Python ModuleNotFoundError Debugging Prompt

You are a senior Python engineer helping me diagnose a ModuleNotFoundError from evidence. Work from the complete traceback, exact interpreter, launch command, working directory, environment, project tree, import statement, package metadata, and deployment context I provide. First distinguish ModuleNotFoundError from ImportError, an exception raised inside an imported module, a circular import, a shadowed standard or third-party module, a missing optional dependency, a packaging or editable-install problem, and an IDE or notebook using a different interpreter. Never invent installed packages, paths, versions, import resolution, shell output, or a successful fix. Do not recommend global or privileged installation by default, deleting environments or lockfiles, weakening package verification, changing `sys.path` blindly, or executing an untrusted setup script.

Python implementation and exact version: [details]
Operating system, shell, container, notebook, IDE, CI, or deployment runtime: [details]
Exact command or action that launches the failing code: [paste]
Complete traceback from first line to final exception: [paste sanitized]
Failing import and smallest relevant code: [paste]
Current working directory and minimal project tree: [paste]
Exact interpreter path and environment type: [venv, conda, container, system, other]
Package manager, dependency file, lockfile, and relevant package versions: [details]
Packaging files and source layout: [pyproject.toml, setup configuration, src layout, namespace packages, other]
Read-only environment evidence: [python -c interpreter and path output, package-show output, import-spec check]
Local files that may shadow the module or package: [list]
Differences between terminal, IDE, notebook, test runner, CI, and production: [details]
Recent moves, renames, dependency, environment, or launch-command changes: [details]
Security, offline, reproducibility, and deployment constraints: [details]

Provide:
1. A concise classification of which module name failed and at what point in the import chain.
2. An evidence table separating confirmed interpreter, environment, working directory, package state, project layout, assumptions, and unknowns.
3. A Python import-resolution trace for the failing name, including parent packages and any shadowing candidates.
4. Safe read-only commands to confirm interpreter identity, environment activation, installed distribution metadata, import specification, current directory, and search path.
5. A ranked root-cause list tied to the supplied evidence rather than a generic instruction to reinstall everything.
6. The smallest reversible fix for the best-supported cause, with exact file or environment scope and why it restores import resolution.
7. Separate remedies when the issue is a missing dependency, wrong interpreter, undeclared dependency, incorrect package layout, bad relative or absolute import, name shadowing, or deployment omission.
8. Verification using the original launch command plus a minimal import check in the same interpreter and environment.
9. Regression protection through dependency declaration, clean-environment installation, CI checks, packaging tests, and documented launch commands where relevant.
10. Rollback steps, remaining unknowns, and the next single piece of evidence to collect if the cause is not proved.

Redact tokens, private registry credentials, user paths, internal hostnames, and personal data. Prefer the project's declared environment and package manager, and label every command that would modify dependencies before presenting it.