Search Results for "github-copilot"
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Showing 7 open source projects for "github-copilot"
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Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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vscode-pull-request-github
GitHub Pull Requests for Visual Studio Code
This extension allows you to review and manage GitHub pull requests and issues in Visual Studio Code. The support includes authenticating and connecting VS Code to GitHub. GitHub Enterprise is supported by the community, please see this PR for how to set it up. Listing and browsing PRs from within VS Code. Reviewing PRs from within VS Code with in-editor commenting. Validating PRs from within VS Code with easy checkouts. -
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Super-Linter
Combination of multiple linters to install as a GitHub Action
...There is no need to set the GitHub Secret as it is automatically set by GitHub, it only needs to be passed to the action. -
3
reviewdog
Automated code review tool integrated with any code analysis tools
...An automated code review tool working with any lint tools and supports local run as well. “reviewdog” provides a way to post review comments to code hosting services, such as GitHub, automatically by integrating with any linter tools with ease. It uses any output of lint tools, with translation if required, and posts them as a comment if the file and line are in diff of patches to review. reviewdog also supports running in a local environment to filter the output of lint tools by diff. We can use various linters and static code analysis tools to detect such problems in local machines, editors, CI services. ... -
4
todo_notifier
Todo Notifier simplifies the management of todo items in your project
...Integrate easily with other project management tools. The package is available on PyPi: https://pypi.org/project/todonotifier/ For more information, please check out the GitHub repository: https://github.com/ashu-tosh-kumar/todo_notifier Detailed code documentation on GitHub Pages: https://ashu-tosh-kumar.github.io/todo_notifier/todonotifier.html Medium Article on how to use: https://at-k.medium.com/streamline-your-todos-with-todo-notifier-for-python-projects-6f95c03a2d34 -
Forever Free Full-Stack Observability | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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5
ThinkReview
AI-powered code reviews for GitLab & Azure DevOps. Zero setup. Powered
I Copilot for Gitlab and Azure DevOps Merge requests (MRs) and Pull Requests (PRs) in your browser. The extension Summarises merge requests , provided suggestions and find potential security issues , provide smart questions to dive deeper and chat with your pull requests The extension works out of the box without any complex setup - Supports custom Self hosted Gitlab as well as gitlab.com and gitlab enterprise Enhance your GitLab MRs and Azure Devops PRsworkflows with automatic patch diff access and AI-powered code reviews. ... -
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Cross Platform Node Guide
Improve front-end engineer workflow & standard, powered by TypeScript
A command-line tool aims to improve front-end engineer workflow and standards, powered by Node.js. Feflow (pronounced /ˈfefləʊ/) is a front-end flow and rule tool to improve engineering efficiency., and is hosted on Github: feflow. At present, it has been used in many applications, such as Now, Huayang Live, Huayang Friends, Mobile QQ Near Hand, Group Video, Group Gift, Huiyin, Tencent Myapp, Penguins and etc. With 80+ WEB/IOS/Andriod stable users, the cumulative production project reached 240+. Feflow refers to the thinking of Pipeline and divides work into five steps: init, develop, build, test, deploy. ... -
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Codeball AI
AI Code Review that finds bugs and fast-tracks your code
...Stay sharp, don't let the bugs pass through. Identifies and approves or labels safe PRs. Save time by fast-tracking PRs that are easy to review. Fully customizable and programmable with GitHub Actions. Codeball Actions are built on multiple smaller building blocks, that are heavily configurable through GitHub Actions. Codeball uses a deep learning model that has been trained on over 1 million Pull Requests. For each contribution, it considers hundreds of inputs. Codeball is optimized for precision, which means it only approves contributions that it's really confident in.
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