Python Unit 3 Lesson 4: Loop control flow 的 Challenge: Infectious diseases

 import virus

population = 10000

infected = 1

can_catch_virus = population - infected

contacts_per_day = 10

newly_recovered = 0

for day in range(90): # day 從 0 開始，到 89。如果要從 1 開始到 90，就要寫成 range(1,91)。

    # Infected chickens spread the virus to those who haven't already had it.

    if day > 13: # 因為 day 是從 0 起算，所以 13 代表 day 14。

        contacts_per_day = 3

    newly_infected = virus.spread(

        infected, can_catch_virus, population, contacts_per_day

    )

    newly_recovered = virus.recover(infected)

    infected = infected + newly_infected - newly_recovered

    can_catch_virus = can_catch_virus - newly_infected

    print(str(infected) + " chickens infected.")

    if infected == 0 :

        break

print("----------")

print(str(population - can_catch_virus) + " chickens caught the virus.")

Python Unit 3 Lesson 3 - For loops - Challenge: Waiting times

 Challenge

import random

num_cashiers = 1

num_cooks = 2

waiting_to_order = 0

waiting_for_food = 0

num_customers_served = 0

for minutes in range(300):

    # Customers arrive every minute and line up to order.

    waiting_to_order = waiting_to_order + random.randint(0, 6)

    

    # Each cashier can take up to three orders per minute.

    new_orders = min(num_cashiers * 3, waiting_to_order)

    

    # After ordering, customers wait for their food to be made.

    waiting_to_order = waiting_to_order - new_orders

    waiting_for_food = waiting_for_food + new_orders

    # Each cook can make up to 1 food per minute.

    new_food = min(num_cooks*1, waiting_for_food)

    num_customers_served = num_customers_served + new_food

    # After providing food, 

    # the customer moves out of the waiting_for_food state.

    waiting_for_food = waiting_for_food - new_food

    

    print(str(waiting_to_order) + " customers waiting to order.")

    print(str(waiting_for_food) + " customers waiting for food.")

print("The total number of customers served is " + \

      str(num_customers_served) + "!")

Bonus

import random

num_cashiers = 2

num_cooks = 5

waiting_to_order = 0

waiting_for_food = 0

num_customers_served = 0

# from 12-2pm the customer arrival rate ever minute = (3, 6)

for minutes in range(120):

    # Customers arrive every minute and line up to order.

    waiting_to_order = waiting_to_order + random.randint(3, 6)

    

    # Each cashier can take up to three orders per minute.

    new_orders = min(num_cashiers * 3, waiting_to_order)

    

    # After ordering, customers wait for their food to be made.

    waiting_to_order = waiting_to_order - new_orders

    waiting_for_food = waiting_for_food + new_orders

    # Each cook can make up to 1 food per minute.

    new_food = min(num_cooks*1, waiting_for_food)

    num_customers_served = num_customers_served + new_food

    # After providing food, 

    # the customer moves out of the waiting_for_food state.

    waiting_for_food = waiting_for_food - new_food

    

    print(str(waiting_to_order) + " customers waiting to order.")

    print(str(waiting_for_food) + " customers waiting for food.")

# Rearrange the staff

num_cashiers = 1

num_cooks = 2

waiting_to_order = 0

waiting_for_food = 0

print("The total number of customers served is " + \

      str(num_customers_served) + "!")

print("----------------------------")

print("----------------------------")

print("----------------------------")

# from 2-5pm the customer arrival rate ever minute = (0, 3)

for minutes in range(180):

    # Customers arrive every minute and line up to order.

    waiting_to_order = waiting_to_order + random.randint(0, 3)

    

    # Each cashier can take up to three orders per minute.

    new_orders = min(num_cashiers * 3, waiting_to_order)

    

    # After ordering, customers wait for their food to be made.

    waiting_to_order = waiting_to_order - new_orders

    waiting_for_food = waiting_for_food + new_orders

    # Each cook can make up to 1 food per minute.

    new_food = min(num_cooks*1, waiting_for_food)

    num_customers_served = num_customers_served + new_food

    # After providing food, 

    # the customer moves out of the waiting_for_food state.

    waiting_for_food = waiting_for_food - new_food

    

    print(str(waiting_to_order) + " customers waiting to order.")

    print(str(waiting_for_food) + " customers waiting for food.")

print("The total number of customers served is " + \

      str(num_customers_served) + "!")

Python Unit 3 Lesson 2 - While loops - Challenge: Dice rolls

Step 1, 2 

import random

dice_total = 0

i = 1 # for counting while loop

while i <= 10:

    # Roll two six-sided dice.

    first_die = random.randint(1, 6)

    second_die = random.randint(1, 6)

    dice_sum = first_die + second_die

    print("You rolled a " + str(dice_sum) + "!")

    dice_total = dice_total + dice_sum

    i = i + 1

dice_average = dice_total / 10

print("The average of dice roll is " + str(dice_average))

Step 3

import random

experiment_times = int(input("How many times do you want \

to repeat the experiment? "))

dice_total = 0

i = 1 # for counting while loop

while i <= experiment_times:

    # Roll two six-sided dice.

    first_die = random.randint(1, 6)

    second_die = random.randint(1, 6)

    dice_sum = first_die + second_die

    print("You rolled a " + str(dice_sum) + "!")

