My Final Portfolio

We’ve made it to the end of the semester, and to the end of finals week! For my final portfolio, I was to take a look back at four of my projects and figure out a way or ways that I could improve them in some way. 

Twitter Bot Revisited: 

At the beginning of the year, I created a Twitter Bot with the help of Cheap Bots, Done Quick that automatically tweeted out random statements that would be “relatable” to pretty much everyone. I found it so fun to do this project, and definitely wanted to do it again! 

Again, I used Cheap Bots, Done Quick, but this time, I decided to spread a passion that I have. I love to write and I love to write anytime I can. It’s my creative outlet. I took Creative Writing back in high school, and LOVED it. Everyday, we had a writing prompt to start the class off. It was always something interesting. I decided that I would create a Twitter Bot that would tweet out random writing prompts that may or may not make sense. They are also pretty silly, but I guess when you’re working with code it’s not all going to be super uniform in terms of grammar, storytelling, clarity, etc. I have the program tweeting out prompts every 6 hours. Below is my code: 

{
	"origin": ["In #geography#, #first# #actions# in a #adjectives_adverbs# #locations#. #transition# #youdo# #celebrities#. #transition# #surprise#."],
	
	"geography": ["Las Vegas", "Los Angeles", "Chicago", "Paris", "Rome", "England", "New Zealand", "New York City", "Mexico", "Canada", "Antarctica", "Ireland", "Scotland", "Egypt", "China", "Japan", "Russia", "the United States", "Madagascar", "Brazil", "Peru", "Iceland", "Greenland", "Texas", "Fredericksburg, Virginia", "California", "Australia"],
	"first": ["You are", "They are", "He is", "She is", "The dog is", "The dogs are", "The cat is", "The cats are", "The doctor is",  "The police officer is", "The teacher is", "Your house is", "Your car is", "Your party is", "Your school is", "The lights are", "We are", "Kids are", "The summer is", "The trees are"],
	"actions": ["hiding", "whispering", "singing", "dancing", "shaking", "speaking", "screaming", "yelling", "drinking", "sleeping", "reading", "watching TV", "sitting", "texting", "chasing", "praying", "decorating", 
"driving", "purchasing", "stealing", "giving", "eating", "playing", "drawing", "falling"],
	"adjectives_adverbs": ["beautiful", "lovely", "scary", "dark", "bright", "corporate", "dirty", "clean", "empty", "full", "big", "small", "tiny", "humongous", "gross", "welcoming", "cozy", "breezy", "cold", "hot", "comfortable", "so overrated", "haunted", "Christmasy", "snowy"],
	"locations": ["house", "school", "library", "store", "nook", "store", "bar", "restaurant", "movie theater", "tunnel", "tent", "box", "bank", "police station", "hospital", "college", "phone booth", "hotel", "abandoned building", "bunker", "ghost town", "bookstore", "coffee shop", "Walmart", "Target", "vending machine", "neighborhood", "parking garage", "city hall", "park", "pool"],
	"youdo": ["You come across", "You run into", "You meet", "You notice", "You wave hello to", "You see"],
	"celebrities": ["Barack Obama", "Donald Trump", "George Clooney", "Chris Evans", "Chris Hemsworth", "Liam Hemsworth", "Robert Downey Jr.", "Mark Wahlberg", "Will Ferrell", "Adam Levine", "Zac Efron", "Ryan Reynolds", "Justin Bieber", "Channing Tatum", "Brad Pitt", "David Beckham", "Ryan Gosling", "Dwayne Johnson", "Justin Timberlake", "Chris Pratt", "Jake Gyllenhaal", "Leonardo DiCaprio", "Johnny Depp", "Tom Cruise", "Ben Affleck", "Ashton Kutcher", "Kanye West", "Robert Pattinson", "Drake", "Daniel Radcliffe", "Jon Hamm", "Matthew McConaughey", "Ellen DeGeneres", "Beyoncé", "Taylor Swift", "Rihanna", "Kim Kardashian", "Megan Fox", "Jennifer Lawrence", "Jennifer Aniston", "Julia Roberts", "Miley Cyrus", "Katy Perry", "Angelina Jolie",  "Ariana Grande", "Emma Watson", "Sandra Bullock", "Jessica Biel", "Oprah", "Anne Hathaway", "Julie Andrews", "Mila Kunis", "Demi Lovato", "Blake Lively", "Selena Gomez", "Michelle Obama", "Hilary Duff", "Hillary Clinton"],
	"transition": ["Next,", "All of a sudden,", "Then,", "Out of nowhere,", "Next thing you know,"],
	"surprise": ["the phone begins to ring", "your phone begins to ring", "your alarm starts to buzz", "the alarm clock starts to buzz", "you are passed a note", "a sign illuminates", "music begins to play", "you hear whispers", "a storm rolls in", "everything goes black", "you wake up", "the radio turns on"]
	

}

One of the combinations I saw this morning on the Cheap Bots, Done Quick page was: 

“In China, The cats are singing in a bright abandoned building. Next, You wave hello to Jennifer Aniston. Then, your phone begins to ring.”

Some examples of Tweets that have already posted: 

As I said, many of them are extremely strange, however I do find some of them hilarious. 

