本文へ移動
cccskills
無料GitHub で公開

matlab-call-python

Call Python libraries from MATLAB using the py. interface, pyrun, pyrunfile, or pyenv. Use when writing or executing MATLAB code that calls Python functions or passes data between MATLAB and Python. REQUIRED when triaging Python errors from MATLAB (ModuleNotFoundError, ImportError, "Unable to resolve the name 'py.*'"). REQUIRED when setting up Python environments for MATLAB, creating virtual environments, or installing Python packages for use with MATLAB.

インストール方法を見る

含まれるファイル(3)

  • SKILL.md7.0 KB
  • manifest.yaml413 B
  • references/environment-setup.md3.1 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Call Python from MATLAB

Call Python libraries from MATLAB using modern APIs, correct environment setup, and structured error recovery.

When to Use

  • Writing MATLAB code that calls Python via py.*, pyrun, or pyrunfile
  • MATLAB code fails with ModuleNotFoundError, Python is not configured, or other Python-related errors
  • User asks to set up Python for MATLAB or create a virtual environment
  • User asks to install a Python package for use in MATLAB

When NOT to Use

  • Calling MATLAB from Python (MATLAB Engine API for Python — different direction)
  • Building MEX files or Python C extensions
  • Pure Python development with no MATLAB involvement
  • MATLAB Compiler or MATLAB Production Server deployment

Rules

NEVER use pyargs

Use MATLAB name=value syntax for Python keyword arguments. pyargs is outdated (name=value available since R2021a).

% TEMPLATE — not executable (requires scikit-learn)
rfc = py.sklearn.ensemble.RandomForestClassifier(n_estimators=int32(100), random_state=int32(42));

NEVER use pyversion

pyversion is not recommended. Use pyenv, which supports terminate, ExecutionMode, and environment switching.

ALWAYS use the Bash tool for pip installs and venv creation

Do not use MATLAB system(). The Bash tool provides streaming output and avoids complex string escaping.

ALWAYS follow recovery procedure before any pip install or venv creation

BEFORE running pip install or creating virtual environments, follow references/environment-setup.md. Do NOT infer Python paths from error tracebacks — those paths show importlib internals, not the correct install target.

ALWAYS ask user confirmation before calling terminate(pyenv)

terminate(pyenv) restarts the Python process and clears all Python state (imported modules, variables, open connections). Always inform the user what will be lost and get explicit consent before calling terminate.

ALWAYS wrap with integer types when Python expects int

MATLAB passes double by default. Python functions expecting int receive float, causing TypeError. Use int32() for counts, indices, and size arguments. If the value won't fit in 32 bits, use int64() or uint64() to prevent overflow.

ALWAYS use pystringarray for string arrays (R2026a or later)

When passing MATLAB string arrays to Python in R2026a or later, use pystringarray. Requires NumPy 2.0 or later. In R2025b and earlier, or when NumPy < 2.0, use py.list(cellstr(...)).

% R2026a and later:
names = ["Alice", "Bob", "Charlie"];
pyNames = pystringarray(names);

% R2025b and earlier:
names = ["Alice", "Bob", "Charlie"];
pyNames = py.list(cellstr(names));

Workflow

When calling Python from MATLAB, follow this workflow.

1. Write the Python code using modern syntax

result = py.module.function(arg1, arg2, kwarg1="value", kwarg2=42);

Prefer py.module.function(...) for direct function calls — it's readable, integrates with the MATLAB workspace, and supports tab completion. Reserve pyrun for multi-statement scripts where variables and imports persist in Python memory across calls (REPL-like execution). Reserve pyrunfile for running a standalone .py file (equivalent to running from the command line; no state carries over).

2. Run the code

Execute via mcp__matlab__evaluate_matlab_code (for inline code) or mcp__matlab__run_matlab_file (for script files).

3. If it succeeds — done

4. If it fails with a Python error — triage

Follow references/environment-setup.md ONLY for environment-related errors:

  1. ModuleNotFoundError
  2. MATLAB error about unresolved py.* name (e.g., "Unable to resolve the name 'py.numpy'")
  3. pyenv().Executable is empty
  4. py or pyenv calls error stating environment is not supported
  5. Any other error suggesting a missing library or unconfigured environment

For all other Python errors (ValueError, TypeError, logic errors in the Python code itself) — debug the code directly. These are code bugs, not environment issues.

Key Functions

FunctionPurposeAvailable From
pyenvQuery/configure Python environmentR2019b
pyrunExecute Python statements; variables persist across callsR2021b
pyrunfileExecute a standalone .py fileR2021b
pystringarrayPass MATLAB string array to PythonR2026a

InProcess vs OutOfProcess

  • OutOfProcess: Launches Python in a separate process. Mitigates third-party library conflicts between MATLAB and Python, therefore works with most Python packages without conflict. terminate(pyenv) restarts Python without restarting MATLAB. Can switch environments freely.
  • InProcess: (default) Launches Python within the same MATLAB process. PREFER for better performance. Cannot terminate. If Python is already loaded in InProcess mode, the user must restart MATLAB entirely to change Python configuration.

