FlashAppAI

📚 Getting Started Guide

🚀 Quick Start

  1. Sign up for a free account - Get 3 CPU cores, 4GB RAM, and 50GB storage!
  2. Access your workspace from the dashboard with 4 main features:
    • 📊 Jupyter - Interactive notebooks for data science
    • 💻 VS Code - Full IDE for development
    • 📤 Upload Files - Transfer files from your computer
    • 🚀 Deploy Apps - Get public URLs for your apps
  3. Upload files from your laptop (.py, .ipynb, .csv, etc.)
  4. Develop in Jupyter or VS Code
  5. Deploy as Flask, Streamlit, or FastAPI app with one click
  6. Share your app URL: https://yourusername-appname.flashappai.org

🐍 Python Development

Creating Virtual Environments

# In VS Code terminal or Jupyter terminal
python3 -m venv myenv              # Create virtual environment
source myenv/bin/activate          # Activate on Linux/Mac
# or
myenv\Scripts\activate            # Activate on Windows

# Your prompt will change to show (myenv)
deactivate                         # To deactivate when done

Installing Packages

# Install individual packages
pip install pandas numpy matplotlib

# Install from requirements file
pip install -r requirements.txt

# Save current packages to file
pip freeze > requirements.txt

# Upgrade packages
pip install --upgrade package_name

Pre-installed Packages

Your environment comes with these packages pre-installed:

📊 Using Jupyter Notebooks

Keyboard Shortcuts

Installing Kernels

# Install Python kernel for your virtual environment
python -m ipykernel install --user --name=myenv

# List available kernels
jupyter kernelspec list

# Remove a kernel
jupyter kernelspec uninstall myenv

💻 VS Code Tips

Essential Shortcuts

Python Development

The Python extension is pre-installed! Features include:

📁 File Management

Your Workspace Structure

Your Workspace/
├── ide/          # VS Code projects
├── notebooks/    # Jupyter notebooks
└── apps/         # Future: deployed applications

Uploading Files

Downloading Files

📤 Uploading Files from Your Computer

How to Upload

  1. Click "Upload Files" on your dashboard
  2. Choose destination: Jupyter or VS Code workspace
  3. Drag & drop files or click to browse
  4. Files are instantly available in your workspace

Supported Files

🚀 Deploying Your Apps

One-Click Deployment

  1. Develop your app in Jupyter or VS Code
  2. Click "Deploy App" on dashboard or use File Manager
  3. Select your workspace (Jupyter/VS Code) and folder
  4. Choose app type (Flask/Streamlit/FastAPI)
  5. Enter file name (.py or .ipynb)
  6. Optionally select a specific requirements.txt file
  7. Get your public URL: https://username-appname.flashappai.org

📦 Dependency Management

🎯 Smart Dependency Detection

  • Automatic Import Detection: We scan your Python files and automatically install required packages
  • Framework Detection: Flask, Streamlit, FastAPI are automatically included based on app type
  • Smart Package Mapping: Common imports like 'sklearn' are mapped to correct pip names ('scikit-learn')

📋 Using requirements.txt

While dependencies are automatically detected, you can add a requirements.txt for additional packages or specific versions: 

# requirements.txt example
pandas==2.0.3
numpy>=1.24.0
requests~=2.31.0
matplotlib
seaborn
custom-package==1.2.3

💡 Multiple Requirements Files

  • Have multiple apps? Use different requirements files: app1-requirements.txt, app2-requirements.txt
  • Select the specific file during deployment in File Manager
  • Or specify the path in Dashboard deployment form

🔄 Deployment Options

Jupyter Notebook Deployment

NEW! Deploy .ipynb files directly - no conversion needed!

Streamlit App Example

import streamlit as st
import pandas as pd
import matplotlib.pyplot as plt

st.title("My Data App")
uploaded_file = st.file_uploader("Choose a CSV file")

if uploaded_file:
    df = pd.read_csv(uploaded_file)
    st.dataframe(df)
    
    fig, ax = plt.subplots()
    df.plot(ax=ax)
    st.pyplot(fig)

Flask App Example

from flask import Flask, jsonify
app = Flask(__name__)

@app.route('/')
def home():
    return "Welcome to my API!"

@app.route('/api/data')
def get_data():
    return jsonify({"message": "Hello World"})

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=5000)

FastAPI Example

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()

class Item(BaseModel):
    name: str
    price: float

@app.get("/")
def read_root():
    return {"Hello": "World"}

@app.post("/items/")
def create_item(item: Item):
    return item

🎯 Deployment Best Practices

⚡ Common Tasks

Clone a GitHub Repository

git clone https://github.com/username/repository.git
cd repository
pip install -r requirements.txt  # If Python project

Data Science Workflow

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt

# Load data
df = pd.read_csv('data.csv')

# Explore
df.head()
df.describe()
df.info()

# Visualize
plt.figure(figsize=(10, 6))
df.plot(kind='bar')
plt.show()

🔧 Troubleshooting

Common Issues

Getting Help

💡 Pro Tips