Software Alternatives, Accelerators & Startups

QuickFS.net VS socketify.py

Compare QuickFS.net VS socketify.py and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

QuickFS.net logo QuickFS.net

Export historical financial statements to Excel for over 12,000 U.S.-listed stocks

socketify.py logo socketify.py

Maybe the fastest web framework for Python and PyPy
  • QuickFS.net Landing page
    Landing page //
    2023-05-08
  • socketify.py Landing page
    Landing page //
    2023-09-24

QuickFS.net features and specs

  • Comprehensive Data Coverage
    QuickFS.net offers extensive financial data coverage, including historical financial statements for public companies. This breadth of data allows users to conduct thorough financial analysis and comparisons.
  • User-Friendly Interface
    The platform is designed to be intuitive and easy to navigate, making it accessible for both novice and experienced users. The clean layout helps users find and analyze data efficiently.
  • Data Export Capabilities
    QuickFS.net allows users to export financial data into Excel spreadsheets for offline analysis. This feature is beneficial for users who require flexibility in data manipulation and reporting.
  • Frequent Updates
    The platform frequently updates its database to ensure that users have access to the latest financial information, which is crucial for making informed investment decisions.

Possible disadvantages of QuickFS.net

  • Limited to Public Companies
    The platform primarily focuses on financial data for publicly traded companies. Users looking for information on private companies might find QuickFS.net less useful.
  • Subscription Cost
    QuickFS.net requires a subscription for full access, which might be a barrier for individual investors or small businesses with limited budgets.
  • Data Presentation Limitations
    While the interface is user-friendly, some users may find the data presentation less customizable compared to more advanced financial analysis tools.
  • Limited Qualitative Data
    The platform focuses heavily on quantitative financial data, which might not satisfy users looking for qualitative insights such as company news or industry trends.

socketify.py features and specs

  • High Performance
    Socketify.py is designed for high scalability and performance, leveraging an efficient event loop and native extensions to handle a large number of concurrent connections efficiently.
  • WebSocket Support
    The library provides built-in support for WebSockets, making it suitable for real-time applications where persistent connections between client and server are necessary.
  • Asynchronous I/O
    Socketify.py is built on top of asynchronous I/O paradigms, allowing non-blocking operations that can improve the throughput of networked applications.
  • Ease of Use
    The library offers a clean and straightforward API with examples and documentation, which lowers the barrier to entry for developers who are new to network programming in Python.
  • Python Integration
    Being a Python library, socketify.py integrates well with existing Python applications and can be included as part of larger, multi-component systems.

Possible disadvantages of socketify.py

  • Limited Adoption
    As a relatively new or niche library, socketify.py might have a smaller user base and community compared to more established frameworks like Flask or Django, which could result in fewer community resources and third-party integrations.
  • Learning Curve
    For developers who are accustomed to synchronous programming paradigms, adapting to the asynchronous programming model of socketify.py may require an initial learning investment.
  • Documentation Depth
    While there is documentation, it might not be as extensive or comprehensive as those of more mature libraries, potentially requiring more experimentation or source code reading to fully grasp advanced features.
  • Potential Stability Issues
    Being less established, there might be undiscovered bugs or stability issues in production environments compared to long-standing Python networking libraries.
  • Ecosystem Limitations
    The library might lack some of the extensive third-party plugins or tools available in more popular frameworks, which could limit its extensibility.

Analysis of socketify.py

Overall verdict

  • Socketify.py is a solid choice for developers seeking a high-performance web framework in Python, particularly for I/O-bound applications requiring speed comparable to frameworks in compiled languages, thanks to its use of uWebSockets under the hood.

