Search Results for "aosp-project-mido"

...Checkout out this demo project, which was set up using PyScaffold and if you are still not convinced yet, also have a look at these reasons to use PyScaffold. After cd-ing into your new project and creating (or activating) an isolated development environment (with virtualenv, conda or your preferred tool), you can do the usual editable install. All configuration can be done in setup.cfg like changing the description, URL, classifiers, installation requirements and so on as defined by setuptools. ...

DVC is built to make ML models shareable and reproducible. It is designed to handle large files, data sets, machine learning models, and metrics as well as code. Version control machine learning models, data sets and intermediate files. DVC connects them with code and uses Amazon S3, Microsoft Azure Blob Storage, Google Drive, Google Cloud Storage, Aliyun OSS, SSH/SFTP, HDFS, HTTP, network-attached storage, or disc to store file contents. Version control machine learning models, data sets,...

Sublime Text plugin providing probably all git has to offer. Sublime Text 2 is not supported. Also, GitSavvy takes advantage of modern features of Sublime Text (like annotations). For the best experience, use the latest Sublime Text dev build. The documentation is probably outdated. Yeah it's sad but you can contribute and I will eventually get onto it but every special view has help available, just press ?. GitSavvy requires Git versions at or greater than 2.18.0. basic Git functionality;...

...It treats repositories and developers as a graph of interactions and applies large-scale matrix factorization to model affinities, with Apache Spark providing the distributed data processing. The project focuses on implicit feedback—stars, watches, and other engagement metrics—so it can build useful recommendations without explicit ratings. A reproducible setup and Makefile-driven workflow streamline tasks like spinning up services, loading datasets, training models, and generating candidate lists. Because it’s built around Spark’s scalable primitives, Albedo can experiment on substantial snapshots of GitHub metadata rather than toy corpora. ...

Support multi-project, multi-environment one-click deployment and online, one-click quick rollback. Online order application, review, deployment, and real-time operation logs. Permissions, notifications, file fingerprints. Independent space resources like gitlab. Custom environment, environment variables. Project administrator, a notification mechanism, custom hooks in each process.

Tracking a Xcode project in a version control system is annoying. Simply adding files can lead to merge conflicts that have to be solved manually, although it would be possible to resolve the conflict automatically if the merge algorithm would be aware of the structure of Xcode's project file. After long and annoying merge sessions in one of my projects, I came to the conclusion, that writing a merge driver for git which understands the structure of the project file would be a worthwhile endeavour, as it would save me from solving the merge conflicts for my co-workers. ...

...Under normal operation, it filters the results to only show statistics about a number of given extensions and by default only includes source files in the statistical analysis. This tool was originally written to help fetch repository statistics from student projects in the course Object-oriented Programming Project (TDA367/DIT211) at Chalmers University of Technology and Gothenburg University. Shows cumulative work by each author in history. Filters results by an extension (default: java,c,cc,cpp,h,hh,hpp,py,glsl,rb,js, SQL). Can display a statistical timeline analysis. Scans for all filetypes (by extension) found in the repository. Multi-threaded; uses multiple instances of git to speed up analysis when possible.