Quick Start

This tutorial is a brief introduction to the different features of PythonTA.

Installation

In PyCharm:

1. Open the Settings dialog (Windows: File -> Settings…, macOS: PyCharm -> Preferences).

2. Go to Project , and select Project Interpreter.

3. Click on the + icon next to the table of installed packages.

4. Search for “python-ta”, and click Install Package.

In the command line:

1. On Windows, run python -m pip install python-ta. On macOS or Linux, run python3 -m pip install python-ta.

Running PythonTA

PythonTA’s code analyzer can be run either through Python code or on the command line.

Running PythonTA via Python code

Option 1. If you have a Python file you’d like to analyze, you can analyze it by adding the following lines of code:

import python_ta
python_ta.check_all()

Here is an example file called sample.py:

"""This file illustrates basic usage of PythonTA's code analysis.
"""


def add_two(x: int, y: int) -> int:
    """Return the sum of x and y.

    PythonTA's analysis of this code will report three issues:

    1. A missing return statement (a logical error)
    2. Missing whitespace around the + (a formatting issue)
    3. The presence of a print call (a code style issue)
    """
    result = x+y
    print(result)


if __name__ == "__main__":
    import python_ta
    python_ta.check_all()

When you run this file, PythonTA will analyse this file and open a webpage showing a report of any issues it found.

Try fixing the above code by adding spaces around the +, and replacing print(result) with return result. After making these changes, re-run the file: PythonTA’s analysis should not find any more issues!

Option 2. If you don’t want to add code to the file being analysed, you can instead call python_ta.check_all from outside the file (e.g., in the Python shell, or a separate Python file) and pass in a filename or path:

import python_ta
python_ta.check_all("sample.py")

Running PythonTA via the command line

You can run PythonTA directly from the command line by passing in a filename or path:

$ python_ta sample.py

Learning about the checks

Our PythonTA Checks webpage describes all checks that are performed by PythonTA. Many of these checks originate from Pylint, and more information can be found on the Pylint documentation website.

You can also look up the documentation for a specific error by its five-character error code (e.g., E0401) by calling the python_ta.doc function:

python_ta.doc("E0401")

This will open up your web browser to the corresponding entry in our documentation page.

Checking contracts

PyTA supports checking preconditions and representation invariants automatically during the execution of a Python program. These are parsed automatically from function/class docstrings, and turned into executable assertions. Type annotations for functions and class instance attributes are also checked. For examples of both the syntax for specifying contracts and resulting behaviour, please check out https://github.com/pyta-uoft/pyta/blob/master/examples/contracts_demo.py.

This kind of checking is completely separate from python_ta.check_all, and can be enabled by inserting the following statements in your if __name__ == '__main__' block:

if __name__ == '__main__':
    import python_ta.contracts as contracts
    contracts.check_all_contracts()

This will add assertions for every function and class in the current module. If you want to assertions to only a subset of the functions/classes, import and use the decorators check_contracts (for functions) and add_class_invariants (for classes) instead.

If you wish to check contracts for your imported modules, pass the module names as arguments to check_all_contracts.