在 Django 的 Templates 文件夹中创建一个表

Question

我正在尝试使用我命名为 law.html 的模板文件在 Django 中创建一个表，该模板文件中的数据格式化为来自我创建的用于从公共网页中抓取信息的函数的数据帧。我正在尝试使用 for 循环来遍历数据，但由于某种原因无法获得所需的输出。

到目前为止，我有一个名为 newlaw 的 DataFrame，它由函数 all_data 调用。数据框 newlaw 是律师姓名和办公室的列表。然后我将all_data 导入到我的views.py 文件夹中并给它字典all_data。在我的law.html 文件夹中，我正在尝试使用 for 循环创建一个表，以便我可以将每条数据放在一个单元格中。

我的views.py中的代码

def law_view(request, *args, **kwargs):
 data = combine_data()
 return render(request, "law.html", {'data': data})

The code in my law.html
```<table class="table table-striped">
    <thead>
        <tr>
            <th>Solicitor_Names</th>
            <th>Offices</th>     
        </tr>
    </thead>
    <tbody>
        {%for solicitor in all_data%}
          <tr>
              <td>{{ solicitor }}</td>
          </tr>
        {% ednfor %}
    </tbody>
</table>```

此代码仅打印列名。我想要的输出看起来像，

Solicitor_Name        Office
John Marston          Ernst & Young
Amy Smith             Kingston Smith
....
....

这是 all_data = combine()

def combine():
from bs4 import BeautifulSoup
import requests
import pandas as pd

urlh = 'http://solicitors.lawsociety.org.uk/search/results?Type=1&IncludeNlsp=True&Pro=True&parameters=%2C1%3BAPL%2C0%3B%2C1%3BPUB%2C0%3B%2C1%3BADV%2C0%3B%2C1%3BAGR%2C0%3B%2C1%3BAVI%2C0%3B%2C1%3BBAN%2C1%3B%2C1%3BBEN%2C0%3B%2C1%3BCHA%2C0%3B%2C1%3BCHI%2C0%3B%2C1%3BCLI%2C0%3B%2C1%3BCOL%2C1%3B%2C1%3BPCO%2C1%3B%2C1%3BCCL%2C0%3B%2C1%3BCOS%2C1%3B%2C1%3BCOM%2C1%3B%2C1%3BCON%2C1%3B%2C1%3BCSU%2C0%3B%2C1%3BCSF%2C0%3B%2C1%3BCSG%2C0%3B%2C1%3BCUT%2C0%3B%2C1%3BCTR%2C1%3B%2C1%3BPRE%2C0%3B%2C1%3BCFI%2C1%3B%2C1%3BCRD%2C0%3B%2C1%3BCRF%2C0%3B%2C1%3BCRG%2C0%3B%2C1%3BCRJ%2C0%3B%2C1%3BCRL%2C0%3B%2C1%3BCRM%2C0%3B%2C1%3BCRS%2C0%3B%2C1%3BCRO%2C1%3B%2C1%3BDEB%2C0%3B%2C1%3BDTR%2C1%3B%2C1%3BDEF%2C0%3B%2C1%3BDRC%2C0%3B%2C1%3BDRO%2C1%3B%2C1%3BEDU%2C0%3B%2C1%3BELC%2C0%3B%2C1%3BELH%2C0%3B%2C1%3BEMP%2C1%3B%2C1%3BENE%2C0%3B%2C1%3BENV%2C0%3B%2C1%3BEUN%2C0%3B%2C1%3BFDS%2C0%3B%2C1%3BFAM%2C0%3B%2C1%3BFAL%2C0%3B%2C1%3BFMC%2C0%3B%2C1%3BFME%2C0%3B%2C1%3BFML%2C0%3B%2C1%3BFPL%2C0%3B%2C1%3BFIS%2C0%3B%2C1%3BHRI%2C0%3B%2C1%3BIMA%2C0%3B%2C1%3BIML%2C0%3B%2C1%3BIMM%2C0%3B%2C1%3BIMG%2C0%3B%2C1%3BIMN%2C0%3B%2C1%3BITE%2C1%3B%2C1%3BINS%2C1%3B%2C1%3BIUR%2C1%3B%2C1%3BIPR%2C1%3B%2C1%3BJRW%2C0%3B%2C1%3BJRL%2C0%3B%2C1%3BLCO%2C1%3B%2C1%3BLRE%2C0%3B%2C1%3BPOA%2C0%3B%2C1%3BLIC%2C1%3B%2C1%3BLIV%2C0%3B%2C