Repository: TheAlgorithms/Python

Issue:
Improve our test coverage
### Feature description

Many of our existing algorithm files have little to no unit testing. This is problematic because this can easily let bugs slip through. We want some assurance that the code we currently have is correct and functional. We welcome all contributors to open PRs to help us add tests to our codebase.

### How to find low-coverage files

Go to the Actions tab in this repository and find the most recent **build** workflow run. Open the logs under "Run Tests" and scroll down until you find the section on code coverage:
```
---------- coverage: platform linux, python 3.12.0-final-0 -----------
Name                                                                          Stmts   Miss  Cover   Missing
-----------------------------------------------------------------------------------------------------------
quantum/q_fourier_transform.py                                                   30     30     0%   14-93
scripts/validate_solutions.py                                                    54     54     0%   2-94
strings/min_cost_string_conversion.py                                            78     75     4%   20-57, 61-75, 79-129
...
```
The "Cover" column tells you what percentage of the lines in that file are covered by tests. We want to increase this percentage for existing files. Find a file with low coverage percentage that you wish to write tests for, add doctests for each function, and open a PR with your changes. You do not need to have a perfect coverage percentage, but all functions should have doctests.

Some files will naturally be hard to write tests for. For example, the file may be poorly written because they lack any functions. Other files might be how-tos, meaning they simply demonstrate how to use an existing library's functions rather than implementing the algorithm themselves. Ignore these kinds of files, as they will need to be rewritten eventually. Furthermore, ignore files in the `web_programming` and `project_euler` directories. Web programming files are inherently hard to test and Project Euler files have their own validation workflow, so don't worry about their test coverage.

_**When you open your PR, put "Contributes to #9943" in the PR description.**_ Do not use the word "fixes", "resolves", or "closes". This issue is an ongoing one, and your PR will not single-handedly resolve this issue.

### How to add doctests

A doctest is a unit test that is contained within the documentation comment (docstring) for a function. Here is an example of what doctests look like within a docstring:
```py
def add(a: int, b: int) -> int:
    """
    Adds two non-negative numbers.
    >>> add(1, 1)
    2
    >>> add(2, 5)
    7
    >>> add(1, 0)
    1
    >>> add(-1, -1)
    Traceback (most recent last):
    ...
    ValueError: Numbers must be non-negative
    """
```
For every function in the file you choose, you should write doctests like the ones shown above in its docstring. If a function doesn't have a docstring, add one. Your doctests should be comprehensive but not excessive: you should write just enough tests to cover all basic cases as well as all edge cases (e.g., negative numbers, empty lists, etc).

Do not simply run a function on some example inputs and put its output as the expected output for a doctest. This assumes that the function is implemented correctly when it might not be. Verify independently that your doctests and their expected outputs are correct. **Your PR will not be merged if it has failing tests.** If you happen to discover a bug while writing doctests, please fix it.

_**Please read our [contributing guidelines](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md) before you contribute.**_


Discussion:
I'll work on the palindrome script
Hi. I am new and would like to contribute to this issue
Please check:
* #10135
* #10156 
@tianyizheng02 Can you please Review this two PRs

> [Adding doctests in simpson_rule.py](https://github.com/TheAlgorithms/Python/pull/10269)

> [Adding doctests in longest_sub_array.py](https://github.com/TheAlgorithms/Python/pull/10194)
Can we close this issue because it is already merged.
No, improving test coverage is an _ongoing_ issue. It can't be resolved by a single PR because there are many, many files that need tests. Right now, it definitely hasn't been resolved.
@tianyizheng02 Can you please review this PR 

- #10540 
Can we ask people to use "Ref" instead "Fixes", so that we don't have keep reopening this issue?
How is the percentage determined? The tests I added only bumped the coverage by 1%
> How is the percentage determined? The tests I added only bumped the coverage by 1%

@RaymondDashWu The coverage percentage is calculated from the total number of lines covered by tests across _all_ files in the repo. As of writing, the latest builds show the following:
```
-----------------------------------------------------------------------------------------------------------
TOTAL                                                                         31846   9986    69%
```
There are 9986 lines of code in total _not_ covered by tests compared to 31846 lines of code in total, which is how the 69% comes about. The tests that you added only improved the coverage for _one_ file out of the hundreds of files that we have, and that's why it barely changed the percentage at all.

