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Twelve Data VS socketify.py

Compare Twelve Data VS socketify.py and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Twelve Data logo Twelve Data

The simplest and most effective way to access both realtime and historical stock, forex, cryptocurrency data, and over 100 technical indicators.

socketify.py logo socketify.py

Maybe the fastest web framework for Python and PyPy
  • Twelve Data Landing page
    Landing page //
    2023-09-23
  • socketify.py Landing page
    Landing page //
    2023-09-24

Twelve Data features and specs

  • Comprehensive Data Coverage
    Twelve Data provides access to a wide range of financial data including real-time and historical data for stocks, ETFs, mutual funds, indices, and forex, which is beneficial for comprehensive market analysis.
  • Affordable Pricing
    Twelve Data offers a variety of pricing plans, including a free tier with essential features, which makes it accessible to individual developers and small businesses.
  • Ease of Use
    The API is designed to be user-friendly with well-documented endpoints, making it easy for developers to integrate the service into their applications.
  • High Scalability
    Twelve Data offers robust and scalable API solutions that can handle a large volume of requests, suitable for both small projects and large-scale applications.
  • Global Market Coverage
    The platform provides data from global markets, allowing users to access information from multiple exchanges around the world.

Possible disadvantages of Twelve Data

  • Limited Advanced Features
    While Twelve Data offers a wide range of basic and intermediate features, it may lack some of the advanced analytics and tools needed by experienced traders or larger financial institutions.
  • Rate Limits on Lower Tiers
    The free and lower-tiered plans come with rate limits that can be restrictive for users requiring frequent data access or handling high traffic.
  • Dependency on API Availability
    As with any third-party data provider, users are dependent on the API's uptime and reliability, which can impact applications if there are outages or downtime.
  • Potential Data Lag for Free Plan
    Users on the free plan may experience delays or less frequent updates compared to those on paid plans, which can be a drawback for time-sensitive applications.

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

Twelve Data videos

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Twelve Data Demo Review

socketify.py videos

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Category Popularity

0-100% (relative to Twelve Data and socketify.py)

Twelve Data

socketify.py

Finance
100 100%
Finance
0% 0
Python
0 0%
Python
100% 100
APIs
100 100%
APIs
0% 0
Web Development
0 0%
Web Development
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Twelve Data and socketify.py

Twelve Data Reviews

  1. Andrew
    Best API for real-time financial data

    Straightforward to use and powerful API to get financial data in real-time and complete historical data. Best in class Python package.

    ๐Ÿ Competitors: Alpha Vantage, Polygon.io
    ๐Ÿ‘ Pros:    Equity data|Forex|Crypto|Affordable|Reliable

socketify.py Reviews

We have no reviews of socketify.py yet.
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Social recommendations and mentions

Based on our record, Twelve Data should be more popular than socketify.py. It has been mentiond 9 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.

Twelve Data mentions (9)

  • I Wanted Real-Time Stock Charts on My Garmin Watch. Monkey C Had Other Plans.
    I chose Twelve Data for stock and crypto prices. Free tier: 800 calls per day. My math: 5 symbols ร— 96 fetches/day (every 15 minutes) = 480 calls. Comfortable margin. - Source: dev.to / 12 days ago
  • Building a Gold (XAUUSD) Trend Tracker with Python and SQLite
    I am using TwelveData forex API for Extraction of raw data from the financial markets in JSON format. - Source: dev.to / about 1 year ago
  • Top 5 Free Financial Data APIs for Building a Powerful Stock Portfolio Tracker โšก
    Twelve Data provides extensive financial market coverage, making it ideal for those looking for a free API for building a stock portfolio tracker. - Source: dev.to / over 1 year ago
  • Webflow Crypto Market Data Ticker
    I'd suggest Twelve Data for the financial data feed, if you have a budget for this: https://twelvedata.com/. Source: over 2 years ago
  • Where can I find a free source of historical S&P500 index data at hourly intervals?
    You can use https://twelvedata.com/ they offer an API and their free plan allows 800 credits a day so over a number of days you could get what you need. Source: about 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 Twelve Data and socketify.py, you can also consider the following products

Alpha Vantage - Alpha Vantage offers free APIs in JSON and CSV formats for realtime and historical stock and forex data, digital/crypto currency data and over 50 technical indicators.

Polygon.io - Polygon.io offers streaming realtime data for stocks/equities, ETFs, Indecies and Forex/Currencies including crypto currencies. Our Real-Time Stock Data APIs help you build the future on fintech.

Financial Modeling Prep - Access all stocks discounted cash flow statements, market price, stock markets news, and learn more about Financial Modeling. Learn M&A, LBO, DCF, Comps, and Financial Statement Modeling thought concrete examples

Hotstoks - The stock market API powered by SQL.

Open Exchange Rates - Free, hourly-updated exchange rates - a simple, accurate, open-source JSON API. Free for personal use, a bargain for everybody else.

Finage - Finage is a next-generation market data feeds provider. We are providing 60.000+ financial data feeds in real-time and historical via APIs and WebSockets such as; Global Stock, Forex, Cryptocurrency, ETFs, Indices, and financial statements, and more.

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