I've recently moved all of my git repositories to Gitlab, this blog post walks through a script I have written to clone all of my repos
For a while, I hosted my own version of Gitlab and, although I owned all the data, the server I had was not powerful enough for the install and would regularly crash and need rebooting. Moving my data across to the main Gitlab site gave me peace of mind that my data was always accessible no matter what time, however, I had less control over the data itself and no way of easily backing it up.
Below is a script is written in PHP which backs up my repositories for me. It is running on a small server I have at home which downloads the data onto a NAS. This NAS has two hard-drives which are mirrored.
The script does the following tasks:
By doing this, if Gitlab closes down tomorrow, I have the data. As I rarely do side projects and updates, the script is set to run monthly. I consider that any work I have done in the last month will be backed up somewhere else (on a live/dev server somewhere).
As this script uses the API, it doesn't need updating each time I add a project to Gitlab itself! I've included the code below with plenty o' comments to help you through.
The first line is a
shebang. This allows you to just run the file without to specify
php when running on the command line.
Visual Analytics and Advanced Data Visualization - How CanvasJS help enterprises in creating custom Interactive and Analytical Dashboards for advanced visual analytics for data visualization
Visualization Best Practices for Data Scientists. Disclaimer: The ideas presented in this article are from the book: Story Telling With Data by Cole Nussbaumer Knaflic.
The agenda of the talk included an introduction to 3D data, its applications and case studies, 3D data alignment and more.
The Importance of Data Visualization - It is the process of converting raw data at hand into easy and understandable image-photo-graphics for fast, effective and accurate…
Data Quality Testing Skills Needed For Data Integration Projects. Data integration projects fail for many reasons. Risks can be mitigated when well-trained testers deliver support. Here are some recommended testing skills.