syntax-error.json

[
 "\n{'code': 'count = sum(int_list)'}",
 "\n{'code': 'count = 0\\nfor i in int_list:\\n    count += i'}",
 "\n{'code': 'import numpy as np\\ncount = np.sum(int_list)'}",
 "\n{'code': 'def sum_int_list(int_list):\\n    count = 0\\n    for i in int_list:\\n        count += i\\n    return count\\n\\ncount = sum_int_list(int_list)'}",
 "\n{'code': 'def get_count(int_list):\\n    count = 0\\n    for i in int_list:\\n        count += i\\n    return count\\n\\ncount = get_count(int_list)'}",
 "\n{'code': 'from functools import reduce\\ncount = reduce(lambda x, y: x + y, int_list)'}",
 "\n{'code': '\\ndef sum_list(int_list):\\n  count = 0\\n  for i in int_list:\\n    count += i\\n  return count\\n\\ncount = sum_list(int_list)'}",
 "\n{'code': 'count = 0\\nfor (index, value) in enumerate(int_list):\\n    count += value\\nif count == 3:\\n', 'level': 'beginner', 'explanation': 'A beginner might be familiar with iterating over a list and adding the elements to a running total.'}",
 "\n{'code': 'count = sum(int_list)\\nif count == 3:\\n', 'level': 'intermediate', 'explanation': 'An intermediate programmer might be familiar with the `sum()` function.'}",
 "\n{'code': 'assert sum(int_list) == 3\\nif count == 3:\\n', 'level': 'expert', 'explanation': 'An expert programmer might use an assertion to check the value of the running total before continuing.'}",
 "\n{'code': 'count = 0\\nfor x in int_list:\\n    count += x\\nif count == 3:\\n', 'level': 'beginner', 'explanation': ''}",
 "\n{'code': 'import numpy as np\\ncount = np.sum(int_list)\\nif count == 3:\\n', 'level': 'intermediate', 'explanation': 'Import the `numpy` library and use the `np.sum()` function to calculate the sum of the list.'}",
 "\n{'code': 'import functools\\ncount = functools.reduce(lambda a, b: a + b, int_list)\\nif count == 3:\\n', 'level': 'expert', 'explanation': 'Use the `functools.reduce()` function to calculate the sum of the list.'}",
 "\n{'code': 'count = sum(int_list)', 'type': 'beginner'}",
 "\n{'code': 'import numpy as np\\ncount = np.sum(int_list)', 'type': 'intermediate'}",
 "\n{'code': 'from itertools import accumulate\\ncount = list(accumulate(int_list))[-1]', 'type': 'expert'}",
 "\n{'code': '\\ncount = 0\\nfor x in int_list:\\n    count += x\\n'}",
 "\n{'code': '\\ncount = sum(int_list)\\n'}",
 "\n{'code': '\\nimport math\\ncount = math.fsum(int_list)\\n'}",
 "\n{'code': '\\nfrom collections import Counter\\ncount = Counter(int_list).most_common()[0][1]\\n'}",
 "\n{'code': '\\nfrom functools import reduce\\ncount = reduce(lambda x, y: x + y, int_list)\\n'}",
 "\n{'code': 'count = sum(int_list)', 'explanation': 'This is a one-liner that uses the built-in `sum` function to calculate the sum of the elements in the `int_list`.', 'level': 'beginner'}",
 "\n{'code': 'count = 0\\nfor value in int_list:\\n    count += value', 'explanation': 'This is a more explicit version of the first example, which uses a `for` loop to iterate over the elements in the `int_list` and add each element to the `count` variable.', 'level': 'intermediate'}",
 "\n{'code': 'from functools import reduce\\ncount = reduce(lambda x, y: x + y, int_list)', 'explanation': 'This is an example using the `reduce` function from the `functools` library. The `reduce` function takes a function and an iterable as arguments, and applies the function to each element in the iterable, reducing the iterable to a single value.', 'level': 'expert'}",
