帮我写出具体实现过程代码

好的，以下是一个更为详细的 Python 实现过程代码，包括读取学校信息、计算学校评分、根据评分排序、输出预测结果等过程：

# 读取学校信息
def read_school_info():
    # 从文件中读取学校信息
    with open('schools.txt', 'r', encoding='utf-8') as f:
        lines = f.readlines()
        schools = []
        for line in lines:
            fields = line.strip().split(',')
            name = fields[0]
            city = fields[1]
            low_score = float(fields[2])
            plan = int(fields[3])
            feature = fields[4]
            school = {'name': name, 'city': city, 'low_score': low_score, 'plan': plan, 'feature': feature}
            schools.append(school)
    return schools

# 计算学校评分
def calculate_score(school, score):
    # 计算学校评分，这里使用加权平均分计算
    # 其中，录取分数线的权重为 0.6，招生计划的权重为 0.3，特色的权重为 0.1
    score_line_weight = 0.6
    plan_weight = 0.3
    feature_weight = 0.1
    score_line_score = (school['low_score'] - score) / school['low_score'] * 100 * score_line_weight
    plan_score = school['plan'] * plan_weight
    feature_score = 0
    if school['feature'] == '艺术生':
        feature_score = 10 * feature_weight
    elif school['feature'] == '体育生':
        feature_score = 5 * feature_weight
    total_score = score_line_score + plan_score + feature_score
    return total_score

# 根据评分对学校进行排序
def sort_schools(schools):
    # 根据评分对学校进行排序
    sorted_schools = sorted(schools, key=lambda x: x['score'], reverse=True)
    return sorted_schools

# 输出预测结果
def output_result(sorted_schools):
    # 输出前 5 个预测结果
    print('根据您的考试成绩，您有可能被以下学校录取：')
    for i in range(5):
        school = sorted_schools[i]
        print('{} - {} - {} - {}'.format(school['name'], school['city'], school['score'], school['feature']))

# 用户输入成绩
score = float(input("请输入您的考试分数："))

# 读取学校信息
schools = read_school_info()

# 计算学校评分
for school in schools:
    school['score'] = calculate_score(school, score)

# 根据评分排序
sorted_schools = sort_schools(schools)

# 输出预测结果
output_result(sorted_schools)

在这个实现过程中，我们假设学校信息存储在一个文本文件 `schools.txt` 中，每一行包含学校名称、所在城市、录取分数线、招生计划和特色等信息，用逗号进行分割。同时，我们使用加权平均分计算学校评分，根据录取分数线、招生计划和特色三个因素进行评分。最后，我们输出前 5 个预测结果，包括学校名称、所在城市、评分和特色等信息。