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knightfallShashy

@knightfallShashy

Joined June 10th, 2026

  • 24Devlogs
  • 6Projects
  • 5Ships
  • 60Votes
just a friendly coder
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Investie is a full stack investment based research app. You can search any stock, and get an AI summary of its financials and a real DCF valuation with proper market data. I built the stack myself with reflex as the frontend, fastAPI backend, and the postures via sup abase. I used finance for the data, and the anthropic API for the summaries. The hardest part was getting it deployed as it took a really long time to do that especially with the python version mismatch. My proudest accomplishment is probably the DCF engine and the AI summaries page.

  • 10 devlogs
  • 25h
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1h 40m 57s logged

This is probably my last devlog for Investie. I’ve finished deploying the reflex frontend and fastAPI backend to Render and Reflex. I spent a frustratingly long time fixing the deploy blockers from Yfinance’s rate limiting. I also spent a good amount of time writing an entire README for the whole project. Requirements.txt was a disaster and I spent a long time fixing it and generating it again. Lastly, I fixed the frontend properties and gave it a proper error message for when yahoo limits requests.

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2h 29m 33s logged

First of all I fixed the market page, instead of everything crammed to the left, it’s in the middle now and looks a lot more organized. Secondly I finally connected Anthropic’s API key to the project in- order to give stock summaries. The prompt for summaries took way too long because I kept changing it. The work done really put into perspective how long it takes to come up with the right prompt so that your tokens aren’t being burned. Im planning on investing a lot more money for the API tokens. lastly, Im starting to work the stock cards and making them clickable and a few other changes here and there.

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3h 16m 47s logged

To start off I fixed the number formatting on my DCF, which was initially showing me just raw numbers. I also found out that apparent reflex state vars doesn’t support f- string format lines which was a bit annoying. The next big thing is that I built a full company name feature. Instead of just searching the ticker you can search the company name and a list will pop up. That specifically took a long time to build. Lastly I wired real market data to the stock cards on the homepage, giving it a realism effect. I still have plans on taking it further and making them clickable.

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I made Growthcalc: a python written investment based calculator app. It has 4 different calculation metrics: an investment growth calculator, a retirement checker, a tax- advantaged vs taxable account comparison, and a loan payoff calculator. In general, the equations was probably the toughest part, understanding them and implementing them. Im really proud of going from nearly no python knowledge, to knowing how to use streamlit and work my way around functions. I also learned different financial concepts that I can use later down my life. Before people test my project they should know that it’s very interactive, try every single tab and basically enjoy. Have fun and look at how much your money can really grow.

  • 4 devlogs
  • 10h
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1h 15m 24s logged

After quite some time Im finally done with the project. I spent quite a long time writing the README since I wanted it quite detailed and didn’t want to leave any information out. Additionally, I deployed my local host through streamlet’s community cloud and got it an actual URL. Growthcalc.streamlit.app. During the streamlit process I also learned the difference between owner controls such as editor, manage, and share. I also figured out the visitors POV as well. All in all, I had a lot of fun with this project and learned a lot finance wise and coding wise.

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1h 53m 20s logged

I built probably my last tab, the Loan payoff Calculator. I had a LOTTTT of bugs with my formula and the overall persona of the concept. There was a confusing /$ display in a few places but I fixed it after some trouble. Apparently streamline treats $ the same way as st.write/st.errors/st.success. I also ended up building the amortization loop with monthly splits for fixed payment and interest based on the remaining balance. Im probably going to spend some time trying to turn this into a final website type project, which I’ve never done before.

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4h 29m 49s logged

This is a big devlog post but I finished two more tabs: A retirement checker tab and a Tax advantage Comparison tab. For the retirement checker I aded the 4% rule comparison logic to it. During the coding I ran into many many bugs, one of them being a dollar sign error and I took rlly long to fix. Also I realized halfway through that the retirement mode was using the return rate and monthly contribution from another tab and it was messing everything up. For the tax advantage tab, I ran two columns where one is tax growth every year, and the other is taxes only at withdrawal. Making the tax loop was incredible hard and it took a long time. Additionally, for th equations themselves, it was all new information for me and I spent way too long writing the wrong equations over and over.

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2h 10m 30s logged

This is my first devlog for growthcalc. I’m basically making an investment calculator. The initial calculation will use compound interest logic with 4 sliders to predict future value of an investment. Along with the math I also added a chart which looks really cool and puts the growth into perspective.

