Advanced Python: Working with Databases

Advanced Python: Working with Databases

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 4h 51m | 1.00 GB


To create functional and useful Python applications, you need a database. Databases allow you to store data from user sessions, track inventory, make recommendations, and more. However, Python is compatible with many options: SQLite, MySQL, and PostgreSQL, among others. Selecting the right database is a skill that advanced developers are expected to master. This course provides an excellent primer, comparing the different types of databases that can be connected through the Python Database API. Instructor Kathryn Hodge teaches the differences between SQLite, MySQL, and PostgreSQL and shows how to use the ORM tool SQLAlchemy to query a database. The final chapters put your knowledge to practical use in two hands-on projects: developing a full-stack application with Python, PostgreSQL, and Flask and creating a data analysis app with pandas and Jupyter Notebook. By the end, you should feel comfortable creating and using databases and be able to decide which Python database is right for you.

Topics include:

  • What is a database?
  • Relational vs. nonrelational databases
  • Creating a SQLite database
  • Editing records in SQLite
  • Creating a MySQL database
  • Encapsulating database operations
  • Creating a PostgreSQL database
  • Interacting with databases using SQLAlchemy
  • Creating a stored procedure
  • Developing full-stack apps with Python and Flask
  • Developing analysis apps with pandas and SQLAlchemy
+ Table of Contents

Introduction
1 Using databases to level up your Python applications
2 What you need to know

Introduction to Databases in Python
3 What is a database
4 Relational databases
5 Non-relational databases
6 Python Database API

Using SQLite in Python
7 What is SQLite
8 Creating an SQLite database
9 Manipulating records in a SQLite database
10 What is SQLAlchemy
11 Setting up a virtual environment for SQLAlchemy
12 Using SQLAlchemy Core with an SQLite database
13 Challenge Create an SQLite database
14 Solution Create an SQLite database

Using MySQL in Python
15 What is MySQL
16 Creating a MySQL database
17 Building tables in a MySQL database
18 Connecting a Python application to a MySQL database
19 Encaspulating database operations to make better applications
20 Developing Pythonic applications with SQLAlchemy ORM
21 Using SQLAlchemy Sessions to transact on a MySQL database
22 Using SQL to import CSV data
23 Leveraging SQLAlchemy and pandas to import CSV data
24 Challenge Create a MySQL database
25 Solution Create a MySQL database

Using PostgreSQL in Python
26 What is PostgreSQL
27 Creating a PostgreSQL database
28 Creating a table in Postgres using Python
29 Inserting data into a Postgres database
30 Interacting with a Postgres database using Python
31 Pythonic Postgres interactions with SQLAlchemy Core
32 Pythonic Postgres interactions with SQLAlchemy ORM
33 Grouping SQL statements with stored procedures
34 Creating a stored procedure in PostgreSQL
35 Using Postgres stored procedures and functions in Python
36 Challenge Create a Postgres database
37 Solution Create a Postgres database

Developing Full-Stack Applications
38 Setting up Flask in a Python application
39 Creating a webpage with Flask
40 Developing additional routes to enhance your application
41 Instantiating a Postgres database using Python
42 Connecting a database to a Pythonic Flask project
43 Feeding data from a database into a Flask application
44 Develop add functionality to a Flask application
45 Challenge Develop delete functionality
46 Solution Develop delete functionality

Developing Analysis Applications
47 Introduction to pandas
48 Setting up pandas and Jupyter Notebook
49 Analyzing data with pandas
50 Integrating SQLAlchemy with pandas

Conclusion
51 Next steps