PythonAnywhere vs Blossom: A Detailed Comparison

PythonAnywhere and Blossom take fundamentally different approaches to their platforms.

PythonAnywhere specializes in Python-specific hosting with a strong emphasis on browser-based file editing and development. Blossom supports more than Python - it can deploy any language to any server.

PythonAnywhere

PythonAnywhere is a unique product that I find fascinating. It’s really designed for beginners and students who are learning Python. You can use a bash console, Python REPL, and upload your files directly in the browser. This is really great when you’re getting started and learning. What’s particularly interesting about PythonAnywhere is that you literally upload your app files within the browser — it feels like an FTP experience. To upload multiple files, you can upload a zip file and use their browser-based console to unzip it to the right folder. Again, it’s completely geared toward beginners.

Git Integration

Even though the main way to update your app is with the browser-based file management system, there are ways to set it up so that your project pulls from a git repository, but they are hacky:

• Git push deployments on PythonAnywhere: You set up a bare git repo with a server-side git post-receive hook. This mimics what Heroku does with git push heroku main.
• Syncing GitHub with PythonAnywhere: This approach is quite clever but definitely also hacky — you add a /webhook endpoint to your app and register it as a GitHub webhook to ping it on a git push.

This is additional manual work you have to do per app.

Performance and Limitations

PythonAnywhere can handle a lot of Python sites. Interestingly, they were way ahead of the container game, having used LXC containers early on before Docker. They use containerization to limit CPU usage. See this comment: Reddit: I was reportedly at the top of their CPU usage charts. The founder mentions that the user was running “big CPU-intensive tasks” which their platform will limit. This is not unique to PythonAnywhere. Most platforms will limit CPU to prevent noisy neighbors from degrading performance for other users on the same server.

PythonAnywhere supports specific versions of Python and may not support the version you want or need to use. See: Reddit: PythonAnywhere.com Alternatives for examples of this limitation. Remember, PythonAnywhere does not ship a Docker image that you can build and control, so you’re restricted to their official language and framework versions.

Worker Process Limitations

PythonAnywhere has significant limitations when it comes to running background worker processes like Celery. According to their forum discussion on Celery support, while you can technically install Celery, running worker processes is problematic:

• Processes in consoles can stop at any time due to system upgrades or server issues (about once a week)
• No guarantee of process persistence for long-running background tasks
• Workarounds involve using scheduled tasks to check if workers are running, which is hacky and unreliable
• Limited support for proper background job processing architectures

Pricing Structure

PythonAnywhere’s plans are based on CPU-seconds. Here’s a snapshot of one of their pricing plans:

$99/mo - 1,000,000 hits/day website on each web app. 10,000 CPU-seconds per day for consoles, scheduled tasks and always-on tasks.

What does that mean in terms of server resources? ChatGPT estimates that it’s probably equivalent to a 4GB 2CPU server, which you can get on Hetzner for $5/mo. That’s a 20x premium. Take ChatGPT’s analysis for what it’s worth, though.

Key Features Summary

Here’s a summary of PythonAnywhere’s key features:

• Purpose-built for Python applications and development
• Deployment with LXC containers even before the invention of Docker
• Pre-configured Python environment with common packages
• Built-in support for Django, Flask, web2py and Bottle
• CPU usage limits on different tiers
• Free tier available with subdomain hosting
• Excellent for Python learning and teaching
• Limited to Python-only applications
• Runs on AWS infrastructure underneath the hood
• Good for small to medium Python projects

Blossom

Blossom is a SaaS platform that fundamentally differs in approach and functionality.

Deployment Approach

Instead, Blossom connects to your git repository and deploys when you git push or when you click deploy from the UI. It works more like other modern hosting providers with git-based workflows and a developer-focused UX.

Infrastructure Management

Additionally, Blossom provisions and manages servers, allowing you to create a fully functional, highly available cluster with multiple servers and a load balancer with a single click. It also sets up VPCs and firewalls to harden infrastructure security.

Container Technology

Blossom builds Docker images and deploys them. Note that a Dockerfile is entirely optional for Blossom. Blossom employs heuristics to automatically build and deploy your application without requiring a Dockerfile. However, you can still use a Dockerfile if you need additional customizations. Blossom offers multiple ways to build your Docker image: automatic detection, Heroku Buildpacks, Railway Nixpacks, static sites, or by using a pre-built Docker image.

Blossom utilizes Docker Compose, which simplifies understanding how containers are running. It also provides the ability to scale processes up and down, offering another layer of scalability.

Process Flexibility

Blossom does not have any limitations with worker processes. You can run any type of process you need with a Procfile. This includes:

• Background worker processes like Celery workers
• Queue processors and job runners
• Scheduled tasks and cron jobs
• Database maintenance processes
• Custom daemons and long-running services

Since Blossom gives you more control over your environment, you can run these processes reliably.

Pricing Structure

Blossom is pay-to-play, it’s not free. Its pricing structure can result in significant cost savings compared to other hosting providers.

Key Features Summary

Here’s a summary of Blossom’s key features:

• Language & Infrastructure Agnostic: Deploy any language or framework to any server or cloud provider.
• Fully Managed PaaS: Modern UI with git-based deployments for seamless workflows.
• Flexible Build Options: Supports Automatic Detection, Buildpacks, Nixpacks, Dockerfile, Static Sites, or pre-built images.
• Containerized Environment: Ubuntu-based host OS with Docker Compose for orchestration, offering excellent application isolation and consistent environments without arbitrary resource limits.
• Full Server Control: Provides complete SSH access for deeper management.
• Predictable Pricing: Offers a 5-day free trial and straightforward per-server pricing with significant cost savings.

Quick Comparison

Conclusion

PythonAnywhere is an interesting option for deploying Python applications—it’s especially designed for beginners. The free tier is nice for getting started and will work great for small projects. Once you start to scale, the paid plans can add up in costs due to their CPU-seconds pricing model.

Blossom offers a more general platform that can handle any type of application—not just Python. It provides more control and flexibility with full SSH access and support for multiple cloud providers, making it ideal for teams who need easy deployment with predictable pricing and without resource quotas.