Library

The algoesup library provides support for testing, timing and linting code. This documentation is for version 0.3.1.

Testing

Simplified testing for Python functions, see the examples.

test

test(function: Callable, test_table: list) -> None

Test the function with the test_table. Report failed tests.

Parameters:

Name	Type	Description	Default
`function`	`Callable`	The function to be tested. Can’t be a built-in function.	required
`test_table`	`list`	The list of tests. Each element of test_table is a list or tuple with: a string (the test case name); one or more values (the inputs to the function); the expected output value.	required

Timing

Tools for measuring and plotting run-times, see the examples.

time_functions

time_functions(
    functions: list[Callable],
    inputs: Callable,
    start: int,
    double: int,
    text: bool = True,
    chart: bool = False,
    value: bool = False,
) -> None

Print or plot the run-times of different functions for the same inputs.

time_functions prints or plots the run-times given list of functions and an input generator. Inputs are generated based on a starting size and are doubled a specified number of times.

Parameters:

Name	Type	Description	Default
`functions`	`list[Callable]`	A list of functions whose run-times will be measured. Must be 1 to 6 functions.	required
`inputs`	`Callable`	A function to generate inputs when given a specific size.	required
`start`	`int`	The starting size for the inputs. Must be positive.	required
`double`	`int`	The number of times to double the input size. Must be non-negative.	required
`text`	`bool`	If True, print the run-times in text format	`True`
`chart`	`bool`	If True plot the run-times using a chart.	`False`
`value`	`bool`	If True x-axis is labelled “Input value” otherwise “Input size”.	`False`

Raises:

Type	Description
`AssertionError`	If input conditions are not satisfied.

time_cases

time_cases(
    function: Callable,
    cases: list[Callable],
    start: int,
    double: int,
    text: bool = True,
    chart: bool = False,
) -> None

Print or plot the run-times of function for different input cases.

time_cases prints or plots the run-times of a single function using a list of different input generators. Inputs are generated based on a starting size and are doubled a specified number of times.

Parameters:

Name	Type	Description	Default
`function`	`Callable`	A function whose run-times will be measured.	required
`cases`	`list[Callable]`	A list of 1 to 6 functions to generate inputs of different cases, e.g. best-, normal- and worst-case.	required
`start`	`int`	The starting size for the inputs. Must be positive.	required
`double`	`int`	The number of times to double the input size. Must be non-negative.	required
`text`	`bool`	If True, print the run-times in text format.	`True`
`chart`	`bool`	If True, plot the run-times using a chart.	`False`

Raises:

Type	Description
`AssertionError`	If input conditions are not satisfied.

time_functions_int

time_functions_int(
    functions: list[Callable],
    generator: Callable = int_value,
    start: int = 1,
    double: int = 10,
    text: bool = True,
    chart: bool = True,
) -> None

Time functions that take a single integer as input.

time_functions_int uses time_functions to measure and display the run-times of a given list of functions that accept a single integer input. The integer inputs are generated starting from a specified value that defaults to 1, and are doubled a specified number of times that defaults to 10.

Parameters:

Name	Type	Description	Default
`functions`	`list[Callable]`	A list of functions whose run-times will be measured. Each function must accept a single integer argument. Must be 1 to 6 functions.	required
`generator`	`Callable`	A function to generate integer inputs. Defaults to `int_value`, which returns a tuple containing the input integer.	`int_value`
`start`	`int`	The starting integer value for inputs. Defaults to 1. Must be positive.	`1`
`double`	`int`	The number of times to double the input integer value. Defaults to 10. Must be non-negative.	`10`
`text`	`bool`	If True, print the run-times in text format.	`True`
`chart`	`bool`	If True, plot the run-times using a chart.	`True`

Linting

Linting tools for Jupyter Notebook environments.

See the type checking and linting examples.

allowed

allowed

Activate/deactivate the allowed linter.

When active, the linter checks each code cell that is executed for any Python constructs that are not listed in the given configuration file.

%allowed on ... activates the linter with any command options given after on
%allowed on is equal to %allowed on --config m269.json
%allowed off deactivates the linter
%allowed shows the current status of the linter
%allowed? shows this documentation and the command’s options

For a list of possible options ..., enter !allowed -h in a code cell. Some options may not be appropriate when running allowed within a notebook.

The --config option expects m269.json, tm112.json or the name of a JSON file with your own configuration.

pytype

pytype

Activate/deactivate the pytype linter.

When active, the linter checks each code cell that is executed for type errors.

%pytype on ... activates the linter with the command options given after on
%pytype on is equal to %pytype on --disable name-error,import-error
%pytype off deactivates the linter
%pytype shows the current status of the linter
%pytype? shows this documentation and the command’s options

For a list of possible options ..., enter !pytype -h in a code cell. Some options may not be appropriate when running pytype within a notebook.

The --disable option expects a list of errors to ignore, without spaces. By default, %pylint ignores these errors:

name-error: cells often use names defined in previous cells
import-error: pytype doesn’t find local modules

ruff

ruff

Activate/deactivate the Ruff linter.

When active, the linter checks each code cell that is executed against the selected code style rules.

%ruff on ... activates the linter with any command options given after on (see [ruff’s list of rules])
%ruff on is equal to %ruff on --select A,B,C90,D,E,W,F,N,PL --ignore D100,W292,F401,F821,D203,D213,D415
%ruff off deactivates the linter
%ruff shows the current status of the linter
%ruff? shows this documentation

The command %ruff on ... will run ruff check --output-format json ... on each cell. For a list of the possible options ..., enter !ruff help check in a code cell. Some options may not be appropriate when running Ruff within a notebook.

The --select and --ignore options expect a list of rule codes, without spaces.

By default, %ruff enables the rules from flake8-builtins (A), flake8-bugbear (B), mccabe (C90), pydocstyle (D), pycodestyle (E, W), pyflakes (F), pep8-naming (N), and pylint (PL).

By default, %ruff ignores these rules:

D100: Missing docstring in public module (notebooks aren’t modules)
W292: No newline at end of file (cells don’t have a trailing blank line)
F401: Imported but unused (cells often import modules that are used later)
F821: Undefined name (cells often use names defined in previous cells)
D203: use D211 instead (no blank line before class docstring)
D213: use D212 instead (docstring starts right after “”“)
D415: use D400 instead (first line of docstring must end in .)