Software Alternatives, Accelerators & Startups

Backtrader VS Thanks (for Python)

Compare Backtrader VS Thanks (for Python) 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.

Backtrader logo Backtrader

Backtrader is a complete and advanced python framework that is used for backtesting and trading.

Thanks (for Python) logo Thanks (for Python)

A Python tool for giving back to the packages we use.
  • Backtrader Landing page
    Landing page //
    2021-09-30
  • Thanks (for Python) Landing page
    Landing page //
    2023-09-16

Backtrader features and specs

  • Versatility
    Backtrader supports a wide variety of data sources and formats, as well as different types of financial instruments, allowing for extensive backtesting and live trading capabilities.
  • Community and Documentation
    The platform has a strong community and comprehensive documentation, making it easier for new users to get started and for experienced users to troubleshoot and optimize their strategies.
  • Python Integration
    Written in Python, Backtrader allows users to leverage Python's extensive ecosystem of libraries for data analysis, machine learning, and other financial computations.
  • Open Source
    As an open-source project, users can modify and extend the platform to meet their specific trading and testing needs without restrictions, and contribute to its development.
  • Flexibility in Strategy Design
    Backtrader offers a flexible and intuitive framework to design complex trading strategies, enabling users to test multiple strategies with different parameters efficiently.

Possible disadvantages of Backtrader

  • Steep Learning Curve
    Despite its flexibility, new users may find Backtrader's extensive features and options overwhelming, requiring a significant amount of time to learn and effectively utilize.
  • Performance Issues
    For very large datasets, Backtrader might experience performance bottlenecks or require additional optimization, as Python is not the fastest language for high-frequency backtesting.
  • Limited Technical Support
    As a community-driven open-source project, Backtrader might lack the formal technical support and customer service that comes with commercial trading platforms.
  • Complexity in Live Trading
    Transitioning from backtesting to live trading can require significant additional setup and potential custom development, especially in integrating broker APIs.
  • Outdated Resources
    Some educational materials and tutorials may be outdated, leading to confusion due to interface or feature updates that are not well-documented.

Thanks (for Python) features and specs

No features have been listed yet.

Analysis of Thanks (for Python)

Overall verdict

  • Thanks is a lightweight, useful utility for Python developers who want to automatically credit open-source dependencies, making it a good niche tool though not a mainstream necessity.

Why this product is good

  • Automatically generates attribution and license acknowledgments for dependencies used in a project
  • Simple and easy to integrate into existing Python workflows
  • Encourages good open-source citizenship by crediting maintainers and libraries
  • Lightweight tool with minimal setup and configuration required
  • Open-source itself, allowing community contributions and transparency

Recommended for

  • Python developers who want to give proper credit to open-source library maintainers
  • Teams maintaining compliance or attribution requirements for open-source usage
  • Open-source project maintainers looking to foster a culture of appreciation
  • Developers building README or documentation sections crediting dependencies

Backtrader videos

Backtrader Python Review

More videos:

  • Review - Algorithmic Trading with Python and Backtrader (Part 1)
  • Review - Backtrader Live Forex Trading with Interactive Brokers (Part 1)

Thanks (for Python) videos

No Thanks (for Python) videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Backtrader and Thanks (for Python))
Finance
100 100%
0% 0
Crowdfunding
0 0%
100% 100
Development
100 100%
0% 0
Developer Tools
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Backtrader seems to be more popular. It has been mentiond 3 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.

Backtrader mentions (3)

  • My reality of trading and how i wish i had never started.
    I do like what I see and hear about backtrader.com. I would say they are a notable exception to my general rule of not trusting or using backtesting frameworks. However, I still think it is important to understand how the framework you are using works. So if you are using backtrader for backtesting you still need to put in the time to understand the backtesting engine. Source: over 3 years ago
  • My reality of trading and how i wish i had never started.
    What about backtrader.com? And I feel like it would be step 2 after you at least have something to backtrade and test haha. Source: over 3 years ago
  • I need to know what can go wrong with my 'masterplan'
    Backtesting is basically applying your strategy on historical price data to see if it makes money. I've used Backtrader it works decently well: https://backtrader.com/. Source: almost 5 years ago

Thanks (for Python) mentions (0)

We have not tracked any mentions of Thanks (for Python) yet. Tracking of Thanks (for Python) recommendations started around Mar 2021.

What are some alternatives?

When comparing Backtrader and Thanks (for Python), you can also consider the following products

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.

OpenSauced - Optimize Your Open Source Project with Deep Insights

Quantopian - Your algorithmic investing platform

Python Package Index - A repository of software for the Python programming language

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

npmpackage.info - Discover detailed information about npm packages. Your go-to source for npm package insights.