Jupyter Guide

To get started, open the file on the right entitled "Step 1...". You'll complete each task for Step 1 in that Jupyter Notebook file. Remember, you must run the cells (ctrl/cmd + Enter) for each task before moving onto the next task in the Jupyter Notebook. Continue until you have completed all tasks in this step. Then when you are ready to move onto the next step, you'll come back and click on the file for the next step until you have completed all tasks in all steps of the lab.

Working with Directories and Files

To review the concepts covered in this step, please refer to the Creating, Reading, Writing, Deleting, and Managing Files and Directories module of the Working with Files in Python course.

Understanding how to work with directories and files is important because it forms the basis of file handling in Python. This includes creating, reading, writing, and deleting files and directories.

In this step, you'll practice these skills by creating, reading, writing, and deleting files and directories using Python's os module. Your task is to create a new directory, write a file within it, read the file, and finally delete both the file and the directory.

Task 1.1: Creating a New Directory

Create a new directory named 'LabFiles' in the current working directory using the os module. After creating the directory, list the contents of the current directory to confirm its creation.

import os

# Create a new directory named 'LabFiles'
os.mkdir('LabFiles')

# Print the list of files/directories in the current directory
os.listdir('.')

Task 1.2: Writing a File

Create a new file named 'demographic_data.txt' in the 'LabFiles' directory and write the string 'This is a test file for demographic data.' to it. After writing to the file, close it and list the contents of the 'LabFiles' directory to confirm the file's creation.

file = open('LabFiles/demographic_data.txt', 'w')
file.write('This is a test file for demographic data.')
file.close()

# Print the list of files in the 'LabFiles' directory
os.listdir('LabFiles')

Task 1.3: Reading a File

Read the contents of the 'demographic_data.txt' file and print them. After reading the file, close it to ensure resources are released properly.

file = open('LabFiles/demographic_data.txt', 'r')
data = file.read()
file.close()

# Print the contents of 'demographic_data.txt'
data

Task 1.4: Deleting a File

Delete the 'demographic_data.txt' file from the 'LabFiles' directory. After deleting the file, list the contents of the 'LabFiles' directory to verify its removal. There should be nothing there.

os.remove('LabFiles/demographic_data.txt')

# Print the list of files in the 'LabFiles' directory to confirm deletion
os.listdir('LabFiles')

Task 1.5: Deleting a Directory

Delete the 'LabFiles' directory. After deleting it, list the contents of the current directory to verify the directory's removal.

os.rmdir('LabFiles')

# Print the list of files/directories in the current directory to confirm deletion
os.listdir('.')

Interacting with System Processes

To review the concepts covered in this step, please refer to the Creating, Reading, Writing, Deleting, and Managing Files and Directories module of the Working with Files in Python course.

Knowing how to interact with system processes is important because it allows you to manage and retrieve information from running processes, which is crucial in many programming tasks such as monitoring system performance, debugging, and automating system maintenance tasks.

Time to interact with your system! In this step, you'll use the psutil module to retrieve system information and interact with running processes. Your goal is to retrieve information related to files, such as disk partitions, disk usage, and disk IO counters, and to print all running processes on your machine in a human-readable format.

Task 2.1: Importing the psutil module

To interact with system processes, you need to import the psutil module. This module provides an interface for retrieving information on running processes and system utilization (CPU, memory, disks, network, sensors) in Python.

import psutil

Task 2.2: Printing All Running Processes

Print all running processes on your machine. This is useful for monitoring which processes are currently active, understanding system resource usage, and identifying potentially unwanted or suspicious processes. Find the jupyter-notebook process that you are using at the moment.

for process in psutil.process_iter(['pid', 'name', 'memory_info']):
     # access these attributes in the process.info dictionary

for process in psutil.process_iter(['pid', 'name', 'memory_info']):
    print(f"PID: {process.info['pid']}, Name: {process.info['name']}, Memory: {process.info['memory_info']}")

Task 2.3: Retrieving Disk Usage Information

You can also use the psutil module to retrieve information about the disk usage of your system. The disk_usage(path) function of the psutil module returns disk usage statistics about the given path as a named tuple including total, used and free space expressed in bytes, plus the percentage of used space.

usage = psutil.disk_usage('/')
usage

Task 2.4: Retrieving Disk IO Counters Information

Finally, you can use the psutil module to retrieve information about the disk IO counters of your system. The disk_io_counters() function of the psutil module returns system-wide disk IO statistics as a named tuple including the number of read and write calls, the amount of data read and written, the time spent reading and writing, and the number of bytes read and written.

io_counters = psutil.disk_io_counters()
io_counters

Working with Environment Variables

To review the concepts covered in this step, please refer to the Creating, Reading, Writing, Deleting, and Managing Files and Directories module of the Working with Files in Python course.

Working with environment variables is important because it allows you to access and manipulate data that your application might need, regardless of the platform it's running on.

Let's explore the environment! In this step, you'll use the os module to retrieve and work with environment variables. Your goal is to retrieve the PATH environment variable and add a new environment variable.

Task 3.1: Importing the os module

To start working with environment variables, you need to import the os module. This module provides a way of using operating system dependent functionality.

import os

Task 3.2: Accessing an environment variable

Now that you have imported the os module, you can use it to access environment variables. Try to access the PATH environment variable.

os.environ['PATH']

Task 3.3: Setting an environment variable

You can also set the value of an environment variable using the os module. Try setting the value of a new environment variable called GREETING to Hello, world!.

os.environ['GREETING'] = 'Hello, world!'

Task 3.4: Verifying the environment variable

Now that you have set the value of GREETING, verify that it has been set correctly by printing its value.

os.environ['GREETING']

Reading and Appending to CSV Files

To review the concepts covered in this step, please refer to the Creating, Reading, Writing, Deleting, and Managing Files and Directories module of the Working with Files in Python course.

Reading and writing to files is important because it's a fundamental way to store and retrieve data in your Python applications.

Ready to read and write? In this step, you'll open a file, append data to it and read lines from it using Python's built-in file handling functions. We'll be using the 'Demographic Data.csv' file.

Task 4.1: Open the File

Open the 'Demographic_Data.csv' file in the current directory in read mode using Python's built-in open() function. Assign the file object to a variable named file.

file = open('Demographic_Data.csv', 'r')

Task 4.2: Read the File

Read the contents of the file using the read() method of the file object. Assign the result to a variable named data and print the results.

data = file.read()
print(data)

Task 4.3: Close the File

Close the file using the close() method of the file object.

file.close()

Task 4.4: Open the File in Append Mode

Open the 'Demographic_Data.csv' file in append mode using Python's built-in open() function. Assign the file object to a variable named file.

file = open('Demographic_Data.csv', 'a')

Task 4.5: Write to the File

Write a new line to the file using the write() method of the file object. The new line should be a string representing a new employee's data. Remember to include a newline character (\n) at the end of the string. The string should be in the format: gender, date of birth, country.

file.write('Male,1990-01-01,USA\n')

Task 4.6: Close the File

Close the file using the close() method of the file object. Access the file in the file tree of the jupyter UI to verify that your changes were made.

file.close()