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values | task_type stringclasses 49
values | difficulty stringclasses 5
values | prompt stringlengths 12 3.09k | context stringclasses 596
values | observations stringlengths 2 170 | constraints stringclasses 242
values | assumptions stringclasses 51
values | plan stringclasses 240
values | strategy stringclasses 240
values | solution stringlengths 5 766 | answer stringlengths 1 766 | verification stringlengths 268 1.71k ⌀ | provenance stringclasses 95
values | quality stringclasses 29
values | education_level stringclasses 6
values | concept_id stringclasses 54
values | evidence stringclasses 29
values | transformation stringclasses 8
values | temporal stringclasses 0
values | runtime stringclasses 0
values | natural_language stringclasses 1
value | translation_status stringclasses 1
value | metadata stringlengths 220 5.58k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
or-coding-py-nested-delimiter-scan-85bd9022ad05 | coding | code_generation | beginner | Implement `delimiters_ok(text: str) -> bool`.
Return True if every round, square, and curly bracket in `text` is correctly
nested and matched. All other characters are ignored. Empty input is valid. | {"language": "python", "repository": {"files": {"solution.py": "def delimiters_ok(text):\n pairs = {\")\": \"(\", \"]\": \"[\", \"}\": \"{\"}\n stack = []\n for ch in text:\n if ch in \"([{\":\n stack.append(ch)\n elif ch in \")]}\":\n if not stack or stack[-1] != pairs[ch]:... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def delimiters_ok(text):
pairs = {")": "(", "]": "[", "}": "{"}
stack = []
for ch in text:
if ch in "([{":
stack.append(ch)
elif ch in ")]}":
if not stack or stack[-1] != pairs[ch]:
return False
stack.pop()
return not stack | def delimiters_ok(text):
pairs = {")": "(", "]": "[", "}": "{"}
stack = []
for ch in text:
if ch in "([{":
stack.append(ch)
elif ch in ")]}":
if not stack or stack[-1] != pairs[ch]:
return False
stack.pop()
return not stack | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 4}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:44Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.625, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.75, "tests": 0.0, "total": 4.35}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "nest... |
or-coding-py-window-max-sum-6217a2479b07 | coding | code_generation | intermediate | Implement `max_window_sum(values, k)` returning the maximum sum of any
contiguous subarray of length `k`. If `k` is larger than the list, raise ValueError. | {"language": "python", "repository": {"files": {"solution.py": "def max_window_sum(values, k):\n if k <= 0 or k > len(values):\n raise ValueError(\"invalid window\")\n current = sum(values[:k])\n best = current\n for i in range(k, len(values)):\n current += values[i] - values[i - k]\n i... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def max_window_sum(values, k):
if k <= 0 or k > len(values):
raise ValueError("invalid window")
current = sum(values[:k])
best = current
for i in range(k, len(values)):
current += values[i] - values[i - k]
if current > best:
best = current
return best | def max_window_sum(values, k):
if k <= 0 or k > len(values):
raise ValueError("invalid window")
current = sum(values[:k])
best = current
for i in range(k, len(values)):
current += values[i] - values[i - k]
if current > best:
best = current
return best | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:44Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.75, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.575, "tests": 0.0, "total": 4.5}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "windo... |
or-coding-py-debug-window-max-sum-929a7ef31c21 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `max_window_sum(values, k)` returning the maximum sum of any
contiguous subarray of length `k`. If `k` is larger than the list, raise ValueError.
--- solution.py (buggy) ---
def max_window_sum... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 3, \"failures\": 2, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_bad (test_solution.Test.test_bad) ... ok\ntest_example (test_solution.Test.test_example) ... FAIL\ntest_k_one (test_solution.Test.test_k_one) ... FAIL\... | ["Forgets to subtract the value leaving the window."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def max_window_sum(values, k):
if k <= 0 or k > len(values):
raise ValueError("invalid window")
current = sum(values[:k])
best = current
for i in range(k, len(values)):
current += values[i] - values[i - k]
if current > best:
best = current
return best | def max_window_sum(values, k):
if k <= 0 or k > len(values):
raise ValueError("invalid window")
current = sum(values[:k])
best = current
for i in range(k, len(values)):
current += values[i] - values[i - k]
if current > best:
best = current
return best | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:44Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.875}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-stable-group-by-af1de6dd3bd2 | coding | code_generation | beginner | Implement `group_in_order(items, key_fn)` that groups consecutive items with
the same key, preserving first-seen group order for non-consecutive keys as well
(like an insertion-ordered map of lists). Return a list of (key, group_list) pairs. | {"language": "python", "repository": {"files": {"solution.py": "def group_in_order(items, key_fn):\n order = []\n buckets = {}\n for item in items:\n key = key_fn(item)\n if key not in buckets:\n buckets[key] = []\n order.append(key)\n buckets[key].append(item)\n r... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def group_in_order(items, key_fn):
order = []
buckets = {}
for item in items:
key = key_fn(item)
if key not in buckets:
buckets[key] = []
order.append(key)
buckets[key].append(item)
return [(key, buckets[key]) for key in order] | def group_in_order(items, key_fn):
order = []
buckets = {}
for item in items:
key = key_fn(item)
if key not in buckets:
buckets[key] = []
order.append(key)
buckets[key].append(item)
return [(key, buckets[key]) for key in order] | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.525, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.825, "tests": 0.0, "total": 4.324999999999999}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0",... |
or-coding-py-lru-cache-map-5dfd0b972649 | coding | code_generation | beginner | Implement class `TinyLRU(capacity)` with `get(key)` (return None if missing)
and `put(key, value)`. Evict the least recently used entry when over capacity.
Both get and put count as use. | {"language": "python", "repository": {"files": {"solution.py": "from collections import OrderedDict\n\nclass TinyLRU:\n def __init__(self, capacity):\n if capacity < 1:\n raise ValueError(\"capacity\")\n self.capacity = capacity\n self._data = OrderedDict()\n\n def get(self, key):\... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from collections import OrderedDict
class TinyLRU:
def __init__(self, capacity):
if capacity < 1:
raise ValueError("capacity")
self.capacity = capacity
self._data = OrderedDict()
def get(self, key):
if key not in self._data:
return None
self._data.move_to_end(key)
return self._data[key]
def put(self, key,... | from collections import OrderedDict
class TinyLRU:
def __init__(self, capacity):
if capacity < 1:
raise ValueError("capacity")
self.capacity = capacity
self._data = OrderedDict()
def get(self, key):
if key not in self._data:
return None
self._data.move_to_end(key)
return self._data[key]
def put(self, key,... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.95, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.7, "tests": 0.0, "total": 4.25}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "lru_cach... |
or-coding-py-debug-lru-cache-map-d25e87700735 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement class `TinyLRU(capacity)` with `get(key)` (return None if missing)
and `put(key, value)`. Evict the least recently used entry when over capacity.
Both get and put count as use.
--- solution.py... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_evict (test_solution.Test.test_evict) ... FAIL\n\n======================================================================\nFAIL: test_evict (test_soluti... | ["get() does not refresh recency."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | from collections import OrderedDict
class TinyLRU:
def __init__(self, capacity):
if capacity < 1:
raise ValueError("capacity")
self.capacity = capacity
self._data = OrderedDict()
def get(self, key):
if key not in self._data:
return None
self._data.move_to_end(key)
return self._data[key]
def put(self, key,... | from collections import OrderedDict
class TinyLRU:
def __init__(self, capacity):
if capacity < 1:
raise ValueError("capacity")
self.capacity = capacity
self._data = OrderedDict()
def get(self, key):
if key not in self._data:
return None
self._data.move_to_end(key)
return self._data[key]
def put(self, key,... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.725, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 3.925, "tests": 0.0, "total": 10.95}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": ... |
or-coding-py-binary-search-first-4a8714ec195f | coding | code_generation | intermediate | Implement `first_ge(sorted_values, target)` returning the smallest index i
such that sorted_values[i] >= target, or len(sorted_values) if none exists.
The list is sorted non-decreasing. | {"language": "python", "repository": {"files": {"solution.py": "def first_ge(sorted_values, target):\n lo, hi = 0, len(sorted_values)\n while lo < hi:\n mid = (lo + hi) // 2\n if sorted_values[mid] < target:\n lo = mid + 1\n else:\n hi = mid\n return lo\n", "test_solu... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def first_ge(sorted_values, target):
lo, hi = 0, len(sorted_values)
while lo < hi:
mid = (lo + hi) // 2
if sorted_values[mid] < target:
lo = mid + 1
else:
hi = mid
return lo | def first_ge(sorted_values, target):
lo, hi = 0, len(sorted_values)
while lo < hi:
mid = (lo + hi) // 2
if sorted_values[mid] < target:
lo = mid + 1
else:
hi = mid
return lo | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.525, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.575, "tests": 0.0, "total": 4.824999999999999}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0",... |
or-coding-py-merge-intervals-cc5bc5fd01ac | coding | code_generation | intermediate | Implement `merge_ranges(ranges)` where each range is [start, end] with
start <= end. Return a new list of disjoint merged ranges sorted by start. | {"language": "python", "repository": {"files": {"solution.py": "def merge_ranges(ranges):\n if not ranges:\n return []\n ordered = sorted(ranges, key=lambda r: r[0])\n out = [list(ordered[0])]\n for start, end in ordered[1:]:\n if start <= out[-1][1]:\n out[-1][1] = max(out[-1][1], ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def merge_ranges(ranges):
if not ranges:
return []
ordered = sorted(ranges, key=lambda r: r[0])
out = [list(ordered[0])]
for start, end in ordered[1:]:
if start <= out[-1][1]:
out[-1][1] = max(out[-1][1], end)
else:
out.append([start, end])
return out | def merge_ranges(ranges):
if not ranges:
return []
ordered = sorted(ranges, key=lambda r: r[0])
out = [list(ordered[0])]
for start, end in ordered[1:]:
if start <= out[-1][1]:
out[-1][1] = max(out[-1][1], end)
else:
out.append([start, end])
return out | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.75, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.575, "tests": 0.0, "total": 4.5}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "merge... |
or-coding-py-debug-merge-intervals-6fc2cea66a6d | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `merge_ranges(ranges)` where each range is [start, end] with
start <= end. Return a new list of disjoint merged ranges sorted by start.
--- solution.py (buggy) ---
def merge_ranges(ranges):
i... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 3, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_empty (test_solution.Test.test_empty) ... ok\ntest_overlap (test_solution.Test.test_overlap) ... ok\ntest_touch (test_solution.Test.test_touch) ... FAI... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def merge_ranges(ranges):
if not ranges:
return []
ordered = sorted(ranges, key=lambda r: r[0])
out = [list(ordered[0])]
for start, end in ordered[1:]:
if start <= out[-1][1]:
out[-1][1] = max(out[-1][1], end)
else:
out.append([start, end])
return out | def merge_ranges(ranges):
if not ranges:
return []
ordered = sorted(ranges, key=lambda r: r[0])
out = [list(ordered[0])]
for start, end in ordered[1:]:
if start <= out[-1][1]:
out[-1][1] = max(out[-1][1], end)
else:
out.append([start, end])
return out | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.875}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-topo-order-50c5ec8cdc24 | coding | code_generation | intermediate | Implement `topo_sort(nodes, edges)` for a directed acyclic graph.
`nodes` is a list of hashable ids. `edges` is a list of (src, dst) meaning
src must come before dst. Return any valid topological order. Raise ValueError
if a cycle exists. | {"language": "python", "repository": {"files": {"solution.py": "from collections import defaultdict, deque\n\ndef topo_sort(nodes, edges):\n incoming = {n: 0 for n in nodes}\n graph = defaultdict(list)\n for src, dst in edges:\n graph[src].append(dst)\n incoming[dst] = incoming.get(dst, 0) + 1\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from collections import defaultdict, deque
def topo_sort(nodes, edges):
incoming = {n: 0 for n in nodes}
graph = defaultdict(list)
for src, dst in edges:
graph[src].append(dst)
incoming[dst] = incoming.get(dst, 0) + 1
incoming.setdefault(src, incoming.get(src, 0))
ready = deque([n for n in nodes if incoming.get... | from collections import defaultdict, deque
def topo_sort(nodes, edges):
incoming = {n: 0 for n in nodes}
graph = defaultdict(list)
for src, dst in edges:
graph[src].append(dst)
incoming[dst] = incoming.get(dst, 0) + 1
incoming.setdefault(src, incoming.get(src, 0))
ready = deque([n for n in nodes if incoming.get... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.collections | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.825, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.975, "tests": 0.0, "total": 4.9}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "topo_o... |
or-coding-py-debug-topo-order-7b0d10953f8f | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `topo_sort(nodes, edges)` for a directed acyclic graph.
`nodes` is a list of hashable ids. `edges` is a list of (src, dst) meaning
src must come before dst. Return any valid topological order. ... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 2, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_chain (test_solution.Test.test_chain) ... FAIL\ntest_cycle (test_solution.Test.test_cycle) ... ok\n\n==================================================... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | from collections import defaultdict, deque
def topo_sort(nodes, edges):
incoming = {n: 0 for n in nodes}
graph = defaultdict(list)
for src, dst in edges:
graph[src].append(dst)
incoming[dst] = incoming.get(dst, 0) + 1
incoming.setdefault(src, incoming.get(src, 0))
ready = deque([n for n in nodes if incoming.get... | from collections import defaultdict, deque
def topo_sort(nodes, edges):
incoming = {n: 0 for n in nodes}
graph = defaultdict(list)
for src, dst in edges:
graph[src].append(dst)
incoming[dst] = incoming.get(dst, 0) + 1
incoming.setdefault(src, incoming.get(src, 0))
ready = deque([n for n in nodes if incoming.get... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.collections | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.825, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.125}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-dijkstra-hops-3cc79c98ed19 | coding | code_generation | beginner | Implement `shortest_cost(graph, start, goal)` where graph maps node ->
list of (neighbor, weight) with non-negative weights. Return the minimum cost
or None if unreachable. | {"language": "python", "repository": {"files": {"solution.py": "import heapq\n\ndef shortest_cost(graph, start, goal):\n best = {start: 0}\n heap = [(0, start)]\n while heap:\n cost, node = heapq.heappop(heap)\n if cost != best.get(node, None):\n continue\n if node == goal:\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import heapq
def shortest_cost(graph, start, goal):
best = {start: 0}
heap = [(0, start)]
while heap:
cost, node = heapq.heappop(heap)
if cost != best.get(node, None):
continue
if node == goal:
return cost
for nxt, weight in graph.get(node, []):
cand = cost + weight
if cand < best.get(nxt, float("inf")):
b... | import heapq
def shortest_cost(graph, start, goal):
best = {start: 0}
heap = [(0, start)]
while heap:
cost, node = heapq.heappop(heap)
if cost != best.get(node, None):
continue
if node == goal:
return cost
for nxt, weight in graph.get(node, []):
cand = cost + weight
if cand < best.get(nxt, float("inf")):
b... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.loops | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.7, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.6, "tests": 0.0, "total": 4.4}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "dijkstra_h... |
or-coding-py-debug-dijkstra-hops-6ee2d302315a | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `shortest_cost(graph, start, goal)` where graph maps node ->
list of (neighbor, weight) with non-negative weights. Return the minimum cost
or None if unreachable.
