Answers for "create sqlite connection python"

create sqlite database python

import sqlite3

conn = sqlite3.connect('TestDB.db')  # You can create a new database by changing the name within the quotes
c = conn.cursor() # The database will be saved in the location where your 'py' file is saved

# Create table - CLIENTS
c.execute('''CREATE TABLE CLIENTS
             ([generated_id] INTEGER PRIMARY KEY,[Client_Name] text, [Country_ID] integer, [Date] date)''')
          
# Create table - COUNTRY
c.execute('''CREATE TABLE COUNTRY
             ([generated_id] INTEGER PRIMARY KEY,[Country_ID] integer, [Country_Name] text)''')
        
# Create table - DAILY_STATUS
c.execute('''CREATE TABLE DAILY_STATUS
             ([Client_Name] text, [Country_Name] text, [Date] date)''')
                 
conn.commit()

# Note that the syntax to create new tables should only be used once in the code (unless you dropped the table/s at the end of the code). 
# The [generated_id] column is used to set an auto-increment ID for each record
# When creating a new table, you can add both the field names as well as the field formats (e.g., Text)

sqlite python connection

import sqlite3

try:
    sqliteConnection = sqlite3.connect('SQLite_Python.db')
    cursor = sqliteConnection.cursor()
    print("Database created and Successfully Connected to SQLite")

    sqlite_select_Query = "select sqlite_version();"
    cursor.execute(sqlite_select_Query)
    record = cursor.fetchall()
    print("SQLite Database Version is: ", record)
    cursor.close()

except sqlite3.Error as error:
    print("Error while connecting to sqlite", error)
finally:
    if (sqliteConnection):
        sqliteConnection.close()
        print("The SQLite connection is closed")

create sqlite database python

import sqlite3
import pandas as pd
from pandas import DataFrame

conn = sqlite3.connect('TestDB.db')  
c = conn.cursor()

read_clients = pd.read_csv (r'C:UsersRonDesktopClientClient_14-JAN-2019.csv')
read_clients.to_sql('CLIENTS', conn, if_exists='append', index = False) # Insert the values from the csv file into the table 'CLIENTS' 

read_country = pd.read_csv (r'C:UsersRonDesktopClientCountry_14-JAN-2019.csv')
read_country.to_sql('COUNTRY', conn, if_exists='replace', index = False) # Replace the values from the csv file into the table 'COUNTRY'

# When reading the csv:
# - Place 'r' before the path string to read any special characters, such as ''
# - Don't forget to put the file name at the end of the path + '.csv'
# - Before running the code, make sure that the column names in the CSV files match with the column names in the tables created and in the query below
# - If needed make sure that all the columns are in a TEXT format

c.execute('''
INSERT INTO DAILY_STATUS (Client_Name,Country_Name,Date)
SELECT DISTINCT clt.Client_Name, ctr.Country_Name, clt.Date
FROM CLIENTS clt
LEFT JOIN COUNTRY ctr ON clt.Country_ID = ctr.Country_ID
          ''')

c.execute('''
SELECT DISTINCT *
FROM DAILY_STATUS
WHERE Date = (SELECT max(Date) FROM DAILY_STATUS)
          ''')
   
#print(c.fetchall())

df = DataFrame(c.fetchall(), columns=['Client_Name','Country_Name','Date'])
print (df) # To display the results after an insert query, you'll need to add this type of syntax above: 'c.execute(''' SELECT * from latest table ''')

df.to_sql('DAILY_STATUS', conn, if_exists='append', index = False) # Insert the values from the INSERT QUERY into the table 'DAILY_STATUS'

# export_csv = df.to_csv (r'C:UsersRonDesktopClientexport_list.csv', index = None, header=True) # Uncomment this syntax if you wish to export the results to CSV. Make sure to adjust the path name
# Don't forget to add '.csv' at the end of the path (as well as r at the beg to address special characters)