代码段不是JSON;最值得注意的是，JSON使用双引号"而不是单引号';但是更重要的是，包含用户数据的各个字典需要全部被安排到一个序列中（如下面的列表中）。

people = [
  {'address': '01261 Cameron Spring\nTaylorfurt, AK 97791', 'id': 35193, 'jobs': ['Energy engineer', 'Engineer, site', 'Environmental health practitioner', 'Biomedical scientist', 'Jewellery designer'], 'mail': 'jsalazar@gmail.com', 'name': 'Lindsey Nguyen', 'sex': 'F', 'username': 'uhebert'},
  {'address': '66992 Welch Brooks\nMarshallshire, ID 56004', 'id': 91970, 'jobs': ['Music therapist', 'Volunteer coordinator', 'Designer, interior/spatial'], 'mail': 'bhudson@gmail.com', 'name': 'Cheryl Lewis', 'sex': 'F', 'username': 'vickitaylor'},
  {'address': 'Unit 1632 Box 2971\nDPO AE 23297', 'id': 1848091, 'jobs': ['Management consultant', 'Engineer, structural', 'Lecturer, higher education', 'Theatre manager', 'Designer, textile'], 'mail': 'darren44@yahoo.com', 'name': 'Julia Allen', 'sex': 'F', 'username': 'sheilaadams'},
  {'address': '9880 Michelle Bridge\nNew Kimberlybury, WY 02583', 'id': 50969, 'jobs': ['Mechanical engineer', 'Retail banker', 'Barrister'], 'mail': 'stevensonsarah@hotmail.com', 'name': 'Gina Stevens', 'sex': 'F', 'username': 'nicole82'},
  {'address': '9080 Monica Crescent Suite 820\nNorth Deanbury, HI 28977', 'id': 676820, 'jobs': ['Network engineer', 'Youth worker', 'Primary school teacher', 'Engineer, broadcasting (operations)'], 'mail': 'denise42@gmail.com', 'name': 'Nicholas Harrington', 'sex': 'M', 'username': 'jean67'},
  {'address': '635 Kenneth Ways Suite 172\nHancockfort, AZ 50544', 'id': 64918, 'jobs': ['Designer, ceramics/pottery', 'Engineer, energy', 'Engineer, manufacturing'], 'mail': 'monique02@hotmail.com', 'name': 'Allison Gomez', 'sex': 'F', 'username': 'james67'}
]

[If如果您不确定该如何回答，您应该编辑问题以关注该问题，或者（最好）发布一个新问题。确保解释数据当前的格式。]
一旦你有了字典序列people，就有很多方法可以组成你的 * { job: [list of 'username', who has this job title in json data] } * 字典。
您可以使用.setdefault的嵌套for循环，如下所示：

job_people = {}
for p in people:
    for j in p['jobs']:
        job_people.setdefault(j, [])
        job_people[j].append(p['username'])

或者您可以使用dictionary comprehension：

jobs = {j for p in people for j in p['jobs']} ## list of unique job titles
job_people = {j: [u['username'] for u in people if j in u['jobs']] for j in jobs}

您可以在一条语句中完成（使用 * job_people = {j: [u['username'] for u in people if j in u['jobs']] for p in people for j in p['jobs']}），但是每个列表（[u['username'] for u in people if j in u['jobs']] *）只构建一次效率更高。
这对示例数据来说并没有太大的影响-因为每个职位似乎只出现一次。[因此每个列表只包含一个人/用户名...]使用上述方法之一，job_people [根据示例数据构建]应该如下所示

{'Energy engineer': ['uhebert'],
 'Engineer, site': ['uhebert'],
 'Environmental health practitioner': ['uhebert'],
 'Biomedical scientist': ['uhebert'],
 'Jewellery designer': ['uhebert'],
 'Music therapist': ['vickitaylor'],
 'Volunteer coordinator': ['vickitaylor'],
 'Designer, interior/spatial': ['vickitaylor'],
 'Management consultant': ['sheilaadams'],
 'Engineer, structural': ['sheilaadams'],
 'Lecturer, higher education': ['sheilaadams'],
 'Theatre manager': ['sheilaadams'],
 'Designer, textile': ['sheilaadams'],
 'Mechanical engineer': ['nicole82'],
 'Retail banker': ['nicole82'],
 'Barrister': ['nicole82'],
 'Network engineer': ['jean67'],
 'Youth worker': ['jean67'],
 'Primary school teacher': ['jean67'],
 'Engineer, broadcasting (operations)': ['jean67'],
 'Designer, ceramics/pottery': ['james67'],
 'Engineer, energy': ['james67'],
 'Engineer, manufacturing': ['james67']}

挑选数据

• 必须使用pickle完成，然后保存为名为“job_people.pickle”的文件 *

一旦你有了job_people字典，你可以用pickle.dump将它保存到“job_people.pickle”中，就像这样：

# import pickle
with open('ob_people.pickle', 'wb') as fp:
    pickle.dump(job_people, fp)

顺便说一句，如果你想把职业列表缩减到更一般的职位，你可以使用字典（比如 * {'Primary school teacher': Teacher', 'Engineer, energy': 'Engineer',....} *）和.get(j,j)，或者定义一个函数，比如

def generalize_job(job_title:str):
    titles_ref = {
        'engineer': ['engineer'], 
        'designer': ['design'],
        'educator': ['educat', 'teach']
    }
    for title, keywords in titles_ref.items():
        for kw in keywords:
            if kw.lower() in job_title.lower(): return title.title() 
    return job_title ## default: return the original string

并在for循环中使用它

job_people = {}
for p in people:
    for j in p['jobs']:
        j = generalize_job(j)
        if p['username'] in job_people.setdefault(j, []): continue
        job_people[j].append(p['username'])

得到job_people，如下所示：

{ 'Engineer': ['uhebert', 'sheilaadams', 'nicole82', 'jean67', 'james67'],
  'Designer': ['uhebert', 'vickitaylor', 'sheilaadams', 'james67'],
  'Educator': ['sheilaadams', 'jean67'],
  'Volunteer coordinator': ['vickitaylor'],
  'Management consultant': ['sheilaadams'],
  'Environmental health practitioner': ['uhebert'],
  'Retail banker': ['nicole82'],'Youth worker': ['jean67'], 
  'Barrister': ['nicole82'], 'Biomedical scientist': ['uhebert'], 
  'Theatre manager': ['sheilaadams'], 'Music therapist': ['vickitaylor'] }