--- solution.py (buggy) ---
i... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 2, \"failures\": 2, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_missing (test_solution.Test.test_missing) ... FAIL\ntest_path (test_solution.Test.test_path) ... FAIL\n\n==============================================... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | import heapq
def shortest_cost(graph, start, goal):
best = {start: 0}
heap = [(0, start)]
while heap:
cost, node = heapq.heappop(heap)
if cost != best.get(node, None):
continue
if node == goal:
return cost
for nxt, weight in graph.get(node, []):
cand = cost + weight
if cand < best.get(nxt, float("inf")):
b... | import heapq
def shortest_cost(graph, start, goal):
best = {start: 0}
heap = [(0, start)]
while heap:
cost, node = heapq.heappop(heap)
if cost != best.get(node, None):
continue
if node == goal:
return cost
for nxt, weight in graph.get(node, []):
cand = cost + weight
if cand < best.get(nxt, float("inf")):
b... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.7, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.0}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"err... |
or-coding-py-heap-median-ebe3df4f8fd3 | coding | code_generation | intermediate | Implement class `RunningMedian` with `add(x)` and `median()` (mean of the
two center values when the count is even). Values are numbers. | {"language": "python", "repository": {"files": {"solution.py": "import heapq\n\nclass RunningMedian:\n def __init__(self):\n self.low = []\n self.high = []\n\n def add(self, x):\n if not self.low or x <= -self.low[0]:\n heapq.heappush(self.low, -x)\n else:\n heapq... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import heapq
class RunningMedian:
def __init__(self):
self.low = []
self.high = []
def add(self, x):
if not self.low or x <= -self.low[0]:
heapq.heappush(self.low, -x)
else:
heapq.heappush(self.high, x)
if len(self.low) > len(self.high) + 1:
heapq.heappush(self.high, -heapq.heappop(self.low))
elif len(self... | import heapq
class RunningMedian:
def __init__(self):
self.low = []
self.high = []
def add(self, x):
if not self.low or x <= -self.low[0]:
heapq.heappush(self.low, -x)
else:
heapq.heappush(self.high, x)
if len(self.low) > len(self.high) + 1:
heapq.heappush(self.high, -heapq.heappop(self.low))
elif len(self... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.85, "constraints": 1.4, "keywords": 0.0, "math_ops": 2.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.525, "tests": 0.0, "total": 6.225}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "heap... |
or-coding-py-parse-kv-config-761c659cab58 | coding | code_generation | intermediate | Implement `parse_kv(text)` for a tiny config language:
- ignore blank lines and lines starting with `#`
- remaining lines are `key = value` (value trimmed, may contain =)
- duplicate keys: last wins
Return a dict. Raise ValueError on lines without `=`. | {"language": "python", "repository": {"files": {"solution.py": "def parse_kv(text):\n result = {}\n for raw in text.splitlines():\n line = raw.strip()\n if not line or line.startswith(\"#\"):\n continue\n if \"=\" not in line:\n raise ValueError(line)\n key, value... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def parse_kv(text):
result = {}
for raw in text.splitlines():
line = raw.strip()
if not line or line.startswith("#"):
continue
if "=" not in line:
raise ValueError(line)
key, value = line.split("=", 1)
result[key.strip()] = value.strip()
return result | def parse_kv(text):
result = {}
for raw in text.splitlines():
line = raw.strip()
if not line or line.startswith("#"):
continue
if "=" not in line:
raise ValueError(line)
key, value = line.split("=", 1)
result[key.strip()] = value.strip()
return result | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 1.05, "tests": 0.0, "total": 4.6000000000000005}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0",... |
or-coding-py-semver-core-cmp-af727ae91767 | coding | code_generation | beginner | Implement `cmp_semver(a, b)` comparing MAJOR.MINOR.PATCH strings (digits
only, no pre-release). Return -1, 0, or 1. | {"language": "python", "repository": {"files": {"solution.py": "def cmp_semver(a, b):\n def parts(s):\n bits = s.split(\".\")\n if len(bits) != 3 or not all(p.isdigit() for p in bits):\n raise ValueError(s)\n return tuple(int(p) for p in bits)\n left, right = parts(a), parts(b)\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def cmp_semver(a, b):
def parts(s):
bits = s.split(".")
if len(bits) != 3 or not all(p.isdigit() for p in bits):
raise ValueError(s)
return tuple(int(p) for p in bits)
left, right = parts(a), parts(b)
return (left > right) - (left < right) | def cmp_semver(a, b):
def parts(s):
bits = s.split(".")
if len(bits) != 3 or not all(p.isdigit() for p in bits):
raise ValueError(s)
return tuple(int(p) for p in bits)
left, right = parts(a), parts(b)
return (left > right) - (left < right) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.45, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.375, "tests": 0.0, "total": 3.9250000000000003}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "... |
or-coding-py-debug-semver-core-cmp-3ec077e8ae1c | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `cmp_semver(a, b)` comparing MAJOR.MINOR.PATCH strings (digits
only, no pre-release). Return -1, 0, or 1.
--- solution.py (buggy) ---
def cmp_semver(a, b):
return (a > b) - (a < b)
--- test_... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_cmp (test_solution.Test.test_cmp) ... FAIL\n\n======================================================================\nFAIL: test_cmp (test_solution.Tes... | ["Compares as strings so 1.10.0 < 1.2.0."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def cmp_semver(a, b):
def parts(s):
bits = s.split(".")
if len(bits) != 3 or not all(p.isdigit() for p in bits):
raise ValueError(s)
return tuple(int(p) for p in bits)
left, right = parts(a), parts(b)
return (left > right) - (left < right) | def cmp_semver(a, b):
def parts(s):
bits = s.split(".")
if len(bits) != 3 or not all(p.isdigit() for p in bits):
raise ValueError(s)
return tuple(int(p) for p in bits)
left, right = parts(a), parts(b)
return (left > right) - (left < right) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:45Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.3, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 2.95, "tests": 0.0, "total": 9.55}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"er... |
or-coding-py-dep-resolution-pins-c28ab4b294ab | coding | code_generation | beginner | Implement `pins_ok(declared, locked)` where declared maps package ->
minimum inclusive version tuple (major, minor, patch) and locked maps package
-> installed version tuple. Every declared package must be present and
installed >= minimum. Extra locked packages are allowed. | {"language": "python", "repository": {"files": {"solution.py": "def pins_ok(declared, locked):\n for name, minimum in declared.items():\n if name not in locked:\n return False\n if locked[name] < minimum:\n return False\n return True\n", "test_solution.py": "import unittest\nfr... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def pins_ok(declared, locked):
for name, minimum in declared.items():
if name not in locked:
return False
if locked[name] < minimum:
return False
return True | def pins_ok(declared, locked):
for name, minimum in declared.items():
if name not in locked:
return False
if locked[name] < minimum:
return False
return True | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.95, "tests": 0.0, "total": 4.2749999999999995}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", ... |
or-coding-py-debug-dep-resolution-pins-1435c42ac5ce | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `pins_ok(declared, locked)` where declared maps package ->
minimum inclusive version tuple (major, minor, patch) and locked maps package
-> installed version tuple. Every declared package must ... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 3, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_missing (test_solution.Test.test_missing) ... ok\ntest_ok (test_solution.Test.test_ok) ... FAIL\ntest_old (test_solution.Test.test_old) ... ok\n\n=====... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def pins_ok(declared, locked):
for name, minimum in declared.items():
if name not in locked:
return False
if locked[name] < minimum:
return False
return True | def pins_ok(declared, locked):
for name, minimum in declared.items():
if name not in locked:
return False
if locked[name] < minimum:
return False
return True | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.modules | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.774999999999999}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {... |
or-coding-py-sql-ident-quote-d0a22efbb77f | coding | code_generation | intermediate | Implement `quote_ident(name)` for a conservative SQL identifier:
accept only `[A-Za-z_][A-Za-z0-9_]*` and wrap in double quotes with internal
quotes doubled. Raise ValueError otherwise. This is defensive quoting, not a
parser for arbitrary SQL. | {"language": "python", "repository": {"files": {"solution.py": "import re\n\ndef quote_ident(name):\n if not re.fullmatch(r\"[A-Za-z_][A-Za-z0-9_]*\", name):\n raise ValueError(\"invalid identifier\")\n return '\"' + name.replace('\"', '\"\"') + '\"'\n", "test_solution.py": "import unittest\nfrom solution ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import re
def quote_ident(name):
if not re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", name):
raise ValueError("invalid identifier")
return '"' + name.replace('"', '""') + '"' | import re
def quote_ident(name):
if not re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", name):
raise ValueError("invalid identifier")
return '"' + name.replace('"', '""') + '"' | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 2.75, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.8, "tests": 0.0, "total": 6.625}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "sql_i... |
or-coding-py-debug-sql-ident-quote-802f0517d1d2 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `quote_ident(name)` for a conservative SQL identifier:
accept only `[A-Za-z_][A-Za-z0-9_]*` and wrap in double quotes with internal
quotes doubled. Raise ValueError otherwise. This is defensive... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 2, \"failures\": 0, \"errors\": 1, \"skipped\": 0, \"passed\": false}\n\ntest_ok (test_solution.Test.test_ok) ... ERROR\ntest_reject (test_solution.Test.test_reject) ... ok\n\n=====================================================... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | import re
def quote_ident(name):
if not re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", name):
raise ValueError("invalid identifier")
return '"' + name.replace('"', '""') + '"' | import re
def quote_ident(name):
if not re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", name):
raise ValueError("invalid identifier")
return '"' + name.replace('"', '""') + '"' | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.774999999999999}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {... |
or-coding-py-parameterized-filter-2992f1833ac8 | coding | code_generation | intermediate | Implement `safe_select_by_id(conn, table, row_id)` using sqlite3.
`table` must match `[a-z_]+`. Execute a parameterized query
`SELECT * FROM {table} WHERE id = ?` and return the list of rows.
Never interpolate `row_id` into the SQL string. | {"language": "python", "repository": {"files": {"solution.py": "import re\n\ndef safe_select_by_id(conn, table, row_id):\n if not re.fullmatch(r\"[a-z_]+\", table):\n raise ValueError(\"table\")\n sql = f'SELECT * FROM \"{table}\" WHERE id = ?'\n return list(conn.execute(sql, (row_id,)))\n", "test_solut... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import re
def safe_select_by_id(conn, table, row_id):
if not re.fullmatch(r"[a-z_]+", table):
raise ValueError("table")
sql = f'SELECT * FROM "{table}" WHERE id = ?'
return list(conn.execute(sql, (row_id,))) | import re
def safe_select_by_id(conn, table, row_id):
if not re.fullmatch(r"[a-z_]+", table):
raise ValueError("table")
sql = f'SELECT * FROM "{table}" WHERE id = ?'
return list(conn.execute(sql, (row_id,))) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.75, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.875, "tests": 0.0, "total": 5.35}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "para... |
or-coding-py-path-confine-9bfc484ac11f | coding | code_generation | beginner | Implement `resolve_under(root, relative)` that joins `relative` to `root`
and returns the resolved path only if it stays inside `root`. Reject `..`
escapes. Use pathlib. Raise ValueError on escape. | {"language": "python", "repository": {"files": {"solution.py": "from pathlib import Path\n\ndef resolve_under(root, relative):\n base = Path(root).resolve()\n target = (base / relative).resolve()\n try:\n target.relative_to(base)\n except ValueError as exc:\n raise ValueError(\"escape\") from ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from pathlib import Path
def resolve_under(root, relative):
base = Path(root).resolve()
target = (base / relative).resolve()
try:
target.relative_to(base)
except ValueError as exc:
raise ValueError("escape") from exc
return str(target) | from pathlib import Path
def resolve_under(root, relative):
base = Path(root).resolve()
target = (base / relative).resolve()
try:
target.relative_to(base)
except ValueError as exc:
raise ValueError("escape") from exc
return str(target) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.exceptions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.65, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.7, "tests": 0.0, "total": 4.199999999999999}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "sl... |
or-coding-py-cidr-contains-880e214734b6 | coding | code_generation | beginner | Implement `ipv4_in_cidr(ip, cidr)` where ip is dotted IPv4 and cidr is
like `10.0.0.0/8`. Return True iff the address is in the prefix. No extra
libraries beyond stdlib. | {"language": "python", "repository": {"files": {"solution.py": "import ipaddress\n\ndef ipv4_in_cidr(ip, cidr):\n return ipaddress.IPv4Address(ip) in ipaddress.IPv4Network(cidr, strict=False)\n", "test_solution.py": "import unittest\nfrom solution import ipv4_in_cidr\n\nclass Test(unittest.TestCase):\n def test_i... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import ipaddress
def ipv4_in_cidr(ip, cidr):
return ipaddress.IPv4Address(ip) in ipaddress.IPv4Network(cidr, strict=False) | import ipaddress
def ipv4_in_cidr(ip, cidr):
return ipaddress.IPv4Address(ip) in ipaddress.IPv4Network(cidr, strict=False) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 3}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.4, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.675, "tests": 0.0, "total": 3.8000000000000003}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", ... |
or-coding-py-fcfs-finish-72e6ead16506 | coding | code_generation | beginner | Implement `fcfs_completion(jobs)` where each job is (arrival, burst) and
jobs are already ordered by arrival time (ties keep given order). Return a list
of completion times in the same order. The CPU is idle until the next arrival
if needed. | {"language": "python", "repository": {"files": {"solution.py": "def fcfs_completion(jobs):\n time = 0\n done = []\n for arrival, burst in jobs:\n time = max(time, arrival) + burst\n done.append(time)\n return done\n", "test_solution.py": "import unittest\nfrom solution import fcfs_completion\n... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def fcfs_completion(jobs):
time = 0
done = []
for arrival, burst in jobs:
time = max(time, arrival) + burst
done.append(time)
return done | def fcfs_completion(jobs):
time = 0
done = []
for arrival, burst in jobs:
time = max(time, arrival) + burst
done.append(time)
return done | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.425, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 1.0, "tests": 0.0, "total": 4.275}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "fcfs_... |
or-coding-py-debug-fcfs-finish-69a773b61602 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `fcfs_completion(jobs)` where each job is (arrival, burst) and
jobs are already ordered by arrival time (ties keep given order). Return a list
of completion times in the same order. The CPU is ... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 2, \"failures\": 2, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_idle (test_solution.Test.test_idle) ... FAIL\ntest_queue (test_solution.Test.test_queue) ... FAIL\n\n==================================================... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def fcfs_completion(jobs):
time = 0
done = []
for arrival, burst in jobs:
time = max(time, arrival) + burst
done.append(time)
return done | def fcfs_completion(jobs):
time = 0
done = []
for arrival, burst in jobs:
time = max(time, arrival) + burst
done.append(time)
return done | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.425, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.725}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-round-robin-trace-992838c315ea | coding | code_generation | advanced | Implement `rr_finish(bursts, quantum)` for processes all arriving at 0,
indexed 0..n-1, using a FIFO ready queue. Return completion times list.
