July 2026
Intermediate to advanced
536 pages
10h 39m
English
Content preview from Python for Algorithmic Trading Cookbook - Second EditionBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Accelerate Financial Market Data Analysis with Polars and DuckDB
In this chapter, we will explore the Python tools that form a modern, high-performance data stack that aligns well with the demands of algorithmic trading. Quantitative research often requires scanning millions of rows of price, volume, fundamentals, and alternative data. Traditional CSV- and pandas-based workflows can become slow as datasets grow. These newer tools address those limitations with columnar storage, vectorized execution, and efficient memory usage.
Parquet provides a compact, columnar file format that compresses data efficiently and supports predicate pushdown, so you read only the columns and rows needed for a query. Polars is a fast DataFrame library written in ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.