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Install Python (version 3.9 to 3.13 for Streamlit support [2025/03/01]) - 3.12 max for tensorflow support
Follow installation guide for Streamlit a. Type python -m venv .venv in the terminal (This will create a ".venv" directory where your virtual environment and its dependencies are installed.) b. Activate environment by typing source .venv/bin/activate in terminal (MacOS) c. Type pip install -r requirements.txt in terminal to install all requirements.
Type streamlit run Start.py to run the main page of the app!

Download MongoDB driver - PyMongo - with python -m pip install "pymongo[srv]"==3.12 to talk with MongoDB database
Install Python certificate using /Applications/Python\ 3.13/Install\ Certificates.command

Name		Name	Last commit message	Last commit date
Latest commit History 35 Commits
.devcontainer		.devcontainer
.streamlit		.streamlit
assets		assets
original_csvs		original_csvs
pages		pages
.gitattributes		.gitattributes
.gitignore		.gitignore
Landing.py		Landing.py
Login.py		Login.py
README.md		README.md
Report.py		Report.py
Start.py		Start.py
Top10.py		Top10.py
algorithm.py		algorithm.py
all_crypto_quarterly.csv		all_crypto_quarterly.csv
all_etf_quarterly.csv		all_etf_quarterly.csv
all_technical_indicators_stocks.csv		all_technical_indicators_stocks.csv
combined_financial_data.csv		combined_financial_data.csv
crypto_technical_indicators.csv		crypto_technical_indicators.csv
database.py		database.py
etf_technical_indicators.csv		etf_technical_indicators.csv
fundamental.py		fundamental.py
macro.py		macro.py
macro_data.csv		macro_data.csv
priceinfo.py		priceinfo.py
requirements.txt		requirements.txt
sentiment_crypto.csv		sentiment_crypto.csv
sentiment_etfs.csv		sentiment_etfs.csv
sentiment_yf.py		sentiment_yf.py
shell_user.py		shell_user.py
stock_fundamentals.csv		stock_fundamentals.csv
stock_sentiment_data.csv		stock_sentiment_data.csv
technical_indicators.csv		technical_indicators.csv
testing.py		testing.py
trainedml_crypto.py		trainedml_crypto.py
trainedml_etf.py		trainedml_etf.py
trainedml_stocks.py		trainedml_stocks.py