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Creating a SQLite database from CSV with Python
In today's data-driven world, having efficient ways to handle data is essential, and SQLite is one of the best solutions for small-scale database systems. SQLite is a popular relational database system, that is easy to use, lightweight, and scalable.
One way to store data in SQLite, is to store it in CSV format. This allows us to store structured data in flat files, which can be easily parsed with the help of Python. In this tutorial, we will learn how to create a SQLite database from CSV files, using Python.
What is a SQLite Database?
SQLite is a software library that provides a relational database management system (RDBMS) that stores data in a self-contained, serverless, zero-configuration, transactional SQL database engine. It is a lightweight, file-based database that is widely used in embedded systems and mobile applications.
A SQLite database is a file-based database that stores data in a structured way, using tables with rows and columns. SQLite databases are self-contained, meaning they do not require a separate server or process to run, and they can be accessed directly by applications.
SQLite is popular because it is easy to set up, requires minimal resources, and supports standard SQL syntax for querying and manipulating data. It is also highly reliable and provides ACID (Atomicity, Consistency, Isolation, Durability) transactions, which ensure that data is always consistent and accurate.
SQLite databases are commonly used in mobile applications, web browsers, desktop software, and other applications that require a small, local database. They are also used in embedded systems and other devices with limited resources, due to their low memory and storage requirements.
Overall, SQLite provides a simple, yet powerful way to store and manage data, making it a popular choice for many developers and applications.
Step 1: Importing Required Modules
We use Python's built-in `sqlite3` module to interact with the SQLite database. In addition, we also use the `csv` module to read the data from the CSV files. To import these modules, run the following code snippet −
Step 2: Creating a Connection
o interact with the SQLite database, we first need to create a connection. The `connect()` method from the `sqlite3` module is used to create a connection to the database. We can also specify a path to the database file.
# creating a connection to the database conn = sqlite3.connect('database.db')
Step 3: Creating a Cursor
A cursor is used to execute SQL queries and fetch data from the database. We can retrieve a cursor object from the connection object using the `cursor()` method.
creating a cursor object cur = conn.cursor()
Step 4: Reading Data from CSV Files
Next, we need to read the data from the CSV file. We can use Python's built-in `csv` module to read the data from the CSV file.
# reading data from the CSV file with open('data.csv') as f: reader = csv.reader(f) data = list(reader)
Step 5: Creating a Table
Before we can insert data into the database, we need to create a table that will hold the data. We can use the `CREATE TABLE` statement to create a table.
# creating a table cur.execute('''CREATE TABLE table_name ( column1_name data_type, column2_name data_type, ... )''')
Step 6: Inserting Data into the Table
Once we have created the table, we can insert data into it. We can use the `INSERT INTO` statement to insert data into the table.
# inserting data into the table for row in data: cur.execute("INSERT INTO table_name (column1_name, column2_name, ...) values (?, ?, ...)", row)
Step 7: Committing Changes
Once we have inserted all the data, we need to commit it to the database.
committing changes conn.commit()
Step 8: Closing the Connection
Finally, we need to close the connection to the database.
closing the connection conn.close()
In this tutorial, we have learned how to create a SQLite database from CSV files, using Python. We have covered the following steps −
Importing Required Modules: The first step is to import the required modules for working with SQLite database in Python.
Creating a Connection: After importing the modules, a connection needs to be established with the database. This connection is used to communicate with the database.
Creating a Cursor: A cursor is created to execute SQL queries and fetch data from the database.
Reading Data from CSV Files: If the data is not already in the database, it needs to be read from a CSV file or other sources.
Creating a Table: A table needs to be created in the database to store the data.
Inserting Data into the Table: The data is inserted into the table using SQL insert statements.
Committing Changes: Once the data is inserted, the changes need to be committed to the database.
Closing the Connection: Finally, the connection to the database is closed to ensure that resources are freed up and to prevent any further communication with the database.
By following these steps, we can easily create SQLite databases from CSV files, and efficiently handle our data.
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