 "\n{'code': 'def count_func(int_list):\\n    count = sum(int_list)\\n    return count\\ncount = count_func(int_list)'}",
 "\n{'code': 'count = 0\\nfor (index, value) in enumerate(int_list):\\n    count += value'}",
 "\n{'code': 'count = 0\\nfor value in int_list:\\n    count += value'}",
 "\n{'code': 'count = 0\\nwhile int_list:\\n    count += int_list.pop()'}",
 "\n{'code': 'def check(int_list): \\n    return sum(int_list) * sum(int_list) - sum(map(lambda x: x*x, int_list)) == 0', 'type': 'expert'}",
 "\n{'code': 'def check(int_list):\\n    result = 0\\n    for item in int_list:\\n        result += item**2\\n    return result - sum(int_list)**2 == 0', 'type': 'intermediate'}",
 "\n{'code': 'def check(int_list):\\n    return sum(map(lambda x: x * x, int_list)) == sum(int_list)**2', 'type': 'beginner'}",
 "\n{'code': 'count = int_list.count(int_list[0])', 'type': 'beginner'}",
 "\n{'code': 'count = sum(int_list)', 'type': 'intermediate'}",
 "\n{'code': 'count = itertools.accumulate(int_list)[-1]', 'type': 'expert'}",
 "\n{'code': '\\ncount=sum(int_list)\\n'}",
 "\n{'code': '\\nimport numpy as np\\ncount=np.sum(int_list)\\n'}",
 "\n{'code': '\\ndef compute_sum(arr):\\n    count = 0\\n    for val in arr:\\n        count += val\\n    return count\\n\\ncount = compute_sum(int_list)\\n'}",
 "\n{'code': '\\ncount = 0\\nfor (index, val) in enumerate(int_list):\\n    count += val\\n'}",
 "\n{'code': '\\ncount = sum(int_list)\\nif int(math.sqrt(sum(int_list))) == count + sum(int_list):\\n    print(\"true\")\\nelse:\\n    print(\"false\")\\n'}",
 "\n{'import numpy as np', 'count = np.sum(int_list)'}",
 "\n{'import functools', 'count = functools.reduce(lambda x,y: x + y, int_list)'}",
 "\n{'count': 0}",
 "\n['count = 0\\nfor i in range(len(int_list)):\\n    count += int_list[i]']",
 "\n['count = functools.reduce(lambda x, y: x + y, int_list)']",
 "\n['count = sum(int_list)']",
 "\n{'code': 'for i in range(len(int_list)): \\n  count += int_list[i]'}",
 "\n{'code': 'from collections import Counter\\ncount = Counter(int_list).most_common(1)[0][1]'}",
 "\n{'code': 'from itertools import accumulate\\ncount = list(accumulate(int_list))[-1]'}",
 "\n{'code': 'import operator\\ncount = reduce(operator.add, int_list)'}",
 "\n{'code': 'count = 0\\nfor value in int_list:\\n    count += value', 'type': 'beginner'}",
 "\n{'code': 'import functools\\ncount = functools.reduce(lambda x,y: x+y, int_list)', 'type': 'intermediate'}",
 "\n{'code': 'def sum_list(int_list):\\n    return sum(int_list)\\ncount = sum_list(int_list)', 'type': 'expert'}",
 "\n{'code': 'count = 0\\nfor item in int_list:\\n    count += item', 'type': 'beginner'}",
 "\n{'code': 'count = functools.reduce(lambda a, b: a + b, int_list)', 'type': 'intermediate'}",
 "\n{'code': 'count = sum(int_list)', 'type': 'expert'}",
 "\n{'code': 'count = sum(int_list)', 'explanation': 'A simple one-liner to calculate sum of a list'}",
 "\n{'code': 'import numpy as np\\ncount = np.sum(int_list)', 'explanation': \"Using numpy's sum function to calculate sum of a list\"}",
