PySaaS is a complete SaaS starter kit built entirely in Python using the Reflex framework. It handles all the common functionality required for SaaS applications including authentication, billing, landing pages, and more - all without writing HTML, CSS, or JavaScript.
Key benefits include:
Save months of development time
Work entirely in Python for both frontend and backend
Includes authentication, billing, landing page, and blog components
Built on Reflex framework (formerly Pynecone)
Integrates with Supabase, Firebase, Lemon Squeezy, and Notion
Build a fully featured SaaS app with Primate.js and Svelte
Go
JavaScript
Python
Ruby
TypeScript
Angular
Handlebars
HTMX
Markdown
Marko
React
Solid
MongoDB
MySQL
PostgreSQL
SQLite
SurrealDB
Stripe
Analog
Next.js
Nuxt
Primate.js
Svelte
SvelteKit
Vue.js
Features:
API
Auth
Blog
CI/CD
Deployment
Docs
Emails
+7 more
Frequently Asked Questions
Python
What makes Python ideal for SaaS development?
Python excels in SaaS development due to its robust ecosystem, strong typing capabilities, and excellent library support. Python boilerplates leverage language-specific features to provide type-safe database queries, efficient API routing, and optimized runtime performance. The language's maturity means you get battle-tested packages for authentication, payment processing, and background jobs that integrate seamlessly.
Next.js
What Next.js-specific architecture patterns are implemented?
Next.js boilerplates leverage the framework's native architecture patterns including its routing system, middleware pipeline, and controller/handler structure. They implement Next.js's conventions for separating concerns, dependency injection, and service layer patterns. The codebase follows Next.js's best practices for organizing models, views/components, and business logic to ensure maintainability as your application grows.
Reflex
What Reflex-specific architecture patterns are implemented?
Reflex boilerplates leverage the framework's native architecture patterns including its routing system, middleware pipeline, and controller/handler structure. They implement Reflex's conventions for separating concerns, dependency injection, and service layer patterns. The codebase follows Reflex's best practices for organizing models, views/components, and business logic to ensure maintainability as your application grows.
Firestore
What Firestore-specific features are leveraged in these boilerplates?
Firestore boilerplates utilize the database's native capabilities including its transaction model (ACID for SQL, eventual consistency for NoSQL), indexing strategies (B-tree, GiST, full-text search), and advanced features like JSON columns, array types, window functions, or document queries. The schema design takes advantage of Firestore's strengths—whether that's PostgreSQL's JSONB, MySQL's full-text search, MongoDB's aggregation pipeline, or Redis's data structures.
SQLite
What SQLite-specific features are leveraged in these boilerplates?
SQLite boilerplates utilize the database's native capabilities including its transaction model (ACID for SQL, eventual consistency for NoSQL), indexing strategies (B-tree, GiST, full-text search), and advanced features like JSON columns, array types, window functions, or document queries. The schema design takes advantage of SQLite's strengths—whether that's PostgreSQL's JSONB, MySQL's full-text search, MongoDB's aggregation pipeline, or Redis's data structures.
Supabase
What Supabase-specific features are leveraged in these boilerplates?
Supabase boilerplates utilize the database's native capabilities including its transaction model (ACID for SQL, eventual consistency for NoSQL), indexing strategies (B-tree, GiST, full-text search), and advanced features like JSON columns, array types, window functions, or document queries. The schema design takes advantage of Supabase's strengths—whether that's PostgreSQL's JSONB, MySQL's full-text search, MongoDB's aggregation pipeline, or Redis's data structures.
Lemon Squeezy
What Lemon Squeezy API features are implemented?
Lemon Squeezy boilerplates implement the provider's complete API suite including checkout sessions, subscription lifecycle management, customer portal, webhook event handling, and invoice generation. They use Lemon Squeezy's latest API version with proper error handling, idempotency keys, and retry logic. The integration includes Lemon Squeezy-specific features like payment intents, setup intents, subscription schedules, and tax calculation APIs.
Python
What Python-specific tools and libraries are included?
Python boilerplates include the language's most popular and production-proven tools. This typically includes testing frameworks, linters, formatters, build tools, and package managers specific to Python. You'll get pre-configured toolchains that enforce best practices, automated testing pipelines, and development environments optimized for Python development workflows.
Next.js
How does Next.js's ORM/database layer work in these boilerplates?
Next.js boilerplates use the framework's native ORM or query builder (Prisma, Eloquent, Active Record, SQLAlchemy, etc.) with pre-configured models for users, subscriptions, teams, and common SaaS entities. They include optimized queries, relationships, migrations, seeders, and database connection pooling. The implementation leverages Next.js's specific features like eager loading, query scopes, and transaction handling for performance.
Reflex
How does Reflex's ORM/database layer work in these boilerplates?
Reflex boilerplates use the framework's native ORM or query builder (Prisma, Eloquent, Active Record, SQLAlchemy, etc.) with pre-configured models for users, subscriptions, teams, and common SaaS entities. They include optimized queries, relationships, migrations, seeders, and database connection pooling. The implementation leverages Reflex's specific features like eager loading, query scopes, and transaction handling for performance.
Firestore
How is the Firestore schema designed for SaaS applications?
Firestore boilerplates include production-tested schemas for multi-tenancy, user management, subscriptions, and billing. The design follows Firestore's best practices for data modeling—whether that's normalized tables with foreign keys (SQL), embedded documents vs. references (MongoDB), or partition key strategies (DynamoDB). Schemas include proper constraints, default values, and relationship management optimized for Firestore's query engine.
SQLite
How is the SQLite schema designed for SaaS applications?
SQLite boilerplates include production-tested schemas for multi-tenancy, user management, subscriptions, and billing. The design follows SQLite's best practices for data modeling—whether that's normalized tables with foreign keys (SQL), embedded documents vs. references (MongoDB), or partition key strategies (DynamoDB). Schemas include proper constraints, default values, and relationship management optimized for SQLite's query engine.
Supabase
How is the Supabase schema designed for SaaS applications?
Supabase boilerplates include production-tested schemas for multi-tenancy, user management, subscriptions, and billing. The design follows Supabase's best practices for data modeling—whether that's normalized tables with foreign keys (SQL), embedded documents vs. references (MongoDB), or partition key strategies (DynamoDB). Schemas include proper constraints, default values, and relationship management optimized for Supabase's query engine.
Lemon Squeezy
How are Lemon Squeezy webhooks handled securely?
Lemon Squeezy webhooks are verified using the provider's signature validation to prevent spoofing attacks. The boilerplate includes webhook endpoints with proper Lemon Squeezy signature verification, event type filtering, and idempotent event processing to handle duplicate deliveries. Events are processed asynchronously with retry logic, and the implementation handles Lemon Squeezy's specific webhook events like subscription updates, payment failures, and customer changes.
