha256:37dd54208da7e1cd875388217d5e00ebd4179249f90fb72437e91a35459a0ad3",
"sha256:a8b2bc7bffae282281c8140a97d3aa9c14da0b136dfe83f850eea9a5f7470427"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2'",
"version": "==2.9.0.post0"
},
"pytz": {
"hashes": [
"sha256:360b9e3dbb49a209c21ad61809c7fb453643e048b38924c765813546746e81c3",
"sha256:5ddf76296dd8c44c26eb8f4b6f35488f3ccbf6fbbd7adee0b7262d43f0ec2f00"
],
"index": "pypi",
"version": "==2025.2"
},
"requests": {
"hashes": [
"sha256:27babd3cda2a6d50b30443204ee89830707d396671944c998b5975b031ac2b2c",
@@ -581,7 +605,7 @@
"sha256:4721f391ed90541fddacab5acf947aa0d3dc7d27b2e1e8eda2be8970586c3274",
"sha256:ff70335d468e7eb6ec65b95b99d3a2836546063f63acc5171de367e834932a81"
],
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2, 3.3'",
"markers": "python_version >= '2.7' and python_version not in '3.0, 3.1, 3.2'",
"version": "==1.17.0"
},
"urllib3": {

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@@ -1,75 +1,85 @@
import pytz
import requests
import datetime
from geopy.geocoders import Nominatim
class Weather:
# Example usage (requires OpenWeatherMap API key)
# Replace 'YOUR_API_KEY' with your actual key from https://openweathermap.org/
def get_weather(self, latitude: float, longitude: float, date_str: str, hour: int) -> dict:
"""
Fetches weather data for the specified location and time.
def get_timezone(latitude: float, longitude: float):
geolocator = Nominatim()
location = geolocator.reverse(f"{latitude}, {longitude}")
if location:
for tag in location.raw['address']:
if 'timezone' in tag:
tz_name = tag.split('=')[1]
return pytz.timezone(tz_name)
def get_weather(latitude: float, longitude: float, date_str: str, hour: int) -> dict:
"""
Fetches weather data for the specified location and time.
Args:
latitude (float): Latitude of the location in degrees.
longitude (float): Longitude of the location in degrees.
date_str (str): Date in YYYYMMDD format.
hour (int): Hour (0-23) when you want to know the weather.
Returns:
dict: Dictionary containing temperature, condition, and sunrise/sunset times.
"""
# Convert date string components for API request
date = f"{date_str[:4]}-{date_str[4:6]}-{date_str[6:8]}"
stats_to_get = [
"temperature_2m",
"relative_humidity_2m",
"dew_point_2m",
"apparent_temperature",
"pressure_msl",
"surface_pressure",
"precipitation",
"rain",
"snowfall",
"cloud_cover",
"cloud_cover_low",
"cloud_cover_mid",
"cloud_cover_high",
"shortwave_radiation",
"direct_radiation",
"direct_normal_irradiance",
"diffuse_radiation",
"global_tilted_irradiance",
"sunshine_duration",
"wind_speed_10m",
"wind_speed_100m",
"wind_direction_10m",
"wind_direction_100m",
"wind_gusts_10m",
"et0_fao_evapotranspiration",
"weather_code",
"snow_depth",
"vapour_pressure_deficit",
"soil_temperature_0_to_7cm",
"soil_temperature_7_to_28cm",
"soil_temperature_28_to_100cm",
"soil_temperature_100_to_255cm",
"soil_moisture_0_to_7cm",
"soil_moisture_7_to_28cm",
"soil_moisture_28_to_100cm",
"soil_moisture_100_to_255cm",
]
stats_to_get = ','.join(stats_to_get)
timezone = get_timezone(latitude, longitude)
try:
api_url = f"https://archive-api.open-meteo.com/v1/archive?latitude={latitude}&longitude={longitude}&timezone={timezone}&start_date={date}&end_date={date}&hourly={stats_to_get}"
response = requests.get(api_url)
data = response.json()
Args:
latitude (float): Latitude of the location in degrees.
longitude (float): Longitude of the location in degrees.
date_str (str): Date in YYYYMMDD format.
hour (int): Hour (0-23) when you want to know the weather.
Returns:
dict: Dictionary containing temperature, condition, and sunrise/sunset times.
"""
# Convert date string components for API request
date = f"{date_str[:4]}-{date_str[4:6]}-{date_str[6:8]}"
if response.status_code != 200:
return {"error": "Failed to fetch weather", "details": data}
stats_to_get = [
"temperature_2m",
"relative_humidity_2m",
"dew_point_2m",
"apparent_temperature",
"pressure_msl",
"surface_pressure",
"precipitation",
"rain",
"snowfall",
"cloud_cover",
"cloud_cover_low",
"cloud_cover_mid",
"cloud_cover_high",
"shortwave_radiation",
"direct_radiation",
"direct_normal_irradiance",
"diffuse_radiation",
"global_tilted_irradiance",
"sunshine_duration",
"wind_speed_10m",
"wind_speed_100m",
"wind_direction_10m",
"wind_direction_100m",
"wind_gusts_10m",
"et0_fao_evapotranspiration",
"weather_code",
"snow_depth",
"vapour_pressure_deficit",
"soil_temperature_0_to_7cm",
"soil_temperature_7_to_28cm",
"soil_temperature_28_to_100cm",
"soil_temperature_100_to_255cm",
"soil_moisture_0_to_7cm",
"soil_moisture_7_to_28cm",
"soil_moisture_28_to_100cm",
"soil_moisture_100_to_255cm",
]
stats_to_get = ','.join(stats_to_get)
try:
api_url = f"https://archive-api.open-meteo.com/v1/archive?latitude={latitude}&longitude={longitude}&start_date={date}&end_date={date}&hourly={stats_to_get}"
response = requests.get(api_url)
data = response.json()
if response.status_code != 200:
return {"error": "Failed to fetch weather", "details": data}
return data
except Exception as e:
return {"error": str(e), "details": f"No weather data available for {latitude}, {longitude} on {date_str}"}
return data
except Exception as e:
return {"error": str(e), "details": f"No weather data available for {latitude}, {longitude} on {date_str}"}