Why this product is good

  • Built on uWebSockets, providing significant performance improvements over traditional Python web frameworks
  • Supports WebSockets natively, making it suitable for real-time applications
  • Lightweight and minimalistic design reduces overhead
  • Compatible with ASGI, allowing integration with existing Python async ecosystem
  • Active development and growing community support on GitHub
  • Good for building high-throughput APIs and services

Recommended for

  • Developers building real-time applications like chat apps or live notifications
  • Projects requiring high concurrency and low latency in Python
  • Teams looking to replace slower WSGI-based frameworks with something faster
  • Applications needing WebSocket support without heavy framework overhead
  • Microservices architectures where performance is critical
  • Python developers wanting an alternative to Node.js for performance-sensitive tasks

Category Popularity

0-100% (relative to QuickFS.net and socketify.py)
Finance
100 100%
0% 0
Python
0 0%
100% 100
Investing
100 100%
0% 0
Web Development
0 0%
100% 100

User comments

Share your experience with using QuickFS.net and socketify.py. For example, how are they different and which one is better?
Log in or Post with

Social recommendations and mentions

Based on our record, QuickFS.net should be more popular than socketify.py. It has been mentiond 14 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

QuickFS.net mentions (14)

  • Source of financial statements for ASX Co's
    Try https://quickfs.net/ , they've got a free option which is pretty handy. Source: over 3 years ago
  • APIโ€™s for Financial Analysis?
    I use quickfs.net, which is one of the more expensive options at $35/month but it allows me to create a decent summarized view on google sheets. I can take a printout of this one pager and scribble notes on it. The data is inaccurate at times. So you definitely need to read the 10Ks if you plan to do a deep dive on a company. Source: over 3 years ago
  • Stock comparasion
    Besides quickfs.net, you can check dataroma.com and tikr.com. I use all tree of then! Source: almost 4 years ago
  • Does it make sense to calculate ROIC this way?
    I do everything in excel. Using tools like quickfs.net, or wisesheets may help you for pulling in data and being able to analyze things more quickly. Accrued exp, taxes payable, and AP are part of working capital as they are non-interest-bearing liabilities. Working capital excludes excess cash and financing items. You'd probably benefit from reading the Valuation book by Koller and anything you can find only... Source: almost 4 years ago
  • DCF model question: Interest Expense
    I hope someone here might be able to point me int he right direction. I am working with a DCF spreadsheet I got, and trying to work through the numbers. One of the inputs is "Interest Expense", but none of the sites I use for historical financial data (barchart.com and quickfs.net) have that as a line item, and while Yahoo finance does have it, their data just gives me three years (I need 4 or 5). Source: almost 4 years ago
View more

socketify.py mentions (2)

  • Show HN: Python framework is faster than Golang Fiber
    These "benchmarks" are useless, they're not testing anything real world except the performance of uWebsockets. There are copy errors all over the place. And then an advertisement: https://github.com/cirospaciari/socketify.py#briefcase-comme... Is this a professional framework that produces proper, real-world benchmarks and... - Source: Hacker News / over 3 years ago
  • This is how I started the development of the fastest ASGI and WSGI Server in TechEmPower Benchmarks
    After starting the project called socketify.py at https://github.com/cirospaciari/socketify.py, I got pretty good results and reviews, but many people asked if socketify.py could be used to create a WSGI and ASGI server. WSGI and ASGI have a lot of overhead, that's is why I choose not to use them in the first place, but adding an ASGI and WSGI server allows a lot of code already written to run faster! Source: over 3 years ago

What are some alternatives?

When comparing QuickFS.net and socketify.py, you can also consider the following products

finbox.io - Online investing tools that makes it faster & easier to find undervalued stocks.

Alpha Spread - Powerful stock valuation platform. Automatic stock valuation under various scenarios. Intrinsic & Relative valuation. Wall Street analysts estimates.

Gurufocus - Historical financial data and insider holdings

Discounting Cash Flows - Automate your stock analysis process using our fully customizable valuation models and extensive global financial data.

Simply Wall Street - Easy stock and portfolio analysis

DiscoverCI - DiscoverCI offers stock analysis, stock research, and stock valuation software to help investors win in the market. Get started with our free tools.