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Queries and code facts checking support for python source code

Project description

codequery

A library to make it easy to write code queries, asserts on code facts and design tests for Python code. It provides a simple wrapper object with an easiear, more readable API to write queries on ast nodes as well as the tokenizer standard libraries.

BEWARE This is just a proof of concept and should be used with care in any professional context. My personal and primary use for this package is to check students code in the context of an introductory programming course. While automated tests do provide good feedback and guidance wrt to functional aspects of the code (whether it does what it is expected to do), they do not provide any feedback wrt to how the code has been written (and, in particular, wrt the way it was NOT expected to be). I use codequery to write easy to read and understand design tests that the students use to restrict the solution space, while still using a conventional testing framework and tooling (namely, pytest and unittests).

how to install

pip3 install codequery

how to use

TBD. However, the following examples should make it clear for simple cases. Soon I will add here a minimal documentation for each query method available in the API.

examples

The test below is used in a programming problem in which the student is asked to implement an in-place bubble sort. It prevents the module under test from: i) importing any modules; ii) using the sort() method and the sorted() function (python built-in functions); and iii) using methods that change lists in structural way, to assure the algorithm is in-place (this forces the programmer to manipulate the list as if it was a simple array, namely, using only item assignments). The calls() method receives a function (or class) name and returns a boolean stating whether that function is called or not from that module.

from codequery import Module

mod = Module(filename="answer.py")

def test_is_inplace():
    assert not mod.imported
    assert not mod.calls("sorted")
    assert not mod.calls(".sort")
    assert not mod.calls(".append")
    assert not mod.calls(".pop")
    assert not mod.calls(".insert")

The test below could be used to complement a query-sort implementation, to require that a recursive solution be written. Observe the select() function being used. It receives either an ast node type (or a string that matches the type name) and returns all the elements in the tree rooted at the given node (in this case, the whole module mod). I'll assume the assert line is self-explanatory (the call() is the same in the example above).

def test_is_recursive():
    functions = mod.select("FunctionDef")
    assert any(f.calls(f) for f in functions)

The next test checks whether the module implements the python main pattern and that it has a main() function, called from it.

def test_uses_main_section():
    mainsect = next(e for e in mod.select("If") if e.get("left") == "__name__")
    mainsect.calls("main")

In fact, as selecting the main section is such a common pattern, codequery has a helper method that makes this code become simpler and more readable. The first line in the example above could be: mainsect = mod.select("main_section").

scripts

Two scripts that use codequery to analyze code scripts are also provided: code-outline and code-profile, which are used to create code outlines (a listing of the most relevant node elements that give the code its outline structure) and code profiles (a vector containing an ordered counting of the most important elements in the code under analysis).

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