This document provides an introduction to a module on Object Oriented Programming in Python. It outlines the lecturer's educational background and research interests. The module aims to teach Python programming and handling large geoscience datasets. Students will learn Python syntax, object-oriented concepts, and apply programming to solve geospatial problems. Assessment includes assignments, exams, and an individual mini project.

1. NDATA SCHOOL OF CLIMATE AND EARTH SCIENCES
EARTH SCIENCES DEPARTMENT
Geo-Information Science
Section
Object Oriented Programming: OBOP 210 – Python
Prepared By
Emmanuel Chinkaka
echinkaka@must.ac.mw

2. First Things First - Introductions
⚫ Bsc Geology, Physics, Chanco, Unima,
⚫ Msc in Geoinfo & Earth Observation, Geological Remote
Sensing & Geophysics, Data Science (Spatial Programming)
⚫ Research focus in Geospatial data, Geodynamics, Tectonic
evolution, Drone Technology and Geological Remote Sensing
and Data Sciences etc
Who is Who?
Emmanuel Chinkaka – Module Lecturer

3. First Things First - Introductions
⚫ Your name,
⚫ Educational background, if you did any post
high school studies
⚫ Your passion and research interest?
⚫ Ambition and career focus?
⚫ What got you interested in Geoinformation
and Earth Observation?
Who is Who?

4. Object Oriented Programming:
OBOP 210
Python Language

5. Module Description
⚫ The module provides a comprehensive
introduction to the use of digital tools
including scripting and handling of ‘Big’ digital
data sets in geological and geoinformation
workflow environment
⚫ The main aim of this module is to give a
general knowledge that allows to create
customized solutions in geodata processing

6. Module Description
⚫ Problem-solving will be a main component of
this module.
⚫ Intended for Earth Scientists, Geologists,
Geophysicists and professionals desiring to
expand their general knowledge in applying
programming skills in studying earth resources.

7. Module Objectives
1) Interpret and compose basic syntax and
semantics of Python language.
2) Understand the concepts of object-orientation.
3) Explain the data types built into the Python
language.
4) Use decisions using if statements and loops.
5) Design and implement programs to solve real-
life geospatial related problems

8. Logistics
⚫ 4 hours/week
⚫ Consultation hours: Tuesday 2- 4pm (Room 59)
⚫ Or make an appointment through email

9. Grading Structure
Grading Structure
Individual
assignments
5% Mid-Semester
Exam
20%
Mini Project 15% Final Exam 60%

10. Week Dates (2019-2020) Topic
1 7 – 11 Oct 19 Introduction to interpreted programming languages >>
setting the environments rights
2 14 – 18 Oct 19 Introduction to Python programming environment
3 21 – 25 Oct 19 Variables, expressions and statements
4 28 Oct – 1 Nov 19 Functions
5 4 – 8 Nov 19 Individual Assignments
6 11 – 15 Nov 19 Conditions and iterations
7 18 – 22 Nov 19 Tutorials
8 25 – 29 Nov 19 Mid-Semester Exam
9 2 – 6 Dec 19 Strings and Lists/Tutorials
10 9 – 13 Dec 19 Dictionaries, Tuples, Files
11 16 – 20 Dec 19 Mid-semester Break
23 Dec 19 – 3 Jan
20
Christmas Break
12 6 – 10 Jan 20 Classes and Objects
13 13 – 17 Jan 20 Introduction to Spatial Programming and Mini
Project
14 20 – 24 Jan 20 Mini Project and Supervision
15 27 – 31 Jan 20 Presentation of Mini Project
16 3 – 7 Feb 20 Study Week
17 10 – 14 Feb 20 End of Semester Exam
18 17 – 21 Feb 20 End of Semester Exam

11. Python Mini Project

12. Introduction to Programming
⚫ The process of creating computer programs is
called programming
⚫ A program is known as a recipe for a computer
⚫ A recipe is a step by step procedure
⚫ In programming terms, this recipe is called an
Algorithm

13. Programming Language
⚫ Instructions for a computer are expressed in a
programming language.
⚫ A programming language is an artificial language
that can be used to control the behavior of a
machine, particularly a computer.

14. Which one?

15. Why Python?
⚫ Python is called a high-level programming
language.
⚫ A high-level programming language is a
programming language that is:
1. more abstract,
2. more easy to use, and
3. more portable across platforms

16. High Vs Low Level Programming
Languages
⚫ High-level languages are closer to humans.
⚫ Low-level languages are closer to machines.
Machine code:
Instructions that a particular processor can
understand and execute.
Humans almost never write programs directly in
machine code!

17. High Vs Low Level Programming
Languages

18. Topic 1
Introduction to interpreted
programming languages
>> setting the
environments rights
Python Programming

19. The way of a Python Program
Interpret:
⚫ To execute a program line by line.
Compile:
⚫ To translate a program for later execution.
Execute (by a computer):
⚫ To carry out the instructions.
Interpreter Vs Complier

20. Different development cycle:
Interpreter Vs Complier

21. Interpreter Vs Complier

22. Python
⚫ Python is usually interpreted.
⚫ Python can also be compiled.
– But this is done in the very last stage.
– To create "ready-for-use" programs.

23. What is a Code?
⚫ The text of a program is called:
- the source code
- the script.
⚫ The compiled text of a program is
called:
- the object code
- the executable
- the byte code