Beancount DKB VS zipline

Compare Beancount DKB vs zipline and see what are their differences.

zipline

Zipline, a Pythonic Algorithmic Trading Library (by quantopian)
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Beancount DKB zipline
- 14
31 17,036
- 0.6%
8.3 0.0
8 days ago 2 months ago
Python Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Beancount DKB

Posts with mentions or reviews of Beancount DKB. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Beancount DKB yet.
Tracking mentions began in Dec 2020.

zipline

Posts with mentions or reviews of zipline. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-01-26.

What are some alternatives?

When comparing Beancount DKB and zipline you can also consider the following projects:

Yahooquery - Python wrapper for an unofficial Yahoo Finance API

backtrader - Python Backtesting library for trading strategies

pyfolio - Portfolio and risk analytics in Python

Tax-Calculator - USA Federal Individual Income and Payroll Tax Microsimulation Model

backtrader - Python Backtesting library for trading strategies [Moved to: https://github.com/mementum/backtrader]

python-fints - Pure-python FinTS (formerly known as HBCI) implementation

PyThalesians - Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians)

munggoggo

quantstats - Portfolio analytics for quants, written in Python

Pyqiwi - Python client for QIWI payment system

qlib - Qlib is an AI-oriented quantitative investment platform that aims to realize the potential, empower research, and create value using AI technologies in quantitative investment, from exploring ideas to implementing productions. Qlib supports diverse machine learning modeling paradigms. including supervised learning, market dynamics modeling, and RL.