A CLI app to run any given Leetcode python solution.
Project description
python_leetcode_runner
Test your leetcode Python solutions locally.
Installation
pip install python-leetcode-runner
Usage
I have a beginner's guide over here
Say your solution file add_numbers.py
looks like this:
class Solution:
def addNumbers(self, nums: list[int]) -> int:
return sum(nums)
All you need to add to the file is a few test cases, usually provided to you in the leetcode question description:
class Solution:
def addNumbers(self, nums: list[int]) -> int:
return sum(nums)
tests = [
(
([1, 2, 3],), # input tuple
6, # output
),
(
([4, 5, 6, 7],), # input tuple
22, # output
),
]
Now, run the code locally by doing:
> pyleet add_numbers.py
Test 1 - ([1, 2, 3])......................................................PASSED
Test 2 - ([4, 5, 6, 7])...................................................PASSED
Custom Validators
In some questions, you don't just have to match expected output with function output. For eg, in some questions it might ask you to modify a list in-place, or some questions might have many acceptable answers.
For that case, you can provide your own custom validator
function.
A validator is a function that receives 3 arguments:
method
: your leetcode solution functioninputs
: your test inputs tupleexpected
: your expected test output value
To make assertions, you have to use assert
statements in the following way:
assert output == expected, (output, expected) # this tuple is important!
For example, let's add custom validation to the addNumbers
method:
class Solution:
def addNumbers(self, nums: list[int]) -> int:
return sum(nums)
tests = [
(
([1, 2, 3],), # input tuple
6, # output
),
(
([4, 5, 6, 7],), # input tuple
22, # output
),
]
def validator(addNumbers, inputs, expected):
nums = inputs[0]
output = addNumbers(nums)
assert output == expected, (output, expected)
Here's a more elaborate example, remove_duplicates:
class Solution:
def removeDuplicates(self, nums: list[int]) -> int:
offset = 0
values: set[int] = set()
for index, num in enumerate(nums):
nums[index - offset] = num
if num in values:
offset += 1
else:
values.add(num)
new_length = len(nums) - offset
return new_length
tests = [
(
([1, 1, 2],),
(2, [1, 2]),
),
(
([0, 0, 1, 1, 1, 2, 2, 3, 3, 4],),
(5, [0, 1, 2, 3, 4]),
),
]
def validator(removeDuplicates, inputs, outputs):
nums, = inputs
length, expected = outputs
new_length = removeDuplicates(nums)
assert length == new_length, (length, new_length)
assert nums[:new_length] == expected, (nums[:new_length], expected)
Run the file against sample inputs by doing:
> pyleet remove_duplicates.py
Test 1 - ([1, 2, 2])......................................................PASSED
Test 2 - ([0, 1, 2, 3, 4, 2, 2, 3, 3, 4]).................................PASSED
Code Snippets
If you're using VSCode, you can use the provided code snippets to help write the test cases faster.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for python_leetcode_runner-1.0.6.tar.gz
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6b7453acf7bcd87cfe8af7deb7d9cda97048ae3995ff098144424413ed162f8d |
|
MD5 | d87a0e492b4bd03ce345d5655cbe5641 |
|
BLAKE2b-256 | e2dc1160d7dfd19dc1510c11f5b2b18dbc27c0b183cfa0d19b8c695a8b959e4a |
Hashes for python_leetcode_runner-1.0.6-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 625f2c97e07df98efc80749fbe88d28c43600b26e6e41076318b4a627969da6b |
|
MD5 | c684a953266df71dce8c16f1bd4c36e5 |
|
BLAKE2b-256 | 81c53dfd9e1b40541b43ca28d8fd3ddfe8ad82b5a662eb2f64e629761571fff6 |