In ExecutionMode="OutOfProcess", when working on a custom Python module and you need to make changes after loading the module, or when you install packages mid-session, ALWAYS call terminate(pyenv) before calling the module again.

In ExecutionMode="InProcess", when working on a custom Python module and you need to make changes after loading the module, ALWAYS reload the module by running:

clear all;
clear classes;
mod = py.importlib.import_module("<module_name>");
py.importlib.reload(mod);

Patterns

Calling a Python function with keyword arguments

rfc = py.sklearn.ensemble.RandomForestClassifier(n_estimators=int32(100), random_state=int32(42));
rfc.fit(XTrain, yTrain);
predictions = double(rfc.predict(XTest));

Configuring MATLAB to use a virtual environment

After creating a virtual environment (venv) using the Bash tool, point MATLAB at it:

% Terminate current Python if loaded
terminate(pyenv);

% Point at venv executable
pyenv(Version="/path/to/.venv/Scripts/python.exe");

% Verify
disp(pyenv().Executable);
py.numpy.array([1, 2, 3]);

Conventions

  • When a keyword argument name conflicts with a MATLAB variable, append Val (e.g., py.complex(imag=imagVal) not py.complex(imag=imag))
  • AVOID "activating" a virtual environment — MATLAB doesn't use activation scripts. Point pyenv(Version=...) at the venv executable directly.

Copyright 2026 The MathWorks, Inc.


レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Guide for accessing financial and economic data in MATLAB using the Datafeed Toolbox. Covers Bloomberg (market data via bloomberg/blp/bloombergHypermedia), FRED (Federal Reserve economic data via fredrs), Haver Analytics (economic data via haver/haverdirect/haverview), and LSEG Datastream (historical data via datastreamws). Use when connecting to any of these data providers from MATLAB.

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。

matlab/matlab-agentic-toolkit1,1492026年10月9日 更新

Read BEFORE writing any code that adds Additive White Gaussian Noise (AWGN) to signals and converts between SNR, Eb/No, Es/No, and per-subcarrier SNR for communications simulations, using awgn(), convertSNR(), berawgn(). The default MATLAB patterns for AWGN (e.g., 'measured' option, manual SNR formulas) produce subtly incorrect results. This skill specifies the correct calling conventions, required function usage, and critical anti-patterns that must be avoided.

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。

matlab/matlab-agentic-toolkit1,1492026年10月9日 更新

Analyze AMS waveform data using Mixed-Signal Blockset utilities: phase noise measurement, clock jitter, anti-aliased resampling, timing measurements, lock time, INL/DNL, ADC/DAC calibration, HSpice import. Use when analyzing time-domain voltage from PLL/VCO/clock simulations, measuring phase noise from variable-step solver output, computing jitter, or resampling non-uniform data.

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。

matlab/matlab-agentic-toolkit1,1492026年10月9日 更新

Design and analyze electrically large antenna structures using MATLAB Antenna Toolbox. Covers reflector antennas (parabolic, Cassegrain, Gregorian, offset, corner, cylindrical, spherical, custom STL), reflectarrays and reconfigurable intelligent surfaces (RIS), antennas installed on platforms (vehicles, aircraft, ships, satellites), and radar cross section (RCS) analysis. Includes solver selection (MoM-PO, PO, MoM, FMM), mesh control, and GPU acceleration. Use when the user wants to design a dish/reflector antenna, reflectarray, analyze an antenna on a platform, or compute RCS.

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。

matlab/matlab-agentic-toolkit1,1492026年10月9日 更新

Analyze data using MATLAB. Use when the task involves tables, timetables, time-series data, numeric arrays, sensor matrices, or gridded data — including but not limited to exploring, row filtering, sorting, cleaning, transforming, aggregating, smoothing, padding, trimming, and answering questions about data. MATLAB provides extensive, easy-to-use built-in functions for these workflows with no additional products required.

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。

matlab/matlab-agentic-toolkit1,1492026年10月9日 更新

S-parameters, insertion loss, fields, currents, mesh control, and solver selection for RF PCB performance validation. TRIGGER: user asks to compute S-parameters, analyze insertion/return loss, extract fields or currents, compare MoM vs FEM, or control mesh for any RF PCB component. Invoke BEFORE writing sparameters() or solver code — API is non-obvious. SKIP: designing or creating components (use the specific matlab-design-pcb-* skill), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn).

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。

matlab/matlab-agentic-toolkit1,1492026年10月9日 更新

matlab のスキルをすべて見る

このスキルの問題を報告する