Streamlit is an open-source Python framework for building interactive web applications, especially for data science, machine learning, analytics, and dashboards.
You can create a web app with only a few lines of Python, without needing HTML, CSS, or JavaScript.
Example
import streamlit as st
st.title(“My First Streamlit App”)
name = st.text_input(“Enter your name”)
if name:
st.write(f”Hello, {name}!”)
Run it with:
streamlit run app.py
This automatically opens a web page where users can interact with your app.
Common Features
Text and markdown display
Interactive widgets:
Buttons
Sliders
Text inputs
Dropdowns
Checkboxes
Data tables and charts
File uploads
Machine learning model interfaces
Real-time updates
Typical Use Cases
Data dashboards
Machine learning demos
Data exploration tools
Internal business applications
AI chatbot interfaces
Research prototypes
Why It’s Popular
Very easy to learn
Pure Python development
Fast prototyping
Integrates well with libraries like:
NumPy
Pandas
Matplotlib
Plotly
Scikit-learn
PyTorch
TensorFlow
Streamlit is maintained by Snowflake and is widely used for turning Python scripts into shareable web applications quickly.
If you’re interested, I can also show how Streamlit compares to frameworks like Flask, Django, or FastAPI.
which web frame is best to develop like app tricentis tosca
Building something like Tricentis Tosca is not really a “single web framework” decision — it’s a full enterprise platform problem (web UI + backend orchestration + test execution engine + distributed services).
So the right answer is: you need a stack, not one framework.
🧠 First: what Tosca actually is (simplified)
Tosca-style tools typically include:
Web-based UI (test design, drag-drop flows)
Backend services (test orchestration, scheduling)
Execution engine (runs tests on agents/machines)
Database (test cases, results, history)
Integrations (CI/CD, Selenium, APIs, etc.)
So you’re building more like a platform, not a website.
🏆 Best practical architecture (modern + scalable)
1. Backend (core logic layer)
Best options:
✅ FastAPI (recommended)
FastAPI
Very fast performance
Great for APIs
Easy async (important for test execution jobs)
Modern and widely used for microservices
👉 Best for:
Test orchestration APIs
Execution triggers
CI/CD integrations
Alternative: Django
Django
Batteries-included (auth, admin panel, ORM)
Strong for monolithic enterprise apps
👉 Best if you want:
Built-in admin UI
Faster full-stack development early stage
2. Frontend (UI like Tosca Studio)
You do NOT use Python frameworks here.
✅ React (most common choice)
Highly interactive UI (drag/drop test flows)
Huge ecosystem
Works well with APIs
You’ll likely also use:
Redux / Zustand (state management)
React Flow (for workflow diagrams like Tosca)
Alternatives:
Angular (very enterprise-heavy, structured)
Vue (simpler, lighter)
👉 If you want Tosca-like experience → React is the best fit
3. Background processing (VERY important)
Tosca-like systems run jobs asynchronously.
Recommended:
Celery + Redis (classic Python stack)
Or Kafka (for large scale distributed execution)
Used for:
Running tests
Scheduling jobs
Parallel execution on agents
4. Test execution layer (core differentiator)
This is what makes Tosca “Tosca”.
You’ll need:
Agent-based runners (on VM/container)
Docker/Kubernetes for scaling
Message queue system
Tools:
Docker
Kubernetes
RabbitMQ / Kafka
Selenium / Playwright (if UI testing)
🧩 Suggested “Tosca-like” stack
⭐ Best balanced architecture:
Frontend: React
Backend API: FastAPI
Async jobs: Celery + Redis
DB: PostgreSQL
Execution layer: Docker + worker agents
Optional scaling: Kubernetes
⚖️ Simple decision guide
Goal Best choice
Fast API backend FastAPI
Enterprise monolith Django
Complex UI (drag/drop workflows) React
Simple internal tool Django + templates
High-scale distributed execution FastAPI + Celery + Kubernetes
🚨 Important reality check
A Tosca-like product is:
❌ Not “a web framework project”
✅ A distributed software platform
The hardest part is NOT the web framework — it’s:
execution engine design
scalability
reliability
test orchestration logic
If you want, I can help you next with:
Architecture diagram for a Tosca-like system
Database schema for test cases & execution
How to design drag-and-drop test builder (like Tosca modules)
MVP plan (what to build first in 2–4 weeks)
Just tell me 👍
yes
Great — I’ll lay out a practical MVP blueprint for building a Tosca-like system (simplified, but real and buildable).
🧱 1. MVP Goal (what you are actually building)
Think of this first version as:
A web app where users can create test cases → run them → see results
Not full Tosca yet. Just the core loop.
🏗️ 2. MVP Architecture (simple but scalable)
🔷 Frontend (UI)
React
React Flow (for visual test steps)
🔷 Backend API
FastAPI
🔷 Database
PostgreSQL
🔷 Job execution
Celery + Redis
🔷 Test runner (agent)
Python worker service (can run Selenium / API tests)
🔄 3. Core Workflow
User creates test case (UI)
↓
Stored in PostgreSQL
↓
User clicks “Run”
↓
FastAPI sends job → Redis queue
↓
Celery worker picks job
↓
Execution engine runs test
↓
Results stored in DB
↓
Frontend displays report
🧩 4. MVP Features (build only these first)
✅ A. Test Case Builder (UI)
Create test case
Add steps:
Open URL
Click element
Input text
Validate text
👉 Store as JSON like:
{
“name”: “Login Test”,
“steps”: [
{ “action”: “open_url”, “value”: “https://app.com” },
{ “action”: “type”, “selector”: “#username”, “value”: “admin” },
{ “action”: “click”, “selector”: “#login” }
]
}
✅ B. Test Execution Engine (core logic)
Python runner:
def run_step(step):
if step[“action”] == “open_url”:
browser.get(step[“value”])
elif step[“action”] == “click”:
browser.find_element(“css selector”, step[“selector”]).click()
elif step[“action”] == “type”:
el = browser.find_element(“css selector”, step[“selector”])
el.send_keys(step[“value”])
(You can use Selenium or Playwright)
✅ C. Backend API (FastAPI)
Endpoints:
POST /testcases
GET /testcases
POST /run/{id}
GET /results/{id}
✅ D. Job Queue (Celery)
Runs tests asynchronously
Stores status: running / passed / failed
✅ E. Results Dashboard
Show:
Passed/failed steps
Logs
Execution time
🧠 5. Data Model (important)
TestCase
id
name
steps (JSON)
TestRun
id
test_case_id
status
started_at
finished_at
StepResult
test_run_id
step_index
status
error_message
🖥️ 6. UI Pages (React)
1. Dashboard
List test cases
Run button
2. Test Builder
Drag-drop steps (React Flow)
3. Execution results
Step-by-step report
⚙️ 7. Tech Stack Summary
Layer Tech
UI React + React Flow
API FastAPI
DB PostgreSQL
Queue Redis
Worker Celery
Execution Selenium / Playwright
🚀 8. Build Plan (realistic)
Phase 1 (Week 1–2)
FastAPI backend
Save test cases
Simple React UI
Phase 2 (Week 3)
Add execution engine
Run tests manually
Phase 3 (Week 4)
Celery async execution
Results dashboard
🔥 9. What makes this “Tosca-like” later
After MVP, you can evolve into:
Drag-drop reusable modules
Keyword-driven testing
Distributed execution agents
CI/CD integration (Jenkins/GitHub Actions)
AI test generation
⚠️ Honest insight
Building full Tricentis Tosca level system is multi-year enterprise work, but this MVP is exactly how such platforms start.