View File

@@ -13,17 +13,26 @@ class Database:
cursor.executescript(sql_script_string)
self.db.commit()
def select(self, index):
def select(self, query, values):
# Query the database for the specified index
cursor = self.db.cursor()
query = "SELECT name, address FROM people WHERE id = ?"
cursor.execute(query, (index,))
cursor.execute(query, values)
result = cursor.fetchone()
if result:
return result
else:
return None
def selectall(self, query, values):
# Query the database for the specified index
cursor = self.db.cursor()
cursor.execute(query, values)
result = cursor.fetchall()
if result:
return result
else:
return None
def insert(self, query, values):
# Insert new entry into the database
cursor = self.db.cursor()

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@@ -138,15 +138,20 @@ CREATE TABLE IF NOT EXISTS team_game (
CREATE TABLE IF NOT EXISTS weather (
game_id INTEGER NOT NULL,
temperature SMALLINT,
wind_speed FLOAT,
air_pressure FLOAT,
temperature FLOAT,
humidity SMALLINT UNSIGNED,
uv_index FLOAT,
air_quality TINYINT UNSIGNED,
percipitation_type CHAR(10),
percipitation_amount FLOAT,
sky_condition CHAR(20),
dew_point FLOAT,
apparent_temperature FLOAT,
air_pressure FLOAT,
wind_speed FLOAT,
precipitation FLOAT,
rain FLOAT,
snowfall FLOAT,
cloud_cover SMALLINT UNSIGNED,
wind_speed FLOAT,
wind_direction SMALLINT UNSIGNED,
wind_gusts SMALLINT UNSIGNED,
sun_rise TIME,
sun_set TIME,
moon_phase TINYINT UNSIGNED,

