jim

created a community modal for non-ysws-orgs to test out Lucy. I also fixed the database in json and some other things.

didn't think of adding this to SoM, did so now. So for the past 4 days, me and some other people have been working on this semi-official tool. It's purpose is to help ysws organizers, and currently features 12 tools including airtable automations, github ai checks, hackatime api wrappers, and a chatbot finetuned on a 1.5k prompt including all past YSWS programs, terminology, and advice. We also coded an admin panel with keys + an audit log (FBI)

added coloured BMI classes and connected test results to db

added the basic cancer ml test functionality! most of the code was copy-paste from previous projects, I gotta update the UI, add some BMI indicators, and connect it with the dataset so the age is auto-filled

i added a what is your birthday on signup so the user's age can be saved in the db. this way for cancer tests, age will be automatically filled! I also updated the dashboard, with an average health score among ages chart, tests you have taken, and account info/logout

got the register page working! it dumps data to a raw json through the controller. still have to make login

created a goofy database controller (database is json btw, dont flame me) - also used internal functions starting with _ for the brag

added sections for each test on the landing page. that includes cancer, diabetes, and mental health. I also created the login/signup page that currently have no functionality (I hate frontend, cant wait to get to the backend). I still have to add some images!

started from scratch on my own, used bootstrap & flask and made around 20 github commits. created the basic hero section of the landing page, routing, base.html, and a colour pallete. I also added a particles.js sphere like thingy

added contacts functionality, fetching contacts from a json and testing if a contact exists with functions. still have to connect everything to the assistant + twillio. I also recieved both the rasberry pis, im setting up the environment!

added jokes & todo functions and class, (uncallable for now)

added logs everywhere, created a basic weather api caller & cordinates fetcher, made listening actually work

added hello messages, a tts and sts engine, also added custom logs with colour (first time using dictionaries in my 4 years of python). i made the voice assistant so if you greet it (etc hi), it greets you back with your name!

created the core structure, speak and listen functionality (no commands parser yet), a config.json with wake words, owner name and some voice engine configs. lastly I made a list of welcome messages that the voice assistant will speak such as Hey _USER_, how can I help you today?

Added gallery page - users PR a yml with info about their project + an image and it shows up at the gallery page!

Authly finally launched! The reason this took so long, is because we revamped the website. Since many people were gonna see the announcements message, the website got high traffic so it had to be perfect. Firstly I updated all rewards and the time people need to get them and changed the images. As you probably know we have a custom idea generator, that allows people to delete ideas (claim) them,and someone decided to spam the delete endpoint and ruined everything. I added a ratelimit + banned ips to the idea api, which took like 2 hours to get working. I also made the authly website more responsive, updated the FAQ, added a github stars tracker, updated the review tracker + tutorial and more! (I also spent 1 hour editing the #announcements markdown message)

alright so this is the biggest update far. a guy helped me and we added many features. First, we created the tracking page where it says the total amount of submissions and a bar showing progress of how many of them we have reviewed, to keep people updated. After that I createed an announcement page, which no other YSWS has, and its basically a page where anybody can post announcements with their account and mark their important from Low-High by making a PR. Lastly, I split all js from html files so the project shows up as js on github. I also added profiles and meta profile links in the blog page.

added corsproxies to idea generator + created rewards sections + created review tracking page and fixed spacing on the wbsite

update main page + change intro animation that was previously borrowed by Hrydia's optimize YSWS

found an dataset of comments written by AI, designed a banner, wrote a function on comments.py to extract comments & made a filedata Class where for each file in a directory you get the extension, source code, full path. Lastly scan.py creates an filedata Class with these data for each file & prints out the structure

I finished functions, with defining functions and calling them. I also removed the video from the docs and hosted it on hackclub cnd. I think we can say the custom programming language is finished. The concept of this is to learn how languages work and gain some more advanced coding experience. I also worked on the docs.

Restructured code, worked on error logging + part of functions. I also added some new token types that include ID,EQ,NEQ,GTE (for if statements)

Added if statements, which can include ==, =<, >=, <, > for statements. Also updated the docs & readme.

Added mathimatical operators on int variable declarations, updated readme & docs

Restrucured code, added environment.py, ast_nodes.py with classes, tokens.py, added the ability to run source code from arguments. made all commands ast nodes classifiers in classes, + working on a repeat <times> {content} block + if block

Added polls and deployed to nest

Added comments, live chat with sockets, and a whiteboard to draw your feelings based on the post. Removed the comments because I added the whiteboard and the live chat. Also connected to firebase realtime db

Created the page to view posts + added a db handler

Created a template for upload page, html structure took 25 mins, but I already had particles from before and it was easier

Created a template for landing page, html structure took 20 mins, tailwindCSS classes 20 minutes, fonts + particles.js 15 minutes

Made an html for docs, examples, and demo, currently https://jimmydin7.github.io/custom-programming-language/docs

Changes the whole directory structure , basically restructured everything... Also made helpers, lang/interpreter, /parser, /tokenizer + more

added the ability to put a raw string inside say(), like say(hello, world!) instead of just variables + changed variable handling on a class on environment.py. Also renamed main to run and now you can put the source code path as an argument

Added tests for: lexer, parser, interpreter. They all have a 'correct' output which is checked to see if it is the same with the output they returned. I also wrote a README for github. Took me a long time because I couldn't figure out the importing on tests, and after some stackoverflow I figured to use sys.

Coded a demo python interpreter to process AST nodes

Added a parser (AST Generator), that was the next step after the tokenizer.

Added a lexer that turns source code into tokens

Took some time, (tried 3 different models), but finally found a lightweight way to capture hand points and faces (haar cascades). This was a lot trial and error, and Im happy I finally found the correct way to do it.

Finished the cancer prediction project, and hosted live on pythonanywhere. This project's goal was to raise awaireness for cancer and I hope people use it.

Hey guys! Today I added the whole functionality to the web UI. Users can fill their data and they can get a prediction. Also there are seperate pages for each question (all styled and pretty-looking). Have a nice day :)

Designed a demo webUI in figma and made it with tailwindCSS, will implement the cancer prediction model logic in a frontend form. The page is static and has some info about the project.

Migrated the backend to python flask with sessions to make a frontend UI

Added a basic model implementation using a Random Forest classifier. It trains on the dataset and outputs the probability (percentage) that a user has cancer.

Found a public dataset to use in order to train my cancer prediction model. It is free and from kaggle, and contains data from more than 2k patients. The content of the dataset contain age, gender, height, weight, smoking and drinking habits, personal cancer past and more.

Adding a logs system - instead of just printing in the terminal, I added functions to handle logs and a logfile. The functions are in utils/logs/logs.py and are called from the main.py