📔
intro-to-python
  • An Introduction to Programming in Python (for Business Students)
  • exercises
    • Data Flow Diagramming Exercise
    • Developer Collaboration Exercise
    • README
    • "Web App" Exercise
      • checkpoints
        • Checkpoint 5: Bootstrap Layout
        • Checkpoint 4: Submitting Data from Web Forms
        • Checkpoint 3: Rendering HTML Pages
        • Checkpoint 1: Routing
        • Checkpoint 2: Modular Organization
      • "Web App" Exercise - Further Exploration
    • hello-world
      • "Hello World (Local)" Exercise
      • "Hello World (Local w/ Version Control)" Exercise
      • "Hello World (Colab)" Exercise
    • "Interface Capabilities" Exercise
    • "Continuous Integration 1, 2, 3" Exercise
    • "Web Service" Exercise
      • "Web Service" Exercise - Further Exploration
    • "Testing 1, 2, 3" Exercise
    • "Command-line Computing" Exercise
      • "Command-line Computing" Exercise
      • Professor Rossetti's Mac Terminal Configuration
      • Command-line Computing Exercise
    • "Codebase Cleanup" Assignment
    • "List Comprehensions" Exercise
    • "Groceries" Exercise
      • Python Datatypes (a.k.a. "Groceries") Exercise
      • Python Datatypes (a.k.a. "Groceries") Exercise
    • "Rock, Paper, Scissors" Exercise
      • "Rock, Paper, Scissors" Exercise
    • README
    • "Monthly Sales Predictions" Exercise
    • Setting up your Local Development Environment
    • "Chart Gallery" Exercise
    • "Run the App" Exercise
    • "Web Requests" Exercise
    • "API Client" Exercise
    • "Custom Functions" Exercise
    • Process Diagramming Exercise
  • notes
    • python
      • packages
        • The bigquery Package
        • The PySimpleGUI Package
        • The dotenv Package
        • The matplotlib Package
        • The requests Package
        • The altair Package
        • The gspread Package
        • The PyMySQL Package
        • The psycopg2 Package
        • The selenium Package
        • The seaborn Package
        • The pytest Package
        • The SpeechRecognition Package
        • The flask Package
        • The pandas Package
        • The spotipy Package
        • The pipenv Package
        • The nltk Package
        • The sqlalchemy Package
        • The pymongo Package
        • The plotly Package
        • The BeautifulSoup Package
        • The sendgrid Package
        • The fpdf Package
        • The autopep8 Package
        • The tweepy Package
        • The twilio Package
        • The tkinter Package
      • Python Datatypes Overview
        • Numbers
        • Classes
        • Dates and Times
        • Strings
        • None
        • Dictionaries
        • Booleans
        • Lists
        • Class Inheritance
      • Control Flow
      • Python Modules
        • The webbrowser Module
        • The time Module
        • The csv Module
        • The sqlite3 Module
        • The itertools Module
        • The json Module
        • The math Module
        • The os Module
        • The statistics Module
        • The random Module
        • The pprint Module
        • The datetime Module
        • The collections Module
      • Printing and Logging
      • Comments
      • Syntax and Style
      • Functions
      • Variables
      • Errors
      • Docstrings
      • File Management
      • User Inputs
      • Debugging
    • clis
      • The git Utility
      • Heroku, and the heroku Utility
      • Anaconda
      • The chromedriver Utility
      • The brew Utility (Mac OS)
      • The pdftotext Utility
      • The python Utility
      • The pip Utility
    • Software
      • Software Licensing
      • Software Documentation
      • Software Ethics
      • Software Testing Overview
      • Application Programming Interfaces (APIs)
      • Software Version Control
      • Software Refactoring Overview
    • devtools
      • The VS Code Text Editor
      • Code Climate
      • Travis CI
      • GitHub Desktop Software
      • Git Bash
      • Google Colab
    • Information Systems
      • Computer Networks
      • Processes
      • Datastores
      • Information Security and Privacy
      • People
    • Technology Project Management
      • Project Management Tools and Techniques
      • The Systems Development Lifecycle (SDLC)
    • hardware
      • Servers
    • Environment Variables
  • projects
    • "Executive Dashboard" Project
      • testing
      • "Exec Dash" Further Exploration Challenges
    • The Self-Directed (a.k.a "Freestyle") Project
      • "Freestyle" Project - Demonstration
      • "Freestyle" Project - Implementation (TECH 2335 Version)
      • "Freestyle" Project - Implementation
      • "Freestyle" Project Proposal
      • plan
    • "Robo Advisor" Project
      • Robo Advisor Project - Automated Testing Challenges
      • "Robo Advisor" Further Exploration Challenges
    • "Shopping Cart" Project
      • "Shopping Cart" Project - Automated Testing Challenges
      • "Shopping Cart" Further Exploration Challenges
      • "Shopping Cart" Project Checkpoints
  • License
  • Exam Prep
  • units
    • Unit 4B: User Interfaces and Experiences (Bonus Material)
    • Unit 5b: Databases and Datastores
    • Module 1 Review
    • Unit 7b: Processing Data from the Internet (Bonus Material)
    • Unit 9: Software Products and Services
    • Unit 8: Software Maintenance and Quality Control
    • Unit 7: Processing Data from the Internet
    • Unit 6: Data Visualization
    • Unit 5: Processing CSV Data
    • Unit 4: User Interfaces and Experiences
    • Unit 3: Python Datatypes
    • Unit 12: Project Presentations
    • Unit 2: Python Language Overview
    • Unit 11: Project Implementation Sprint
    • Unit 1: The Python Development Environment
    • Unit 10: Software Planning, Analysis, and Design
    • Unit 0: Onboarding
    • Unit 5B: Advanced Data Analytics
  • Contributor's Guide
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  • Detecting Installations
  • Detecting Versions
  • Usage
  • Interactive Console
  • Executing Scripts