 "\n{'code': 'count = 0\\nfor value in int_list:\\n    count += value', 'explanation': 'A more verbose version of the first code snippet'}",
 "\n{'code': 'count = 0\\nfor index, value in enumerate(int_list):\\n    count += value', 'explanation': 'A more verbose version of the second code snippet'}",
 "\n{'code': 'from functools import reduce\\ncount = reduce(lambda x, y: x + y, int_list)', 'explanation': \"Using functools' reduce function to calculate sum of a list\"}",
 "\n{'code': '\\ndef sum(lst):\\n    count = 0\\n    for value in lst:\\n        count += value\\n    return count\\ncount = sum(int_list)\\n'}",
 "\n{'code': '\\ncount = 0\\nfor value in int_list:\\n    count += value\\n'}",
 "\n{'code': '\\nfrom functools import reduce\\ncount = reduce(lambda a, b: a + b, int_list)\\n'}",
 "\n{'code': '\\nfrom itertools import accumulate\\ncount = list(accumulate(int_list))[-1]\\n'}",
 "\n{'code': '\\nimport numpy as np\\ncount = np.sum(int_list)\\n'}",
 "\n{'code': '\\nimport pandas as pd\\ncount = pd.Series(int_list).sum()\\n'}",
 "\n{'code': 'import numpy as np\\ncount = np.sum(int_list)', 'type': 'expert', 'imports': ['numpy']}",
 "\n{'code': 'count = 0\\nfor value in int_list:\\n    count += value', 'type': 'beginner', 'imports': []}",
 "\n{'code': 'count = sum(int_list)', 'type': 'intermediate', 'imports': []}",
 "\n{'code': 'import statistics\\ncount = statistics.mode(int_list)'}",
 "\n{'code': 'count = int_list[0]'}",
 "\n{'code': 'import numpy as np\\ncount = np.std(int_list)', 'type': 'beginner', 'imports': ['numpy']}",
 "\n{'code': 'count = statistics.pstdev(int_list)', 'type': 'intermediate', 'imports': ['statistics']}",
 "\n{'code': 'count = math.sqrt(sum([(x - mean)**2 for x in int_list]) / (len(int_list) - 1))', 'type': 'expert', 'imports': []}",
 "\n{'code': 'count = sum(map(int, int_list))', 'type': 'beginner'}",
 "\n{'code': 'count = 0\\nfor i in int_list:\\n    count += i', 'type': 'intermediate'}",
 "\n{'code': 'import functools\\ncount = functools.reduce(lambda x, y: x + y, int_list)', 'type': 'expert'}",
 "\n{'code': 'import numpy as np\\ncount=np.sum(int_list)', 'type': 'expert', 'imports': ['numpy']}",
 "\n{'code': 'count = 0\\nfor value in int_list:\\n    count += value', 'type': 'intermediate', 'imports': []}",
 "\n{'code': 'count = int_list[0]\\nfor value in int_list[1:]:\\n    count += value', 'type': 'beginner', 'imports': []}",
 "\n{'code': 'count = 0\\nfor i in int_list:\\n    count += i', 'type': 'beginner'}",
 "\n{'code': 'count = functools.reduce(lambda x, y: x + y, int_list, 0)', 'type': 'intermediate'}",
 "\n{'code': 'import numpy as np\\ncount = np.sum(int_list)', 'type': 'expert'}",
 "\n{'code': 'count = sum(int_list) if int_list else 0', 'type': 'beginner'}",
 "\n{'code': 'count = 0\\nfor value in int_list:\\n    count += value', 'type': 'intermediate'}",
 "\n{'code': 'from functools import reduce\\ncount = reduce(lambda x, y: x + y, int_list)', 'type': 'expert'}",
 "\n{'code': 'sum(int_list)'}",
 "\n{'code': '\\ncount = 0\\nfor i in range(len(int_list)):\\n    count += int_list[i]\\n'}",
 "\n{'code': 'sum(int_list)', 'type': 'expert'}",
 "\n{'code': 'count = int_list[0] + sum(int_list[1:])', 'type': 'beginner'}",
 "\n{'code': 'count = 0\\nfor elem in int_list:\\n    count += elem', 'type': 'intermediate'}",
