我目前正在研究家庭作业分配，其中我必须编写一个函数，该功能可以计算文本文件的每条唯一行的SHA-256哈希码，并将这些哈希码的HEX Digests转换为整数。我设法使用了代码来实现这一目标，但是有一个额外的信用条款，我想见面，我不确定如何实施：

Question

import matplotlib.pyplot as plt
import hashlib

def file_processing_function(file_path):

    unique_lines = set()

    with open (file_path, 'r') as f:
        for line in f:
            unique_lines.add(line.rstrip())
        return unique_lines

def sha256_calc(line):
    
    m = hashlib.sha256(line.encode('utf-8'))
    return m.hexdigest()

def sha256_to_int(hex_digest):
    
     return int(hex_digest, 16)

def file_processing(file_path):
    
    unique_lines = file_processing_function(file_path)

    results = []
    for line in unique_lines:
        hex_digest = sha256_calc(line)
        integer_value = sha256_to_int(hex_digest)
        results.append((line, hex_digest, integer_value))

    return results

def printer(results):
    for line, hex_digest, integer_value in results:
        print(f'Line: {line} \n SHA-256: {hex_digest} \n Int:{integer_value}\n')

def plot_histogram(results, bins = 20):
    
    integer_values = [int(integer_value) for _, _, integer_value in results if isinstance(integer_value, int)]

    plt.figure(figsize=(10, 6))
    plt.hist(integer_values, bins = bins, color = 'purple', edgecolor = 'black')
    plt.title(f'Histogram Based on SHA-256 of {file_path}')
    plt.xlabel('Integer Values')
    plt.ylabel('Frequency')
    plt.grid(axis='y', linestyle='--', linewidth=0.7, alpha=0.7)
    plt.show()

file_path= 'wordcount.txt'
results = file_processing(file_path)
printer(results)
plot_histogram(results, bins = 20)

这是我到目前为止所拥有的，但是该代码正在带回typeerror

Traceback (most recent call last):
  File "c:\Users\serle\OneDrive\Desktop\Pyprojects\Hash Reader\Hash Reader Sha-256.py", line 53, in <module>
    plot_histogram(results, bins = 20)
  File "c:\Users\serle\OneDrive\Desktop\Pyprojects\Hash Reader\Hash Reader Sha-256.py", line 43, in plot_histogram
    plt.hist(integer_values, bins = bins, color = 'purple', edgecolor = 'black')
  File "C:\Users\serle\AppData\Local\Programs\Python\Python312\Lib\site-packages\matplotlib\pyplot.py", line 3440, in hist
    return gca().hist(
           ^^^^^^^^^^^
  File "C:\Users\serle\AppData\Local\Programs\Python\Python312\Lib\site-packages\matplotlib\__init__.py", line 1473, in inner
    return func(
           ^^^^^
  File "C:\Users\serle\AppData\Local\Programs\Python\Python312\Lib\site-packages\matplotlib\axes\_axes.py", line 7001, in hist
    m, bins = np.histogram(x[i], bins, weights=w[i], **hist_kwargs)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\serle\AppData\Local\Programs\Python\Python312\Lib\site-packages\numpy\lib\_histograms_impl.py", line 797, in histogram
    bin_edges, uniform_bins = _get_bin_edges(a, bins, range, weights)
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\serle\AppData\Local\Programs\Python\Python312\Lib\site-packages\numpy\lib\_histograms_impl.py", line 430, in _get_bin_edges
    first_edge, last_edge = _get_outer_edges(a, range)
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\serle\AppData\Local\Programs\Python\Python312\Lib\site-packages\numpy\lib\_histograms_impl.py", line 314, in _get_outer_edges
    if not (np.isfinite(first_edge) and np.isfinite(last_edge)):
            ^^^^^^^^^^^^^^^^^^^^^^^
TypeError: ufunc 'isfinite' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''

我对matplotlib不太好，有什么想法吗？

def plot_histogram(results, file_path, bins=20):

    integer_values = []
    for _, _, integer_value in results:
        try:

            integer_value = int(integer_value)
            if np.isfinite(integer_value):
                integer_values.append(integer_value)
        except (ValueError, TypeError):
            continue  # Skip if the value is not a valid integer
    
    plt.figure(figsize=(10, 6))
    plt.hist(integer_values, bins=bins, color='purple', edgecolor='black')
    plt.title(f'Histogram Based on SHA-256 of {file_path}')
    plt.xlabel('Integer Values')
    plt.ylabel('Frequency')
    plt.grid(axis='y', linestyle='--', linewidth=0.7, alpha=0.7)
    plt.show()

这很可能会起作用：

通向

Answer 1

函数明确函数，以使标题动态创建。

也在

plot_histogram()

转换周围添加了一个

try-except

块，以确保每个值都转换为
1. integer_value

   并检查

   int