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pre-commit by Yelp VS QuantConnect

Compare pre-commit by Yelp VS QuantConnect and see what are their differences

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pre-commit by Yelp logo pre-commit by Yelp

A framework for managing and maintaining multi-language pre-commit hooks

QuantConnect logo 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.
  • pre-commit by Yelp Landing page
    Landing page //
    2022-01-08
  • QuantConnect Landing page
    Landing page //
    2023-10-15

pre-commit by Yelp features and specs

  • Comprehensive Hook Management
    Pre-commit provides a robust framework to manage and configure git hooks in a standardized way, simplifying the process of ensuring code quality.
  • Language Agnostic
    Supports hooks written in all kinds of languages including Python, Ruby, JavaScript, etc., making it versatile and adaptable to any codebase.
  • Ease of Setup
    Installing and configuring pre-commit hooks is straightforward, often just involving the addition of a simple configuration file to the repository.
  • Version Control
    Pre-commit ensures that the same versions of hooks are consistently run across developers' environments by locking the version of each hook.
  • Centralized Configuration
    Project-wide configuration means that all contributors use the same hooks and settings, fostering code consistency and quality.

Possible disadvantages of pre-commit by Yelp

  • Learning Curve
    New users might face a learning curve initially when setting up a configuration file and understanding how to integrate it with existing workflows.
  • Performance Overhead
    Running hooks can add a noticeable delay when committing code, especially in larger projects with many hooks.
  • Dependency Management
    Some hooks might introduce additional dependencies that need to be managed within the project's environment.
  • Complex Configuration for Advanced Use
    While simple setups are easy, more complex configurations can become intricate and harder to manage.
  • Limited to Pre-defined Hooks
    If a desired hook isn't available, users may have to create their own, which can require additional effort and maintenance.

QuantConnect features and specs

  • Comprehensive Data Access
    QuantConnect provides access to a wide range of financial data which is crucial for developing and testing trading algorithms. This includes equities, futures, FOREX, and cryptocurrencies, which allows users to backtest strategies with historical data.
  • Cloud-Based Development
    The platform is cloud-based, which means users can access their projects from anywhere and don't need to worry about the computational resources required for large backtesting tasks. This also facilitates easy collaboration.
  • Wide Language Support
    QuantConnect supports multiple programming languages including C#, Python, and F#. This allows developers to choose from different languages they are comfortable with while coding algorithms.
  • Lean Algorithm Framework
    The open-source Lean Algorithm Framework is at the core of QuantConnect, providing a robust and flexible foundation for algorithmic trading strategies which can be customized to meet specific needs.
  • Community and Collaboration
    QuantConnect has an active community where users can share ideas, collaborate on projects, and seek help from others which enhances learning and innovation.

Possible disadvantages of QuantConnect

  • Complexity for Beginners
    The platform may be overwhelming for beginners due to the vast array of features and the requirement for programming skills, which can be a steep learning curve for some users.
  • Pricing Structure
    While QuantConnect offers free access with certain limitations, advanced features and higher data allowances come at a cost. This pricing may be a barrier for casual or small-scale users.
  • Limited Asset Classes for Free Users
    Free users may face limitations in terms of the number of asset classes and data sources available, which could restrict the range of strategies they are able to develop and test.
  • Dependence on Internet Connection
    As a cloud-based platform, an active internet connection is required to develop and execute algorithms, which could be a problem for users with unreliable internet access.
  • Execution Latency
    Running algorithms on a cloud platform might introduce latency issues which can be a disadvantage if executing strategies that require ultra-low latency transaction speeds.

pre-commit by Yelp videos

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QuantConnect videos

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Difference between Quantopian Quantiacs Quantconnect

More videos:

  • Review - Step by Step Algorithmic Trading Guide with QuantConnect

Category Popularity

0-100% (relative to pre-commit by Yelp and QuantConnect)

pre-commit by Yelp

QuantConnect

Git
100 100%
Git
0% 0
Finance
0 0%
Finance
100% 100
Code Collaboration
100 100%
Code Collaboration
0% 0
Development
0 0%
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 pre-commit by Yelp and QuantConnect

pre-commit by Yelp Reviews

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QuantConnect Reviews

TradingView Alternatives For Budget Conscious Traders
QuantConnect is a quantitative trading platform where you can develop algorithms in Python. It’s gaining popularity for its collaborative environment and large data library that supports backtesting and live trading. QuantConnect is flexible and supports multiple asset classes so it’s good for algorithmic traders.
Source: medium.com

Social recommendations and mentions

Based on our record, pre-commit by Yelp seems to be a lot more popular than QuantConnect. While we know about 150 links to pre-commit by Yelp, we've tracked only 9 mentions of QuantConnect. 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.

pre-commit by Yelp mentions (150)

  • Scalable Python backend: Building a containerized FastAPI Application with uv, Docker, and pre-commit: a step-by-step guide
    Pre-commit is a framework for managing and maintaining multi-language pre-commit hooks, ensuring consistency and quality in your codebase by running checks before a commit is finalized. - Source: dev.to / 4 months ago
  • Crafting a Custom SAM Template for Your AWS Lambda Function, Resource, and Operations
    Just give you an idea of how to implement a template for serverless in your organization; you can create multiple cases and embed the practice of your organization to the template like pre-commit, cicd, lambda-layer-secret, lambda-layer-powertools and more. - Source: dev.to / 5 months ago
  • 12 Steps to Organize and Maintain Your Python Codebase for Beginners
    Instead of running these tools manually every time you make changes, you can automate the process with pre-commit hooks. Pre-commit hooks run automatically before each commit, blocking the commit if any tool fails. - Source: dev.to / 6 months ago
  • How I use git
    Our team is small and we use: 
      git hooks from https://pre-commit.com.
    - Source: Hacker News / 7 months ago
  • How to Estimate Cloud Costs with Terraform and InfraCost
    You can also add InfraCost as part of the pre-commit. With pre-commit, you can define some hooks that you can easily run before you push your code. There are multiple ways to install pre-commit, and you can find examples here. - Source: dev.to / 8 months ago
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QuantConnect mentions (9)

  • I'm a dev, we're in 2023, what should i start with ?
    I use https://quantconnect.com/ to backtest new algos and discover new algos. They support C# and python. Source: over 2 years ago
  • Where can I Learn OOP for trading in python? I’ve been looking for some information, but I didn’t find anything, any help?
    Use quantconnect.com, their API forces you to use OOP there so it's a good practice. Source: almost 3 years ago
  • Backtesting tools
    For stocks and crypto: QuantConnect and Backtrader For options: MesoSim and OptionNetExplorer. Source: almost 3 years ago
  • what do you guys think about Joel Greenblatt and his magic formula of investing? backtests of his formula return on average above 20% per annum
    Only you can teach you how to do it. quantconnect.com has a lot of tutorials and other documentation that should be enough for you to learn from. I'm still learning the process of backtesting and I'm not aware of an "easy" way to perform this type of work. Source: almost 3 years ago
  • What are some things you have automated, using python?
    Thanks for the pointer. quantconnect.com and interactive brokers. I have a little fantasy that I'll do this once I retire and hand over 1% of my nest egg to it; see how it does... Hand over some more, etc... Source: over 3 years ago
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What are some alternatives?

When comparing pre-commit by Yelp and QuantConnect, you can also consider the following products

Python Poetry - Python packaging and dependency manager.

Quantopian - Your algorithmic investing platform

EditorConfig - EditorConfig is a file format and collection of text editor plugins for maintaining consistent coding styles between different editors and IDEs.

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

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.

quantra - A public API for quantitative finance made with Quantlib

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