Ignore context-switch cost. | {"language": "python", "repository": {"files": {"solution.py": "from collections import deque\n\ndef rr_finish(bursts, quantum):\n remaining = list(bursts)\n finish = [None] * len(bursts)\n q = deque(range(len(bursts)))\n t = 0\n while q:\n i = q.popleft()\n run = min(quantum, remaining[i])... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from collections import deque
def rr_finish(bursts, quantum):
remaining = list(bursts)
finish = [None] * len(bursts)
q = deque(range(len(bursts)))
t = 0
while q:
i = q.popleft()
run = min(quantum, remaining[i])
remaining[i] -= run
t += run
if remaining[i] == 0:
finish[i] = t
else:
q.append(i)
return fini... | from collections import deque
def rr_finish(bursts, quantum):
remaining = list(bursts)
finish = [None] * len(bursts)
q = deque(range(len(bursts)))
t = 0
while q:
i = q.popleft()
run = min(quantum, remaining[i])
remaining[i] -= run
t += run
if remaining[i] == 0:
finish[i] = t
else:
q.append(i)
return fini... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.625, "constraints": 1.4, "keywords": 3.0, "math_ops": 1.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.575, "tests": 0.0, "total": 7.8}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "round_... |
or-coding-py-debug-round-robin-trace-426b74f925fc | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `rr_finish(bursts, quantum)` for processes all arriving at 0,
indexed 0..n-1, using a FIFO ready queue. Return completion times list.
Ignore context-switch cost.
--- solution.py (buggy) ---
fr... | {"failure": {"command": "python harness.py", "output": "\ntest_rr (test_solution.Test.test_rr) ... "}, "language": "python", "repository": {"files": {"solution.py": "from collections import deque\n\ndef rr_finish(bursts, quantum):\n remaining = list(bursts)\n finish = [None] * len(bursts)\n q = deque(range(len... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | from collections import deque
def rr_finish(bursts, quantum):
remaining = list(bursts)
finish = [None] * len(bursts)
q = deque(range(len(bursts)))
t = 0
while q:
i = q.popleft()
run = min(quantum, remaining[i])
remaining[i] -= run
t += run
if remaining[i] == 0:
finish[i] = t
else:
q.append(i)
return fini... | from collections import deque
def rr_finish(bursts, quantum):
remaining = list(bursts)
finish = [None] * len(bursts)
q = deque(range(len(bursts)))
t = 0
while q:
i = q.popleft()
run = min(quantum, remaining[i])
remaining[i] -= run
t += run
if remaining[i] == 0:
finish[i] = t
else:
q.append(i)
return fini... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:46Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.625, "constraints": 1.4, "keywords": 3.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 2.9, "tests": 0.0, "total": 12.825}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-lru-page-faults-e1513d15e836 | coding | code_generation | beginner | Implement `lru_faults(pages, frames)` counting page faults with LRU
replacement among `frames` slots. Empty frames fill first. | {"language": "python", "repository": {"files": {"solution.py": "def lru_faults(pages, frames):\n slot = []\n used = []\n faults = 0\n for page in pages:\n if page in slot:\n used.remove(page)\n used.append(page)\n continue\n faults += 1\n if len(slot) < ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def lru_faults(pages, frames):
slot = []
used = []
faults = 0
for page in pages:
if page in slot:
used.remove(page)
used.append(page)
continue
faults += 1
if len(slot) < frames:
slot.append(page)
else:
victim = used.pop(0)
idx = slot.index(victim)
slot[idx] = page
used.append(page)
return faults | def lru_faults(pages, frames):
slot = []
used = []
faults = 0
for page in pages:
if page in slot:
used.remove(page)
used.append(page)
continue
faults += 1
if len(slot) < frames:
slot.append(page)
else:
victim = used.pop(0)
idx = slot.index(victim)
slot[idx] = page
used.append(page)
return faults | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:58Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.65, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.4, "tests": 0.0, "total": 3.9}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "lru_page... |
or-coding-py-banker-safe-3b58e6d2a848 | coding | code_generation | intermediate | Implement `is_safe(available, allocation, need)` for the Banker's algorithm
safety check. `available` is a list of resource counts. `allocation` and `need`
are lists of per-process lists. Return True iff a safe sequence exists. | {"language": "python", "repository": {"files": {"solution.py": "def is_safe(available, allocation, need):\n work = list(available)\n finish = [False] * len(allocation)\n while True:\n progressed = False\n for i, done in enumerate(finish):\n if done:\n continue\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def is_safe(available, allocation, need):
work = list(available)
finish = [False] * len(allocation)
while True:
progressed = False
for i, done in enumerate(finish):
if done:
continue
if all(need[i][j] <= work[j] for j in range(len(work))):
for j in range(len(work)):
work[j] += allocation[i][j]
finish[i] = Tr... | def is_safe(available, allocation, need):
work = list(available)
finish = [False] * len(allocation)
while True:
progressed = False
for i, done in enumerate(finish):
if done:
continue
if all(need[i][j] <= work[j] for j in range(len(work))):
for j in range(len(work)):
work[j] += allocation[i][j]
finish[i] = Tr... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:58Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.loops | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.65, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.625, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.8, "tests": 0.0, "total": 4.675000000000001}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "s... |
or-coding-py-token-bucket-f0a6eaa2b164 | coding | code_generation | intermediate | Implement class `TokenBucket(rate, burst)` with `allow(time, cost=1)`.
`rate` is tokens per time unit, `burst` is max tokens. Start full at t=0.
`time` is non-decreasing. Return True if the request is admitted. | {"language": "python", "repository": {"files": {"solution.py": "class TokenBucket:\n def __init__(self, rate, burst):\n self.rate = rate\n self.burst = burst\n self.tokens = float(burst)\n self.t = 0.0\n\n def allow(self, time, cost=1):\n if time < self.t:\n raise Val... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | class TokenBucket:
def __init__(self, rate, burst):
self.rate = rate
self.burst = burst
self.tokens = float(burst)
self.t = 0.0
def allow(self, time, cost=1):
if time < self.t:
raise ValueError("time")
self.tokens = min(self.burst, self.tokens + (time - self.t) * self.rate)
self.t = time
if self.tokens >= c... | class TokenBucket:
def __init__(self, rate, burst):
self.rate = rate
self.burst = burst
self.tokens = float(burst)
self.t = 0.0
def allow(self, time, cost=1):
if time < self.t:
raise ValueError("time")
self.tokens = min(self.burst, self.tokens + (time - self.t) * self.rate)
self.t = time
if self.tokens >= c... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:58Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.7, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.775, "tests": 0.0, "total": 5.2}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "token_... |
or-coding-py-debug-token-bucket-ba68a47d70d8 | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement class `TokenBucket(rate, burst)` with `allow(time, cost=1)`.
`rate` is tokens per time unit, `burst` is max tokens. Start full at t=0.
`time` is non-decreasing. Return True if the request is ad... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_burst_then_refill (test_solution.Test.test_burst_then_refill) ... FAIL\n\n======================================================================\nFAIL:... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | class TokenBucket:
def __init__(self, rate, burst):
self.rate = rate
self.burst = burst
self.tokens = float(burst)
self.t = 0.0
def allow(self, time, cost=1):
if time < self.t:
raise ValueError("time")
self.tokens = min(self.burst, self.tokens + (time - self.t) * self.rate)
self.t = time
if self.tokens >= c... | class TokenBucket:
def __init__(self, rate, burst):
self.rate = rate
self.burst = burst
self.tokens = float(burst)
self.t = 0.0
def allow(self, time, cost=1):
if time < self.t:
raise ValueError("time")
self.tokens = min(self.burst, self.tokens + (time - self.t) * self.rate)
self.t = time
if self.tokens >= c... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:58Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.7, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.0}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"err... |
or-coding-py-openapi-required-d4f6731d64e0 | coding | code_generation | beginner | Implement `missing_required(schema, payload)` where schema is
`{"required": [...], "properties": {name: {"type": "string"|"number"|"boolean"}}}`.
Return sorted names that are missing or have the wrong JSON type.
Extra payload keys are ignored. | {"language": "python", "repository": {"files": {"solution.py": "def missing_required(schema, payload):\n types = {\"string\": str, \"number\": (int, float), \"boolean\": bool}\n bad = []\n for name in schema.get(\"required\", []):\n if name not in payload:\n bad.append(name)\n cont... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def missing_required(schema, payload):
types = {"string": str, "number": (int, float), "boolean": bool}
bad = []
for name in schema.get("required", []):
if name not in payload:
bad.append(name)
continue
declared = schema["properties"][name]["type"]
if declared == "number" and isinstance(payload[name], bool):
b... | def missing_required(schema, payload):
types = {"string": str, "number": (int, float), "boolean": bool}
bad = []
for name in schema.get("required", []):
if name not in payload:
bad.append(name)
continue
declared = schema["properties"][name]["type"]
if declared == "number" and isinstance(payload[name], bool):
b... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.675, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.725, "tests": 0.0, "total": 4.0}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "openap... |
or-coding-py-debug-openapi-required-4ba8a9abe615 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `missing_required(schema, payload)` where schema is
`{"required": [...], "properties": {name: {"type": "string"|"number"|"boolean"}}}`.
Return sorted names that are missing or have the wrong JS... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_types (test_solution.Test.test_types) ... FAIL\n\n======================================================================\nFAIL: test_types (test_soluti... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def missing_required(schema, payload):
types = {"string": str, "number": (int, float), "boolean": bool}
bad = []
for name in schema.get("required", []):
if name not in payload:
bad.append(name)
continue
declared = schema["properties"][name]["type"]
if declared == "number" and isinstance(payload[name], bool):
b... | def missing_required(schema, payload):
types = {"string": str, "number": (int, float), "boolean": bool}
bad = []
for name in schema.get("required", []):
if name not in payload:
bad.append(name)
continue
declared = schema["properties"][name]["type"]
if declared == "number" and isinstance(payload[name], bool):
b... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.675, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.975}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-layer-ports-b6582f00b6e8 | coding | code_generation | beginner | Implement `allowed_import(from_layer, to_layer, rules)` where layers are
strings and rules is a list of (src, dst) allowed edges. A module may always
import from its own layer. Return True iff the import is permitted. | {"language": "python", "repository": {"files": {"solution.py": "def allowed_import(from_layer, to_layer, rules):\n if from_layer == to_layer:\n return True\n allowed = set(rules)\n return (from_layer, to_layer) in allowed\n", "test_solution.py": "import unittest\nfrom solution import allowed_import\n\nc... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def allowed_import(from_layer, to_layer, rules):
if from_layer == to_layer:
return True
allowed = set(rules)
return (from_layer, to_layer) in allowed | def allowed_import(from_layer, to_layer, rules):
if from_layer == to_layer:
return True
allowed = set(rules)
return (from_layer, to_layer) in allowed | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.4, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.85, "tests": 0.0, "total": 3.85}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "layer_po... |
or-coding-py-debug-layer-ports-26eff8f48a77 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `allowed_import(from_layer, to_layer, rules)` where layers are
strings and rules is a list of (src, dst) allowed edges. A module may always
import from its own layer. Return True iff the import... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_hex (test_solution.Test.test_hex) ... FAIL\n\n======================================================================\nFAIL: test_hex (test_solution.Tes... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def allowed_import(from_layer, to_layer, rules):
if from_layer == to_layer:
return True
allowed = set(rules)
return (from_layer, to_layer) in allowed | def allowed_import(from_layer, to_layer, rules):
if from_layer == to_layer:
return True
allowed = set(rules)
return (from_layer, to_layer) in allowed | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.4, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 3.775, "tests": 0.0, "total": 10.475}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-infix-rpn-eval-24d19ffbb57b | coding | code_generation | intermediate | Implement `eval_rpn(tokens)` for integers and + - * / (integer division
toward zero is NOT required: use Python `//` toward -inf). Tokens are strings. | {"language": "python", "repository": {"files": {"solution.py": "def eval_rpn(tokens):\n stack = []\n ops = {\n \"+\": lambda a, b: a + b,\n \"-\": lambda a, b: a - b,\n \"*\": lambda a, b: a * b,\n \"/\": lambda a, b: a // b,\n }\n for tok in tokens:\n if tok in ops:\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def eval_rpn(tokens):
stack = []
ops = {
"+": lambda a, b: a + b,
"-": lambda a, b: a - b,
"*": lambda a, b: a * b,
"/": lambda a, b: a // b,
}
for tok in tokens:
if tok in ops:
b = stack.pop()
a = stack.pop()
stack.append(ops[tok](a, b))
else:
stack.append(int(tok))
if len(stack) != 1:
raise ValueError... | def eval_rpn(tokens):
stack = []
ops = {
"+": lambda a, b: a + b,
"-": lambda a, b: a - b,
"*": lambda a, b: a * b,
"/": lambda a, b: a // b,
}
for tok in tokens:
if tok in ops:
b = stack.pop()
a = stack.pop()
stack.append(ops[tok](a, b))
else:
stack.append(int(tok))
if len(stack) != 1:
raise ValueError... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.7, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.6, "tests": 0.0, "total": 6.9}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "infix_rpn_... |
or-coding-py-debug-infix-rpn-eval-cadd2bbd5165 | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `eval_rpn(tokens)` for integers and + - * / (integer division
toward zero is NOT required: use Python `//` toward -inf). Tokens are strings.
