Software Alternatives, Accelerators & Startups

flake8 VS Quantopian

Compare flake8 VS Quantopian 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.

flake8 logo flake8

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

Quantopian logo Quantopian

Your algorithmic investing platform
  • flake8 Landing page
    Landing page //
    2022-12-20
  • Quantopian Landing page
    Landing page //
    2023-07-27

flake8 features and specs

  • Comprehensive Style Guide Enforcement
    Flake8 helps maintain code standards by checking for adherence to PEP 8, which is the official style guide for Python code. This ensures consistency and readability across large codebases.
  • Plugin Support
    Flake8's modular design allows for the addition of plugins, meaning you can customize and extend its functionality to enforce additional rules or standards specific to your project.
  • Ease of Use
    It's straightforward to install and use Flake8, which integrates easily into most workflows, whether it's via command line or integration with text editors and IDEs.
  • Error Detection
    Flake8 combines several tools into a single package to detect syntax errors, undefined names, and other issues in Python code, thus improving code quality.

Possible disadvantages of flake8

  • False Positives
    Flake8 might sometimes generate false positives, particularly when used in complex or non-standard code scenarios, which can lead to time spent verifying whether an issue is genuine.
  • Performance
    For very large projects, running Flake8 can be resource-intensive, potentially slowing down the development process as it parses large amounts of code.
  • Configuration Overhead
    While customizable, configuring Flake8 to fit the specific needs of a project may require significant initial effort, especially when tailoring the rules and integrating with various tools.
  • Not a Full Linter Replacement
    Flake8 is focused on style and simple static analysis; it doesn't cover deeper static analysis tasks, such as type checking or advanced linting, which might necessitate supplementary tools.

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.

flake8 videos

Linters and fixers: never worry about code formatting again (Vim + Ale + Flake8 & Black for Python)

More videos:

  • Review - flake8 на максималках: что, как и зачем / Илья Лебедев

Quantopian videos

Algorithmic Trading with Python and Quantopian p. 1

More videos:

  • Review - Quantopian, simple strategies

Category Popularity

0-100% (relative to flake8 and Quantopian)
Code Coverage
100 100%
0% 0
Finance
0 0%
100% 100
Code Analysis
100 100%
0% 0
Tool
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, flake8 seems to be more popular. It has been mentiond 5 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.

flake8 mentions (5)

  • How I start every new Python backend API project
    Repos: - repo: https://github.com/pre-commit/pre-commit-hooks rev: v4.3.0 hooks: - id: trailing-whitespace - id: check-merge-conflict - id: check-yaml args: [--unsafe] - id: check-json - id: detect-private-key - id: end-of-file-fixer - repo: https://github.com/timothycrosley/isort rev: 5.10.1 hooks: - id: isort - repo:... - Source: dev.to / over 2 years ago
  • Flake8 took down the gitlab repository in favor of github
    I just ran `pre-commit autoupdate`. It's asking for a username for https://gitlab.com/pycqa/flake8. :-(. Source: over 2 years ago
  • flake8-length: Flake8 plugin for a smart line length validation.
    Flake8 plugin for a smart line length validation. Source: over 2 years ago
  • Make your Django project newbie contributor friendly with pre-commit
    $ pre-commit install Pre-commit installed at .git/hooks/pre-commit $ git add .pre-commit-config.yaml $ git commit -m "Add pre-commit config" [INFO] Initializing environment for https://github.com/pre-commit/pre-commit-hooks. [INFO] Initializing environment for https://gitlab.com/pycqa/flake8. [INFO] Initializing environment for https://github.com/pycqa/isort. [INFO] Initializing environment for... - Source: dev.to / almost 4 years ago
  • On unit testing
    If you're looking for just good automated error checking, I personally use a bunch of flake8 plugins via pre-commit hooks: flake8-bugbear, flake8-builtins, flake8-bandit, etc. You can find a bunch of sites that give recommended plugins and you just need to pick which ones you care about :). Source: about 4 years ago

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 flake8 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.

PyFlakes - A simple program which checks Python source files for errors.

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.

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