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Git Worktrees: Replace Your Pile of Clones with One Manageable Repository

Table Of Contents What is a Git worktree? Why use worktrees instead of several clones? A practical directory convention Everyday Git worktree commands Consolidating several independent clones Safety rules before starting Phase 1: Inventory every clone Phase 2: Choose the canonical repository Phase 3: Decide what each clone should become Phase 4: Convert one clone Moving a worktree Recovering a deleted .git worktree file When should a worktree be locked? When should git worktree prune be used? Final validation Quick reference Closing thoughts Have you ever ended up with a directory structure like this? ~/src/project ~/src2/project ~/src3/project ~/src4/project Each directory started innocently enough. One was for main . Another was for a feature branch. A third contained a half-finished experiment. The fourth had several untracked test files you were afraid to lose. Eventually, each clone had its own: stale view of the remote repository, duplicated Git history, local-only commits, modified files, ignored test artifacts, and unknown relationship to the others. Git worktrees are designed to solve this problem. A worktree gives you multiple checked-out working directories backed by one shared Git repository. Each working directory can have its own branch and uncommitted changes, while commits, branches, tags, remotes, and fetched objects remain shared. This article covers two things: How to use Git worktrees during normal development. How to safely consolidate several independent clones into one worktree-based layout without losing local work. The shell examples are written to work in both Bash and zsh . What is a Git worktree? A normal Git clone contains: the object database, commit history, branches, tags, remotes, remote-tracking references, and one checked-out working directory. A linked worktree adds another checked-out working directory to that same repository. For example: ~/src/project main ~/src/project-FEATURE-123 FEATURE-123 ~/src/project-HOTFIX-456 HOTFIX-45

2026-07-26 原文 →
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🔥 777genius / agent-teams-ai - You're the boss, agents are your team. They handle tasks on

GitHub热门项目 | You're the boss, agents are your team. They handle tasks on their own, message each other, and review each other's work. You just watch the kanban board and give high-level commands. Codex/Claude/OpenCode/Cursor/Grok/GitHub Copilot/Kiro/Z.AI/MiniMax/Kimi(200+ models, 75+ LLM providers, free models no auth). Build your AI company with multiple teams | Stars: 1,680 | 23 stars today | 语言: TypeScript

2026-07-26 原文 →
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Validate Kubernetes Manifests with Flux Schema

If you run GitOps with Flux, a broken manifest usually gets caught the slow way: it merges, the reconciler chokes, and you find out from a failing Kustomization. Flux Schema, the plugin that shipped with Flux 2.9, moves that check left into CI. It validates every YAML document against JSON Schema and CEL rules using the same evaluation logic as the Kubernetes API server, so a bad field fails the pull request instead of the cluster. Install and run it Flux Schema is a CLI plugin, not part of the core binary. Install it through the plugin system: $ flux plugin install schema $ flux schema --help Pin a version in CI so a new release never changes your gate's behavior mid-sprint: $ flux plugin install schema@0.5.0 Point it at a directory of manifests and it validates each document: $ flux schema validate ./manifests It ships with built-in schemas for Kubernetes, OpenShift, Gateway API, and the Flux CRDs, so a fresh install already knows your HelmRelease and Kustomization kinds without any setup. Strict validation flags unknown fields, wrong types, and missing required properties as hard errors, which catches the typos kubectl apply --dry-run=client quietly ignores. What CEL adds over plain schema checks JSON Schema catches shape problems: a string where an int belongs, a misspelled key. CEL rules catch logic problems. Because Flux Schema runs the x-kubernetes-validations rules embedded in CRDs through the same CEL engine the API server uses, a manifest that violates a cross-field constraint (say, a replica count that must stay below a limit, or two mutually exclusive fields both set) fails in CI with the exact message the cluster would have returned. You are testing against the real admission logic, not a stale copy of it. Wire it into a config file Drop a .fluxschema.yml at your repo root to control what gets checked. The file uses the schema.plugin.fluxcd.io/v1beta1 API and a Config kind: apiVersion : schema.plugin.fluxcd.io/v1beta1 kind : Config skipKind : - Secret s

2026-07-26 原文 →
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