Streamlit Random Apps

Made with ❤️ from Gar's Bar

• Streamlit Random Apps
  • 🎯 Darts API Playground
  • 🔗 URL Scanner
  • 🥞 WSGI Stack vs Streamlit
  • 🎸 Guitar Tuner
  • 💻 Streamlit Full Stack 3 Ways
    • 🐭 Littlest
    • 🐘 Postgres Version
    • 🐀 Go Backend Version
  • 📈 Fidelity / Personal Stock Account Dashboard
  • 🗻 Peak Weather: NH 4,000 Footers
  • 🐼 Pandas Power
  • ✍🏻 Text Recognition Dataset Generator App
  • 🐙 Github Lines of Code Analyzer
  • 📚 AWS Textract Document Text Scan
  • 💰 Roommate Spending Ledger Visualization
  • Darts Intro
  • Function to Streamlit Form
  • PDF Merge and Split Utility
  • Python Web Form Generator
  • Basic File Drop
  • Gif Maker

🎯 Darts API Playground

Explore the Datasets, Metrics, and Models of the Darts Time Series library.

See: Github Repo

🔗 URL Scanner

Using AWS Rekognition + Streamlit to provide interactive OCR URL Scanner / Text Extraction on real world images.

See: Github Repo

🥞 WSGI Stack vs Streamlit

Comparing an interactive web app built with bottle + htmx to the same idea built with streamlit.

In folder wsgi_comparison

🎥 Watch: Youtube Breakdown ✍🏻 Read: Blog Post

Left: ~50 lines of Python and HTML

Right: ~15 lines of Python

🎸 Guitar Tuner

Simple guitar tuner powered by streamlit-webrtc

💻 Streamlit Full Stack 3 Ways

Demo of Full Stack Streamlit Concept. Deployed with 3 increasingly complicated backends.

See: Github Repo

🐭 Littlest

🐘 Postgres Version

🐀 Go Backend Version

📈 Fidelity / Personal Stock Account Dashboard

Upload a CSV export from Fidelity investment account(s) and visualize profits and losses from select tickers and accounts.

See: Github Repo

💰 Personal Spending Dashboard

Upload a CSV or excel with at least a date column and spending amount column to analyze maximum and average spending over different time periods.

🗻 Peak Weather: NH 4,000 Footers

Use async http request library httpx to make 48 api calls roughly simultaneously in one Python process. Feed a dashboard of weather for all 4,000 foot mountains in New Hampshire.

See: Github Repo

🐼 Pandas Power

Demoing useful functionalities of Pandas library in a web app.

Currently:

• read_html: Parse dataframes from html (url, upload, or raw copy+paste)

✍🏻 Text Recognition Dataset Generator App

Putting a frontend on TRDG CLI tool. Primary goal: creating classic videogame text screenshots with known ground truth labels

🐙 Github Lines of Code Analyzer

Shallow clone a repo then use unix + pandas tools to count how many lines of each file type are present

streamlit run github_code_analyze.py

📚 AWS Textract Document Text Scan

Using AWS Textract + S3 + Streamlit to provide interactive OCR Web App.

See: Github Repo

💰 Roommate Spending Ledger Visualization

Using Pandas + Plotly + SQLite to show a full stack use case of Time Series Data. Analyze spending over time per person (could be adapted to categories / tags / etc).

See: Github Repo

Darts Intro

~1 for 1 exploration of Darts quick start with Streamlit + some interactive forecasting of Uploaded CSV.

Exploring Time Series in: Github Repo

Function to Streamlit Form

Powered by Streamlit-Pydantic. Utilizes inspect.signature to build an input class to a function definition.

What's the point?

Even more rapid development!

Take any CLI or other functional API and create an input form for them. Encourage developers to write accurate type hints ;)

from inspect import Parameter
import streamlit as st
import streamlit_pydantic as sp
from inspect import signature
from pydantic import create_model


def crunch_the_numbers(ticker: str, num_periods: int = 10) -> dict:
    return {"ticker": ticker, "value": num_periods * 100.00}

pydantic_fields = {
    x.name: (
        (x.annotation, ...)
        if x.default == x.empty
        else (x.annotation, x.default)
    )
    for x in signature(crunch_the_numbers).parameters.values()
}
PydanticFormModel = create_model("PydanticFormModel", **pydantic_fields)

input_col, output_col = st.columns(2)
with input_col:
    data = sp.pydantic_form(key="some_form", model=PydanticFormModel)
if data:
    output_col.json(crunch_the_numbers(**data.dict()))

PDF Merge and Split Utility

Powered by pypdf2 library, feel free to use reportlab or something else.

JPG or PNG output optionally, powered by pdf2image (requires brew insall poppler / apt install poppler-utils or conda install -c conda-forge poppler? github)

Combines multiple PDFs into a single PDF or splits a single PDF into multiple PDFs.

Python Web Form Generator

Powered by Streamlit-Pydantic. Generate a Streamlit web form UI + Pydantic models from an example JSON data structure.

See: Github Repo

Basic File Drop

Not live, as there is no point.

Make a web frontend that you can access from local network and drop any number of files to host computer! All in ~10 lines of code.

import streamlit as st
from pathlib import Path

files = st.file_uploader("uploads", accept_multiple_files=True)
destination = Path('downloads')
destination.mkdir(exist_ok=True)

for f in files:
    bytes_data = f.read()
    st.write("filename:", f.name)
    st.write(f"{len(bytes_data) = }")
    new_file = destination / f.name
    new_file.write_bytes(bytes_data)

Gif Maker