projectEli/Database/progress/update.py

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Python
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import sqlite3
import os
import csv
# starting_ids.py
starting_ids = {
"exp": 1,
}
def get_data_type(value):
try:
int(value)
return "INTEGER"
except ValueError:
try:
float(value)
return "REAL"
except ValueError:
return "TEXT"
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# Connect to the SQLite database and delete existing tables
conn = sqlite3.connect("database.db")
cursor = conn.cursor()
# Get a list of CSV files in the "data" directory
data_dir = "data" # Change this to your data directory path
csv_files = [f for f in os.listdir(data_dir) if f.endswith(".csv")]
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# Drop all existing tables except for sqlite_sequence
cursor.execute("PRAGMA foreign_keys = OFF;")
cursor.execute(
"SELECT name FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_sequence';"
)
existing_tables = cursor.fetchall()
for table in existing_tables:
cursor.execute(f"DROP TABLE IF EXISTS {table[0]};")
# Commit the changes to delete existing tables
conn.commit()
# Iterate through CSV files and create new tables
for csv_file in csv_files:
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table_name = os.path.splitext(csv_file)[0]
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# Read the first row of the CSV file to determine the column names
with open(os.path.join(data_dir, csv_file), newline="") as csvfile:
csv_reader = csv.reader(csvfile)
header = next(csv_reader)
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# Read the second row to determine data types
with open(os.path.join(data_dir, csv_file), newline="") as csvfile:
csv_reader = csv.reader(csvfile)
next(csv_reader) # Skip the header row
data_row = next(csv_reader)
data_types = [get_data_type(value) for value in data_row]
# Add a primary key column if needed (replace 'unique_id' with your unique identifier column name)
if "unique_id" in header:
header[header.index("unique_id")] += " PRIMARY KEY"
# Generate the CREATE TABLE statement dynamically based on the column names and data types
create_table_sql = f"CREATE TABLE IF NOT EXISTS {table_name} (\n"
for column_name, data_type in zip(header, data_types):
create_table_sql += f" {column_name} {data_type},\n"
create_table_sql = create_table_sql.rstrip(",\n") + "\n);"
# Execute the CREATE TABLE statement
cursor.execute(create_table_sql)
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# Read and insert data from the CSV file into the table
with open(os.path.join(data_dir, csv_file), newline="") as csvfile:
csv_reader = csv.reader(csvfile)
next(csv_reader) # Skip the header row
for row in csv_reader:
placeholders = ",".join(["?"] * len(row))
insert_sql = f"INSERT INTO {table_name} VALUES ({placeholders});"
cursor.execute(insert_sql, row)
# Commit the changes and close the connection
conn.commit()
conn.close()
# Connect to the SQLite database
conn = sqlite3.connect("database.db")
cursor = conn.cursor()
# Define the directory where the CSV files are located
csv_directory = "data" # Change this to your directory path
# Function to load data from a CSV file into a table
def load_csv_data(csv_path, table_name, cursor, starting_id):
# Delete existing data in the table
delete_query = f"DELETE FROM {table_name}"
cursor.execute(delete_query)
with open(csv_path, newline="") as csvfile:
csv_reader = csv.reader(csvfile)
next(csv_reader) # Skip the header row if it exists in the CSV
for row in csv_reader:
# Exclude the first column (id) from the row
values = row[1:]
placeholders = ", ".join(["?"] * len(values))
insert_query = f"INSERT INTO {table_name} VALUES (?, {placeholders})"
cursor.execute(insert_query, [starting_id] + values)
starting_id += 1
# Get a list of CSV files in the data directory
csv_files = [f for f in os.listdir(csv_directory) if f.endswith(".csv")]
# Loop through the CSV files and load data into respective tables
for csv_file in csv_files:
table_name = os.path.splitext(csv_file)[
0
] # Remove the file extension to get the table name
csv_path = os.path.join(csv_directory, csv_file)
if table_name in starting_ids:
starting_id = starting_ids[table_name]
load_csv_data(csv_path, table_name, cursor, starting_id)
# Commit the changes and close the connection
conn.commit()
conn.close()