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mypy VS Quantopian

Compare mypy VS Quantopian and see what are their differences

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Contents:
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  3. » Reviews
  4. » Alternatives

mypy logo mypy

Mypy is an experimental optional static type checker for Python that aims to combine the benefits of dynamic (or "duck") typing and static typing.

Quantopian logo Quantopian

Your algorithmic investing platform
  • mypy Landing page
    Landing page //
    2020-01-06
  • Quantopian Landing page
    Landing page //
    2023-07-27

mypy features and specs

  • Static Type Checking
    Mypy provides static type checking for Python code, allowing developers to detect type errors during development rather than at runtime.
  • Improved Code Quality
    By catching type errors early, Mypy helps ensure code correctness and maintainability, leading to improved overall code quality.
  • Better Documentation
    Mypy's type annotations serve as a form of documentation, making it easier for developers to understand the expected types of function parameters and return values.
  • Easy Integration
    Mypy can be easily integrated with existing Python projects incrementally, allowing teams to adopt type checking gradually.
  • Support for Python 3 Typing
    Mypy supports Python 3's type hinting syntax, making it a natural fit for modern Python codebases.

Possible disadvantages of mypy

  • Partial Support for Python Features
    Mypy may not fully support some dynamic features of Python, leading to limitations in its type-checking capabilities for certain code patterns.
  • Initial Learning Curve
    Developers unfamiliar with type annotations or static type checking may face a learning curve when first adopting Mypy in their projects.
  • Additional Code Overhead
    Mypy requires additional type annotations in the code, which can add to the overall codebase size and require extra effort to maintain.
  • Performance Overhead
    While Mypy itself does not affect runtime performance, running type checks during development can introduce additional processing time.
  • Incompatibility with Some Libraries
    Certain third-party libraries may not provide type stubs or may not be fully compatible with Mypy's type checking, requiring developers to create custom stubs.

Quantopian features and specs

  • Community Collaboration
    Quantopian provided a platform for users to share and collaborate on trading algorithms, enabling users to learn from each other and improve their strategies.
  • Access to Data
    Quantopian offered access to a wide range of financial data sets, which allowed users to develop and back-test their algorithms using historical data.
  • Comprehensive Development Environment
    It featured an integrated development environment (IDE) with tools for coding, testing, and back-testing trading strategies in Python, which was user-friendly and powerful.
  • Educational Resources
    Quantopian provided various educational resources, including lectures, tutorials, and a supportive community forum, which were beneficial for both beginners and experienced traders.
  • Competition and Incentives
    Quantopian organized contests that incentivized users to develop successful trading algorithms, with the potential to receive a live trading allocation from the company.

Possible disadvantages of Quantopian

  • Shutting Down Services
    Quantopian shut down its retail offering in 2020, which meant that users could no longer use their platform for developing and testing new algorithms.
  • Limited Live Trading Options
    Users found limited options for deploying their strategies into live trading. Quantopian allowed this only for algorithms selected for allocation, which reduced accessibility for many users.
  • Dependence on Platform
    Users who developed algorithms on Quantopian's platform were heavily dependent on it, and when it shut down, they had to transition to other platforms, which could be challenging.
  • Resource Limitations
    There were computational and resource limitations for users, which could restrict the complexity of the algorithms and back-testing users could perform without additional infrastructure.
  • Portfolio Selection Process
    The selection process for having algorithms licenced for live trading allocation was competitive and not transparent to many users, which could lead to frustration.

mypy videos

+ Add

Convincing an entire engineering org to use and like mypy

More videos:

  • Review - Start Being Static with MyPy - Mark Koh - PyGotham 2017

Quantopian videos

+ Add

Algorithmic Trading with Python and Quantopian p. 1

More videos:

  • Review - Quantopian, simple strategies

Category Popularity

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User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare mypy and Quantopian

mypy Reviews

7 best recommended IntelliJ IDEA Python plugins - Programmer Sought
This plugin from the JetBrains plugin market integrates MyPy into your Intellij. If you need some guidance, the MyPy website provides a lot of documentation to help you install and use MyPy to improve your Python code.
Source: www.programmersought.com

Quantopian Reviews

We have no reviews of Quantopian yet.
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Social recommendations and mentions

Based on our record, mypy seems to be more popular. It has been mentiond 50 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.

mypy mentions (50)

  • Java in the Small
    I've always admired many of Java's features, but let's not act like the reason for using Java for scripting is the pitfalls of Python. It's just because of an underlying preference for Java. 1. https://mypy-lang.org/. - Source: Hacker News / 5 months ago
  • Moving your bugs forward in time
    ‍I’m not here to tell people which languages they should love. But if you do find yourself writing production code in a dynamically typed language like Python, Ruby, or JavaScript, I would give serious consideration to opting into the type-checking tools that have become available in those ecosystems. In Python, consider requiring type hints and adding mypy checks to your CI to move your type safety bugs forward... - Source: dev.to / 12 months ago
  • Embracing Modern Python for Web Development
    Mypy is "an optional static type checker for Python that aims to combine the benefits of dynamic (or "duck") typing and static typing". As Python is dynamically typed, Mypy adds an extra layer of safety by checking types at compile time (based on type annotations conforming to PEP 484), catching potential errors before runtime. - Source: dev.to / over 1 year ago
  • A Tale of Two Kitchens - Hypermodernizing Your Python Code Base
    Mypy stands as an essential static type-checking tool. Its primary function is to verify the correctness of types in your codebase. However, manually annotating types in legacy code can be laborious and time-consuming. - Source: dev.to / over 1 year ago
  • Lua: The Little Language That Could
    Lua is a great language for embedding, but one thing I wish it had was some form of optional type annotations that could be checked by a linter. Something like mypy for Lua would be super-useful. Source: almost 2 years ago
View more

Quantopian mentions (0)

We have not tracked any mentions of Quantopian yet. Tracking of Quantopian recommendations started around Mar 2021.

What are some alternatives?

When comparing mypy and Quantopian, you can also consider the following products

PyLint - Pylint is a Python source code analyzer which looks for programming errors.

QuantConnect - QuantConnect provides a free algorithm backtesting tool and financial data so engineers can design algorithmic trading strategies. We are democratizing algorithm trading technology to empower investors.

flake8 - A wrapper around Python tools to check the style and quality of Python code.

quantra - A public API for quantitative finance made with Quantlib

SonarQube - SonarQube, a core component of the Sonar solution, is an open source, self-managed tool that systematically helps developers and organizations deliver Clean Code.

CloudQuant - Crowd based algorithmic trading development and backtesing for stock market trading.

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