{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"bigcodebench","formal_name":"BigCodeBench","introduction":"BigCodeBench poses 1,140 function-level tasks drawn across 139 libraries. It tests whether a model can compose several real APIs correctly rather than write one self-contained function.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://bigcode-bench.github.io/","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"b60efff0-f581-5d10-92db-7f7de4b6e16b","task_key":"default--v0~2e1~2e0~5fhf--b60efff0-f581-5d10-92db-7f7de4b6e16b","task_revision_id":"1","upstream_id":"","short_description":"BigCodeBench v0.1.0_hf b60efff0-f581-5d10-92db-7f7de4b6e16b","config":"default","split":"v0.1.0_hf","body":"{\"code_prompt\":\"import re\\nimport nltk\\nnltk.download('stopwords')\\nfrom nltk.corpus import stopwords\\nfrom textblob import TextBlob\\n# Constants\\nSTOPWORDS = set(stopwords.words('english'))\\ndef task_func(text):\\n\",\"complete_prompt\":\"import re\\nimport nltk\\nnltk.download('stopwords')\\n\\nfrom nltk.corpus import stopwords\\nfrom textblob import TextBlob\\n\\n# Constants\\nSTOPWORDS = set(stopwords.words('english'))\\n\\ndef task_func(text):\\n    \\\"\\\"\\\"\\n    Remove duplicate and stopwords from a string \\\"text.\\\"\\n    Then, analyze the sentiment of the text using TextBlob.\\n\\n    Parameters:\\n    - text (str): The text string to analyze.\\n\\n    Returns:\\n    - Sentiment: The sentiment of the text.\\n\\n    Requirements:\\n    - re\\n    - nltk.corpus.stopwords\\n    - textblob.TextBlob\\n\\n    Example:\\n    >>> text = \\\"The quick brown fox jumps over the lazy dog and the dog was not that quick to respond.\\\"\\n    >>> sentiment = task_func(text)\\n    >>> print(sentiment)\\n    Sentiment(polarity=0.13888888888888887, subjectivity=0.6666666666666666)\\n    \\\"\\\"\\\"\\n\",\"entry_point\":\"task_func\",\"instruct_prompt\":\"Remove duplicate and stopwords from a string \\\"text.\\\" Then, analyze the sentiment of the text using TextBlob.\\nThe function should output with:\\n    Sentiment: The sentiment of the text.\\nYou should write self-contained code starting with:\\n```\\nimport re\\nimport nltk\\nnltk.download('stopwords')\\nfrom nltk.corpus import stopwords\\nfrom textblob import TextBlob\\n# Constants\\nSTOPWORDS = set(stopwords.words('english'))\\ndef task_func(text):\\n```\",\"libs\":\"['nltk', 'textblob', 're']\"}","display_format":"code","language":"","answer_status":"published","assets":[],"source_url":"https://bigcode-bench.github.io/","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}