Python Resource Pack 7

Python Resource Pack 7

Python Resource Pack 7 is a set of coding challenges designed to support the teaching and learning of the Python programming language.

This pack is designed for those who have some experience of programming in Python, such as completing the exercises in Resource Packs 1 - 6. It is suitable for teaching Python in schools at AS and A Level, for tutors and learners in adult learning classes or for the hobbyist learning at home.

As part of the higher-level learning and exam preparation for which the pack is designed, these challenges necessitate a greater degree of design and coding ability than the challenges in Resource Pack 6. Emphasis is placed on the system life cycle and program documentation by requiring:

• Preparatory design before attempting to code the solution to the challenge.
• Full validation to prevent the wrong type of data or incorrect values from being entered.
• The use of meaningful names for variables, functions and procedures.
• Fully commenting code.
• Full testing (both unsuccessful and successful tests, together with any corrective actions) to be recorded as a part of the solution alongside the code.

The pack is designed to support learning that has previously taken place in the classroom, via self-directed study, or by following tutorials.

The pack contains nine challenges, each consisting of:

• A pdf file with one or more coding challenges and, in some cases, supplementary extension work.
• Fully commented example solutions to the challenge or challenges and any extensions.

The following topics are introduced:

• The // mathematical operator to perform integer division.
• The [:n] string operator to get the leftmost n characters of a string.
• The [-n:] string operator to get the rightmost n characters of a string.
• The re.sub regular expression function.
• The chr() and ord() commands to get a character from an ASCII value.
• The pow() command to calculate powers.
• The math.sqrt() command for calculating square roots.

The challenges are designed so that self-directed research will be required to complete them; they are not a cut-and-paste tutorial.