    dice_total = dice_total + dice_sum

    i = i + 1

dice_average = dice_total / experiment_times

print("The average of dice roll for " + \

      str(experiment_times) + " times is " + str(dice_average))

The Python Tutorial

•  1. Whetting Your Appetite
• 2. Using the Python Interpreter
• 2.1. Invoking the Interpreter
• 2.1.1. Argument Passing
• 2.1.2. Interactive Mode
• 2.2. The Interpreter and Its Environment
• 2.2.1. Source Code Encoding
• 3. An Informal Introduction to Python
• 3.1. Using Python as a Calculator
• 3.1.1. Numbers
• 3.1.2. Strings
• 3.1.3. Lists
• 3.2. First Steps Towards Programming
• 4. More Control Flow Tools
• 4.1. if Statements
• 4.2. for Statements
• 4.3. The range() Function
• 4.4. break and continue Statements, and else Clauses on Loops
• 4.5. pass Statements
• 4.6. Defining Functions
• 4.7. More on Defining Functions
• 4.7.1. Default Argument Values
• 4.7.2. Keyword Arguments
• 4.7.3. Special parameters
• 4.7.3.1. Positional-or-Keyword Arguments
• 4.7.3.2. Positional-Only Parameters
• 4.7.3.3. Keyword-Only Arguments
• 4.7.3.4. Function Examples
• 4.7.3.5. Recap
• 4.7.4. Arbitrary Argument Lists
• 4.7.5. Unpacking Argument Lists
• 4.7.6. Lambda Expressions
• 4.7.7. Documentation Strings
• 4.7.8. Function Annotations
• 4.8. Intermezzo: Coding Style
• 5. Data Structures
• 5.1. More on Lists
• 5.1.1. Using Lists as Stacks
• 5.1.2. Using Lists as Queues
• 5.1.3. List Comprehensions
• 5.1.4. Nested List Comprehensions
• 5.2. The del statement
• 5.3. Tuples and Sequences
• 5.4. Sets
• 5.5. Dictionaries
• 5.6. Looping Techniques
• 5.7. More on Conditions
• 5.8. Comparing Sequences and Other Types
• 6. Modules
• 6.1. More on Modules
• 6.1.1. Executing modules as scripts
• 6.1.2. The Module Search Path
• 6.1.3. “Compiled” Python files
• 6.2. Standard Modules
• 6.3. The dir() Function
• 6.4. Packages
• 6.4.1. Importing * From a Package
• 6.4.2. Intra-package References
• 6.4.3. Packages in Multiple Directories
• 7. Input and Output
• 7.1. Fancier Output Formatting
• 7.1.1. Formatted String Literals
• 7.1.2. The String format() Method
• 7.1.3. Manual String Formatting
• 7.1.4. Old string formatting
• 7.2. Reading and Writing Files
• 7.2.1. Methods of File Objects
• 7.2.2. Saving structured data with json
• 8. Errors and Exceptions
• 8.1. Syntax Errors
• 8.2. Exceptions
• 8.3. Handling Exceptions
• 8.4. Raising Exceptions
• 8.5. Exception Chaining
• 8.6. User-defined Exceptions
• 8.7. Defining Clean-up Actions
• 8.8. Predefined Clean-up Actions
• 9. Classes
• 9.1. A Word About Names and Objects
• 9.2. Python Scopes and Namespaces
• 9.2.1. Scopes and Namespaces Example
• 9.3. A First Look at Classes
• 9.3.1. Class Definition Syntax
• 9.3.2. Class Objects
• 9.3.3. Instance Objects
• 9.3.4. Method Objects
• 9.3.5. Class and Instance Variables
• 9.4. Random Remarks
• 9.5. Inheritance
• 9.5.1. Multiple Inheritance
• 9.6. Private Variables
• 9.7. Odds and Ends
• 9.8. Iterators
• 9.9. Generators
• 9.10. Generator Expressions
• 10. Brief Tour of the Standard Library
• 10.1. Operating System Interface
• 10.2. File Wildcards
• 10.3. Command Line Arguments
• 10.4. Error Output Redirection and Program Termination
• 10.5. String Pattern Matching
• 10.6. Mathematics
• 10.7. Internet Access
• 10.8. Dates and Times
• 10.9. Data Compression
• 10.10. Performance Measurement
• 10.11. Quality Control
• 10.12. Batteries Included
• 11. Brief Tour of the Standard Library — Part II
• 11.1. Output Formatting
• 11.2. Templating
• 11.3. Working with Binary Data Record Layouts
• 11.4. Multi-threading
• 11.5. Logging
• 11.6. Weak References
• 11.7. Tools for Working with Lists
• 11.8. Decimal Floating Point Arithmetic
• 12. Virtual Environments and Packages
• 12.1. Introduction
• 12.2. Creating Virtual Environments
• 12.3. Managing Packages with pip
• 13. What Now?
• 14. Interactive Input Editing and History Substitution
• 14.1. Tab Completion and History Editing
• 14.2. Alternatives to the Interactive Interpreter
• 15. Floating Point Arithmetic: Issues and Limitations
• 15.1. Representation Error
• 16. Appendix
• 16.1. Interactive Mode
• 16.1.1. Error Handling
• 16.1.2. Executable Python Scripts
• 16.1.3. The Interactive Startup File
• 16.1.4. The Customization Modules

Python 3.9.1 documentation

 

Python Machine Learning Tutorial (Data Science)

 Python Machine Learning Tutorial (Data Science)