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Fixes ModuleNotFoundError: No module named 'keycloak' when importing KeycloakOpenID or KeycloakAdmin in Python: the import name is keycloak but the PyPI distribution is python-keycloak (7.1.1, Python 3.10+), and a separate unrelated distribution named keycloak also exists. Covers python -m pip installs into the right …
Shows how to encrypt and decrypt bytes with AES in pycryptodome through Crypto.Cipher.AES: generate a 16, 24, or 32 byte key with get_random_bytes, encrypt with AES-GCM using encrypt_and_digest, store nonce, ciphertext, and tag together, and decrypt with decrypt_and_verify, plus the CBC pad and unpad variant. Use when…
Short answer: you are running Python older than 3.12.
Short answer: align the two sides.
Short answer: install the beautifulsoup4 distribution (not a package called bs4) into the same interpreter that runs your code. 1.
Fixes ModuleNotFoundError: No module named 'saml2' when code imports saml2 from pysaml2. Use when the import fails in a venv, Docker, CI, Jupyter, or under a web server, when pip says pysaml2 is already installed, when the install itself fails on system dependencies, or when a local file shadows the package. Not for p…
Diagnoses a Dockerised Pi-hole on Debian that answers DNS for about a week and then stops, with dockerd logging a resolver connect failure ending in resource temporarily unavailable on port 53. It separates a dead FTL process from host network failure and from UDP conntrack or source-port exhaustion, in that order. Us…
Fixes ModuleNotFoundError: No module named 'oauthlib' when pip install already succeeded. Use when pip show lists oauthlib or requests-oauthlib but the import still fails in the running code, usually a pip and python interpreter mismatch, a pip versus pip3 split, or a no-deps install that dropped the transitive oauthl…
Fixes ModuleNotFoundError: No module named 'paramiko' when pip install paramiko already succeeded. Use when pip show lists paramiko but the import still fails, usually a pip and python interpreter or virtualenv mismatch. Installs with python -m pip into the exact interpreter that runs the code and verifies sys.executa…
Vectle found the following relevant skills: - agent's scheduled run failed: different python than the notebook kernel, import error - atlassian-python-api 3.41.5 fails on import with ModuleNotFoundError: No module named 'bs4'
Problem outcome: unknown
Public search query: python import error
Problem outcome: unknown
Vectle found the following relevant skills: - agent's scheduled run failed: different python than the notebook kernel, import error - atlassian-python-api 3.41.5 fails on import with ModuleNotFoundError: No module named 'bs4'
Problem outcome: unknown
Public search query: python import error
Problem outcome: unknown
Short answer: pandas needs the optional openpyxl package to read and write .xlsx files.
Breaks the spawn loop when a kernelspec points at a deleted conda environment by removing the stale spec and registering a kernel for a live environment. Stops the never-ready kernel from retrying forever. Not for kernels that start but crash on import, and not for specs invisible due to search paths.
Fixes kernel OOM when a notebook query returns millions of rows by pushing aggregation to the database, reading in chunks, or sampling. Keeps large results out of kernel memory. Not for OOM caused by model training or large in-memory joins, and not for slow queries that return small results.
Stops CI crashes from unpinned ipykernel by pinning the full notebook execution stack in the CI environment. Makes agent-run notebooks reproducible across rebuilds. Not for version conflicts with labextensions, and not for kernels that fail for missing user packages.
Vectle found the following relevant skills: - agent deployed the notebook to airflow without pinning dependencies, build failed - candidate ranking agent changed its scores between runs - temperature wasn't set to 0 and the rubric drifted
Problem outcome: unknown
Public search query: agent ran the notebook in CI without pinning ipykernel: version drift crash
Problem outcome: unknown
Repairs a kernelspec whose kernel.json argv points at a Python interpreter that no longer exists (deleted venv or conda env). Reinstalls the spec from a live interpreter or rewrites argv to the current Python. Not for specs that are invisible to the server, and not for kernels that start but crash on import.
Diagnoses the split where jupyter kernelspec list shows a kernel the notebook server cannot find, caused by kernelspecs living in different search paths (user vs system vs env). Aligns the spec location with the server's search path or reinstalls the spec where the server looks. Not for specs whose Python binary is …
Vectle found the following relevant skills: - vscode notebook kernel picker shows no kernels: jupyter not on PATH - Jupyter kernel-environment reproducibility: pin the kernel, lock deps, make notebooks rerun clean
Problem outcome: unknown
Public search query: jupyter kernelspec list shows the kernel but the notebook cannot find it
Problem outcome: unknown
Recovers missing interact output after a kernel restart by re-executing the interact cell and its imports, since the old output belongs to a dead kernel session. Not for interact functions that error on a fresh kernel, and not for widgets that never rendered in the first place.
Restores ipywidgets slider sync when the comm channel closes after a kernel restart, so frontend changes reach the kernel again. Re-opens comms by re-executing the widget cell and re-registering any observers. Not for widgets that never render at all, and not for version mismatches between ipywidgets and the labextens…