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ExternalSoftware Engineering
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Detecting Cycles and Loops in a Dependency Graph

A cycle in a build graph, an import graph or a task DAG turns a topological sort into an error message that usually does not say which edges are at fault. Getting the path out is not much harder than getting the boolean, and it is the only version anyone can act on. The first attempt almost everyone writes keeps a single visited set and reports a cycle when it reaches a node already in it: # WRONG def has_cycle(graph): visited = set() def dfs(node): if node in visited:

aitutorialllm
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ExternalSoftware Engineering
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Nukkad Chat Corner 🍵 | Comfort Food Isn’t a Restaurant — It’s a Thela. That’s Where the Soul Gets Comfort. I Sculpted Mine in CSS.

This is a submission for Frontend Challenge - Comfort Food Edition, CSS Art. When DEV said comfort food, I didn't think of restaurant platters or Sunday lunch. I thought of home. College. Friends walking through the city with no plan except to find something to eat. I thought of the aroma that hits you when you pass a thela — that small street cart — and your feet turn toward it before your brain catches up. 😮‍💨 That smell. That steam. That queue. That's where this project starts. Back here in

frontendchallengedevchallengecss
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ExternalSoftware Engineering
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A Two-Model Bake-Off on Your Own Repo: Isolating Runs With Git Worktrees

Most model comparisons I read have the same flaw: the models never touch the same problem under the same conditions. One gets a carefully groomed prompt, the other gets a sloppy one. One runs against a clean checkout, the other inherits half-finished edits from the previous attempt. The conclusion tells you more about the harness than the models. I wanted a comparison I could actually trust for my codebase, so I built a small bake-off harness around git worktree. It runs two coding models agains

aigitproductivity
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ExternalSoftware Engineering
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Building a Personal Finance App with Open Banking APIs in 2026 (No Certificates Required)

Building a personal finance app used to mean begging users to paste a CSV export — or worse, to share their banking password with a screen-scraping service. Open Banking was supposed to fix that, and under PSD2 it largely has. Every regulated EU/UK bank now exposes a standard API that returns your balances and transactions as clean JSON, with your explicit consent. So why isn't every indie developer shipping a net-worth dashboard on top of it? Because the "official" path to those APIs requires a

openbankingfintechpython
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ExternalSoftware Engineering
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Vibes Are Not a Benchmark: A 30-Minute Harness to Test Whether a Free Coding Model Can Touch Your Repo

Last month I wrote about the six questions I ask every new model. Those questions are good for a first impression, but they have a blind spot: they tell me how a model talks about code, not whether it can survive contact with my code. So I built a small, ugly, reproducible harness that runs any coding model against five tasks drawn from my own git history, scores the results with my real test suite, and writes the outcome to a CSV. This post is that harness, the reasoning behind it, and where fr

aiproductivitypython
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ExternalSoftware Engineering
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My README Promised Flags My CLI Doesn't Have. I Built a Drift Detector.

A stranger opened an issue on one of my small CLI tools last month: "The --watch flag in your README doesn't exist." They were right. I had removed --watch two releases earlier, rewritten the feature as a config option, updated the changelog, and forgotten the README's usage section entirely. Worse, the README still showed a fenced code block demonstrating the flag, so every new user was copy-pasting a command that errored out immediately. This is documentation drift, and it's embarrassingly com

documentationclipython
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ExternalSoftware Engineering
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ML Feature Store Versioning: Reproducible Quants

ML Feature Store Versioning: Reproducible Quants By Shakti Tiwari · Educational only · Not investment advice This article explains ml feature store versioning: reproducible quants from first principles. No live market numbers are quoted; the structure is what lasts. ML Feature Store Versioning: Reproducible Quants is one of those subjects that sounds simple until you implement it, at which point the hidden complexity appears. The first version works on a laptop with a tiny file; the second ver

pythonmachinelearningtrading
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