惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园 - 三生石上(FineUI控件)
S
SegmentFault 最新的问题
阮一峰的网络日志
阮一峰的网络日志
freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
雷峰网
雷峰网
Apple Machine Learning Research
Apple Machine Learning Research
WordPress大学
WordPress大学
博客园 - 司徒正美
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
宝玉的分享
宝玉的分享
爱范儿
爱范儿
月光博客
月光博客
The GitHub Blog
The GitHub Blog
M
MIT News - Artificial intelligence
H
Hackread – Cybersecurity News, Data Breaches, AI and More
B
Blog
T
Tailwind CSS Blog
美团技术团队
D
Docker
V
Visual Studio Blog
Martin Fowler
Martin Fowler
博客园 - 聂微东
The Cloudflare Blog

all models are wrong

-> Going both ways in R <- finding homologous probes using biomaRt Profiling in R More Segment HMMs Nasty Python Things MICROCOSMOGRAPHIA ACADEMICA Pebl The Pirate Bay Trial Latex, Beamer, Python, Beauty
Python and Numpy integers
2009-03-30 · via all models are wrong

March 30, 2009

I keep getting bitten on the bum with Python and ‘proper’ programming things. Today it’s this:


In [253]: 8**14
Out[253]: 4398046511104L

In [254]: 8**(numpy.int32(14))
Out[254]: 0

I would feel guilty about this if I had to specify the type of numbers I was using, but this is a dynamic programming language! How the hell am I supposed to know that raising an int by a numpy.int32 will force the result to also be an numpy.int32 (and therefore (silently) 0 because int32 can’t hold my number) whereas raising an int by an int will result in a long? Why didn’t the int32 become a long also? Or an int64 or something that could hold my number?

Gah!