Agile deployment platform for Ruby, Node.js, Clojure, Java, Python, and Scala. Setup takes only minutes and deploys are instant through git. Leave tedious server maintenance to Heroku and focus on your code.
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Which is more popular?
Based on our record, Heroku
seems to be a lot more popular than Stackless Python.
While we know about 74 links to Heroku,
we've tracked only 3 mentions of Stackless Python.
social mentions
74 vs 3
Cloud Computing popularity
100% vs 0%
alternatives listed
240+ vs 5
Base details
Website, pricing, platforms and company facts side by side.
Ease of Use Heroku offers an extremely user-friendly interface and a high level of abstraction, making it easy for developers to deploy, manage, and scale applications without worrying about the underlying infrastructure.
Quick Deployment One of Heroku’s strongest points is the ability to deploy applications quickly using Git. Developers can push their code to Heroku with a simple command, streamlining the entire process.
Scalability Heroku provides effortless scaling options by allowing developers to add more dynos (containers) with a single command to handle increased traffic and workload.
Add-Ons Ecosystem Heroku offers a rich ecosystem of add-ons, such as databases, caching, monitoring, and more, which can be easily integrated into applications to extend their functionality.
Automatic Updates Heroku automatically handles operating system and server updates, allowing developers to focus solely on their application code rather than maintenance tasks.
Free Tier Heroku offers a free tier with sufficient resources to host small projects and learn the platform without incurring costs, making it accessible for beginners and small-scale applications.
Possible disadvantages
Cost While Heroku offers a free tier, the costs can quickly add up for larger applications and professional use. Paid plans and additional dynos or add-ons can become expensive.
Performance Heroku’s performance can sometimes be suboptimal compared to other cloud providers, particularly when running high-performance or resource-intensive applications.
Limited Control Heroku abstracts away a lot of infrastructure management, which can be a downside for developers who need fine-grained control over their environments and configurations.
Dyno Sleeping Applications running on Heroku’s free tier experience 'dyno sleeping,' where the application goes to sleep after 30 minutes of inactivity, causing a delay when it wakes up after receiving a new request.
Vendor Lock-In Relying heavily on Heroku’s ecosystem and platform-specific features can lead to vendor lock-in, making it challenging to migrate to another platform if needed.
Add-On Costs The costs for add-ons can also become significant, as many useful features and integrations require paid add-ons, increasing the overall expense.
Efficient Concurrency Stackless Python provides microthreads, also known as tasklets, which offer efficient concurrency by allowing multiple tasks to run in a single thread without the overhead of traditional threading.
Simplified Code The microthreading model can lead to simplified code when compared to multithreading, as it avoids the complexities associated with locks and synchronization primitives.
Improved Performance Due to the avoidance of context switching between OS-level threads, Stackless Python can achieve improved performance for I/O-bound applications.
Flexibility Stackless Python allows developers to pause and resume functions at almost any point, providing great flexibility for creating advanced flow control mechanisms.
Low Memory Footprint Tasklets in Stackless Python are lightweight, leading to a lower memory footprint compared to traditional threading models.
Possible disadvantages
Compatibility Stackless Python may face compatibility issues with certain Python libraries and extensions that are not designed to work with its microthreading model.
Limited Community and Support Stackless Python has a smaller user base compared to standard Python, which can result in limited community support and fewer resources for learning and troubleshooting.
Platform Limitations Some platforms may not fully support or benefit from Stackless Python's features due to differences in underlying system architectures.
Debugging Challenges Debugging can be more challenging in Stackless Python due to its non-standard execution model, requiring developers to understand its unique flow control mechanisms.
Maintenance and Updates Since Stackless Python diverges from the standard Python implementation, it may lag in adopting new features and updates present in the latest Python releases.
Analysis
An editorial look at what each product does well and who it suits.
HerokuStackless Python
Overall verdict
Heroku is a solid choice for developers seeking a straightforward, cloud-based solution for deploying and managing applications. However, it may not be the most cost-effective option for large-scale or data-intensive applications.
Why this product is good
Heroku is a popular platform as a service (PaaS) due to its ease of use, fast deployment process, and robust support for multiple programming languages. It allows developers to focus on building applications without worrying about the underlying infrastructure. Heroku offers scaling capabilities, a wide variety of add-ons, and a strong developer community.
Recommended for
Heroku is recommended for startups, small to medium-sized applications, hobby projects, and developers who value ease of use and quick deployment cycles. It is particularly suited for those who are developing web applications in languages such as Ruby, Node.js, Python, and others supported by the platform.
Overall verdict
Stackless Python is a solid, mature alternative Python implementation that excels at massive concurrency through lightweight microthreads (tasklets), making it a good choice for specific concurrent and cooperative multitasking workloads, though its niche status means smaller community support compared to CPython.
Why this product is good
Provides tasklets (microthreads) that allow hundreds of thousands of concurrent tasks with very low memory overhead
Offers channels for clean, safe communication and synchronization between tasklets without traditional locking headaches
Supports cooperative and preemptive scheduling, giving developers fine-grained control over concurrency
Enables serialization (pickling) of running tasklets, which is powerful for saving and migrating program state
Proven in production at scale, most famously powering the MMO game EVE Online
Largely maintains compatibility with standard CPython code and libraries
Recommended for
Developers building highly concurrent applications requiring massive numbers of lightweight threads
Game servers and simulations needing efficient cooperative multitasking (like EVE Online's use case)
Projects that benefit from tasklet serialization for state migration or persistence
Systems programmers exploring alternatives to threads or async frameworks for concurrency
Users comfortable working with a specialized Python distribution outside the mainstream CPython ecosystem
Heroku provides a developer-focused platform for the needs of simplified application deployment, including managed, easy-to-use PostgreSQL databases. It comes with intuitive tools and integrations, which can be...
SnapDeploy offers 100 free hours that never expire (Heroku has no free tier). Paid plans start at $9/month. Heroku's Eco dyno starts at $5/month but sleeps after 30 minutes; production-ready Standard dynos start at...
Heroku’s focus on simplicity and developer experience makes it a perfect fit for those who want to focus on building their apps, not babysitting servers. Startups and small businesses, in particular, can benefit from...
Title: [TIL][Python] Online PDF Page-by-Page Viewing and Comparison Tool for Importing Data (Python online PDF Viewer and comparison) and Python Snippets
Published: false
Date: 2023-08-04 00:00:00 UTC
Tags:
Canonical_url:...
- Source: dev.to
/
over 3 years ago
Review Apps run the code in any GitHub PR in a complete, disposable Heroku application. Review Apps each have a unique URL you can share. It’s then super easy for anyone to try the new code.
- Source: dev.to
/
over 2 years ago
Client uses a ton of Python too, mind you they have a very special interpreter. https://github.com/stackless-dev/stackless/wiki/.
- Source: Hacker News
/
about 4 years ago
How does Go "know" when a goroutine hits IO and can switch to another goroutine? Why don't other languages like Javascript/Python do this?
For the sake of “well, actually” completionism, this is possible in Python with stackless or the gevent library and some hacks, but when Guido and pals backed the standard awful way of doing async in commercial languages (async/await and...
Source:
about 4 years ago
How to Choose the Right Python Concurrency API
Is stackless still an alternative? (It used to be quite hot 1.5 decade ago) https://github.com/stackless-dev/stackless/wiki/.
- Source: Hacker News
/
about 4 years ago
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When comparing Heroku and Stackless Python, you can also consider the following products.
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