workflow

Is there an easy way to write C code that can access its Git version hash? I wrote software in C to collect scientific data in a laboratory setting. My code records the data it collects in a .yaml file for later analysis. My experiments change from day-to-day and I often have to modify the code. To keep track of revisions, I use a git repository. I would like to be able to include the Git revision hash as a comment in my .yaml data files. That way, I could look at the .yaml file and know exactly what code was used to generate the data shown in that file. Is there an easy way to do this

温馨提示：本文中Alfred是Mac平台的工具，不适用于其他平台。 Alfred 是Mac平台上被很多人吹爆的一款效率提升软件，我刚毕业工作的时候就看到公司内网有人推荐，但没有尝试。 后来我跳槽后自己买了Macbook pro，在努力把笔记本打造成高效开发工具时，又重新发现了这个app，又毫不犹豫的购买了Powerpack，结合一些workflow，很多繁琐的工作变得非常简单，比如之前百度搜索一个东西，需要打开浏览器，然后打开百度，再输入要搜的词，再点搜索一套组合拳下来几十秒就过去了，有了Alfred 快捷键+触发词+搜索词+回车 几秒钟搞定。下图是我最近一月来每天的Alfred的使用频率，工作日平均每天有30+次的使用率。 那究竟Alfred是啥？Mac又个功能叫“聚焦”，它可以帮你搜索本机的一些内容，比如文件、应用程序、浏览器书签……，但功能仅限于此。Alfred类似有聚焦，操作方式也类似，但功能比聚焦强大的多。除了聚焦搜拥有的简单搜索功能，Alfred还可以设置action，用某个关键词触发一个动作，或者设置快捷键。默认继承了一些系统快捷设置，比如mac用户从windows过来最不习惯的就是不能快速锁屏，甚至不知道怎么锁屏，通过Alfred的快捷命令就可以秒锁屏了。 我个人最喜欢也是最常用的就是ClickBoard Histroy，它可以保存你近期复制粘贴的所有东西

I am new to Python as I want to expand skills that I learned using R. In R I tend to load a bunch of libraries, sometimes resulting in function name conflicts. What is best practice in Python. I have seen some specific variations that I do not see a difference between import pandas , from pandas import * , and from pandas import DataFrame What are the differences between the first two and should I just import what I need. Also, what would be the worst consequences for someone making small programs to process data and compute simple statistics. UPDATE I found this excellent guide . It explains

I'm a team leader in our web development company, and I'd like to implement Git workflow in our team. Reading documentation and articles I've found the following structure good for us: We have a repository in a Bitbucket. Master branch is considered to contain stable code only. Every dev must create his own branch and implement features/bugfixes in his own branch. Once he decides, that his code is ready, he creates a nice branch history (using rebase, amend, cherry-pick etc.) and pushes it to Bitbucket, where creates a pull request to master branch. QA verifies functionality and approves (or

Let's say I have a commit history with 5 commits. I know that I can rebase my commits locally when making a pull request which will then have them rebased into a single commit. A common use case for this is: Make local commits, working on feature Squash commits Make Pull Request Receive review comments Update PR appropriately I can do this locally on my machine and then push my change again (using -f since the rebase makes it out of sync with the remote). This is kind of annoying. However, this requires that I do a rebase every time I address review comments - is there any way I can do this

I have exhaustively searched for answers to my question here and on Google. I have found some great resources and learning tools for understanding Git and what it does, but I need to get some clarification, and assistance. What I am doing is working on a side-project for work both at my office and at home. (I'm migrating C# code to Java to help me learn both languages.) The setup : Environment: Windows 7 (VS 2008 is on an XP virtual machine) Git: msysgit 1.7.4 IDEs: VS 2008 and Eclipse Git plugins: Eclipse: I am using EGit. VS 2008: I plan on using one mentioned here on SO, Git Extensions Git

when I put a new DAG python script in the dags folder, I can view a new entry of DAG in the DAG UI but it was not enabled automatically. On top of that, it seems does not loaded properly as well. I can only click on the Refresh button few times on the right side of the list and toggle the on/off button on the left side of the list to be able to schedule the DAG. These are manual process as I need to trigger something even though the DAG Script was put inside the dag folder. Anyone can help me on this ? Did I missed something ? Or this is a correct behavior in airflow ? By the way, as mentioned