--- solution.py (buggy) ---
def eval_rpn(tokens):
... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 2, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_div (test_solution.Test.test_div) ... ok\ntest_expr (test_solution.Test.test_expr) ... FAIL\n\n========================================================... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def eval_rpn(tokens):
stack = []
ops = {
"+": lambda a, b: a + b,
"-": lambda a, b: a - b,
"*": lambda a, b: a * b,
"/": lambda a, b: a // b,
}
for tok in tokens:
if tok in ops:
b = stack.pop()
a = stack.pop()
stack.append(ops[tok](a, b))
else:
stack.append(int(tok))
if len(stack) != 1:
raise ValueError... | def eval_rpn(tokens):
stack = []
ops = {
"+": lambda a, b: a + b,
"-": lambda a, b: a - b,
"*": lambda a, b: a * b,
"/": lambda a, b: a // b,
}
for tok in tokens:
if tok in ops:
b = stack.pop()
a = stack.pop()
stack.append(ops[tok](a, b))
else:
stack.append(int(tok))
if len(stack) != 1:
raise ValueError... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.7, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.0}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"err... |
or-coding-py-mini-typecheck-unify-593cc25f6fe5 | coding | code_generation | intermediate | Implement `unify(a, b)` for a tiny type language: types are strings
('Int', 'Bool') or lists ['Fun', t1, t2]. Variables are strings starting with
`?`. Return a dict substitution or None on failure. Do not need occurs-check
beyond rejecting assigning a variable to a type that contains it as a nested list. | {"language": "python", "repository": {"files": {"solution.py": "def occurs(var, typ):\n if typ == var:\n return True\n if isinstance(typ, list):\n return any(occurs(var, part) for part in typ[1:])\n return False\n\ndef apply_sub(sub, typ):\n if isinstance(typ, str):\n return sub.get(typ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def occurs(var, typ):
if typ == var:
return True
if isinstance(typ, list):
return any(occurs(var, part) for part in typ[1:])
return False
def apply_sub(sub, typ):
if isinstance(typ, str):
return sub.get(typ, typ)
return [typ[0], *(apply_sub(sub, p) for p in typ[1:])]
def unify(a, b, sub=None):
sub = dict(sub... | def occurs(var, typ):
if typ == var:
return True
if isinstance(typ, list):
return any(occurs(var, part) for part in typ[1:])
return False
def apply_sub(sub, typ):
if isinstance(typ, str):
return sub.get(typ, typ)
return [typ[0], *(apply_sub(sub, p) for p in typ[1:])]
def unify(a, b, sub=None):
sub = dict(sub... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 1.075, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 1.275, "tests": 0.0, "total": 5.325}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "mi... |
or-coding-py-static-unused-38afb5319518 | coding | code_generation | intermediate | Implement `unused_assigns(lines)` for a toy language: lines are
`x = ...` or `use x`. Names are `[a-z]+`. Return sorted names assigned at
least once and never used. Later use counts. | {"language": "python", "repository": {"files": {"solution.py": "import re\n\ndef unused_assigns(lines):\n assigned = set()\n used = set()\n for line in lines:\n m = re.fullmatch(r\"([a-z]+) = .*\", line.strip())\n if m:\n assigned.add(m.group(1))\n continue\n m = re.f... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import re
def unused_assigns(lines):
assigned = set()
used = set()
for line in lines:
m = re.fullmatch(r"([a-z]+) = .*", line.strip())
if m:
assigned.add(m.group(1))
continue
m = re.fullmatch(r"use ([a-z]+)", line.strip())
if m:
used.add(m.group(1))
return sorted(assigned - used) | import re
def unused_assigns(lines):
assigned = set()
used = set()
for line in lines:
m = re.fullmatch(r"([a-z]+) = .*", line.strip())
if m:
assigned.add(m.group(1))
continue
m = re.fullmatch(r"use ([a-z]+)", line.strip())
if m:
used.add(m.group(1))
return sorted(assigned - used) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.55, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.75, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.75, "tests": 0.0, "total": 5.65}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "static... |
or-coding-py-doc-extract-params-c3a9d5470e58 | coding | code_generation | beginner | Implement `google_args(docstring)` extracting Args from a Google-style
docstring. Return a list of (name, description) for lines indented like
` name: desc`. Ignore other sections. | {"language": "python", "repository": {"files": {"solution.py": "def google_args(docstring):\n lines = docstring.splitlines()\n out = []\n in_args = False\n for line in lines:\n if line.strip() == \"Args:\":\n in_args = True\n continue\n if in_args and line.strip().endswit... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def google_args(docstring):
lines = docstring.splitlines()
out = []
in_args = False
for line in lines:
if line.strip() == "Args:":
in_args = True
continue
if in_args and line.strip().endswith(":") and not line.startswith(" "):
break
if in_args:
stripped = line.strip()
if ": " in stripped:
name, desc = stri... | def google_args(docstring):
lines = docstring.splitlines()
out = []
in_args = False
for line in lines:
if line.strip() == "Args:":
in_args = True
continue
if in_args and line.strip().endswith(":") and not line.startswith(" "):
break
if in_args:
stripped = line.strip()
if ": " in stripped:
name, desc = stri... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.625, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.6, "tests": 0.0, "total": 3.95}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "doc_e... |
or-coding-py-debug-doc-extract-params-513944f8b950 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `google_args(docstring)` extracting Args from a Google-style
docstring. Return a list of (name, description) for lines indented like
` name: desc`. Ignore other sections.
--- solution.py (bugg... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_args (test_solution.Test.test_args) ... FAIL\n\n======================================================================\nFAIL: test_args (test_solution.... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def google_args(docstring):
lines = docstring.splitlines()
out = []
in_args = False
for line in lines:
if line.strip() == "Args:":
in_args = True
continue
if in_args and line.strip().endswith(":") and not line.startswith(" "):
break
if in_args:
stripped = line.strip()
if ": " in stripped:
name, desc = stri... | def google_args(docstring):
lines = docstring.splitlines()
out = []
in_args = False
for line in lines:
if line.strip() == "Args:":
in_args = True
continue
if in_args and line.strip().endswith(":") and not line.startswith(" "):
break
if in_args:
stripped = line.strip()
if ": " in stripped:
name, desc = stri... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.625, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.925}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-migrate-rename-keys-ae57de445432 | coding | code_generation | beginner | Implement `migrate_v1_to_v2(payload)` renaming keys `userName`->`username`
and `emailAddress`->`email`, leaving other keys. Missing keys stay missing. | {"language": "python", "repository": {"files": {"solution.py": "def migrate_v1_to_v2(payload):\n mapping = {\"userName\": \"username\", \"emailAddress\": \"email\"}\n return {mapping.get(k, k): v for k, v in payload.items()}\n", "test_solution.py": "import unittest\nfrom solution import migrate_v1_to_v2\n\nclass ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def migrate_v1_to_v2(payload):
mapping = {"userName": "username", "emailAddress": "email"}
return {mapping.get(k, k): v for k, v in payload.items()} | def migrate_v1_to_v2(payload):
mapping = {"userName": "username", "emailAddress": "email"}
return {mapping.get(k, k): v for k, v in payload.items()} | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.35, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.35, "tests": 0.0, "total": 3.5500000000000003}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "... |
or-coding-py-compat-flag-23b7947ba53a | coding | code_generation | beginner | Implement `api_supported(client, server)` where versions are (major, minor).
Compatible iff major matches and client.minor <= server.minor. | {"language": "python", "repository": {"files": {"solution.py": "def api_supported(client, server):\n return client[0] == server[0] and client[1] <= server[1]\n", "test_solution.py": "import unittest\nfrom solution import api_supported\n\nclass Test(unittest.TestCase):\n def test_ok(self):\n self.assertTrue... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def api_supported(client, server):
return client[0] == server[0] and client[1] <= server[1] | def api_supported(client, server):
return client[0] == server[0] and client[1] <= server[1] | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.3, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.4, "tests": 0.0, "total": 3.3}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "compat_fla... |
or-coding-py-dockerfile-user-99c246d38333 | coding | code_generation | beginner | Implement `dockerfile_runs_as_root(text)` returning True if the last
USER instruction is missing or is `USER root` / `USER 0` (ignoring case on
root). Comment lines starting with # are ignored. | {"language": "python", "repository": {"files": {"solution.py": "def dockerfile_runs_as_root(text):\n user = None\n for raw in text.splitlines():\n line = raw.strip()\n if not line or line.startswith(\"#\"):\n continue\n parts = line.split()\n if parts[0].upper() == \"USER\":... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def dockerfile_runs_as_root(text):
user = None
for raw in text.splitlines():
line = raw.strip()
if not line or line.startswith("#"):
continue
parts = line.split()
if parts[0].upper() == "USER":
user = parts[1] if len(parts) > 1 else ""
if user is None:
return True
return user.lower() == "root" or user == "0" | def dockerfile_runs_as_root(text):
user = None
for raw in text.splitlines():
line = raw.strip()
if not line or line.startswith("#"):
continue
parts = line.split()
if parts[0].upper() == "USER":
user = parts[1] if len(parts) > 1 else ""
if user is None:
return True
return user.lower() == "root" or user == "0" | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.55, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.725, "tests": 0.0, "total": 4.0}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "docke... |
or-coding-py-debug-dockerfile-user-4c8fafbbafc1 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `dockerfile_runs_as_root(text)` returning True if the last
USER instruction is missing or is `USER root` / `USER 0` (ignoring case on
root). Comment lines starting with # are ignored.
--- solu... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_last_user (test_solution.Test.test_last_user) ... FAIL\n\n======================================================================\nFAIL: test_last_user ... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def dockerfile_runs_as_root(text):
user = None
for raw in text.splitlines():
line = raw.strip()
if not line or line.startswith("#"):
continue
parts = line.split()
if parts[0].upper() == "USER":
user = parts[1] if len(parts) > 1 else ""
if user is None:
return True
return user.lower() == "root" or user == "0" | def dockerfile_runs_as_root(text):
user = None
for raw in text.splitlines():
line = raw.strip()
if not line or line.startswith("#"):
continue
parts = line.split()
if parts[0].upper() == "USER":
user = parts[1] if len(parts) > 1 else ""
if user is None:
return True
return user.lower() == "root" or user == "0" | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:04:59Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.55, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.85}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"e... |
or-coding-py-compose-depends-cf786caf91fe | coding | code_generation | intermediate | Implement `startup_order(depends)` where depends maps service -> list of
services it needs first. Return a topological order. Raise ValueError on cycles. | {"language": "python", "repository": {"files": {"solution.py": "from collections import defaultdict, deque\n\ndef startup_order(depends):\n nodes = set(depends)\n for deps in depends.values():\n nodes.update(deps)\n incoming = {n: 0 for n in nodes}\n graph = defaultdict(list)\n for svc, deps in de... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from collections import defaultdict, deque
def startup_order(depends):
nodes = set(depends)
for deps in depends.values():
nodes.update(deps)
incoming = {n: 0 for n in nodes}
graph = defaultdict(list)
for svc, deps in depends.items():
for dep in deps:
graph[dep].append(svc)
incoming[svc] += 1
ready = deque([n... | from collections import defaultdict, deque
def startup_order(depends):
nodes = set(depends)
for deps in depends.values():
nodes.update(deps)
incoming = {n: 0 for n in nodes}
graph = defaultdict(list)
for svc, deps in depends.items():
for dep in deps:
graph[dep].append(svc)
incoming[svc] += 1
ready = deque([n... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.collections | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.85, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.625, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.525, "tests": 0.0, "total": 4.6}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "compo... |
or-coding-py-debug-compose-depends-e6950cea10f0 | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `startup_order(depends)` where depends maps service -> list of
services it needs first. Return a topological order. Raise ValueError on cycles.
--- solution.py (buggy) ---
from collections imp... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_order (test_solution.Test.test_order) ... FAIL\n\n======================================================================\nFAIL: test_order (test_soluti... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | from collections import defaultdict, deque
def startup_order(depends):
nodes = set(depends)
for deps in depends.values():
nodes.update(deps)
incoming = {n: 0 for n in nodes}
graph = defaultdict(list)
for svc, deps in depends.items():
for dep in deps:
graph[dep].append(svc)
incoming[svc] += 1
ready = deque([n... | from collections import defaultdict, deque
def startup_order(depends):
nodes = set(depends)
for deps in depends.values():
nodes.update(deps)
incoming = {n: 0 for n in nodes}
graph = defaultdict(list)
for svc, deps in depends.items():
for dep in deps:
graph[dep].append(svc)
incoming[svc] += 1
ready = deque([n... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.collections | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.85, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.15}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"e... |
or-coding-py-async-gather-ok-95298ce50108 | coding | code_generation | intermediate | Implement `first_true(predicates)` where predicates is a list of zero-arg
callables. Return the index of the first that returns a truthy value, or -1.
Later predicates must not be called after success (short-circuit). | {"language": "python", "repository": {"files": {"solution.py": "def first_true(predicates):\n for i, fn in enumerate(predicates):\n if fn():\n return i\n return -1\n", "test_solution.py": "import unittest\nfrom solution import first_true\n\nclass Test(unittest.TestCase):\n def test_short(self... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def first_true(predicates):
for i, fn in enumerate(predicates):
if fn():
return i
return -1 | def first_true(predicates):
for i, fn in enumerate(predicates):
if fn():
return i
return -1 | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.6, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.625, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.8, "tests": 0.0, "total": 4.625}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "async_... |
or-coding-py-mutex-counter-52c971c4e6a9 | coding | code_generation | beginner | Implement `threaded_increment(n_threads, n_each)` that starts n_threads
threads each adding n_each to a shared integer behind a threading.Lock.
Return the final count (must equal n_threads * n_each). | {"language": "python", "repository": {"files": {"solution.py": "import threading\n\ndef threaded_increment(n_threads, n_each):\n lock = threading.Lock()\n value = {\"n\": 0}\n\n def worker():\n for _ in range(n_each):\n with lock:\n value[\"n\"] += 1\n\n threads = [threading... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import threading
def threaded_increment(n_threads, n_each):
lock = threading.Lock()
value = {"n": 0}
def worker():
for _ in range(n_each):
with lock:
value["n"] += 1
threads = [threading.Thread(target=worker) for _ in range(n_threads)]
for t in threads:
t.start()
for t in threads:
t.join()
return value["... | import threading
def threaded_increment(n_threads, n_each):
lock = threading.Lock()
value = {"n": 0}
def worker():
for _ in range(n_each):
with lock:
value["n"] += 1
threads = [threading.Thread(target=worker) for _ in range(n_threads)]
for t in threads:
t.start()
for t in threads:
t.join()
return value["... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.625, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.65, "tests": 0.0, "total": 4.25}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "mute... |
or-coding-py-two-sum-index-9c2e41fc19d9 | coding | code_generation | beginner | Implement `pair_indices(nums, target)` returning a pair of distinct indices
i < j such that nums[i] + nums[j] == target, or None. Prefer the lexicographically
smallest (i, j). | {"language": "python", "repository": {"files": {"solution.py": "def pair_indices(nums, target):\n seen = {}\n best = None\n for i, value in enumerate(nums):\n need = target - value\n if need in seen:\n cand = (seen[need], i)\n if best is None or cand < best:\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def pair_indices(nums, target):
seen = {}
best = None
for i, value in enumerate(nums):
need = target - value
if need in seen:
cand = (seen[need], i)
if best is None or cand < best:
best = cand
if value not in seen:
seen[value] = i
return best | def pair_indices(nums, target):
seen = {}
best = None
for i, value in enumerate(nums):
need = target - value
if need in seen:
cand = (seen[need], i)
if best is None or cand < best:
best = cand
if value not in seen:
seen[value] = i
return best | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.55, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.675, "tests": 0.0, "total": 4.2}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "two_s... |
or-coding-py-edit-distance-k-d9911a04d868 | coding | code_generation | intermediate | Implement `within_edit(a, b, k)` True iff Levenshtein distance(a, b) <= k.
