Solution #57393d9b-59e2-47b2-8b3e-e09cbb074c22

failed

Score

0% (0/5)

Runtime

56μs

Delta

-100.0% vs parent

-100.0% vs best

Regression from parent

Solution Lineage

Current0%Regression from parent
4a9c0ecb39%Regression from parent
5308c74564%Regression from parent
5a97585772%Improved from parent
5266c9ec0%Regression from parent
da617b596%Regression from parent
06ed21e748%Improved from parent
b618404727%Regression from parent
35f1acec41%Regression from parent
aacb270845%Improved from parent
44170f1439%Improved from parent
d4a144706%Regression from parent
ac75ae0340%Regression from parent
5d1898f963%Improved from parent
669949f251%Regression from parent
cdf35bb558%Improved from parent
1c6ceef237%Regression from parent
a48275e057%Improved from parent
b6016c2857%Improved from parent
5fad927440%Regression from parent
cb4d87e147%Improved from parent
7f265cec45%Improved from parent
2143671f19%Improved from parent
c0d68d5c0%Regression from parent
ae54b0ca54%Regression from parent
e0f66b5554%Improved from parent
465e93a245%Regression from parent
73be1f5e49%Improved from parent
dd5155da19%Improved from parent
a9d69e700%Regression from parent
63acaad058%Improved from parent
1265a3fc48%Improved from parent
693a4dda33%Regression from parent
d5bf925948%Regression from parent
48e560c749%Improved from parent
78afbd2538%Improved from parent
f0098ec50%Same as parent
bb8caee80%Regression from parent
ce53db5152%Improved from parent
9e6f727542%Improved from parent
2c6b742934%Regression from parent
223a455254%Improved from parent
4a54e07352%Improved from parent
99326a1432%Improved from parent
d8629f4919%Regression from parent
0deb287347%Improved from parent
e4b007c347%Improved from parent
32b7128c43%Regression from parent
f209f80655%Improved from parent
9161b31714%Regression from parent
9ab0f66324%Improved from parent
110fbd0b0%Regression from parent
e3d01a5c52%Improved from parent
c6fc252643%Regression from parent
23b4491152%Improved from parent
03aea6db43%Regression from parent
5f1a15ce53%Improved from parent
f22b171153%Same as parent
7b6d9f0953%Improved from parent
0401f74f12%Regression from parent
b96fbcb340%Improved from parent
84cc9d0420%First in chain

Code

def solve(input):
    data = input.get("data", "")
    if not isinstance(data, str) or len(data) == 0:
        return 999.0

    # Implement a simple dictionary-based compression algorithm
    def dictionary_compress(s):
        dictionary = {}
        output = []
        current_substring = ''
        max_dict_size = 256

        for char in s:
            new_substring = current_substring + char
            if new_substring in dictionary:
                current_substring = new_substring
            else:
                if current_substring:
                    output.append(dictionary[current_substring])
                else:
                    output.append(ord(char))
                if len(dictionary) < max_dict_size:
                    dictionary[new_substring] = len(dictionary) + 1
                current_substring = char

        if current_substring:
            if current_substring in dictionary:
                output.append(dictionary[current_substring])
            else:
                output.append(ord(current_substring))

        return output

    def dictionary_decompress(compressed):
        dictionary = {}
        output = []
        current_substring = ''
        inverse_dictionary = {v: k for k, v in dictionary.items()}

        for code in compressed:
            if code in inverse_dictionary:
                entry = inverse_dictionary[code]
            else:
                entry = current_substring + current_substring[0]

            output.append(entry)
            if current_substring:
                new_entry = current_substring + entry[0]
                if len(dictionary) < 256:
                    dictionary[new_entry] = len(dictionary) + 1

            current_substring = entry

        return ''.join(output)

    compressed_data = dictionary_compress(data)
    decompressed_data = dictionary_decompress(compressed_data)

    if decompressed_data != data:
        return 999.0

    original_size = len(data) * 8  # in bits (assuming 8 bits per character)
    compressed_size = len(compressed_data) * 8  # assuming each code is stored in 8 bits

    return compressed_size / float(original_size)