Welcome to our new Python PostgreSQL management tutorial! If you often find yourself intrigued by the power and versatility of Python or fascinated by how PostgreSQL efficiently manages data in RDBMS, wait until you see them working together!
Table of contents
What is Python PostgreSQL Management?
Python PostgreSQL Management is all about leveraging Python’s prowess in handling tasks in PostgreSQL. PostgreSQL is a powerful, open-source object-relational database system that uses and extends the SQL language combined with many features to safely store and scale complicated data workloads.
Why Should You Learn It?
Combining Python with PostgreSQL opens a world of data management and analytics possibilities. Python acts like a Swiss army knife, handling data manipulation, while PostgreSQL serves as a robust storage system. Together, they offer an excellent approach for simplifying complex data-related tasks, everything from web services to data mining.
What it Offers?
In the world of Big Data, where data is king, Python’s simple syntax and vast library ecosystem makes it a great language for data manipulation. On the other hand, PostgreSQL’s capabilities, such as full ACID compliance and MVCC support, make it ideal for complex data management tasks. This is a compelling combo for anyone from absolute beginners to experienced pythonistas.
Part 2: Starting With Python and PostgreSQL
To work with PostgreSQL, we need to install the ‘psycopg2’ module. It’s PostgreSQL’s most popular Python adapter and delivers many Python-friendly features.
pip install psycopg2
Once installed, we can proceed to establish a connection with a PostgreSQL:
import psycopg2 try: connection = psycopg2.connect(user = "your_user", password = "your_password", host = "127.0.0.1", port = "5432", database = "your_database") cursor = connection.cursor() # Print PostgreSQL Connection properties print ( connection.get_dsn_parameters(),"\n") except (Exception, psycopg2.Error) as error : print ("Error while connecting to PostgreSQL", error)
With a successful connection, we can execute queries. Let’s create a new table named “students”:
cursor.execute("CREATE TABLE students (id INT PRIMARY KEY NOT NULL,name TEXT NOT NULL,class TEXT NOT NULL,age INT NOT NULL);")
To view the ‘students’ table structure we have just created:
cursor.execute("SELECT column_name, data_type FROM information_schema.columns \ WHERE table_name = 'students';") print("Column details: ") column_details = cursor.fetchall() for row in column_details: print(" ", row, "of type", row)
Part 3: More on Python PostgreSQL Management
Next, we’ll demonstrate inserting data into the ‘students’ table.
cursor.execute("INSERT INTO students (ID,NAME,CLASS,AGE) \ VALUES (1, 'Raju', 'V', 9)") connection.commit()
To select data from the ‘students’ table:
cursor.execute("SELECT * from students") rows = cursor.fetchall() for row in rows: print (" ", row, row, row, row)
To update entries in the ‘students’ table:
cursor.execute("UPDATE students set AGE = 10 where ID = 1") connection.commit()
Finally, remember to close database connection once your work completes:
cursor.close() connection.close() print("PostgreSQL connection is closed")
Through these examples, it’s clear how Python can make PostgreSQL management simpler and more accessible to those familiar with Python and seeking to leverage PostgreSQL’s advanced features.
Part 3: Advanced Python PostgreSQL Management
Python, combined with psycopg2, allows us to delivere more sophisticated operations on PostgreSQL. Let’s delve into some of these in detail.
Just as we can add and update entries, we can also delete them using the DELETE FROM command.
cursor.execute("DELETE from students WHERE id = 1;") connection.commit()
Select with Conditions
We can select specific datasets from our database with some conditions using the WHERE clause.
cursor.execute("SELECT * from students WHERE age > 10") rows = cursor.fetchall() for row in rows: print (" ", row, row, row, row)
The ORDER BY keyword sorts the records in ascending or descending order based on one or more columns.
cursor.execute("SELECT * from students ORDER BY age") rows = cursor.fetchall() for row in rows: print (" ", row, row, row, row)
Grouping records in PostgreSQL can be done by “GROUP BY” statement, it allows us to arrange similar data into groups. Let’s group our students based on their class.
cursor.execute("SELECT COUNT(*), class FROM students GROUP BY class") rows = cursor.fetchall() for row in rows: print (row, "students in class", row)
We can also join hard-coded data with our current students data.
cursor.execute( """ SELECT students.id, students.name, students.age, static_data.phone FROM students INNER JOIN ( VALUES (1, '555-1212'), (2, '555-2323') ) AS static_data (id, phone) ON students.id = static_data.id """ ) rows = cursor.fetchall() for row in rows: print(row, row, row, row)
In the same way, you can join different tables in your PostgreSQL database. This shows how powerful the combination of Python and PostgreSQL can be when working with data at any scale.
Be sure to close the database connection after you’re done:
cursor.close() connection.close() print("PostgreSQL connection is closed")
With these advanced Python PostgreSQL management features, you have the tools to dive in and start building complex database applications with flexibility, ease, and reliability. These are just a starting point – your imagination is the limit!
Part 4: Where to go next?
By now, you should have a basic understanding of how to manage PostgreSQL databases with Python. But don’t stop here! The beauty of programming and data management lies in the depth and breadth of concepts and practices to explore.
Our recommendation? Go deeper into Python with us at Zenva. We offer the Python Mini-Degree – a comprehensive collection of courses that teaches Python programming. Python is known for its simple syntax and versatility, making it a must-learn language for aspiring coders and seasoned developers alike.
The Python Mini-Degree will take you beyond PostgreSQL management, shedding light on topics ranging from coding basics and algorithms to object-oriented programming, game development, and app development.
Why choose Zenva? Here’s why:
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Leveraging the flexibility of Python and the robust storage system of PostgreSQL, you’ve begun to unlock your coding abilities and learn how to effectively manage data. This is just the beginning of your Python and PostgreSQL journey, and while this introduction has hopefully made you feel empowered and excited, there is so much more to learn in the incredible world of programming.
Take these newfound skills to the next level and dive deeper into Python with our Python Mini-Degree. Arm yourself with the in-depth knowledge necessary to pursue a career in coding and stand out in today’s technology-driven world. We hope you continue to grow, to learn, and to be inspired by the limitless possibilities that a coding education can offer. Happy learning, and we hope to see you in our courses soon!
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