You may use DP. Strings are short. | {"language": "python", "repository": {"files": {"solution.py": "def within_edit(a, b, k):\n if abs(len(a) - len(b)) > k:\n return False\n prev = list(range(len(b) + 1))\n for i, ca in enumerate(a, start=1):\n row = [i]\n for j, cb in enumerate(b, start=1):\n cost = 0 if ca == cb... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def within_edit(a, b, k):
if abs(len(a) - len(b)) > k:
return False
prev = list(range(len(b) + 1))
for i, ca in enumerate(a, start=1):
row = [i]
for j, cb in enumerate(b, start=1):
cost = 0 if ca == cb else 1
row.append(min(row[j - 1] + 1, prev[j] + 1, prev[j - 1] + cost))
prev = row
return prev[-1] <= k | def within_edit(a, b, k):
if abs(len(a) - len(b)) > k:
return False
prev = list(range(len(b) + 1))
for i, ca in enumerate(a, start=1):
row = [i]
for j, cb in enumerate(b, start=1):
cost = 0 if ca == cb else 1
row.append(min(row[j - 1] + 1, prev[j] + 1, prev[j - 1] + cost))
prev = row
return prev[-1] <= k | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.5, "constraints": 1.4, "keywords": 0.0, "math_ops": 2.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.45, "tests": 0.0, "total": 5.550000000000001}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slu... |
or-coding-py-cycle-list-4961dd97c673 | coding | code_generation | beginner | Represent a singly linked list as nodes `{"v": value, "n": next_or_None}`.
Implement `has_cycle(head)` using constant extra memory (Floyd). | {"language": "python", "repository": {"files": {"solution.py": "def has_cycle(head):\n slow = head\n fast = head\n while fast and fast[\"n\"]:\n slow = slow[\"n\"]\n fast = fast[\"n\"][\"n\"]\n if slow is fast:\n return True\n return False\n", "test_solution.py": "import unit... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def has_cycle(head):
slow = head
fast = head
while fast and fast["n"]:
slow = slow["n"]
fast = fast["n"]["n"]
if slow is fast:
return True
return False | def has_cycle(head):
slow = head
fast = head
while fast and fast["n"]:
slow = slow["n"]
fast = fast["n"]["n"]
if slow is fast:
return True
return False | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.45, "tests": 0.0, "total": 3.625}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "cycle... |
or-coding-py-debug-cycle-list-92acf22819df | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Represent a singly linked list as nodes `{"v": value, "n": next_or_None}`.
Implement `has_cycle(head)` using constant extra memory (Floyd).
--- solution.py (buggy) ---
def has_cycle(head):
slow = head
... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_cycle (test_solution.Test.test_cycle) ... FAIL\n\n======================================================================\nFAIL: test_cycle (test_soluti... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def has_cycle(head):
slow = head
fast = head
while fast and fast["n"]:
slow = slow["n"]
fast = fast["n"]["n"]
if slow is fast:
return True
return False | def has_cycle(head):
slow = head
fast = head
while fast and fast["n"]:
slow = slow["n"]
fast = fast["n"]["n"]
if slow is fast:
return True
return False | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.875}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-bst-validate-4c158319df27 | coding | code_generation | beginner | Nodes are `{"v": int, "l": node|None, "r": node|None}`. Implement
`is_bst(root)` with strict ordering (left < v < right) for the whole tree. | {"language": "python", "repository": {"files": {"solution.py": "def is_bst(root, lo=None, hi=None):\n if root is None:\n return True\n v = root[\"v\"]\n if lo is not None and v <= lo:\n return False\n if hi is not None and v >= hi:\n return False\n return is_bst(root[\"l\"], lo, v) a... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def is_bst(root, lo=None, hi=None):
if root is None:
return True
v = root["v"]
if lo is not None and v <= lo:
return False
if hi is not None and v >= hi:
return False
return is_bst(root["l"], lo, v) and is_bst(root["r"], v, hi) | def is_bst(root, lo=None, hi=None):
if root is None:
return True
v = root["v"]
if lo is not None and v <= lo:
return False
if hi is not None and v >= hi:
return False
return is_bst(root["l"], lo, v) and is_bst(root["r"], v, hi) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.525, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.55, "tests": 0.0, "total": 3.6750000000000003}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "... |
or-coding-py-debug-bst-validate-fbc45fa163b6 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Nodes are `{"v": int, "l": node|None, "r": node|None}`. Implement
`is_bst(root)` with strict ordering (left < v < right) for the whole tree.
--- solution.py (buggy) ---
def is_bst(root, lo=None, hi=None... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 2, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_bad (test_solution.Test.test_bad) ... ok\ntest_ok (test_solution.Test.test_ok) ... FAIL\n\n============================================================... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def is_bst(root, lo=None, hi=None):
if root is None:
return True
v = root["v"]
if lo is not None and v <= lo:
return False
if hi is not None and v >= hi:
return False
return is_bst(root["l"], lo, v) and is_bst(root["r"], v, hi) | def is_bst(root, lo=None, hi=None):
if root is None:
return True
v = root["v"]
if lo is not None and v <= lo:
return False
if hi is not None and v >= hi:
return False
return is_bst(root["l"], lo, v) and is_bst(root["r"], v, hi) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.525, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.825}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-cli-argv-1cfeb4dc50c7 | coding | code_generation | intermediate | Implement `parse_flags(argv)` for a tiny CLI: flags `--name value` and
boolean `--verbose` present-or-not. Remaining tokens are positional.
Return `{"flags": dict, "args": list}`. `--verbose` maps to True. | {"language": "python", "repository": {"files": {"solution.py": "def parse_flags(argv):\n flags = {}\n args = []\n i = 0\n while i < len(argv):\n tok = argv[i]\n if tok == \"--verbose\":\n flags[\"verbose\"] = True\n i += 1\n elif tok.startswith(\"--\"):\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def parse_flags(argv):
flags = {}
args = []
i = 0
while i < len(argv):
tok = argv[i]
if tok == "--verbose":
flags["verbose"] = True
i += 1
elif tok.startswith("--"):
name = tok[2:]
if i + 1 >= len(argv):
raise ValueError("missing")
flags[name] = argv[i + 1]
i += 2
else:
args.append(tok)
i += 1
return ... | def parse_flags(argv):
flags = {}
args = []
i = 0
while i < len(argv):
tok = argv[i]
if tok == "--verbose":
flags["verbose"] = True
i += 1
elif tok.startswith("--"):
name = tok[2:]
if i + 1 >= len(argv):
raise ValueError("missing")
flags[name] = argv[i + 1]
i += 2
else:
args.append(tok)
i += 1
return ... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.75, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.65, "tests": 0.0, "total": 7.0}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "cli_argv... |
or-coding-py-makefile-targets-d2abd26b36ee | coding | code_generation | beginner | Implement `make_targets(text)` extracting target names from lines matching
`target: deps` at column 0 (no leading whitespace). Skip `.PHONY` and comments. | {"language": "python", "repository": {"files": {"solution.py": "def make_targets(text):\n names = []\n for raw in text.splitlines():\n if not raw or raw.startswith(\"\\t\") or raw.startswith(\" \") or raw.startswith(\"#\"):\n continue\n if \":\" not in raw:\n continue\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def make_targets(text):
names = []
for raw in text.splitlines():
if not raw or raw.startswith("\t") or raw.startswith(" ") or raw.startswith("#"):
continue
if ":" not in raw:
continue
target = raw.split(":", 1)[0].strip()
if target and target != ".PHONY":
names.append(target)
return names | def make_targets(text):
names = []
for raw in text.splitlines():
if not raw or raw.startswith("\t") or raw.startswith(" ") or raw.startswith("#"):
continue
if ":" not in raw:
continue
target = raw.split(":", 1)[0].strip()
if target and target != ".PHONY":
names.append(target)
return names | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.5, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.5, "tests": 0.0, "total": 3.6}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "makefile_t... |
or-coding-py-ci-junit-counts-bd792f4e3f79 | coding | code_generation | intermediate | Implement `junit_counts(xml)` for a tiny subset: count `failures=` and
`tests=` on the first `<testsuite ...>` tag using regex. Return
`{"tests": int, "failures": int}`. | {"language": "python", "repository": {"files": {"solution.py": "import re\n\ndef junit_counts(xml):\n m = re.search(r\"<testsuite\\b[^>]*>\", xml)\n if not m:\n raise ValueError(\"no testsuite\")\n tag = m.group(0)\n tests = int(re.search(r'tests=\"(\\d+)\"', tag).group(1))\n failures = int(re.sea... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import re
def junit_counts(xml):
m = re.search(r"<testsuite\b[^>]*>", xml)
if not m:
raise ValueError("no testsuite")
tag = m.group(0)
tests = int(re.search(r'tests="(\d+)"', tag).group(1))
failures = int(re.search(r'failures="(\d+)"', tag).group(1))
return {"tests": tests, "failures": failures} | import re
def junit_counts(xml):
m = re.search(r"<testsuite\b[^>]*>", xml)
if not m:
raise ValueError("no testsuite")
tag = m.group(0)
tests = int(re.search(r'tests="(\d+)"', tag).group(1))
failures = int(re.search(r'failures="(\d+)"', tag).group(1))
return {"tests": tests, "failures": failures} | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.575, "tests": 0.0, "total": 4.65}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "ci_ju... |
or-coding-py-healthcheck-backoff-7f8970814d92 | coding | code_generation | intermediate | Implement `backoff_delays(retries, base, cap)` returning a list of length
`retries` with delays min(cap, base * 2**i) for i=0..retries-1. | {"language": "python", "repository": {"files": {"solution.py": "def backoff_delays(retries, base, cap):\n return [min(cap, base * (2 ** i)) for i in range(retries)]\n", "test_solution.py": "import unittest\nfrom solution import backoff_delays\n\nclass Test(unittest.TestCase):\n def test_cap(self):\n self.a... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def backoff_delays(retries, base, cap):
return [min(cap, base * (2 ** i)) for i in range(retries)] | def backoff_delays(retries, base, cap):
return [min(cap, base * (2 ** i)) for i in range(retries)] | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:00Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.25, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.45, "tests": 0.0, "total": 4.550000000000001}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "s... |
or-coding-py-hot-path-count-07accf47237f | coding | code_generation | intermediate | Implement `majority_nlogn_forbidden(nums)` finding the element that
appears more than n/2 times. Use Boyer-Moore. Guarantee O(n) time, O(1) extra
memory aside from the input. The input is guaranteed to have a majority. | {"language": "python", "repository": {"files": {"solution.py": "def majority(nums):\n vote = 0\n cand = None\n for x in nums:\n if vote == 0:\n cand = x\n vote += 1 if x == cand else -1\n return cand\n", "test_solution.py": "import unittest\nfrom solution import majority\n\nclass Te... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def majority(nums):
vote = 0
cand = None
for x in nums:
if vote == 0:
cand = x
vote += 1 if x == cand else -1
return cand | def majority(nums):
vote = 0
cand = None
for x in nums:
if vote == 0:
cand = x
vote += 1 if x == cand else -1
return cand | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.4, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.75, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.775, "tests": 0.0, "total": 4.525}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "hot_p... |
or-coding-py-arena-bump-f435a0b50f59 | coding | code_generation | beginner | Implement class `BumpArena(size)` with `alloc(n)` returning the start
offset of n contiguous bytes or None if it will not fit, and `reset()` to
free everything. No coalescing needed. | {"language": "python", "repository": {"files": {"solution.py": "class BumpArena:\n def __init__(self, size):\n self.size = size\n self.offset = 0\n\n def alloc(self, n):\n if n < 0 or self.offset + n > self.size:\n return None\n start = self.offset\n self.offset += n\... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | class BumpArena:
def __init__(self, size):
self.size = size
self.offset = 0
def alloc(self, n):
if n < 0 or self.offset + n > self.size:
return None
start = self.offset
self.offset += n
return start
def reset(self):
self.offset = 0 | class BumpArena:
def __init__(self, size):
self.size = size
self.offset = 0
def alloc(self, n):
if n < 0 or self.offset + n > self.size:
return None
start = self.offset
self.offset += n
return start
def reset(self):
self.offset = 0 | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.675, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.7, "tests": 0.0, "total": 4.475}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "arena_... |
or-coding-py-debug-arena-bump-5fee1936384d | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement class `BumpArena(size)` with `alloc(n)` returning the start
offset of n contiguous bytes or None if it will not fit, and `reset()` to
free everything. No coalescing needed.
--- solution.py (bu... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_alloc (test_solution.Test.test_alloc) ... FAIL\n\n======================================================================\nFAIL: test_alloc (test_soluti... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | class BumpArena:
def __init__(self, size):
self.size = size
self.offset = 0
def alloc(self, n):
if n < 0 or self.offset + n > self.size:
return None
start = self.offset
self.offset += n
return start
def reset(self):
self.offset = 0 | class BumpArena:
def __init__(self, size):
self.size = size
self.offset = 0
def alloc(self, n):
if n < 0 or self.offset + n > self.size:
return None
start = self.offset
self.offset += n
return start
def reset(self):
self.offset = 0 | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.675, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.975}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-tokenize-c-idents-85906e6bb602 | coding | code_generation | intermediate | Implement `c_idents(source)` returning identifiers matching
`[A-Za-z_][A-Za-z0-9_]*` in order, skipping those inside double-quoted strings.
