Pipfile

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

Pipfile.lock

@@ -1,7 +1,7 @@
 {
     "_meta": {
         "hash": {
-            "sha256": "e9b6a65b58f567612bd972fe4d418a525f8ce074120f1b49939a2a5e73f07ac9"
+            "sha256": "126729a6f98a1153aadb9df0008587107239cbb495b6d44f658c16a275f11a0a"
         },
         "pipfile-spec": 6,
         "requires": {
@@ -18,11 +18,11 @@
     "default": {
         "certifi": {
             "hashes": [
-                "sha256:2e0c7ce7cb5d8f8634ca55d2ba7e6ec2689a2fd6537d8dec1296a477a4910057",
+                "sha256:c1d2ec05395148ee10cf672ffc28cd37ea0ab0d99f9cc74c43e588cbd111b079",
-                "sha256:d747aa5a8b9bbbb1bb8c22bb13e22bd1f18e9796defa16bab421f7f7a317323b"
+                "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": {

data/build_weather.py

@@ -1,75 +1,85 @@
+import pytz
 import requests
 import datetime
+from geopy.geocoders import Nominatim
 
-class Weather:
+def get_timezone(latitude: float, longitude: float):
-    # Example usage (requires OpenWeatherMap API key)
+    geolocator = Nominatim()
-    # Replace 'YOUR_API_KEY' with your actual key from https://openweathermap.org/
+    location = geolocator.reverse(f"{latitude}, {longitude}")
-    def get_weather(self, latitude: float, longitude: float, date_str: str, hour: int) -> dict:
+
-        """
+    if location:
-        Fetches weather data for the specified location and time.
+        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:
+        if response.status_code != 200:
-            latitude (float): Latitude of the location in degrees.
+            return {"error": "Failed to fetch weather", "details": data}
-            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 = [
+        return data
-            "temperature_2m",
+    
-            "relative_humidity_2m",
+    except Exception as e:
-            "dew_point_2m",
+        return {"error": str(e), "details": f"No weather data available for {latitude}, {longitude} on {date_str}"}
-            "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}"}

data/db_connect.py

@@ -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, values)
-        cursor.execute(query, (index,))
         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()

data/sql/build_db.sql

@@ -138,15 +138,20 @@ CREATE TABLE IF NOT EXISTS team_game (
 
 CREATE TABLE IF NOT EXISTS weather (
     game_id INTEGER NOT NULL,
-    temperature SMALLINT,
+    temperature FLOAT,
-    wind_speed FLOAT,
-    air_pressure FLOAT,
     humidity SMALLINT UNSIGNED,
-    uv_index FLOAT,
+    dew_point FLOAT,
-    air_quality TINYINT UNSIGNED,
+    apparent_temperature FLOAT,
-    percipitation_type CHAR(10),
+    air_pressure FLOAT,
-    percipitation_amount FLOAT,
+    wind_speed FLOAT,
-    sky_condition CHAR(20),
+    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,

data/stats_importer.py

@@ -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],
+
+        ]

main.py

@@ -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"
+    #build_db_path = "./data/sql/build_db.sql"
-    fill_parks_path = "./data/sql/prefill_parks.sql"
+    #fill_parks_path = "./data/sql/prefill_parks.sql"
-    fill_teams_path = "./data/sql/prefill_teams.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(build_db_path)
-    db_conn.run_sql_file(fill_parks_path)
+    #db_conn.run_sql_file(fill_parks_path)
-    db_conn.run_sql_file(fill_teams_path)
+    #db_conn.run_sql_file(fill_teams_path)
 
-    imp = Importer(db_conn)
+    #imp = Importer(db_conn)
-    imp.parse_all_data("./data/stats/to_import", "./data/stats/imported/")
+    #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)