This is why I said in my previous comment that this is an _ongoing_ issue. No single PR will improve our coverage enough to "fix" this issue.
Hi @tianyizheng02 Have code coverage improved from 16% to 85% (or 100% when not including the main block) for the `graphs/dijkstra_algorithm.py` file ([linked above](https://github.com/TheAlgorithms/Python/pull/10695))
> d by tests compared to 31846 lines of code in total, which is how the 69% comes about. The tests that you added only improved the coverage for _one_ file out of the hundreds of files that we have, and that's why it barely changed the percentage at all.

Thanks for this info @tianyizheng02! I figured out that I've actually been looking at the wrong percentages for test coverage. I was looking at the loading of the test session percentages thinking that's what you pointed out in the first screenshot

<img width="591" alt="image" src="https://github.com/TheAlgorithms/Python/assets/33266041/2ceced9c-4a10-4cf0-ab3c-5e6e3f4ccd46">
Hi, I was looking at the Fibonacci function, and I found an untested function "fib_recursive_term" that was nested inside of the fib_recursive function. I added tests for it, so in terms of this issue it's all good now.

But I was just wondering whether or not I should define that function globally because I don't see the point of having it nested in the fib_recursive function. 

So I want to propose to move the fib_recursive_term out from the fib_recursive function and have it as a separate function above it, would there be any issue if that happens? 


Maybe you can create a new issue for it since the scope of this issue
seems to be only addition of do tests?

On Sat, Oct 21, 2023, 2:40 PM Kento ***@***.***> wrote:

> Hi, I was looking at the Fibonacci function, and I found an untested
> function "fib_recursive_term" that was nested inside of the fib_recursive
> function. I added tests for it, so in terms of this issue it's all good now.
>
> But I was just wondering whether or not I should define that function
> globally because I don't see the point of having it nested in the
> fib_recursive function.
>
> So I want to propose to move the fib_recursive_term out from the
> fib_recursive function and have it as a separate function above it, would
> there be any issue if that happens?
>
> —
> Reply to this email directly, view it on GitHub
> <https://github.com/TheAlgorithms/Python/issues/9943#issuecomment-1773726996>
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@tianyizheng02 Please help review my pull request so I can write more tests for this repo.
https://github.com/TheAlgorithms/Python/pull/10751
@SaiHarshaK alright, ill make a new issue for the nested functions thing, meanwhile I'll make a pull request where I've implemented doctests to several functions once I double check everything 

Resolving patch:
diff --git a/maths/binomial_coefficient.py b/maths/binomial_coefficient.py
--- a/maths/binomial_coefficient.py
+++ b/maths/binomial_coefficient.py
@@ -1,10 +1,48 @@
 def binomial_coefficient(n: int, r: int) -> int:
     """
-    Find binomial coefficient using pascals triangle.
+    Find binomial coefficient using Pascal's triangle.
+
+    Calculate C(n, r) using Pascal's triangle.
+
+    :param n: The total number of items.
+    :param r: The number of items to choose.
+    :return: The binomial coefficient C(n, r).
 
     >>> binomial_coefficient(10, 5)
     252
+    >>> binomial_coefficient(10, 0)
+    1
+    >>> binomial_coefficient(0, 10)
+    1
+    >>> binomial_coefficient(10, 10)
+    1
+    >>> binomial_coefficient(5, 2)
+    10
+    >>> binomial_coefficient(5, 6)
+    0
+    >>> binomial_coefficient(3, 5)
+    0
+    >>> binomial_coefficient(-2, 3)
+    Traceback (most recent call last):
+        ...
+    ValueError: n and r must be non-negative integers
+    >>> binomial_coefficient(5, -1)
+    Traceback (most recent call last):
+        ...
+    ValueError: n and r must be non-negative integers
+    >>> binomial_coefficient(10.1, 5)
+    Traceback (most recent call last):
+        ...
+    TypeError: 'float' object cannot be interpreted as an integer
+    >>> binomial_coefficient(10, 5.1)
+    Traceback (most recent call last):
+        ...
+    TypeError: 'float' object cannot be interpreted as an integer
     """
+    if n < 0 or r < 0:
+        raise ValueError("n and r must be non-negative integers")
+    if 0 in (n, r):
+        return 1
     c = [0 for i in range(r + 1)]
     # nc0 = 1
     c[0] = 1
@@ -17,4 +55,8 @@ def binomial_coefficient(n: int, r: int) -> int:
     return c[r]
 
 
-print(binomial_coefficient(n=10, r=5))
+if __name__ == "__main__":
+    from doctest import testmod
+
+    testmod()
+    print(binomial_coefficient(n=10, r=5))


Test patch: