In this tutorial, you have learned how to develop a Python program to query data from tables in an SQLite database. Select_all_tasks(conn) Code language: Python ( python )ĭef create_connection (db_file): """ create a database connection to the SQLite databaseĭef select_task_by_priority (conn, priority): """ This main() function creates a connection to the database C:\sqlite\db\pythonsqlite.db and calls the functions to query all rows from the tasks table and select tasks with priority 1: def main ():ĭatabase = r"C:\sqlite\db\pythonsqlite.db" # create a database connection The fetchall() method fetched all matching tasks by the priority. When the cursor executed the SELECT statement, it substituted the question mark ( ?) by the priority argument. The question mark ( ?) in the query is the placeholder. In the select_task_by_priority() function, we selected the tasks based on a particular priority. This function query tasks by priority: def select_task_by_priority (conn, priority): """Ĭur.execute( "SELECT * FROM tasks WHERE priority=?", (priority,)) In the select_all_tasks() function, we created a cursor, executed the SELECT statement, and called the fetchall() to fetch all tasks from the tasks table. Print(row) Code language: Python ( python ) This function selects all rows from the tasks table and displays the data: def select_all_tasks (conn): """ Return conn Code language: Python ( python ) In the following example, we will use the tasks table created in the creating tables tutorial.įirst, create a connection to an SQLite database specified by a file: def create_connection (db_file): """ create a database connection to the SQLite database Finally, loop the cursor and process each row individually.After that, call the fetchall() method of the cursor object to fetch the data.Next, create a Cursor object using the cursor method of the Connection object.First, establish a connection to the SQLite database by creating a Connection object.To query data in an SQLite database from Python, you use these steps: Table.to_csv(os.path.join(csv_path,table_name + '.Summary: in this tutorial, we will show you step by step how to query data in SQLite from Python. Table.to_csv(os.path.join(csv_path,table_name + '.csv'), index_label='index') Print("Parsing CSV File ",i," : ",table_name) Table.to_excel(writer, sheet_name=table_name, index=False) Print("Parsing Excel Sheet ",i," : ",table_name) Table = pd.read_sql_query("SELECT * from %s" % table_name, db) Writer = pd.ExcelWriter(excel_path, engine='xlsxwriter') #for writing to excel(xlsx) we will be needing this! Main_path=os.path.join(external_folder,internal_folder)Įxcel_path=os.path.join(main_path,"Excel_Multiple_Sheets.xlsx") if excel_path=None else excel_pathĬsv_path=main_path if csv_path=None else csv_pathĬursor.execute("SELECT name FROM sqlite_master WHERE type='table' ") Internal_folder="Saved_Dataframes_"+file_name Įxten=os.path.splitext(base_name) #.file_extension Print("Reading database file from location :",dbpath)Įxternal_folder,base_name=os.path.split(os.path.abspath(dbpath))įile_name=os.path.splitext(base_name) #firstname without. In this tutorial, youll learn how to store and retrieve data using Python, SQLite, and SQLAlchemy as well as with flat files. Print("To locate your file, set dbpath=")ĭbpath = find(extension,os.getcwd()) if dbpath=None else dbpath Print("Multiple files found! Selecting the first one found!") Print("Atleast one of the parameters need to be true: csvs or excels") #convert sqlite databases(.db.sqlite) to pandas dataframe(excel with each table as a different sheet or individual csv sheets)ĭef save_db(dbpath=None,excel_path=None,csv_path=None,extension="*.sqlite",csvs=True,excels=True): #finds files in a directory corresponding to a regex query Print("Directory already existed : ", dir) #creates a directory without throwing an error Note: You don't need to know the table names in advance! import os, fnmatch db and creates an excel file out of it with each table as a sheet or makes individual tables into csvs. I wrote a piece of code up that saves tables in a database file such as.
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