Part 6

Intro to Programming

9.10.2025

Last Week

• mixed types of items in lists
• matrices
• references
• lists as arguments and return values
• dictionary
• tuple

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Feedback from Part 5

• When to use lists / tuples / dictionaries?
• Why the tests fail even if my exercise works for me: note the "small" differences (print vs. return, print formatting etc.)
• THIS: "On how I can deal with longer complicated tasks, though am getting better by every part." You ARE getting there!
• Problem solving or creating larger programs seems difficult
• Maybe a "cheatsheet" of list and string operations and similar would be nice → this is an excellent idea, I'm going to add it to the TODO list
• Shallow or deep copy → maybe little bit too complicated for this course, but is an important issue e.g. with matrices

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Reading files

Typical action in programs

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Using text files is easy in Python

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Other file formats may be more complicated

Example

Reading file contents

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with-block handles automatic closing of file

Handling files one row at a time

Method read reads the contents of the entire file

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Often, it's easier to read file one row at a time

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This is easy with the for statement

CSV Files

Comma Separated Values

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Several data points in one row, separated with suitable character (i.e. a separator)

Splitting strings

String can be splitted into a list with the split method

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The separator character is provided as an argument

Reading same file several times

File can be read in with-block only once

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Removing extra characters

Reading data from file also returns line feed characters

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Easiest way to get rid of these is to use the strip method

Creating a file

New file can be created by providing character 'w' as the second argument for the open function

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Note, that if file exists, is will be overwritten!

Writing to file

Lines can be written to the file with the write method

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Please note, that the linefeeds must be added manually

Appending data to file

New data can be appended after the existing data in the 'a' file mode

Writing a CSV file

Emptying and removing files

Validating inputs

Typical examples of erroneous input data:

• missing or empty input values in mandatory fields, such as empty strings when the length of the string is critical
• negative values where only positive values are accepted, such as -15 as the amount of an ingredient in a recipe
• missing files or typos in filenames
• values that are too small or too large, for example when working with dates and times
• invalid indexes, such as trying to access index 3 in the string "hey"
• values of a wrong type, such as strings when integers are expected

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Validating input (2)

It's often possible to prepare for erroneous data

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Inputted data can be validate with conditions

Exceptions

Some errors are difficult to check with conditional statements only

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Exceptions are errors that occur during the execution of programs

Preparing for exceptions

Exceptions can be caught with try-except structure

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Typical exceptions

ValueError

TypeError

IndexError

ZeroDivisionError

Exceptions in file handling

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More than one except block

If more than one error may be thrown in the try block, it can be followed with more than one except block

Undefined exception

All possible exceptions can be caught by not defining the exception in the except block

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Note, that this also catches the errors made by the programmer

Passing exceptions

Exception thrown in a function is passed back to the caller of the function

Throwing exceptions

Exception can be thrown manually with keyword raise

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This is a good method for handling e.g. invalid parameters in functions

Local variables

Variables defined in functions are only visible inside functions

Keyword global

Variables defined in the main program can be used inside functions with keyword global

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This is, in general, a bad idea. Instead of side effects, the functions should return a value

Next week

Modules

Random

Handling times and dates

More file handling

Own modules

More about Python's features

Few words about the exam