Do not handle escapes other than `\\` and `\"`. Comments are not supported. | {"language": "python", "repository": {"files": {"solution.py": "def c_idents(source):\n ident = []\n out = []\n i = 0\n n = len(source)\n while i < n:\n ch = source[i]\n if ch == '\"':\n i += 1\n while i < n:\n if source[i] == \"\\\\\":\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def c_idents(source):
ident = []
out = []
i = 0
n = len(source)
while i < n:
ch = source[i]
if ch == '"':
i += 1
while i < n:
if source[i] == "\\":
i += 2
continue
if source[i] == '"':
i += 1
break
i += 1
continue
if ch.isalnum() or ch == "_":
j = i
while j < n and (source[j].isalnum() or source[j] ... | def c_idents(source):
ident = []
out = []
i = 0
n = len(source)
while i < n:
ch = source[i]
if ch == '"':
i += 1
while i < n:
if source[i] == "\\":
i += 2
continue
if source[i] == '"':
i += 1
break
i += 1
continue
if ch.isalnum() or ch == "_":
j = i
while j < n and (source[j].isalnum() or source[j] ... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.95, "constraints": 1.4, "keywords": 0.0, "math_ops": 2.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.65, "tests": 0.0, "total": 6.575}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "toke... |
or-coding-py-debug-tokenize-c-idents-f76b8c1f1103 | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `c_idents(source)` returning identifiers matching
`[A-Za-z_][A-Za-z0-9_]*` in order, skipping those inside double-quoted strings.
Do not handle escapes other than `\\` and `\"`. Comments are no... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_skip_string (test_solution.Test.test_skip_string) ... FAIL\n\n======================================================================\nFAIL: test_skip_s... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def c_idents(source):
ident = []
out = []
i = 0
n = len(source)
while i < n:
ch = source[i]
if ch == '"':
i += 1
while i < n:
if source[i] == "\\":
i += 2
continue
if source[i] == '"':
i += 1
break
i += 1
continue
if ch.isalnum() or ch == "_":
j = i
while j < n and (source[j].isalnum() or source[j] ... | def c_idents(source):
ident = []
out = []
i = 0
n = len(source)
while i < n:
ch = source[i]
if ch == '"':
i += 1
while i < n:
if source[i] == "\\":
i += 2
continue
if source[i] == '"':
i += 1
break
i += 1
continue
if ch.isalnum() or ch == "_":
j = i
while j < n and (source[j].isalnum() or source[j] ... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.95, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.25}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"e... |
or-coding-py-refcount-toy-e57fc477513c | coding | code_generation | beginner | Implement class `Rc` with `inc()`, `dec()`, and `alive()` for a toy
refcount. `dec` below zero raises ValueError. Start at 1. | {"language": "python", "repository": {"files": {"solution.py": "class Rc:\n def __init__(self):\n self.count = 1\n\n def inc(self):\n self.count += 1\n\n def dec(self):\n if self.count <= 0:\n raise ValueError(\"underflow\")\n self.count -= 1\n\n def alive(self):\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | class Rc:
def __init__(self):
self.count = 1
def inc(self):
self.count += 1
def dec(self):
if self.count <= 0:
raise ValueError("underflow")
self.count -= 1
def alive(self):
return self.count > 0 | class Rc:
def __init__(self):
self.count = 1
def inc(self):
self.count += 1
def dec(self):
if self.count <= 0:
raise ValueError("underflow")
self.count -= 1
def alive(self):
return self.count > 0 | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.675, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.5, "tests": 0.0, "total": 4.275}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "refcou... |
or-coding-py-zip-longest-fill-fa335858e41a | coding | code_generation | beginner | Implement `zip_fill(*seqs, fill=None)` equivalent to padding all sequences
to the longest length then zipping. Return a list of tuples. | {"language": "python", "repository": {"files": {"solution.py": "def zip_fill(*seqs, fill=None):\n seqs = [list(s) for s in seqs]\n if not seqs:\n return []\n n = max(len(s) for s in seqs)\n out = []\n for i in range(n):\n out.append(tuple(s[i] if i < len(s) else fill for s in seqs))\n re... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def zip_fill(*seqs, fill=None):
seqs = [list(s) for s in seqs]
if not seqs:
return []
n = max(len(s) for s in seqs)
out = []
for i in range(n):
out.append(tuple(s[i] if i < len(s) else fill for s in seqs))
return out | def zip_fill(*seqs, fill=None):
seqs = [list(s) for s in seqs]
if not seqs:
return []
n = max(len(s) for s in seqs)
out = []
for i in range(n):
out.append(tuple(s[i] if i < len(s) else fill for s in seqs))
return out | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.425, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.475, "tests": 0.0, "total": 3.875}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "zi... |
or-coding-py-coverage-uncovered-0981a6b7636b | coding | code_generation | beginner | Implement `uncovered(lines, hit)` where `lines` is a set of executable line
numbers and `hit` is a list of line numbers executed (with duplicates). Return
sorted executable lines that never appear in `hit`. | {"language": "python", "repository": {"files": {"solution.py": "def uncovered(lines, hit):\n seen = set(hit)\n return sorted(n for n in lines if n not in seen)\n", "test_solution.py": "import unittest\nfrom solution import uncovered\n\nclass Test(unittest.TestCase):\n def test_gap(self):\n self.assertEq... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def uncovered(lines, hit):
seen = set(hit)
return sorted(n for n in lines if n not in seen) | def uncovered(lines, hit):
seen = set(hit)
return sorted(n for n in lines if n not in seen) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.275, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.8, "tests": 0.0, "total": 3.6750000000000003}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "s... |
or-coding-py-flake-rerun-0082fc318002 | coding | code_generation | beginner | Implement `classify_flaky(results)` where results is a list of bool pass/fail
for the same test. Return `pass` if all True, `fail` if all False, `flaky` otherwise. | {"language": "python", "repository": {"files": {"solution.py": "def classify_flaky(results):\n if not results:\n raise ValueError(\"empty\")\n if all(results):\n return \"pass\"\n if not any(results):\n return \"fail\"\n return \"flaky\"\n", "test_solution.py": "import unittest\nfrom so... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def classify_flaky(results):
if not results:
raise ValueError("empty")
if all(results):
return "pass"
if not any(results):
return "fail"
return "flaky" | def classify_flaky(results):
if not results:
raise ValueError("empty")
if all(results):
return "pass"
if not any(results):
return "fail"
return "flaky" | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.45, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.625, "tests": 0.0, "total": 3.8000000000000003}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0",... |
or-coding-py-review-complexity-8e95f6406df3 | coding | code_generation | intermediate | Implement `nested_loop_depth(source)` counting the maximum nesting of
lines that strip-start with `for ` or `while ` based on leading indent (4 spaces).
This is a review heuristic, not a Python parser. | {"language": "python", "repository": {"files": {"solution.py": "def nested_loop_depth(source):\n best = 0\n for raw in source.splitlines():\n if not raw.strip():\n continue\n indent = (len(raw) - len(raw.lstrip(\" \"))) // 4\n stripped = raw.strip()\n if stripped.startswith(... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def nested_loop_depth(source):
best = 0
for raw in source.splitlines():
if not raw.strip():
continue
indent = (len(raw) - len(raw.lstrip(" "))) // 4
stripped = raw.strip()
if stripped.startswith("for ") or stripped.startswith("while "):
best = max(best, indent + 1)
return best | def nested_loop_depth(source):
best = 0
for raw in source.splitlines():
if not raw.strip():
continue
indent = (len(raw) - len(raw.lstrip(" "))) // 4
stripped = raw.strip()
if stripped.startswith("for ") or stripped.startswith("while "):
best = max(best, indent + 1)
return best | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.loops | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.775, "tests": 0.0, "total": 4.975}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "re... |
or-coding-py-debug-review-complexity-30413396f099 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `nested_loop_depth(source)` counting the maximum nesting of
lines that strip-start with `for ` or `while ` based on leading indent (4 spaces).
This is a review heuristic, not a Python parser.
... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_depth (test_solution.Test.test_depth) ... FAIL\n\n======================================================================\nFAIL: test_depth (test_soluti... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def nested_loop_depth(source):
best = 0
for raw in source.splitlines():
if not raw.strip():
continue
indent = (len(raw) - len(raw.lstrip(" "))) // 4
stripped = raw.strip()
if stripped.startswith("for ") or stripped.startswith("while "):
best = max(best, indent + 1)
return best | def nested_loop_depth(source):
best = 0
for raw in source.splitlines():
if not raw.strip():
continue
indent = (len(raw) - len(raw.lstrip(" "))) // 4
stripped = raw.strip()
if stripped.startswith("for ") or stripped.startswith("while "):
best = max(best, indent + 1)
return best | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.774999999999999}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {... |
or-coding-py-wasm-leb-u32-d0df71ce4311 | coding | code_generation | beginner | Implement `decode_uleb128(data: bytes)` decoding one unsigned LEB128
integer from the start of data and returning (value, bytes_consumed). | {"language": "python", "repository": {"files": {"solution.py": "def decode_uleb128(data):\n result = 0\n shift = 0\n for i, byte in enumerate(data):\n result |= (byte & 0x7F) << shift\n if byte & 0x80 == 0:\n return result, i + 1\n shift += 7\n if shift > 35:\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def decode_uleb128(data):
result = 0
shift = 0
for i, byte in enumerate(data):
result |= (byte & 0x7F) << shift
if byte & 0x80 == 0:
return result, i + 1
shift += 7
if shift > 35:
raise ValueError("overflow")
raise ValueError("truncated") | def decode_uleb128(data):
result = 0
shift = 0
for i, byte in enumerate(data):
result |= (byte & 0x7F) << shift
if byte & 0x80 == 0:
return result, i + 1
shift += 7
if shift > 35:
raise ValueError("overflow")
raise ValueError("truncated") | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.525, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.425, "tests": 0.0, "total": 4.05}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "wasm_... |
or-coding-py-debug-wasm-leb-u32-3c9497a82fe3 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `decode_uleb128(data: bytes)` decoding one unsigned LEB128
integer from the start of data and returning (value, bytes_consumed).
--- solution.py (buggy) ---
def decode_uleb128(data):
result =... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 2, \"failures\": 1, \"errors\": 1, \"skipped\": 0, \"passed\": false}\n\ntest_multi (test_solution.Test.test_multi) ... FAIL\ntest_small (test_solution.Test.test_small) ... ERROR\n\n===============================================... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def decode_uleb128(data):
result = 0
shift = 0
for i, byte in enumerate(data):
result |= (byte & 0x7F) << shift
if byte & 0x80 == 0:
return result, i + 1
shift += 7
if shift > 35:
raise ValueError("overflow")
raise ValueError("truncated") | def decode_uleb128(data):
result = 0
shift = 0
for i, byte in enumerate(data):
result |= (byte & 0x7F) << shift
if byte & 0x80 == 0:
return result, i + 1
shift += 7
if shift > 35:
raise ValueError("overflow")
raise ValueError("truncated") | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 2}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.525, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.825}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-glob-match-star-9bbfe8b3863c | coding | code_generation | intermediate | Implement `glob_match(pat, name)` supporting only `*` (any sequence) and
literal characters. No character classes. Match the whole name. | {"language": "python", "repository": {"files": {"solution.py": "def glob_match(pat, name):\n def rec(i, j):\n if i == len(pat):\n return j == len(name)\n if pat[i] == \"*\":\n return rec(i + 1, j) or (j < len(name) and rec(i, j + 1))\n if j < len(name) and pat[i] == name[j]... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def glob_match(pat, name):
def rec(i, j):
if i == len(pat):
return j == len(name)
if pat[i] == "*":
return rec(i + 1, j) or (j < len(name) and rec(i, j + 1))
if j < len(name) and pat[i] == name[j]:
return rec(i + 1, j + 1)
return False
return rec(0, 0) | def glob_match(pat, name):
def rec(i, j):
if i == len(pat):
return j == len(name)
if pat[i] == "*":
return rec(i + 1, j) or (j < len(name) and rec(i, j + 1))
if j < len(name) and pat[i] == name[j]:
return rec(i + 1, j + 1)
return False
return rec(0, 0) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.5, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.375, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.45, "tests": 0.0, "total": 4.925000000000001}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "s... |
or-coding-py-debug-glob-match-star-37ca0c9f3328 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `glob_match(pat, name)` supporting only `*` (any sequence) and
literal characters. No character classes. Match the whole name.
--- solution.py (buggy) ---
def glob_match(pat, name):
def rec(i... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_star (test_solution.Test.test_star) ... FAIL\n\n======================================================================\nFAIL: test_star (test_solution.... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def glob_match(pat, name):
def rec(i, j):
if i == len(pat):
return j == len(name)
if pat[i] == "*":
return rec(i + 1, j) or (j < len(name) and rec(i, j + 1))
if j < len(name) and pat[i] == name[j]:
return rec(i + 1, j + 1)
return False
return rec(0, 0) | def glob_match(pat, name):
def rec(i, j):
if i == len(pat):
return j == len(name)
if pat[i] == "*":
return rec(i + 1, j) or (j < len(name) and rec(i, j + 1))
if j < len(name) and pat[i] == name[j]:
return rec(i + 1, j + 1)
return False
return rec(0, 0) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:01Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.5, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 3.975, "tests": 0.0, "total": 10.775}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-env-expand-56b651320e58 | coding | code_generation | intermediate | Implement `expand_vars(text, env)` replacing `$NAME` and `${NAME}` where NAME
is `[A-Z_][A-Z0-9_]*`. Unknown names become empty string. Do not expand inside
single quotes `'...'`. | {"language": "python", "repository": {"files": {"solution.py": "import re\n\nTOKEN = re.compile(r\"\\$({)?([A-Z_][A-Z0-9_]*)(?(1)})\")\n\ndef expand_vars(text, env):\n out = []\n i = 0\n in_single = False\n while i < len(text):\n ch = text[i]\n if ch == \"'\" :\n in_single = not in_... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import re
TOKEN = re.compile(r"\$({)?([A-Z_][A-Z0-9_]*)(?(1)})")
def expand_vars(text, env):
out = []
i = 0
in_single = False
while i < len(text):
ch = text[i]
if ch == "'" :
in_single = not in_single
out.append(ch)
i += 1
continue
if not in_single and ch == "$":
m = TOKEN.match(text, i)
if m:
out.appen... | import re
TOKEN = re.compile(r"\$({)?([A-Z_][A-Z0-9_]*)(?(1)})")
def expand_vars(text, env):
out = []
i = 0
in_single = False
while i < len(text):
ch = text[i]
if ch == "'" :
in_single = not in_single
out.append(ch)
i += 1
continue
if not in_single and ch == "$":
m = TOKEN.match(text, i)
if m:
out.appen... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.85, "constraints": 1.4, "keywords": 0.0, "math_ops": 2.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.575, "tests": 0.0, "total": 6.0249999999999995}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "... |
or-coding-py-systemd-wanted-cbf71b9551eb | coding | code_generation | beginner | Implement `parse_wantedby(unit_text)` returning the WantedBy= value from an
`[Install]` section, or None. Last matching line wins. Ignore comments. | {"language": "python", "repository": {"files": {"solution.py": "def parse_wantedby(unit_text):\n section = None\n wanted = None\n for raw in unit_text.splitlines():\n line = raw.split(\";\", 1)[0].split(\"#\", 1)[0].strip()\n if not line:\n continue\n if line.startswith(\"[\") a... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def parse_wantedby(unit_text):
section = None
wanted = None
for raw in unit_text.splitlines():
line = raw.split(";", 1)[0].split("#", 1)[0].strip()
if not line:
continue
if line.startswith("[") and line.endswith("]"):
section = line[1:-1]
continue
if section == "Install" and line.startswith("WantedBy="):
wan... | def parse_wantedby(unit_text):
section = None
wanted = None
for raw in unit_text.splitlines():
line = raw.split(";", 1)[0].split("#", 1)[0].strip()
if not line:
continue
if line.startswith("[") and line.endswith("]"):
section = line[1:-1]
continue
if section == "Install" and line.startswith("WantedBy="):
wan... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.55, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.45, "tests": 0.0, "total": 3.8500000000000005}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "... |
or-coding-py-debug-systemd-wanted-2d060e31c4f0 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `parse_wantedby(unit_text)` returning the WantedBy= value from an
`[Install]` section, or None. Last matching line wins. Ignore comments.
