Different phases of a Python project

Before we discuss the optimal development life cycle, let's start by identifying the different phases of a Python project. Each phase can be thought of as a group of activities that are similar in nature, as illustrated in the following diagram:

Figure 1.2 – Various phases of a Python project

The various phases of a typical Python project are outlined here:

• Requirement analysis: This phase is about collecting the requirements from all key stakeholders and then analyzing them to understand what needs to be done and later think about the how part of it. The stakeholders can be our actual users of the software or business owners. It is important to collect the requirements in as much detail as possible. Wherever possible, requirements should be fully laid out, understood, and discussed with the end user and stakeholders before starting the design and development.

  An important point is to ensure that the requirement-analysis phase should be kept out of the iterative loop of the design, development, and testing phases. Requirement analysis should be fully conducted and complete before moving on to the next phases. The requirements should include both functional requirements (FRs) and non-functional requirements (NFRs). FRs should be grouped into modules. Within each module, the requirements should be numbered in an effort to map them as closely as possible with the code modules.

• Design: Design is our technical response to the requirements as laid out in the requirement phase. In the design phase, we figure out the how part of the equation. It is a creative process where we use our experience and skills to come up with the right set and structure of modules and the interactions between them in the most efficient and optimal way.

  Note that coming up with the right design is an important part of a Python project. Any missteps in the design phase will be much more expensive to correct than missteps in later phases. By some measure, it takes 20 times more effort to change the design and implement the design changes in the subsequent phases (for example, coding phase), as compared to a similar degree of changes if they happen in the coding phase—for example, the inability to correctly identify classes or figure out the right data and compute the dimension of the project will have a major impact as compared to a mistake when implementing a function. Also, because coming up with the right design is a conceptual process, mistakes may not be obvious and cannot be caught by testing. On the other hand, errors in the coding will be caught by a well-thought-out exception-handling system.

  In the design phase, we perform the following activities:

  a) We design the structure of the code and identify the modules within the code.

  b) We decide the fundamental approach and decide whether we should be using functional programming, OOP, or a hybrid approach.

  c) We also identify the classes and functions and choose the names of these higher-level components.

  We also produce higher-level documentation.

• Coding: This is the phase where we will implement the design using Python. We start by implementing the higher-level abstractions, components, and modules identified by the design first, followed by the detailed coding. We will keep a discussion about the coding phase to a minimum in this section as we will discuss it extensively throughout the book.
• Testing: Testing is the process of verifying our code.
• Deployment: Once thoroughly tested, we need to hand over the solution to the end user. The end user should not see the details of our design, coding, or testing. Deployment is the process of providing a solution to the end user that can be used to solve the problem as detailed in the requirements. For example, if we are working to develop a machine learning (ML) project to predict rainfall in Ottawa, the deployment is about figuring out how to provide a usable solution to the end user.

Having understood what the different phases of a project are, we will move on to see how we can strategize the overall process.