The topics from the previous lessons are enough to require many months of intensive training, but even they don't reflect everything about Python development. In this lesson, we'll briefly cover some other important aspects.
Big Data Analysis
People often use Python for:
- Big data analysis
- Machine learning
- Neural networks
- Statistical calculations
- Computer Vision
- OpenCV
- Natural Language Processing
Creating user interaction interfaces
Many Python programs provide a GUI (Graphical User Interface). Other programs communicate with users by voice through voice assistants or by text through chatbots. Organizing human-machine interaction is a booming industry with its techniques, laws, and scientific foundations. And this industry is essential because a program only succeeds if it satisfies its users.
Infrastructure
Adding features is only half the battle. To develop applications, you have to:
- First, set up the developer environment using Docker Compose
- After development, the application needs to be uploaded somewhere. To do this, you need to set up a production environment, the one where the site will run
- Once we have done it, we need to deploy the site in production
Modern infrastructure is code, so it needs to be programmed. Here is a list of the most significant programs for this purpose:
- Ansible
- Terraform
- Docker
Operation
Any working site needs maintenance. Problems can arise from anywhere, disk space might have run out, there may have been a network failure, or there is an error in the operation logic that occurs only with specific input data.
You should find out about all this as early as possible. Operating software involves many things, including monitoring, setting up alerts, collecting logs, and using other tools. We recommend two resources to start exploring this topic: DataDog and Rollbar.
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