--- solution.py (buggy) ---
def parse_wantedby(unit_te... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_install (test_solution.Test.test_install) ... FAIL\n\n======================================================================\nFAIL: test_install (test_... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def parse_wantedby(unit_text):
section = None
wanted = None
for raw in unit_text.splitlines():
line = raw.split(";", 1)[0].split("#", 1)[0].strip()
if not line:
continue
if line.startswith("[") and line.endswith("]"):
section = line[1:-1]
continue
if section == "Install" and line.startswith("WantedBy="):
wan... | def parse_wantedby(unit_text):
section = None
wanted = None
for raw in unit_text.splitlines():
line = raw.split(";", 1)[0].split("#", 1)[0].strip()
if not line:
continue
if line.startswith("[") and line.endswith("]"):
section = line[1:-1]
continue
if section == "Install" and line.startswith("WantedBy="):
wan... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.55, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 3.65, "tests": 0.0, "total": 10.5}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"e... |
or-coding-py-k8s-resource-parse-75bda9ed0cce | coding | code_generation | beginner | Implement `parse_cpu(value)` converting Kubernetes CPU strings: `100m` -> 0.1,
`2` -> 2.0. Raise ValueError otherwise. | {"language": "python", "repository": {"files": {"solution.py": "def parse_cpu(value):\n if value.endswith(\"m\") and value[:-1].isdigit():\n return int(value[:-1]) / 1000.0\n if value.replace(\".\", \"\", 1).isdigit():\n return float(value)\n raise ValueError(value)\n", "test_solution.py": "impor... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def parse_cpu(value):
if value.endswith("m") and value[:-1].isdigit():
return int(value[:-1]) / 1000.0
if value.replace(".", "", 1).isdigit():
return float(value)
raise ValueError(value) | def parse_cpu(value):
if value.endswith("m") and value[:-1].isdigit():
return int(value[:-1]) / 1000.0
if value.replace(".", "", 1).isdigit():
return float(value)
raise ValueError(value) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.375, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.375, "tests": 0.0, "total": 4.35}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "k8s_r... |
or-coding-py-ring-buffer-180e5d3a925c | coding | code_generation | intermediate | Implement `Ring(n)` with `push(x)` (overwrite oldest when full) and
`snapshot()` returning items oldest-to-newest. | {"language": "python", "repository": {"files": {"solution.py": "class Ring:\n def __init__(self, n):\n if n < 1:\n raise ValueError(\"n\")\n self.buf = [None] * n\n self.n = n\n self.i = 0\n self.size = 0\n\n def push(self, x):\n self.buf[self.i] = x\n s... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | class Ring:
def __init__(self, n):
if n < 1:
raise ValueError("n")
self.buf = [None] * n
self.n = n
self.i = 0
self.size = 0
def push(self, x):
self.buf[self.i] = x
self.i = (self.i + 1) % self.n
self.size = min(self.size + 1, self.n)
def snapshot(self):
start = (self.i - self.size) % self.n
return [sel... | class Ring:
def __init__(self, n):
if n < 1:
raise ValueError("n")
self.buf = [None] * n
self.n = n
self.i = 0
self.size = 0
def push(self, x):
self.buf[self.i] = x
self.i = (self.i + 1) % self.n
self.size = min(self.size + 1, self.n)
def snapshot(self):
start = (self.i - self.size) % self.n
return [sel... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.7, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.325, "tests": 0.0, "total": 5.125}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "ring_b... |
or-coding-py-debug-ring-buffer-514ee7f986a6 | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `Ring(n)` with `push(x)` (overwrite oldest when full) and
`snapshot()` returning items oldest-to-newest.
--- solution.py (buggy) ---
class Ring:
def __init__(self, n):
if n < 1:
raise Value... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_wrap (test_solution.Test.test_wrap) ... FAIL\n\n======================================================================\nFAIL: test_wrap (test_solution.... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | class Ring:
def __init__(self, n):
if n < 1:
raise ValueError("n")
self.buf = [None] * n
self.n = n
self.i = 0
self.size = 0
def push(self, x):
self.buf[self.i] = x
self.i = (self.i + 1) % self.n
self.size = min(self.size + 1, self.n)
def snapshot(self):
start = (self.i - self.size) % self.n
return [sel... | class Ring:
def __init__(self, n):
if n < 1:
raise ValueError("n")
self.buf = [None] * n
self.n = n
self.i = 0
self.size = 0
def push(self, x):
self.buf[self.i] = x
self.i = (self.i + 1) % self.n
self.size = min(self.size + 1, self.n)
def snapshot(self):
start = (self.i - self.size) % self.n
return [sel... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.7, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.0}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"err... |
or-coding-py-union-find-39864eb16b6c | coding | code_generation | intermediate | Implement `UnionFind(n)` with 0..n-1 elements, `find(i)`, `union(i,j)`
returning True if they were in different sets. Use path compression and union by rank. | {"language": "python", "repository": {"files": {"solution.py": "class UnionFind:\n def __init__(self, n):\n self.p = list(range(n))\n self.r = [0] * n\n\n def find(self, i):\n while self.p[i] != i:\n self.p[i] = self.p[self.p[i]]\n i = self.p[i]\n return i\n\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | class UnionFind:
def __init__(self, n):
self.p = list(range(n))
self.r = [0] * n
def find(self, i):
while self.p[i] != i:
self.p[i] = self.p[self.p[i]]
i = self.p[i]
return i
def union(self, i, j):
a, b = self.find(i), self.find(j)
if a == b:
return False
if self.r[a] < self.r[b]:
a, b = b, a
self.p[b]... | class UnionFind:
def __init__(self, n):
self.p = list(range(n))
self.r = [0] * n
def find(self, i):
while self.p[i] != i:
self.p[i] = self.p[self.p[i]]
i = self.p[i]
return i
def union(self, i, j):
a, b = self.find(i), self.find(j)
if a == b:
return False
if self.r[a] < self.r[b]:
a, b = b, a
self.p[b]... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.85, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.625, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.55, "tests": 0.0, "total": 4.625}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "unio... |
or-coding-py-debug-union-find-61bad24087bb | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `UnionFind(n)` with 0..n-1 elements, `find(i)`, `union(i,j)`
returning True if they were in different sets. Use path compression and union by rank.
--- solution.py (buggy) ---
class UnionFind:... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_uf (test_solution.Test.test_uf) ... FAIL\n\n======================================================================\nFAIL: test_uf (test_solution.Test.t... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | class UnionFind:
def __init__(self, n):
self.p = list(range(n))
self.r = [0] * n
def find(self, i):
while self.p[i] != i:
self.p[i] = self.p[self.p[i]]
i = self.p[i]
return i
def union(self, i, j):
a, b = self.find(i), self.find(j)
if a == b:
return False
if self.r[a] < self.r[b]:
a, b = b, a
self.p[b]... | class UnionFind:
def __init__(self, n):
self.p = list(range(n))
self.r = [0] * n
def find(self, i):
while self.p[i] != i:
self.p[i] = self.p[self.p[i]]
i = self.p[i]
return i
def union(self, i, j):
a, b = self.find(i), self.find(j)
if a == b:
return False
if self.r[a] < self.r[b]:
a, b = b, a
self.p[b]... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.85, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.15}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"e... |
or-coding-py-knapsack-01-5de1ee8eaac8 | coding | code_generation | intermediate | Implement `knapsack(weights, values, cap)` 0/1 knapsack maximum value. | {"language": "python", "repository": {"files": {"solution.py": "def knapsack(weights, values, cap):\n dp = [0] * (cap + 1)\n for w, v in zip(weights, values):\n for c in range(cap, w - 1, -1):\n dp[c] = max(dp[c], dp[c - w] + v)\n return dp[cap]\n", "test_solution.py": "import unittest\nfrom ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def knapsack(weights, values, cap):
dp = [0] * (cap + 1)
for w, v in zip(weights, values):
for c in range(cap, w - 1, -1):
dp[c] = max(dp[c], dp[c - w] + v)
return dp[cap] | def knapsack(weights, values, cap):
dp = [0] * (cap + 1)
for w, v in zip(weights, values):
for c in range(cap, w - 1, -1):
dp[c] = max(dp[c], dp[c - w] + v)
return dp[cap] | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.35, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.625, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.2, "tests": 0.0, "total": 4.775}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "knaps... |
or-coding-py-debug-knapsack-01-21172d049b8a | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `knapsack(weights, values, cap)` 0/1 knapsack maximum value.
--- solution.py (buggy) ---
def knapsack(weights, values, cap):
dp = [0] * (cap - 1)
for w, v in zip(weights, values):
for c in ... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 0, \"errors\": 1, \"skipped\": 0, \"passed\": false}\n\ntest_ks (test_solution.Test.test_ks) ... ERROR\n\n======================================================================\nERROR: test_ks (test_solution.Test... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def knapsack(weights, values, cap):
dp = [0] * (cap + 1)
for w, v in zip(weights, values):
for c in range(cap, w - 1, -1):
dp[c] = max(dp[c], dp[c - w] + v)
return dp[cap] | def knapsack(weights, values, cap):
dp = [0] * (cap + 1)
for w, v in zip(weights, values):
for c in range(cap, w - 1, -1):
dp[c] = max(dp[c], dp[c - w] + v)
return dp[cap] | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.35, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 3.9, "tests": 0.0, "total": 10.549999999999999}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"... |
or-coding-py-bfs-levels-5c27c81b563d | coding | code_generation | beginner | Implement `bfs_order(graph, start)` returning nodes in BFS order. graph maps
node -> iterable of neighbors. Skip missing neighbor keys. | {"language": "python", "repository": {"files": {"solution.py": "from collections import deque\n\ndef bfs_order(graph, start):\n seen = {start}\n q = deque([start])\n order = []\n while q:\n node = q.popleft()\n order.append(node)\n for nxt in graph.get(node, []):\n if nxt not... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from collections import deque
def bfs_order(graph, start):
seen = {start}
q = deque([start])
order = []
while q:
node = q.popleft()
order.append(node)
for nxt in graph.get(node, []):
if nxt not in seen:
seen.add(nxt)
q.append(nxt)
return order | from collections import deque
def bfs_order(graph, start):
seen = {start}
q = deque([start])
order = []
while q:
node = q.popleft()
order.append(node)
for nxt in graph.get(node, []):
if nxt not in seen:
seen.add(nxt)
q.append(nxt)
return order | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.loops | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.475, "tests": 0.0, "total": 3.7750000000000004}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0"... |
or-coding-py-interval-coverage-973204b58c0f | coding | code_generation | intermediate | Implement `covered_length(ranges)` total length covered by [start,end]
half-open intervals. Overlaps count once. | {"language": "python", "repository": {"files": {"solution.py": "def covered_length(ranges):\n if not ranges:\n return 0\n ordered = sorted(ranges)\n total = 0\n cs, ce = ordered[0]\n for s, e in ordered[1:]:\n if s > ce:\n total += ce - cs\n cs, ce = s, e\n else... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def covered_length(ranges):
if not ranges:
return 0
ordered = sorted(ranges)
total = 0
cs, ce = ordered[0]
for s, e in ordered[1:]:
if s > ce:
total += ce - cs
cs, ce = s, e
else:
ce = max(ce, e)
total += ce - cs
return total | def covered_length(ranges):
if not ranges:
return 0
ordered = sorted(ranges)
total = 0
cs, ce = ordered[0]
for s, e in ordered[1:]:
if s > ce:
total += ce - cs
cs, ce = s, e
else:
ce = max(ce, e)
total += ce - cs
return total | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.conditionals | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.55, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.125, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.3, "tests": 0.0, "total": 4.575}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "inter... |
or-coding-py-rate-limit-sliding-dfd9e3aba9b3 | coding | code_generation | beginner | Implement `SlidingWindow(limit, window)` with `allow(t)` where t is
non-decreasing time. At most `limit` events in (t-window, t]. | {"language": "python", "repository": {"files": {"solution.py": "from collections import deque\n\nclass SlidingWindow:\n def __init__(self, limit, window):\n self.limit = limit\n self.window = window\n self.q = deque()\n\n def allow(self, t):\n while self.q and self.q[0] <= t - self.win... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from collections import deque
class SlidingWindow:
def __init__(self, limit, window):
self.limit = limit
self.window = window
self.q = deque()
def allow(self, t):
while self.q and self.q[0] <= t - self.window:
self.q.popleft()
if len(self.q) >= self.limit:
return False
self.q.append(t)
return True | from collections import deque
class SlidingWindow:
def __init__(self, limit, window):
self.limit = limit
self.window = window
self.q = deque()
def allow(self, t):
while self.q and self.q[0] <= t - self.window:
self.q.popleft()
if len(self.q) >= self.limit:
return False
self.q.append(t)
return True | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.675, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.425, "tests": 0.0, "total": 4.2}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "rate_l... |
or-coding-py-debug-rate-limit-sliding-104b463756ae | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `SlidingWindow(limit, window)` with `allow(t)` where t is
non-decreasing time. At most `limit` events in (t-window, t].