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3h 30m 54s logged

I built a pipeline for the DCF valuation logic to connect through the FastAPI endpoints (aka Get/fmp/ticker/get_full_dcf_valuation). I also fixed an issue on the startup with my backend server as fastapi was downgraded while starlette was upgraded. Additionally, I’ve finally made up my mind instead of using fmp by paying $19 a month, im going with yfinance’s free library. The switch made me change ALOT of Fmp code around. Lastly, I’ve started wiring the reflex frontend with the backend and wrote my “state” class. Overall I built new endpoints, changed previous ones, and worked on existing ones with major bug fixes in the middle.

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3h 40m 27s logged

Big frontend push this session. I finished building out all five core pages: Home, Markets, Watchlist, About, and Contact. I also wired up a shared navbar with real routing. The ticker research input now lives on the Markets page instead of Home, freeing up the homepage for additional details. Built out the Home page hero to match a Bloomberg Terminal-inspired design: a dark section with a faint SVG chart-line pattern behind the text, and an “Explore Markets” button that actually routes to /markets. Also I made a scrollable charts section In the top. Overall it was filled with a lot of complicated Reflex design and painful bugs. I’m going to connect the backend and frontend soon though.

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2h 43m 6s logged

Wrapped up the last piece of the core DCF math, then started the actual website since real cash flow data is still held behind the FMP Starter upgrade. I built the WACC math which ties into the Dcf calculation. Additionally, I have started my frontend by installing reflex and starting to work on the site itself. It’s still in it’s starting stages but took a lot of bug fixing.

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1h 49m 48s logged

Picked up where I left off with two small FMP cleanup items, then spent most of this session building the actual valuation math. Found out the $19/mo Starter tier does not extend that 5-year cap, it only unlocks the balance sheet/cash flow endpoints and more bandwidth. Every function got hand verified against math I worked out on paper before trusting the code, there is nothing that went in without me being able to explain why the numbers came out the way they did. I have much more screenshots, but didn’t have the time to paste them.

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1h 51m 1s logged

I built out functions to pull income statements, balance sheets, and cash flow statements straight from FMP, following the same pattern as my earlier company profile integration. Income statement worked immediately with real multi-year data for Apple. Balance sheet and cash flow both came back with a 404 though. Apparently, my free-tier FMP account likely doesn’t include full financial statement access, based on comparing their pricing page (that data seems to be behind their $19/mo Starter plan). Rather than paying right away, I’m holding off and treating this as a “figure out before launch” decision.

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1h 56m 30s logged

I finally built out my database session and my first company table model. Aditionally I also wrote a POST/ companies endpoint that takes data, validates it, and saves it to the database. Lastly after so much fixing I finally got a clean 200 response back with Microsoft’s data and a real database ID, so the full loop — request → validate → save → confirm — is working end to end now.

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1h 46m 25s logged

This is my first devlog for Investie. So far I finished installing all my requirements, I made a Fast API server with a few words on it. Additionally, I ended up getting a bunch of important files made that are needed for the project. Lastly, I signed up with SupaBase to launch my site through their network and use it for API key connections. The main part of today was debugging, which took a painfully long time.

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Built a credit risk model that predicts the probability of default for loan borrowers using logistic regression. The most challenging part was understanding why logistic regression works for this problem instead of linear regression — the sigmoid curve keeps outputs between 0 and 1, which is essential for probabilities. I’m proud of building a fully functional expected loss function from scratch that a real bank risk team could use. To test it, run the script with the CSV in the same folder and call expected_loss_func() with any borrower’s details to get their expected dollar loss.

  • 2 devlogs
  • 2h
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Built a natural gas contract pricing model in Python for the JPMorgan Chase Quantitative Research Virtual Experience (Task 2).

The model calculates the fair value of a storage contract where a client buys gas cheaply in summer, stores it, and sells it at a premium in winter. It accounts for every cash flow — purchase cost, sale revenue, monthly storage fees, and per-MMBtu injection/withdrawal costs.

The most challenging part was figuring out how to calculate storage duration in months from two datetime objects, and making sure the for loops were subtracting vs adding the right cash flows at the right time.

Proud that I built this line by line with a real understanding of what each piece does rather than just copying code.

To test it: download the executable from the release, make sure Nat_Gas.csv is in the same folder, and run it. You’ll see two contract valuations printed — one summer-to-winter trade worth $2,073,333 and one fall-to-winter trade worth $3,481,600.

  • 1 devlog
  • 2h
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