Explore >> Select a destination
|
You are here 
|
blog.thea.codes | ||
| | | | |
hjr265.me
|
|
| | | | | Docker has been providing a health check mechanism for quite some time. It is useful in identifying issues with programs that can fail in ways other than just outright crashing. And it is easy to set up. Docker health checks work periodically running a program within the container and observing its exit status. If it exits with a 0, the container is considered healthy. If it exits with a 1, the container is considered to be unhealthy. | |
| | | | |
www.joeltok.com
|
|
| | | | | Python dependency management for reproducibility, using built-in libraries. | |
| | | | |
vickiboykis.com
|
|
| | | | | When I'm working with Jupyter notebooks, I often want to work with them from within a virtual environment. The general best practice is that you should always use either virtual environments or Docker containers for working with Python, for reasons outlined in this post, or you're gonna have a bad time. I know I have. The workflow is a little long, so I thought I'd document it for future me here. | |
| | | | |
christophilus.com
|
|
| | | |||