--- solution.py (buggy) ---
from collections import deque
class Sliding... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_sw (test_solution.Test.test_sw) ... FAIL\n\n======================================================================\nFAIL: test_sw (test_solution.Test.t... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | from collections import deque
class SlidingWindow:
def __init__(self, limit, window):
self.limit = limit
self.window = window
self.q = deque()
def allow(self, t):
while self.q and self.q[0] <= t - self.window:
self.q.popleft()
if len(self.q) >= self.limit:
return False
self.q.append(t)
return True | from collections import deque
class SlidingWindow:
def __init__(self, limit, window):
self.limit = limit
self.window = window
self.q = deque()
def allow(self, t):
while self.q and self.q[0] <= t - self.window:
self.q.popleft()
if len(self.q) >= self.limit:
return False
self.q.append(t)
return True | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.675, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 3.675, "tests": 0.0, "total": 10.649999999999999}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details":... |
or-coding-py-base64-pad-5ba7bc4c7cea | coding | code_generation | beginner | Implement `b64_pad(s)` adding the correct `=` padding to a base64 string
without padding. Do not decode. | {"language": "python", "repository": {"files": {"solution.py": "def b64_pad(s):\n m = len(s) % 4\n if m == 1:\n raise ValueError(\"invalid\")\n if m:\n s += \"=\" * (4 - m)\n return s\n", "test_solution.py": "import unittest\nfrom solution import b64_pad\n\nclass Test(unittest.TestCase):\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def b64_pad(s):
m = len(s) % 4
if m == 1:
raise ValueError("invalid")
if m:
s += "=" * (4 - m)
return s | def b64_pad(s):
m = len(s) % 4
if m == 1:
raise ValueError("invalid")
if m:
s += "=" * (4 - m)
return s | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.4, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.75, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.4, "tests": 0.0, "total": 4.15}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "base64_p... |
or-coding-py-debug-base64-pad-9acf4723aaf4 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `b64_pad(s)` adding the correct `=` padding to a base64 string
without padding. Do not decode.
--- solution.py (buggy) ---
def b64_pad(s):
m = len(s) % 4
if m != 1:
raise ValueError("invali... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 0, \"errors\": 1, \"skipped\": 0, \"passed\": false}\n\ntest_pad (test_solution.Test.test_pad) ... ERROR\n\n======================================================================\nERROR: test_pad (test_solution.T... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | def b64_pad(s):
m = len(s) % 4
if m == 1:
raise ValueError("invalid")
if m:
s += "=" * (4 - m)
return s | def b64_pad(s):
m = len(s) % 4
if m == 1:
raise ValueError("invalid")
if m:
s += "=" * (4 - m)
return s | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:02Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.4, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 3.3, "tests": 0.0, "total": 10.0}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"err... |
or-coding-py-retry-predicate-827fb6f0d571 | coding | code_generation | beginner | Implement `retry(fn, retries, retry_on)` calling fn until it returns without
raising an exception in retry_on, up to retries+1 attempts. Re-raise the last. | {"language": "python", "repository": {"files": {"solution.py": "def retry(fn, retries, retry_on):\n last = None\n for _ in range(retries + 1):\n try:\n return fn()\n except retry_on as exc:\n last = exc\n raise last\n", "test_solution.py": "import unittest\nfrom solution imp... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def retry(fn, retries, retry_on):
last = None
for _ in range(retries + 1):
try:
return fn()
except retry_on as exc:
last = exc
raise last | def retry(fn, retries, retry_on):
last = None
for _ in range(retries + 1):
try:
return fn()
except retry_on as exc:
last = exc
raise last | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.exceptions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.575, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.5, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.55, "tests": 0.0, "total": 4.2250000000000005}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "... |
or-coding-py-ini-sections-c58ba9a266c7 | coding | code_generation | beginner | Implement `parse_ini(text)` returning dict[str, dict[str, str]] for
`[section]` and `key=value` lines. Ignore blanks and `;` comments. | {"language": "python", "repository": {"files": {"solution.py": "def parse_ini(text):\n data = {}\n section = None\n for raw in text.splitlines():\n line = raw.split(\";\", 1)[0].strip()\n if not line:\n continue\n if line.startswith(\"[\") and line.endswith(\"]\"):\n ... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | def parse_ini(text):
data = {}
section = None
for raw in text.splitlines():
line = raw.split(";", 1)[0].strip()
if not line:
continue
if line.startswith("[") and line.endswith("]"):
section = line[1:-1]
data.setdefault(section, {})
continue
if section is None or "=" not in line:
raise ValueError(line)
k, v... | def parse_ini(text):
data = {}
section = None
for raw in text.splitlines():
line = raw.split(";", 1)[0].strip()
if not line:
continue
if line.startswith("[") and line.endswith("]"):
section = line[1:-1]
data.setdefault(section, {})
continue
if section is None or "=" not in line:
raise ValueError(line)
k, v... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.625, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.4, "tests": 0.0, "total": 3.875}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "ini_s... |
or-coding-py-dag-longest-b3d7369135cf | coding | code_generation | intermediate | Implement `longest_path_dag(nodes, edges, weight)` where edges are (u,v)
and weight[(u,v)] is a number. Graph is DAG. Return the maximum path weight
(possibly a single node path of weight 0). | {"language": "python", "repository": {"files": {"solution.py": "from collections import defaultdict, deque\n\ndef longest_path_dag(nodes, edges, weight):\n graph = defaultdict(list)\n indeg = {n: 0 for n in nodes}\n for u, v in edges:\n graph[u].append(v)\n indeg[v] += 1\n dist = {n: 0 for n i... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from collections import defaultdict, deque
def longest_path_dag(nodes, edges, weight):
graph = defaultdict(list)
indeg = {n: 0 for n in nodes}
for u, v in edges:
graph[u].append(v)
indeg[v] += 1
dist = {n: 0 for n in nodes}
q = deque([n for n in nodes if indeg[n] == 0])
seen = 0
while q:
u = q.popleft()
see... | from collections import defaultdict, deque
def longest_path_dag(nodes, edges, weight):
graph = defaultdict(list)
indeg = {n: 0 for n in nodes}
for u, v in edges:
graph[u].append(v)
indeg[v] += 1
dist = {n: 0 for n in nodes}
q = deque([n for n in nodes if indeg[n] == 0])
seen = 0
while q:
u = q.popleft()
see... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.loops | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.775, "constraints": 1.4, "keywords": 0.0, "math_ops": 1.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.725, "tests": 0.0, "total": 5.1000000000000005}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", ... |
or-coding-py-debug-dag-longest-d96d6c083461 | coding | debugging | expert | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `longest_path_dag(nodes, edges, weight)` where edges are (u,v)
and weight[(u,v)] is a number. Graph is DAG. Return the maximum path weight
(possibly a single node path of weight 0).
--- soluti... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 0, \"errors\": 1, \"skipped\": 0, \"passed\": false}\n\ntest_lp (test_solution.Test.test_lp) ... ERROR\n\n======================================================================\nERROR: test_lp (test_solution.Test... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | from collections import defaultdict, deque
def longest_path_dag(nodes, edges, weight):
graph = defaultdict(list)
indeg = {n: 0 for n in nodes}
for u, v in edges:
graph[u].append(v)
indeg[v] += 1
dist = {n: 0 for n in nodes}
q = deque([n for n in nodes if indeg[n] == 0])
seen = 0
while q:
u = q.popleft()
see... | from collections import defaultdict, deque
def longest_path_dag(nodes, edges, weight):
graph = defaultdict(list)
indeg = {n: 0 for n in nodes}
for u, v in edges:
graph[u].append(v)
indeg[v] += 1
dist = {n: 0 for n in nodes}
q = deque([n for n in nodes if indeg[n] == 0])
seen = 0
while q:
u = q.popleft()
see... | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.775, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 11.075}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {"payload": {... |
or-coding-py-min-heap-k-1732990ad1d2 | coding | code_generation | beginner | Implement `k_smallest(nums, k)` returning the k smallest values sorted
ascending. k may be 0. If k > n, return all sorted. | {"language": "python", "repository": {"files": {"solution.py": "import heapq\n\ndef k_smallest(nums, k):\n if k <= 0:\n return []\n return sorted(heapq.nsmallest(min(k, len(nums)), nums))\n", "test_solution.py": "import unittest\nfrom solution import k_smallest\n\nclass Test(unittest.TestCase):\n def te... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | import heapq
def k_smallest(nums, k):
if k <= 0:
return []
return sorted(heapq.nsmallest(min(k, len(nums)), nums)) | import heapq
def k_smallest(nums, k):
if k <= 0:
return []
return sorted(heapq.nsmallest(min(k, len(nums)), nums)) | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.375, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.525, "tests": 0.0, "total": 3.5}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "min_he... |
or-coding-py-sha256-prefix-ac24cc8583f0 | coding | code_generation | beginner | Implement `constant_eq(a, b)` comparing two strings in time that depends
only on the length of the longer input (iterate zip_longest). Return True iff equal. | {"language": "python", "repository": {"files": {"solution.py": "from itertools import zip_longest\n\ndef constant_eq(a, b):\n diff = 0\n for x, y in zip_longest(a, b, fillvalue=None):\n diff |= (x != y)\n return not diff\n", "test_solution.py": "import unittest\nfrom solution import constant_eq\n\nclass... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | from itertools import zip_longest
def constant_eq(a, b):
diff = 0
for x, y in zip_longest(a, b, fillvalue=None):
diff |= (x != y)
return not diff | from itertools import zip_longest
def constant_eq(a, b):
diff = 0
for x, y in zip_longest(a, b, fillvalue=None):
diff |= (x != y)
return not diff | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.425, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.0, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.6, "tests": 0.0, "total": 3.625}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "sha256... |
or-coding-py-debug-sha256-prefix-c13add5c1824 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `constant_eq(a, b)` comparing two strings in time that depends
only on the length of the longer input (iterate zip_longest). Return True iff equal.
--- solution.py (buggy) ---
from itertools i... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_eq (test_solution.Test.test_eq) ... FAIL\n\n======================================================================\nFAIL: test_eq (test_solution.Test.t... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | from itertools import zip_longest
def constant_eq(a, b):
diff = 0
for x, y in zip_longest(a, b, fillvalue=None):
diff |= (x != y)
return not diff | from itertools import zip_longest
def constant_eq(a, b):
diff = 0
for x, y in zip_longest(a, b, fillvalue=None):
diff |= (x != y)
return not diff | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.425, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 3.425, "tests": 0.0, "total": 10.149999999999999}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details":... |
or-coding-py-log-level-filter-c471621f9dc2 | coding | code_generation | beginner | Implement `filter_logs(lines, min_level)` where each line starts with
DEBUG|INFO|WARN|ERROR. Levels increase in that order. Keep lines at or above min_level. | {"language": "python", "repository": {"files": {"solution.py": "ORDER = {\"DEBUG\": 0, \"INFO\": 1, \"WARN\": 2, \"ERROR\": 3}\n\ndef filter_logs(lines, min_level):\n threshold = ORDER[min_level]\n out = []\n for line in lines:\n lvl = line.split(\" \", 1)[0]\n if ORDER.get(lvl, -1) >= threshold:... | [] | ["Use only the Python standard library unless the prompt says otherwise.", "The hidden tests in test_solution.py must pass."] | [] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ["Read the specification", "Implement the function or class", "Satisfy the tests"] | ORDER = {"DEBUG": 0, "INFO": 1, "WARN": 2, "ERROR": 3}
def filter_logs(lines, min_level):
threshold = ORDER[min_level]
out = []
for line in lines:
lvl = line.split(" ", 1)[0]
if ORDER.get(lvl, -1) >= threshold:
out.append(line)
return out | ORDER = {"DEBUG": 0, "INFO": 1, "WARN": 2, "ERROR": 3}
def filter_logs(lines, min_level):
threshold = ORDER[min_level]
out = []
for line in lines:
lvl = line.split(" ", 1)[0]
if ORDER.get(lvl, -1) >= threshold:
out.append(line)
return out | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.functions | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 0.25, "observations": 0.0, "plan": 1.2000000000000002, "prompt_length": 0.5, "tests": 0.0, "total": 3.825}, "language": "python", "pipeline_version": "1.4.0", "schema_version": "1.4.0", "slug": "log_l... |
or-coding-py-debug-log-level-filter-da77656a8211 | coding | debugging | advanced | The following Python module fails its tests. Produce a corrected solution.py that preserves the intended behaviour.
Implement `filter_logs(lines, min_level)` where each line starts with
DEBUG|INFO|WARN|ERROR. Levels increase in that order. Keep lines at or above min_level.
--- solution.py (buggy) ---
ORDER = {"DEBUG"... | {"failure": {"command": "python harness.py", "output": "OPEN_REASON_RESULT {\"tests_run\": 1, \"failures\": 1, \"errors\": 0, \"skipped\": 0, \"passed\": false}\n\ntest_filter (test_solution.Test.test_filter) ... FAIL\n\n======================================================================\nFAIL: test_filter (test_sol... | ["Seeded mutation of the reference implementation."] | ["Do not weaken or delete tests", "Keep the public API"] | [] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ["Reproduce the failure", "Identify the defect", "Apply a minimal fix", "Re-run tests"] | ORDER = {"DEBUG": 0, "INFO": 1, "WARN": 2, "ERROR": 3}
def filter_logs(lines, min_level):
threshold = ORDER[min_level]
out = []
for line in lines:
lvl = line.split(" ", 1)[0]
if ORDER.get(lvl, -1) >= threshold:
out.append(line)
return out | ORDER = {"DEBUG": 0, "INFO": 1, "WARN": 2, "ERROR": 3}
def filter_logs(lines, min_level):
threshold = ORDER[min_level]
out = []
for line in lines:
lvl = line.split(" ", 1)[0]
if ORDER.get(lvl, -1) >= threshold:
out.append(line)
return out | {"command": "python harness.py", "compiler_version": null, "details": {"payload": {"errors": 0, "failures": 0, "passed": true, "skipped": 0, "tests_run": 1}, "timed_out": false}, "exit_code": null, "memory_mb": null, "method": "sandbox:subprocess", "passed": true, "result": "passed", "runtime_s": null, "runtime_version... | {"commit": null, "derived": false, "derived_from": null, "generated_at": "2026-08-19T02:05:03Z", "generator": "open_reason.generation.coding", "generator_version": "1.4.0", "license": "Apache License 2.0", "license_spdx": "Apache-2.0", "retrieved_at": null, "source": "open_reason.generation.coding", "source_id": null, ... | {"evidence_confidence": 0.617, "notes": [], "score_components": {"authority_score": 0.55, "community_score": 0.0, "cross_source_score": 0.0, "provenance_score": 1.0, "recency_score": 0.7, "verification_score": 1.0}, "tier": "S", "verification_method": "sandbox:python", "verified": true} | null | python.testing | null | ["task_generation", "difficulty_assignment", "verification", "knowledge_normalization"] | null | null | en | original | {"concept_id_inferred": true, "difficulty_score": {"code_size": 0.475, "constraints": 1.4, "keywords": 0.0, "math_ops": 3.0, "observations": 0.3, "plan": 1.6, "prompt_length": 4.0, "tests": 0.0, "total": 10.774999999999999}, "failure_verification": {"command": "python harness.py", "compiler_version": null, "details": {... |
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