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@@ -2,6 +2,7 @@ import os
import csv
import shutil
from data.db_connect import Database
from data.build_weather import get_weather
class Importer:
def __init__(self, database: Database):
@@ -71,6 +72,19 @@ class Importer:
)
"""
game_data = [
game_stats["date"], game_stats["num-of-game"], game_stats["day-of-week"],
game_stats["length-in-outs"], game_stats["day-night"], game_stats["completion-info"],
game_stats["forfeit"], game_stats["protest"], game_stats["park-id"],
game_stats["attendance"], game_stats["length-in-min"], game_stats["home-plate-ump-id"],
game_stats["home-plate-ump-name"], game_stats["1b-plate-ump-id"], game_stats["1b-plate-ump-name"],
game_stats["2b-plate-ump-id"], game_stats["2b-plate-ump-name"], game_stats["3b-plate-ump-id"],
game_stats["3b-plate-ump-name"], game_stats["lf-plate-ump-id"], game_stats["lf-plate-ump-name"],
game_stats["rf-plate-ump-id"], game_stats["rf-plate-ump-name"],
]
game_id = self.database.insert(insert_game, game_data)
insert_team_game = """
INSERT INTO team_game
(
@@ -124,19 +138,6 @@ class Importer:
)
"""
game_data = [
game_stats["date"], game_stats["num-of-game"], game_stats["day-of-week"],
game_stats["length-in-outs"], game_stats["day-night"], game_stats["completion-info"],
game_stats["forfeit"], game_stats["protest"], game_stats["park-id"],
game_stats["attendance"], game_stats["length-in-min"], game_stats["home-plate-ump-id"],
game_stats["home-plate-ump-name"], game_stats["1b-plate-ump-id"], game_stats["1b-plate-ump-name"],
game_stats["2b-plate-ump-id"], game_stats["2b-plate-ump-name"], game_stats["3b-plate-ump-id"],
game_stats["3b-plate-ump-name"], game_stats["lf-plate-ump-id"], game_stats["lf-plate-ump-name"],
game_stats["rf-plate-ump-id"], game_stats["rf-plate-ump-name"],
]
game_id = self.database.insert(insert_game, game_data)
visiting_team_data = [
game_id, game_stats["visiting-team"], game_stats["visiting-game-num"],
game_stats["visiting-score"], game_stats["visiting-line-scores"], game_stats["visiting-at-bats"],
@@ -189,3 +190,35 @@ class Importer:
self.database.insert(insert_team_game, visiting_team_data)
self.database.insert(insert_team_game, home_team_data)
park_data = self.database.select("SELECT latitude, longitude FROM parks WHERE park_id = ?", (game_stats["park-id"],))
hour = 15 if game_stats["day-night"] == "D" else 19
historic_weather = get_weather(park_data[0], park_data[1], game_stats["date"], hour)
historic_weather = historic_weather["hourly"]
insert_into_weather = """
INSERT INTO weather
(
game_id, temperature, humidity,
dew_point, apparent_temperature, air_pressure,
wind_speed, precipitation, rain,
snowfall, cloud_cover, wind_speed,
wind_direction, wind_gusts, sun_rise,
sin_set, moon_phase
)
VALUES
(
?, ?, ?,
?, ?, ?,
?, ?, ?,
?, ?, ?,
?, ?, ?,
?, ?
)
"""
weather_data = [
game_id, historic_weather["temperature_2m"][hour], historic_weather["relative_humidity_2m"][hour],
]

21
main.py
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@@ -2,7 +2,7 @@ import numpy as np # helps with the math
import matplotlib.pyplot as plt # to plot error during training
from data.db_connect import Database
from data.stats_importer import Importer
from data.build_weather import Weather
from data.build_weather import get_weather
# input data
inputs = np.array([[0, 0, 1, 0],
@@ -59,23 +59,26 @@ class NeuralNetwork:
return prediction
if __name__ == '__main__':
build_db_path = "./data/sql/build_db.sql"
fill_parks_path = "./data/sql/prefill_parks.sql"
fill_teams_path = "./data/sql/prefill_teams.sql"
#build_db_path = "./data/sql/build_db.sql"
#fill_parks_path = "./data/sql/prefill_parks.sql"
#fill_teams_path = "./data/sql/prefill_teams.sql"
db_file = "./database/baseball.db"
db_conn = Database(db_file)
db_conn.run_sql_file(build_db_path)
db_conn.run_sql_file(fill_parks_path)
db_conn.run_sql_file(fill_teams_path)
#db_conn.run_sql_file(build_db_path)
#db_conn.run_sql_file(fill_parks_path)
#db_conn.run_sql_file(fill_teams_path)
imp = Importer(db_conn)
imp.parse_all_data("./data/stats/to_import", "./data/stats/imported/")
#imp = Importer(db_conn)
#imp.parse_all_data("./data/stats/to_import", "./data/stats/imported/")
#we = Weather()
#print(we.get_weather(39.26733000, -76.79831000, "20250706", 12))
park_data = db_conn.select("SELECT latitude, longitude FROM parks WHERE park_id = ? OR park_id = ?", ("ATL03","KAN06",))
print(park_data[0])
else:
# create neural network
NN = NeuralNetwork(inputs, outputs)