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Translate all code to English (#1836)

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* Review the EN heading format.

* Fix pythontutor headings.

* Fix pythontutor headings.

* bug fixes

* Fix headings in **/summary.md

* Revisit the CN-to-EN translation for Python code using Claude-4.5

* Revisit the CN-to-EN translation for Java code using Claude-4.5

* Revisit the CN-to-EN translation for Cpp code using Claude-4.5.

* Fix the dictionary.

* Fix cpp code translation for the multipart strings.

* Translate Go code to English.

* Update workflows to test EN code.

* Add EN translation for C.

* Add EN translation for CSharp.

* Add EN translation for Swift.

* Trigger the CI check.

* Revert.

* Update en/hash_map.md

* Add the EN version of Dart code.

* Add the EN version of Kotlin code.

* Add missing code files.

* Add the EN version of JavaScript code.

* Add the EN version of TypeScript code.

* Fix the workflows.

* Add the EN version of Ruby code.

* Add the EN version of Rust code.

* Update the CI check for the English version  code.

* Update Python CI check.

* Fix cmakelists for en/C code.

* Fix Ruby comments
This commit is contained in:
Yudong Jin
2025-12-31 07:44:52 +08:00
committed by GitHub
parent 45e1295241
commit 2778a6f9c7
1284 changed files with 71557 additions and 3275 deletions
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10
en/codes/python/chapter_heap/top_k.py
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@@ -14,15 +14,15 @@ import heapq
def top_k_heap(nums: list[int], k: int) -> list[int]:
"""Using heap to find the largest k elements in an array"""
# Initialize min-heap
"""Find the largest k elements in array based on heap"""
# Initialize min heap
heap = []
# Enter the first k elements of the array into the heap
# Enter the first k elements of array into heap
for i in range(k):
heapq.heappush(heap, nums[i])
# From the k+1th element, keep the heap length as k
# Starting from the (k+1)th element, maintain heap length as k
for i in range(k, len(nums)):
# If the current element is larger than the heap top element, remove the heap top element and enter the current element into the heap
# If current element is greater than top element, top element exits heap, current element enters heap
if nums[i] > heap[0]:
heapq.heappop(heap)
heapq.heappush(heap, nums[i])