The "MLOps-Basics" project by graviraja, designed as a comprehensive guide to MLOps practices, has seen no recent development activity, with the last commit occurring over 1000 days ago. The project aims to educate practitioners on MLOps through weekly modules covering various aspects such as model building and serverless deployment.
Recent issues highlight ongoing challenges with AWS Lambda, notably #28, which remains unresolved after 1024 days, indicating persistent difficulties with serverless deployment. Other issues like #38 (malformed URLs) suggest accessibility problems, while #36 and #35 point to compatibility challenges with tools like SQLite3 and DVC.
| Timespan | Opened | Closed | Comments | Labeled | Milestones |
|---|---|---|---|---|---|
| 7 Days | 0 | 0 | 0 | 0 | 0 |
| 30 Days | 1 | 0 | 2 | 1 | 1 |
| 90 Days | 1 | 0 | 2 | 1 | 1 |
| 1 Year | 1 | 0 | 2 | 1 | 1 |
| All Time | 18 | 10 | - | - | - |
Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.
Recent GitHub issue activity for the "MLOps-Basics" project shows a mix of both longstanding and newly reported issues, with some issues remaining open for over 1000 days. Notably, Issue #28, which involves an AWS Lambda function test error, has been active for 1024 days and was updated just a day ago, indicating ongoing challenges in resolving this problem. The presence of multiple issues related to AWS Lambda (e.g., #28, #36) suggests recurring difficulties with serverless deployment environments. Additionally, Issue #38 about malformed URLs indicates potential accessibility problems with external resources linked in the project. A common theme among the issues is the integration and compatibility of various tools and environments, such as Docker, AWS Lambda, and DVC.
#38: Malformed URLs
#28: AWS Lambda Function: Test error
#36: Lambda Environment Support for SQLite3 Older Versions
#35: DVCFiles alternative not working
#32: Error with numpy and transformers modules
#31: Cannot use load_dataset('glue', 'cola') in Week0 requirements.txt
#30: Key error on Week1
#29: Change Dimension of Softmax from 0 to 1 in modules from week 1 to 4
The dataset provides information on a series of pull requests (PRs) for the "MLOps-Basics" repository by graviraja. This repository is structured as a comprehensive guide to MLOps, with weekly modules covering various aspects of machine learning operations. The data includes details about open and closed PRs, highlighting contributions and changes to the project.
#37: new - Open for 97 days, this PR involves significant deletions across multiple files, suggesting a major cleanup or refactor by Vinayak Sonawane. It has not been merged yet.
#24: Fix Codes in Week_0 for details - Open for 1073 days, this PR addresses minor code improvements and typo corrections by Seungyun Baek. Despite its age, it remains unmerged.
#34: Feature/week 4 - Closed on the same day it was created, this PR likely introduced new features or updates related to Week 4's module.
#33: Feature/week 0 - Also closed on the day of creation, this PR probably involved initial setup or enhancements for Week 0's content.
#22: fixed valid loss in early stopping callback - Addressed an issue with early stopping logic and was closed promptly after creation.
#20: fixed earlystopping callback - Similar to #22, this PR focused on refining early stopping mechanisms and was closed quickly.
#18: updated metric calls - This PR updated how metrics were called within the project and was closed shortly after being opened.
#15: added returning loss in training step - Introduced changes to return loss during training steps, enhancing model training feedback.
#13: Week9 - Aimed at updates or features related to Week 9's module, closed swiftly after a brief edit period.
#12: Serverless Lambda - Focused on serverless deployment aspects using AWS Lambda, closed on the same day as creation.
#11: Week7 - Related to Week 7's content, closed immediately upon creation.
#9: CICD flow - Implemented CI/CD workflows, closed promptly after submission.
#8: added docker related code - Introduced Docker-related functionalities and was closed quickly.
#7: Added images to the readme - Enhanced documentation with images, contributing to better project understanding.
#6: Added onnx conversion and onnxruntime inference - Focused on model packaging and inference using ONNX, closed shortly after an edit.
#5: updated dvc readme - Updated documentation related to data version control with DVC, closed quickly.
#4: Added dvc - Introduced DVC into the project for data version control purposes, closed immediately upon creation.
#3: Added hydra configurations - Integrated Hydra configurations for better management of settings and parameters, closed promptly.
#2: Week1 - Weights and Bias Integration - Focused on integrating Weights & Biases for monitoring purposes in Week 1's module, closed swiftly.
#1: Project Setup - Initial project setup PR that laid the groundwork for subsequent developments, closed immediately upon creation.
The "MLOps-Basics" repository exhibits a structured approach towards implementing MLOps practices through weekly modules that cover a broad spectrum of topics from project setup to advanced deployment techniques like serverless computing with AWS Lambda. The pull requests reflect a mix of feature additions, bug fixes, and documentation enhancements that align with the project's educational objectives.
A notable observation is the presence of two open PRs (#37 and #24) that have remained unmerged for extended periods—97 days and over 1073 days respectively. PR #37 involves extensive deletions across numerous files without any additions, indicating a possible major refactor or cleanup effort that might require careful review due to its potential impact on existing functionalities. In contrast, PR #24 focuses on minor code improvements and typo corrections but has been stagnant for nearly three years; this suggests either a lack of prioritization or oversight in maintaining code quality over time.
The rapid closure of most other PRs suggests an efficient workflow where changes are reviewed and integrated swiftly—often on the same day they are created—indicating a well-managed project with clear objectives for each module's development phase. However, this efficiency might also point towards a lack of thorough review processes which could overlook potential issues in favor of quick integration.
Overall, while the repository demonstrates strong community engagement and adherence to MLOps best practices through its structured modules and use of industry-standard tools, attention should be given to addressing long-standing open PRs to ensure continuous improvement and maintain high code quality standards across all modules. Additionally, implementing more rigorous review processes could enhance the robustness of integrated changes while fostering a collaborative environment that encourages timely resolution of outstanding contributions from external collaborators.
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