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The python Utility

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Last updated 4 years ago

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"Python is a programming language that lets you work quickly and integrate systems more effectively" -

Before you can execute Python programs on your computer, you'll first need to install the Python command-line utility.

Over the past few years there has been a shift in the community from Python Version 2 to Python Version 3. But these days we assume everyone is using Python 3, and this semester we will be using Python 3, exclusively. We might use different minor versions of Python 3 (like 3.7 or 3.8), depending on their compatibility with specific third-party packages we may be using on a given project.

Anaconda provides a command-line utility called conda to help us manage different versions of Python. Before proceeding, please take a moment to .

When you are ready, either use the Anaconda default "base" environment, or create and activate a new Anaconda environment, and within the environment execute the commands below.

Detecting Installations

To see if Python is already installed, and if so where:

# Mac Terminal:
which python

# Windows Command Prompt or Git Bash:
where python

If you see a filepath output, it means Python is installed at the location specified, so you can advance to the version detection instructions below. Otherwise, if you see an empty result or an error message, that usually means Python is not installed.

Detecting Versions

Let's see which version of Python is installed:

python --version

If you see a result here like "Python 3.8.3" (or some other 3.x version), it means the specified version of Python is installed, so you can advance to the usage instructions below. Otherwise, if you see an empty result, error message, or 2.x version, that usually means Python is not installed (properly).

Usage

After Python is installed, you should be able to execute Python commands.

Interactive Console

# Mac Terminal:
python

# Windows Git Bash:
python -i # for interactive

If you type python on Mac Terminal (or python -i on Windows Git Bash) and press "enter", you will enter into an interactive Python console where you can evaluate Python statements and expressions. When you are done using the Python console, you can shut it down by typing exit() and pressing "enter".

Executing Scripts

python path/to/my_script.py

You can alternatively use the python utility to execute a pre-written Python program, by specifying its filepath. To test this out yourself, follow the instructions in the .

Python Website
install Anaconda and get familiar with the conda utility
Hello World (Local) Exercise
a screenshot of using the python console to perform a simple calculation (2+2 = 4)
a screenshot of the output resulting from running a python script from the command-line. the hello message is printed in the terminal