A fast and efficient Python build system to package and deploy applications
Vectorized build system for packages and images
Build isolation using Docker
Caching individual build steps
ML packages are always available on the latest GPU hardware
Available to most key languages
Seamless CI/CD Experience
Autobuild can be enabled for any package or image
Set it up once, and any push to the source repo will trigger a build of affected packages and images
Batch jobs use the latest version of an image, so you can always be sure what they're running with
Run automated user-defined tests against new image versions after they're built
The Ultimate SDLC
SDLC - Build Automation
Automatic based on git flow
Different rules can apply to different branches
Build multiple packages from one repo
Automatic update of all images and jobs that depend on a new version of a package
SDLC - Type Checker
Automatic type annotations out of the box
SDLC - Type Checker Dev Experience
Easily catch type errors
Compare dt.app by Datatailr versus Conda
Feature
Conda
dt.app
System Package Integration
Requires duplication and maintenance of Linux distribution low-level packages
Packages integrate well with those provided by Linux system package manager; allows for greater focus
Dependency Management
Complex dependency graphs with version specifics. Longer build times and prone to errors (e.g., conda dependency resolution can fail after many hours of “building”)
Simplified, based on package names. Builds are typically 3x faster than with Conda-build and not prone to error.
Build Isolation
Relies on environment management
Utilizes Docker for complete isolation
Caching Individual Build Steps
Does not offer this level of granular caching
Repeated builds take advantage of Docker by caching individual build steps at Docker level, which can drastically cut down build times in CI/CD pipelines and avoid failed builds.
OS & Distribution Support
MacOS, Windows and Linux, excluding Alpine distribution due to lack of support for musl C runtime distributions
Linux only
Focus on Portability
Ecosystem ported high number of system packages, but at the expense of developer effort
Low, focuses on leveraging existing system resources