I gave the name “Wrighte Now!” to the twitter bot because I thought it was a play on words. Write now, right now! Combined. Boom. 

(I also believe that this code will definitely print out over 100,000 iterations. I did the math last night and I think I did it correctly.) 

(27 * 20 * 25 * 25 * 31 * 6 * 58 * 5 * 12 = 218,457,000,000 — Each number represents how many variables are in each category.)

Remix Project Revisited: 

Another one of the projects from the semester that I really enjoyed and wanted to keep experimenting with was my Remix Project. The first time I did it, I had a poem print out that included quotes from TV shows such as FriendsThe Office, and the movie The Fault in Our Stars. The result was pretty great, in my opinion. Maybe I’m just biased. This time I wanted to do something similar but I wanted it to include more possibilities! I had only used about 15 quotes from each show last time, and this time I wanted to put more effort into it. 

This time, I was going to use Jupyter Notebooks with Python again to create the same format of the poems I made last time, however, there would be a lot more for the computer to choose from. I started out by researching the top 100 songs of 2018, and after finding my answer from Billboard, I began to look up the lyrics for every song. I looked through the lyrics of each song and chose one line from each of them. Many of the songs were quite inappropriate, so I had to really dig for something appropriate. Finally, I had 1 lyric from 100 different songs. Next, I chose to look up the top 100 songs from the year I was born, 1996. Thanks to a website called Music Outfitters, I was able to find a list. Again, some of these songs were inappropriate, but I was still able to find 1 lyric from all 100 songs. Lastly, I decided to look up the top songs of all time. I only chose 100 even though there are WAY more than 100 top songs of all time. I had to look in many different places because numerous sites would just give me “20 of the Top Songs of All Time” or something like that. Songs that I used were anywhere from the 1980s, 1990s, 2000s, and present day. At last, I had a major long list of 300 lyrics. 

I plugged in the code in order for the computer to choose from each list at random. Last time, I only had it print out 5 lines from each group, but this time I decided to have it print 100 times from each group, since each group had 100 choices. I’m sure there is quite a bit of repetition but I think that that makes it more fun! 

You can find the full code here on my GitHub page!

Here are just some snippets of the resulting poetry:

I think it sounds pretty great! 

Glitch Project Revisited: 

Another one of the projects I really enjoyed this semester was the Glitch Project. If you remember, I used pictures of my childhood. I got some pretty shocking results. I really wanted to do it again, but with different pictures. 

I decided that I wanted to use pictures that gave you a different perspective, literally! Many of these images were aerial view images I found on Unsplash. It was cool to look at all of these pictures that were basically just bird’s-eye-view focused. How many times do you get to see these perspectives, yourself? I doubt you said often. I chose to use Text Edit to work with Databending. I had wanted to use Audacity again, but for some reason it would not allow me to. I followed all of the instructions from Dr. Whalen’s videos and had even watched other YouTube tutorials. It still would not let me work with it no matter what I did. I was very frustrated as I really liked the results I got when using Audacity. However, the results I got from TextEdit were pretty great too. This time, I aimlessly cut and paste random chunks of data. This was perfect because it really began to glitch the more I chose at random. Some images came out awesome and some turned out to where you can’t really tell what it was to begin with. 

After transforming 4 images with TextEdit, I decided to go back to Pixel sorting which I did using my Python terminal in Jupyter Notebooks. I loaded the images into the pixelsort.py software, and it would sort the pixels for me following any instructions I gave it. Some of these results were a little more underwhelming than those I had last time, but they were still pretty cool in the ways that it avoided some spots and glitched over others. It felt more uniform this time. I created four more glitches with this method. You can see the code I used to do this on my GitHub page!

Here are the four that were glitched with Text Edit: 

Here are the four images glitched with the Python terminal and pixelsort.py:

I really love how all of these turned out! All of these pictures, I believe, tell quite a story. For example, you’re on the top of the Eiffel Tower and you look down and everything is just a blur, literally, or you’re crossing the Golden Gate Bridge and there is this large, pixelated wave ahead of you. The pictures that were created using TextEdit remind me of film. When I was a kid, my mom would take pictures all the time, and we had a film camera, and we would develop them and they would look oily and glossy and you had to hold them up to the light to tell what picture was what. 

NaNoGenMo Revisited: 

Guess what? I wrote another >50,000 word novel with my computer! Last time, I combined stories such as Cinderella, Mary Poppins, Nancy Drew, and more. This story turned out pretty well, but it wasn’t my absolute favorite! 

I decided I really wanted to improve it, so I did! I decided to include around 10 chapters from different banned books! I used novels such as Catcher in the Rye, Grapes of Wrath, The Great Gatsby, The Awakening, To Kill a Mockingbird, and one more short story that I don’t believe is banned but one that I really enjoyed in middle school, The Landlady. I named this new novel: The Banned Ones. I remember all of middle and high school learning about banned books and having Banned Book week. I read all of these books in high school and middle school, and found them pretty interesting, to be honest! I combined all of these stories into one text file. 

Next, I created the code that resembles the original code for my original NaNoGenMo novel. 

I then had the final product! Enjoy! 

I have really enjoyed this class this semester, and I’m honestly sad that it’s over. I have learned and done more than I ever thought I could! 

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