Datasets:

abdullahashraf122
/

algomyth-code-generation-benchmark

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
Algorithm Name: string
Algorithm Type: string
Time Complexity: string
Space Complexity: string
Data Structure: string
Algorithm Paradigm: string
Input Requirement: string
Worst Case Complexity: string
Average Case Complexity: string
Best Case Complexity: string
Iterative/Recursive: string
Use Cases: string
Question: string
Input: string
Expected Output: string
Algorithm in Python: string
Python Code Snippet: string
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 2325
to
{'Algorithm Name': Value('string'), 'Algorithm Type': Value('string'), 'Time Complexity': Value('string'), 'Space Complexity': Value('string'), 'Data Structure': Value('string'), 'Algorithm Paradigm': Value('string'), 'Question': Value('string'), 'Input': Value('string'), 'Expected Output': Value('string'), 'Python Code Snippet': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 147, in get_rows_or_raise
                  return get_rows(
                      dataset=dataset,
                  ...<4 lines>...
                      column_names=column_names,
                  )
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 127, in get_rows
                  rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
                File "/src/services/worker/src/worker/utils.py", line 483, in safe_iter
                  yield from ds.decode(False) if ds.features else ds
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2951, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 547, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 220, in _generate_tables
                  yield Key(file_idx, batch_idx), self._cast_table(pa_table)
                                                  ~~~~~~~~~~~~~~~~^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/parquet/parquet.py", line 156, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              Algorithm Name: string
              Algorithm Type: string
              Time Complexity: string
              Space Complexity: string
              Data Structure: string
              Algorithm Paradigm: string
              Input Requirement: string
              Worst Case Complexity: string
              Average Case Complexity: string
              Best Case Complexity: string
              Iterative/Recursive: string
              Use Cases: string
              Question: string
              Input: string
              Expected Output: string
              Algorithm in Python: string
              Python Code Snippet: string
              -- schema metadata --
              pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 2325
              to
              {'Algorithm Name': Value('string'), 'Algorithm Type': Value('string'), 'Time Complexity': Value('string'), 'Space Complexity': Value('string'), 'Data Structure': Value('string'), 'Algorithm Paradigm': Value('string'), 'Question': Value('string'), 'Input': Value('string'), 'Expected Output': Value('string'), 'Python Code Snippet': Value('string')}
              because column names don't match

Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.

YAML Metadata Warning:The task_categories "text2text-generation" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Algomyth Code Generation Benchmark

Parent GitHub Repository: https://github.com/abdullah00ashraf/abdullah00ashraf
Ecosystem Documentation: Axiyon / Producttolaunch Catalog

Part of the Axiyon Intelligence / Producttolaunch Research Ecosystem.
Author: Abdullah Ashraf (@abdullahashraf122)
GitHub Ecosystem: https://github.com/abdullah00ashraf

Dataset Description

Algomyth is an algorithmic evaluation and synthetic prompt benchmark designed for evaluating LLM code-generation accuracy across searching, sorting, and discrete mathematical algorithms. It features 1,000 standard algorithmic challenge formulations paired with 1,000 varied prompt phrasings, expected complexity boundaries, input test cases, and reference Python implementations.

Features

Algorithm Name: e.g. Linear Search, Binary Search
Algorithm Type: Category (Searching, Sorting, Graph, DP)
Time & Space Complexity: Theoretical Big-O bounds ($O(n)$, $O(1)$)
Question / Prompt: Natural language user query prompt variations
Expected Output: Ground-truth evaluation result
Python Code Snippet: Canonical reference implementation

Usage

from datasets import load_dataset
dataset = load_dataset("abdullahashraf122/algomyth-code-generation-benchmark")
print(dataset["train"][0])

Downloads last month: -