<jupyter_start><jupyter_text>Machine Learning/Data for Internet of Things Practice Assignment: Hello, world!This first assignment is intended to help you get set up in the course.  You'll also be writing your first lines of Python code! Assignments are set up using "template" repositories.  The idea is that these templates for each assignment will provide a framework for you to work with.  Your job is to follow each assignment's instructions and fill in the missing pieces of code and/or text. Assignment goalsYou're going to learn four things in this assignment:1.   How to use Jupyter (Colaboratory) notebooks2.   How to set up your Google Colaboratory and GitHub accounts3.   How to access and submit assignments4.   How to write a (tiny!) Python program and run it  Part 1: Jupyter notebooks, Google Colaboratory, and GitHubYou should start by going through [this notebook](https://github.com/ContextLab/cs-for-psych/blob/master/slides/module_1/introduction_and_overview.ipynb) to familiarize yourself with Jupyter notebooks and Google Colaboratory (and setting up your Google Colaboratory and GitHub accounts).  Follow the instructions in the notebook to set up your accounts.Change the code in the next cell to indicate that you've gone through the introductory notebook, read about Jupyter/Colaboratory notebooks, set up your Google Colaboratory account, and set up your GitHub account.  You should change each variable from `False` to `True` to show which tasks you have (by self-report) accomplished.  Also update the `github_username` variable to indicate your GitHub username.<jupyter_code>#I have read through the Introduction and Overview notebook
READ_INTRODUCTION = True

#I understand (at a high level) what Jupyter notebooks are and how to read and
#interact with them (or I have been in touch with the course instructor to ask for help)
LEARNED_ABOUT_JUPYTER = True

#I've created (or already have) a Google account and can access Google
#Colaboratory under my own account
ACCESS_COLABORATORY = True

#I've created a GitHub account
CREATED_GITHUB_ACCOUNT = True
github_username = "ciaranomalley"<jupyter_output><empty_output><jupyter_text>Part 2: Your first computer program!Let's learn about the `print` command.  This super useful function lets you display text.  A lot of the programming we'll do in this course will rely on using `print` to display the results of calculations.  We'll also use `print` to "debug" our code.  We'll learn more formally about what debugging means, but the general idea is that it's about diagnosing and correcting problems with your computer programs (code).  One simple debugging approach is to have your program periodically print out useful messages (using `print`) to help you understand what's happening.The most basic way to use the `print` function is to call `print(...)`, replacing "`...`" with the text you want displayed, enclosed in single (`'`) or double (`"`) quotes, like this:```print('Hello, world!')```Modify the code in the next cell to print a greeting to yourself (e.g. "Hello, Jeremy!" or something to that effect, replacing "Jeremy" with your own name).  Check your work by pressing shift + return to run your code.  It should print out your greeting below your code.<jupyter_code>print("Ciaran O'Malley")<jupyter_output>Ciaran O'Malley<jupyter_text>Print name, hello world etc.  Congrats, programmer!It may not seem like much happened, but that one line of code for printing your message is a complete and valid Python 3.x computer program.  We'll be writing substantially more complicated and interesting programs in this course, but you should pat yourself on the back for reaching your first programming milestone: writing your version of the famous ["Hello, world!" program](https://en.wikipedia.org/wiki/%22Hello,_World!%22_program) that has helped introduce nearly every modern programmer to the world of coding.  Getting helpTo learn more about any Python command or function, you can type `?` into a code cell (relacing "``" with the actual function name, e.g. `print`) and press shift + return to execute it.  Try getting help using this approach for the following functions: `print`, `input`, and `open`.  Click the `x` to close the help documentation once you're done scrolling through it.  If you're already familiar with reading [API documentation](https://en.wikipedia.org/wiki/Application_programming_interface), you may notice some interesting features of these functions.  For example, together `print`, `input`, and `open` constitute a basic but powerful set of functions that allow you to read and write to files-- including remotely (e.g., web pages)!  And don't worry if the documentation seems inscrutible right now.  As you learn more about Python programming you'll start to build up a sense of the contexts in which different parts of the documentation apply, and you'll also build up a vocabulary that will allow you to communicate (e.g., by reading and writing documentation asking questions, etc.) with other programmers.<jupyter_code>?print<jupyter_output><empty_output><jupyter_text>Equivalently, you can also use the `help` function to print out the same documentation to the console:<jupyter_code>help(print)<jupyter_output>Help on built-in function print in module builtins:

print(...)
    print(value, ..., sep=' ', end='\n', file=sys.stdout, flush=False)
    
    Prints the values to a stream, or to sys.stdout by default.
    Optional keyword arguments:
    file:  a file-like object (stream); defaults to the current sys.stdout.
    sep:   string inserted between values, default a space.
    end:   string appended after the last value, default a newline.
    flush: whether to forcibly flush the stream.
{'fraction_non_alphanumeric': 0.06429070580013976, 'fraction_numerical': 0.0020964360587002098, 'mean_word_length': 4.914256198347108, 'pattern_counts': {'":': 0, '<': 15, '<?xml version=': 0, '>': 15, 'https://': 3, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '56117', 'license': 'MIT', 'n_tokens_mistral': 1488, 'n_tokens_neox': 1415, 'n_words': 786, 'path': 'CiaranOmalley_Hello_of_hello_world_assignment.ipynb', 'repo_name': 'ciaranomalley/cs-for-psych', 'size': '5724'}