如何使用流行度在开源库之间进行选择 (How to choose between open source libraries using popularity)

Through my career as a product manager, I’ve worked closely with engineers to build many technology products (and even hacked some together myself).

在担任产品经理的整个职业生涯中，我与工程师紧密合作，开发了许多技术产品(甚至自己也一起破解了一些产品)。

When developing technology products, one of the most critical choices we can make is between competing sets of libraries and frameworks. One key ingredient is relative popularity, for several reasons:

在开发技术产品时，我们可以做出的最关键的选择之一是在竞争的库和框架集之间进行选择。关键因素之一是相对受欢迎 ，原因如下：

Proxy for the Best. Especially in open source, the “market” is fairly efficient. Developers generally gravitate towards the best technologies and vote with their feet.
最佳代理 。尤其是在开源中，“市场”相当有效。开发人员通常倾向于最好的技术，并用脚投票。
Help. While formal documentation is critically important, Stack Overflow questions and Medium tutorials are sometimes even more beneficial to move up the learning curve and to debug. Code snippets and tips from practitioners boost development speed and impact tremendously.
帮忙。尽管正式文档至关重要，但堆栈溢出问题和中级教程有时甚至对提高学习曲线和调试更为有益。练习者的代码片段和技巧极大地提高了开发速度并产生了巨大的影响。
Talent. The more popular a library is, the more likely you’ll be able to find people who know how to use it to help build your product.
人才库越受欢迎，您越有可能找到知道如何使用它来帮助您构建产品的人。
Future Enhancements. A vibrant user base and community ensures continued development on the project in the future, reducing the chance that it will become obsolete.
未来的改进 。活跃的用户群和社区确保了该项目在将来的持续开发，从而减少了该项目被淘汰的机会。

人气代理 (Proxies for Popularity)

There are several ways to measure the popularity of OS libraries:

有几种方法可以衡量OS库的流行程度：

Stack Overflow questions
堆栈溢出问题
Github stars
Github星星
Google Trends
Google趋势

StackShare should also get an honorable mention here as a good way to find popular tools.

StackShare在这里也应该得到荣誉奖，这是找到流行工具的好方法。

判断动量 (Judging Momentum)

However, these measures need a time based component. Without taking into account metric momentum, the above measures are purely backward looking — they help inform what was the best technology, not what is or what will be.

但是，这些措施需要基于时间的组件。在不考虑度量指标动量的情况下，上述措施纯粹是向后看的-它们有助于告知什么是最好的技术，而不是什么是什么或将是什么。

Therefore, more often, when evaluating competing libraries, I’ll often look at charts of these statistics over time. There are several apps that allow us to do that:

因此，在评估竞争性库时，通常会经常查看这些统计数据随时间变化的图表。有几个应用程序可以使我们做到这一点：

Stack Overflow Trends. Open source tool by Rob McDiarmid. Also directly from Stack Overflow.
堆栈溢出趋势 。 Rob McDiarmid的开源工具。也可以直接从Stack Overflow中获取。
Github Star History. Similar tools include StarTrack, Stargraph, and this project. Unfortunately, most use the Github API for this which seems to be quite unreliable and buggy.
GitHub上的星史 。类似的工具包括StarTrack ， Stargraph和该项目。不幸的是，大多数人为此使用Github API，这似乎非常不可靠且有错误。
Google Trends, of course, works out of the box, but seems somewhat more spiky and less informative than the other two measures.
Google趋势当然是开箱即用的，但与其他两项指标相比，它显得有些刺眼且信息量不足。

Google Cloud has also made both Stack Overflow and Github data available as part of their Public Datasets program. And here’s a post that digs into some insights from Stack Overflow.

Google Cloud还已将Stack Overflow和Github数据作为其公共数据集计划的一部分提供。这是一篇文章，探讨了Stack Overflow的一些见解。

示例：Flask与Django (Example: Flask versus Django)

Flask and Django are two popular Python web application frameworks that I personally have a lot of experience with. Flask is lighter weight and more flexible, while Django has much more built in and is more feature rich.

Flask和Django是两个流行的Python Web应用程序框架，我个人对此有很多经验。 Flask的重量更轻且更灵活，而Django具有更多内置功能和更多功能。

Let’s see how these rank using our methodologies above:

让我们看看如何使用上面的方法对它们进行排名：

Github Stars: Django currently has 40k stars on Github while Flask has 42k stars — they are neck and neck. I tried several of the Github history trackers, but they all timed out on me.
Github星星 ： Django目前在Github上拥有4万颗星星，而Flask有42k颗星星-它们并驾齐驱。我尝试了一些Github历史记录跟踪器，但它们对我都超时了。
Stack Overflow: Django has 191k questions, while Flask has 26k questions. The trend shows Flask picking up, but still a long ways away.
堆栈溢出 ： Django有191k个问题，而Flask有26k个问题。趋势表明Flask有所回升，但还有很长的路要走。
Google Trends: Django is currently about twice as popular as Flask, according to Google Trends.
Google趋势：根据Google趋势，Django当前的流行度是Flask的两倍。

Note that of course, relative popularity is only one factor in choosing between libraries. Between Flask and Django, for example, I tend to choose Flask for quick prototyping as well as when I am developing a non traditional app and need a ton of flexibility. I tend to choose Django when I’d like out of the box functionality for things like user accounts, administration, and built in ORM.

请注意 ，当然，相对流行度只是在库之间进行选择的一个因素。例如，在Flask和Django之间，我倾向于选择Flask来进行快速原型制作以及在开发非传统应用程序时需要大量灵活性。当我想要开箱即用的功能(如用户帐户，管理和内置ORM)时，我倾向于选择Django。

Hope this helps! Thanks for reading.

希望这可以帮助！谢谢阅读。