 "\n{'code': 'def count(arr):\\n    return sum(arr)\\ncount = count(int_list)', 'type': 'expert'}",
 "\n{'code': 'import math\\ncount = math.fsum(int_list)', 'type': 'expert'}",
 "\n{'code': 'count = 0\\nfor i in int_list:\\n    count+=i', 'type': 'beginner'}",
 "\n{'code': 'import numpy as np\\ncount=np.sum(int_list)', 'type': 'intermediate'}",
 "\n{'code': 'def calculate_count(int_list):\\n  result=0\\n  for i in int_list:\\n    result+=i\\n  return result\\ncount = calculate_count(int_list)', 'type': 'expert'}",
 "\n{'code': 'count = sum(int_list)', 'type': 'beginner', 'comments': 'Sum all values of int_list in a single statement.'}",
 "\n{'code': 'count = 0\\nfor val in int_list:\\n    count += val', 'type': 'intermediate', 'comments': 'Sum all values of int_list using a for loop.'}",
 "\n{'code': 'count = functools.reduce(lambda a, b: a + b, int_list)', 'type': 'expert', 'comments': 'Use functools.reduce to efficiently sum all values of int_list.'}",
 "\n{'count': 10, 'int_list': [1, 2, 3, 4, 5]}",
 "\n{'code': 'int_list = list(map(int, int_list))\\ncount = sum(int_list)'}",
 "\n{'code': 'from functools import reduce\\ncount = reduce(lambda x,y: x+y, int_list)'}",
 "\n{'code': 'from operator import add\\ncount = reduce(add, int_list)'}",
 "\n{'code': 'for i in int_list: count += i', 'type': 'beginner'}",
 "\n{'code': 'sum(int_list)', 'type': 'intermediate'}",
 "\n{'code': 'count = 0\\nfor num in int_list:\\n    count += num'}",
 "\n{'code': 'count = functools.reduce(lambda x, y: x + y, int_list)'}",
 "\n{'code': 'count = int_list.sum()'}",
 "\n{'code': 'count = 0\\nfor item in int_list:\\n    count += item'}",
 "\n{'code': 'def count_sum(int_list):\\n    return sum(int_list)'}",
 "\n{'code': 'def count_sum(int_list):\\n    count = 0\\n    for i in int_list:\\n        count += i\\n    return count'}",
 "\n{'code': 'def count_sum(int_list):\\n    return len(int_list)*sum(int_list)'}",
 "\n{'code': 'def count_sum(int_list):\\n    count = 0\\n    for i in range(len(int_list)):\\n        count += int_list[i]\\n    return count'}",
 "\n{'code': 'from functools import reduce\\ncount = reduce(lambda x, y: x + y, int_list)', 'type': 'intermediate'}",
 "\n{'code': \"\\n            if __name__ == '__main__':\\n                count = sum(int_list)\\n                print(count)\\n            \", 'type': 'expert'}",
 "\n{'code': 'def count_sum(int_list):\\n    return sum(int_list)', 'type': 'expert', 'imports': []}",
 "\n{'code': 'def count_sum(int_list):\\n    return list(map(sum, int_list))[0]', 'type': 'expert', 'imports': []}",
 "\n{'code': 'def count_sum(int_list):\\n    return int(sum(int_list))', 'type': 'expert', 'imports': []}",
 "\n{'code': 'from statistics import mean\\ndef count_sum(int_list):\\n    return mean(int_list)', 'type': 'intermediate', 'imports': ['statistics']}",
 "\n{'code': 'def count_sum(int_list):\\n    temp_sum = 0\\n    for i in range(len(int_list)):\\n        temp_sum += int_list[i]\\n    return temp_sum', 'type': 'beginner', 'imports': []}",
 "\n{'code': 'import numpy as np\\ncount=np.sum(int_list)', 'type': 'expert'}",
 "\n{'code': 'count = 0\\nfor (index, value) in enumerate(int_list):\\n    count += value', 'type': 'intermediate'}",
 "\n{'code': 'for (index, value) in enumerate(int_list):\\n    count += 1', 'type': 'beginner'}"
]