Create different DBs for each table
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cbc1c08350
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@ -1,3 +1,4 @@
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DB_NAME = "igdb"
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DB_NAME = "igdb"
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DB_USER = "igdb"
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DB_USER = "igdb"
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DB_PW = "agentorange"
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DB_PW = "agentorange"
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ADMIN_PW = "fuckmonsanto"
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@ -76,10 +76,14 @@ class Annual_Change(db.Model):
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class User(db.Model):
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class User(db.Model):
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uid = db.Column(db.Integer, primary_key=True)
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uid = db.Column(db.Integer, primary_key=True)
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registration_date = db.Column(db.DateTime, nullable=False)
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registration_date = db.Column(db.DateTime, nullable=False)
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username = db.Column(db.String(20), nullable=False, unique=True)
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password = db.Column(db.String(60))
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def __init__(self, uid):
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def __init__(self, uid, username, password):
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self.uid = uid
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self.uid = uid
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self.registration_date = datetime.today()
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self.registration_date = datetime.today()
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self.username = username
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self.password = password
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def create_tables():
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def create_tables():
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@ -1,6 +1,7 @@
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from iso3166 import countries as co
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from iso3166 import countries as co
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from pandas import DataFrame, concat, read_csv
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from pandas import DataFrame, concat, read_csv
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from csv import QUOTE_NONNUMERIC
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from csv import QUOTE_NONNUMERIC
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from constants import ADMIN_PW
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def country_conversion(political_unit) -> str:
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def country_conversion(political_unit) -> str:
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@ -12,6 +13,7 @@ def select_columns() -> DataFrame:
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min_year = 2010
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min_year = 2010
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fields = [
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fields = [
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"POLITICAL_UNIT",
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"POLITICAL_UNIT",
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"NAME",
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"WGMS_ID",
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"WGMS_ID",
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"YEAR",
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"YEAR",
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"AREA_SURVEY_YEAR",
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"AREA_SURVEY_YEAR",
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@ -31,10 +33,29 @@ def select_columns() -> DataFrame:
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return data
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return data
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def create_databases(df):
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users = {"UID": [7843], "USERNAME": ["admin"], "PASSWORD": [ADMIN_PW]}
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files = {
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"glacier": "../data/glacier.csv",
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"annual_data": "../data/annual_data.csv",
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"annual_change": "../data/annual_change.csv",
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"users": "../data/users.csv",
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}
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dataframes = {
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"glacier": df[["POLITICAL_UNIT", "NAME", "WGMS_ID"]].drop_duplicates(),
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"annual_data": df[["WGMS_ID", "YEAR", "AREA_SURVEY_YEAR"]],
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"annual_change": df[
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["WGMS_ID", "YEAR", "AREA_CHANGE", "THICKNESS_CHG", "VOLUME_CHANGE"]
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],
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"users": DataFrame(users),
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}
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for key, val in dataframes.items():
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val.to_csv(files[key], index=False, quoting=QUOTE_NONNUMERIC)
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def main():
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def main():
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df = select_columns()
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df = select_columns()
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database = "../data/igdb.csv"
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create_databases(df)
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df.to_csv(database, index=False, quoting=QUOTE_NONNUMERIC)
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if __name__ == "__main__":
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if __name__ == "__main__":
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@ -0,0 +1,22 @@
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from db_setup import create_connection
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from pandas import DataFrame, read_csv, to_sql
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def create_dataframe() -> DataFrame:
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csv_file = "../data/igdb.csv"
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df = read_csv(csv_file)
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return df
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def insert_data(df, conn):
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df.to_sql("glacier", con=conn, if_exists="replace", index=False)
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def main():
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conn = create_connection()
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df = create_dataframe()
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insert_data(df, conn)
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if __name__ == "__main__":
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main()
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@ -0,0 +1,2 @@
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"UID","USERNAME","PASSWORD"
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7843,"admin","fuckmonsanto"
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@ -39,6 +39,8 @@ datos relevantes para estudios acerca del cambio climático, y acotando éstos a
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4. *RD4*: Datos del administrador
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4. *RD4*: Datos del administrador
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- ID - /Entero de 4 dígitos/
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- ID - /Entero de 4 dígitos/
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- Fecha de alta - /Fecha en formato dd-mm-yyyy/
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- Fecha de alta - /Fecha en formato dd-mm-yyyy/
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- Nombre de usuario - /Cadena de 20 caracteres máximo/
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- Contraseña - /Cadena de 60 caracteres máximo/
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*** Funcionales
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*** Funcionales
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