「oop」の検索結果

Use when adding or changing tuning values, items, enemies, abilities or levels - put them in the engine's data assets (ScriptableObject, Resource, DataAsset/DataTable, JSON/RON) with validation and stable IDs, keep runtime state out of shared data, inject services instead of singletons, and test data invariants.

日本語の概要は準備中です。原文の説明を表示しています。

Use when writing Bevy (Rust ECS) game code - pin and respect the repo's minor version, plugins/systems/queries/resources, schedules with FixedUpdate and Time, states and run conditions, messages vs observers across versions, required components, testing systems with App::update and a manual time strategy, compile-time and allocation hygiene.

日本語の概要は準備中です。原文の説明を表示しています。

Use when writing or running Unreal Engine tests - which test type fits (simple/complex automation tests, Automation Specs, functional tests, CQTest, Low-Level Tests, Gauntlet), naming and filters, latent tests, and the headless UnrealEditor-Cmd run with report export, exit handling and screenshot captures.

日本語の概要は準備中です。原文の説明を表示しています。

Use when starting any game task, before writing tests - find out which editors and runners exist on this machine, keep gameplay rules in engine-independent classes with an injected clock and seeded RNG, and report exactly what could not run.

日本語の概要は準備中です。原文の説明を表示しています。

Use when building a 2D web game with Phaser (3.x/4.x) or PixiJS 8 in TypeScript - framework vs renderer, Phaser scenes/game objects/arcade physics/groups as pools/scale manager/loader, scene shutdown cleanup, PixiJS 8 async init, Assets bundles, ticker units and destroy, and keeping rules in plain TS modules.

日本語の概要は準備中です。原文の説明を表示しています。

Use when writing or running Godot tests - gdUnit4 or GUT (whichever the repo has), unit tests on typed GDScript classes, scene runners for frames, physics, input and signals, headless CLI with --import first, reports and exit codes, and C# tests via gdUnit4Net or plain dotnet test.

日本語の概要は準備中です。原文の説明を表示しています。

Use when writing Godot 4 GDScript - static typing everywhere, scene composition with component nodes, call down/signal up, @onready caching, Resources as data duplicated per instance, autoloads only for services, state machines, pooling, physics in _physics_process, and threaded loading.

日本語の概要は準備中です。原文の説明を表示しています。

Use when you are about to hand off a change a player can see - the exact steps to look at it running (web game in the browser at two viewports plus a seeded Playwright smoke run for input and console errors; engine games through a headless frame capture), the checklist, and how to report what could not be observed.

日本語の概要は準備中です。原文の説明を表示しています。

Use when writing Unreal Engine 5 C++ - the gameplay framework classes and where logic belongs, UObject/AActor/UActorComponent lifecycle, UPROPERTY/UFUNCTION and GC-safe pointers (TObjectPtr, TWeakObjectPtr), subsystems, the C++/Blueprint boundary, Enhanced Input, tick discipline, and compiling from the command line.

日本語の概要は準備中です。原文の説明を表示しています。

Use when building or changing features, preprocessing, encoders, resampling or train/validation/test splits — keep every fitted transform inside a Pipeline fitted on training folds only, and build time and group features without seeing the future or the same entity twice

日本語の概要は準備中です。原文の説明を表示しています。

Use when training, tuning, comparing or evaluating a model — choosing the cross-validation scheme, baselines, tuning inside CV, thresholds and calibration, per-slice metrics, feature importance and error analysis

日本語の概要は準備中です。原文の説明を表示しています。

Use when a task touches a Jupyter or marimo notebook, asks to productionise or schedule notebook logic, or when you are tempted to do the work in a notebook — extract logic into tested modules, keep the notebook thin and reproducible, and commit it the way the repo does

日本語の概要は準備中です。原文の説明を表示しています。

Use when you meet a new dataset, table, file or source, before building features or a model on it, or when a number looks wrong — profile grain, keys, nulls, cardinality, time coverage and target balance, and persist what you learn as code

日本語の概要は準備中です。原文の説明を表示しています。

Use when tools from the jupyter, duckdb, dbt, mlflow, huggingface or postgres MCP servers appear in your tool list, or before reaching for one — what each is good for, what it can damage, and the CLI fallback when it is not connected

日本語の概要は準備中です。原文の説明を表示しています。

Use when a model is served online (FastAPI, BentoML) or scored in batch, when changing how a model artifact is loaded or versioned, or when adding drift, quality or prediction monitoring and a rollout plan for a new model

日本語の概要は準備中です。原文の説明を表示しています。

Use when starting a Python data or ML project, adding its first tooling, or changing pyproject.toml, the lockfile, the package layout or the lint/type/test configuration — detect the repo's tooling first, then uv, ruff, mypy, pytest and a src layout

日本語の概要は準備中です。原文の説明を表示しています。

Use when writing tests for data or ML code — what to test at each layer (transforms, schemas, properties, pipeline smoke, model-quality thresholds, determinism and parity), how to build small synthetic fixtures, and what not to test

日本語の概要は準備中です。原文の説明を表示しています。

Use when a task asks for a model, a score, a forecast or a prediction-driven feature — pin down the decision, target, unit, prediction time, metric and baseline before writing any modelling code

日本語の概要は準備中です。原文の説明を表示しています。

Use when a change trains a model, reports a metric, or touches seeds, data or model versions, the lockfile, MLflow or DVC — what every run must log, seeding, environment pinning, data versioning and keeping tests off the shared tracking server

日本語の概要は準備中です。原文の説明を表示しています。

Use when dataframe code is slow or runs out of memory, when data outgrows pandas, or when writing pandas 3, Polars or DuckDB code — vectorisation, dtypes, Copy-on-Write, lazy and out-of-core execution, and measuring before and after

日本語の概要は準備中です。原文の説明を表示しています。

Use when writing or changing analytical SQL or a dbt model — CTE structure, window functions, grain and join correctness, dbt data tests, unit tests, contracts and incremental models, and how to run them

日本語の概要は準備中です。原文の説明を表示しています。

Use when you are about to hand off any number, table, chart or analysis someone will act on (a metric query, a dbt mart, a report, an experiment readout) — the pre-delivery checklist for data quality, calculation, reasonableness and presentation, and the pitfalls that produce plausible wrong numbers

日本語の概要は準備中です。原文の説明を表示しています。

Use when data crosses a boundary into your code (file, API, warehouse table, upload, model input or output), when a join or cleaning step can change row counts, or when adding pandera, Great Expectations, Pydantic or dbt checks

日本語の概要は準備中です。原文の説明を表示しています。

Use when designing or analysing an A/B test, computing power or sample size, testing whether a difference is real, or writing any statistical claim — effect sizes with intervals, SRM checks, multiple comparisons and causal caveats

日本語の概要は準備中です。原文の説明を表示しています。