只要有可能,PyFunctional将延迟计算。这是通过跟踪已经应用到序列的转换列表来完成的,并且只有在一个动作被调用时才对它们进行求值。在PyFunctional中,这被称为跟踪谱系。这也是PyFunctional缓存计算结果的能力,以防止昂贵的重新计算。这主要是为了保持明智的行为,并谨慎使用。 例如,调用size()将缓存基础序列。 如果这没...
PyFunctional makes creating data pipelines easy by using chained functional operators. Here are a few examples of what it can do:Chained operators: seq(1, 2, 3).map(lambda x: x * 2).reduce(lambda x, y: x + y) Expressive and feature complete API Read and write text, csv, json, ...
EntilZha/PyFunctionalPublic NotificationsYou must be signed in to change notification settings Fork135 Star2.4k Code Issues14 Pull requests6 Actions Projects Security Insights Additional navigation options New issue Closed Description povilasb EntilZha commentedon Dec 16, 2016 ...
Sign in Sign up EntilZha / PyFunctional Public Notifications Fork 135 Star 2.4k Code Issues 14 Pull requests 6 Actions Projects Security Insights New issue Improve GitHub Action workflow #214 Merged EntilZha merged 5 commits into EntilZha:master from samer-hamood:improve_git_hub_act...
PyFunctional Features PyFunctionalmakes creating data pipelines easy by using chained functional operators. Here are a few examples of what it can do: Chained operators:seq(1, 2, 3).map(lambda x: x * 2).reduce(lambda x, y: x + y) ...
PyFunctional Features PyFunctionalmakes creating data pipelines easy by using chained functional operators. Here are a few examples of what it can do: Chained operators:seq(1, 2, 3).map(lambda x: x * 2).reduce(lambda x, y: x + y) ...