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1. #Sqlite database python how to
2. #Sqlite database python install
3. #Sqlite database python software
4. #Sqlite database python code

How to Write a SQL Queryįeel free to download the European Soccer Data to your PostgreSQL database. You'll be able to integrate the technologies with ease. The nice thing about Python is that it has libraries for SQLite, MySQL, and PostgreSQL. But because you imported the psycopg library, you now speak a language AWS Redshift can understand. In it of itself, AWS Redshift would not understand the above code.

#Sqlite database python code

You just created a database connection! When you imported the psycopg library, you translated the Python code you wrote above to speak to the PostgreSQL database (AWS Redshift). You'll need to read and use the credentials from your config file: con = nnect(dbname= "db_name", host=config, port = config,user=config, password=config) Now that your Python script can access your JSON config file, you'll want to create a database connection. config_file = open(r"C:\Users\yourname\config.json") The json.load() function reads the JSON file so you can access your database credentials in the next step. Next, you'll want to access your config file. In this instance, the library will enable Python to store the data your SQL query returns into a data frame. The pandas library will enable you to use all of pandas' statistical capabilities for your Python script. We imported JSON because creating a JSON config file is a secure way to store your database credentials. You'll notice we also imported the JSON and pandas libraries. #Library for reading the config file, which is in JSON It's a universal Python library for PostgreSQL databases. First, you'll want to import the psycopg library. Let's take a PostgreSQL database, AWS Redshift, for example. Otherwise, your Python code will be a foreign language to the database you're trying to connect to. These instructions guide your computer on how it can interact with your SQL database. You can import these libraries into your Python script.ĭatabase-specific Python libraries serve as supplemental instructions. Python and SQL databases connect through custom Python libraries. You'll be able to use your Python skills to manipulate data from a SQL database. You won't have to switch between different programming languages.Ĭonnecting Python and a SQL database will also make your data science work more convenient. You'll also be able to communicate between different data sources. Connecting Python to a SQL database will allow you to use Python for its automation capabilities. Perhaps you work in data engineering and you need to build an automated ETL pipeline. In this case, you'd need to connect a SQL database so you can store the data coming from the web application.

As I mentioned earlier, you might be working on a web application. There are many use cases for when someone would want to connect Python to a SQL database. You might be wondering, "why should I care about connecting Python and a SQL database?" You'll be able to write those statements with less latency than what a SQLite database would give you. Longer insert, update, and select statements need a lot of computing power. They'll provide long-term infrastructure and bolster your security.Īnother reason they're great for enterprises is that they can handle high performance activities. If you need to scale fast, MySQL and PostgreSQL are your best bet. That said, given the context of the article, they fit into a similar category.īoth database types are great for enterprise solutions. There are distinct differences between MySQL and PostgreSQL. You won't be able to customize features or add a ton of multi-user functionality. That said, you'll be stuck with limited functionality. The pros are that you can move faster with a SQLite database relative to MySQL and PostgreSQL. If you're creating an MVP or don't need a ton of data storage space, you'll want to go with a SQLite database.

#Sqlite database python install

This means that you don't have to install an extra application or use a separate server to run the database. SQLite is best known for being an integrated database.

The rest of the article will use terms referenced in Sameer's article. If you aren't familiar with relational databases (RDBMS), I suggest you check out Sameer's article on basic RDBMS terminology here. The code will show you how to write a SQL query to pull data from a PostgreSQL database and store the data in a pandas data frame. And I'll end the article with some Python code. I'll explain the key differences of each database and the corresponding use cases. I'll talk about the most popular databases, SQLite, MySQL, and PostgreSQL. In this article I'm going to share with you how Python and the different SQL databases interact. Of the many tools I've used, Python and Structured Query Language (SQL) are two of my favorites.

#Sqlite database python software

Over the years I've had the opportunity to work with different types of software and tools.

One of my greatest joys as a developer is learning how different technologies intersect.