1%3BLIS%2C0%3B%2C1%3BLIT%2C0%3B%2C1%3BLPH%2C0%3B%2C1%3BLPP%2C0%3B%2C1%3BMAR%2C0%3B%2C1%3BMED%2C1%3B%2C1%3BMHE%2C0%3B%2C1%3BMHL%2C0%3B%2C1%3BMAA%2C1%3B%2C1%3BMIL%2C0%3B%2C1%3BNDI%2C0%3B%2C1%3BPEN%2C1%3B%2C1%3BPIN%2C0%3B%2C1%3BPIR%2C0%3B%2C1%3BPLA%2C0%3B%2C1%3BPRZ%2C0%3B%2C1%3BPRP%2C0%3B%2C1%3BPRT%2C0%3B%2C1%3BPRW%2C0%3B%2C1%3BPCI%2C0%3B%2C1%3BPCP%2C0%3B%2C1%3BPCT%2C0%3B%2C1%3BPCW%2C0%3B%2C1%3BPNE%2C0%3B%2C1%3BTAX%2C0%3B%2C1%3BTAC%2C1%3B%2C1%3BTAE%2C0%3B%2C1%3BTAH%2C1%3B%2C1%3BTAM%2C0%3B%2C1%3BTAP%2C0%3B%2C1%3BTAT%2C0%3B+'
r = requests.get(urlh)
soup = BeautifulSoup(r.content, 'html.parser')

names = []
roles = []
offices = []
locations = []

for i in range(1,2):
    url = 'http://solicitors.lawsociety.org.uk/search/results?Type=1&IncludeNlsp=True&Pro=True&parameters=%2C1%3BAPL%2C0%3B%2C1%3BPUB%2C0%3B%2C1%3BADV%2C0%3B%2C1%3BAGR%2C0%3B%2C1%3BAVI%2C0%3B%2C1%3BBAN%2C1%3B%2C1%3BBEN%2C0%3B%2C1%3BCHA%2C0%3B%2C1%3BCHI%2C0%3B%2C1%3BCLI%2C0%3B%2C1%3BCOL%2C1%3B%2C1%3BPCO%2C1%3B%2C1%3BCCL%2C0%3B%2C1%3BCOS%2C1%3B%2C1%3BCOM%2C1%3B%2C1%3BCON%2C1%3B%2C1%3BCSU%2C0%3B%2C1%3BCSF%2C0%3B%2C1%3BCSG%2C0%3B%2C1%3BCUT%2C0%3B%2C1%3BCTR%2C1%3B%2C1%3BPRE%2C0%3B%2C1%3BCFI%2C1%3B%2C1%3BCRD%2C0%3B%2C1%3BCRF%2C0%3B%2C1%3BCRG%2C0%3B%2C1%3BCRJ%2C0%3B%2C1%3BCRL%2C0%3B%2C1%3BCRM%2C0%3B%2C1%3BCRS%2C0%3B%2C1%3BCRO%2C1%3B%2C1%3BDEB%2C0%3B%2C1%3BDTR%2C1%3B%2C1%3BDEF%2C0%3B%2C1%3BDRC%2C0%3B%2C1%3BDRO%2C1%3B%2C1%3BEDU%2C0%3B%2C1%3BELC%2C0%3B%2C1%3BELH%2C0%3B%2C1%3BEMP%2C1%3B%2C1%3BENE%2C0%3B%2C1%3BENV%2C0%3B%2C1%3BEUN%2C0%3B%2C1%3BFDS%2C0%3B%2C1%3BFAM%2C0%3B%2C1%3BFAL%2C0%3B%2C1%3BFMC%2C0%3B%2C1%3BFME%2C0%3B%2C1%3BFML%2C0%3B%2C1%3BFPL%2C0%3B%2C1%3BFIS%2C0%3B%2C1%3BHRI%2C0%3B%2C1%3BIMA%2C0%3B%2C1%3BIML%2C0%3B%2C1%3BIMM%2C0%3B%2C1%3BIMG%2C0%3B%2C1%3BIMN%2C0%3B%2C1%3BITE%2C1%3B%2C1%3BINS%2C1%3B%2C1%3BIUR%2C1%3B%2C1%3BIPR%2C1%3B%2C1%3BJRW%2C0%3B%2C1%3BJRL%2C0%3B%2C1%3BLCO%2C1%3B%2C1%3BLRE%2C0%3B%2C1%3BPOA%2C0%3B%2C1%3BLIC%2C1%3B%2C1%3BLIV%2C0%3B%2C1%3BLIS%2C0%3B%2C1%3BLIT%2C0%3B%2C1%3BLPH%2C0%3B%2C1%3BLPP%2C0%3B%2C1%3BMAR%2C0%3B%2C1%3BMED%2C1%3B%2C1%3BMHE%2C0%3B%2C1%3BMHL%2C0%3B%2C1%3BMAA%2C1%3B%2C1%3BMIL%2C0%3B%2C1%3BNDI%2C0%3B%2C1%3BPEN%2C1%3B%2C1%3BPIN%2C0%3B%2C1%3BPIR%2C0%3B%2C1%3BPLA%2C0%3B%2C1%3BPRZ%2C0%3B%2C1%3BPRP%2C0%3B%2C1%3BPRT%2C0%3B%2C1%3BPRW%2C0%3B%2C1%3BPCI%2C0%3B%2C1%3BPCP%2C0%3B%2C1%3BPCT%2C0%3B%2C1%3BPCW%2C0%3B%2C1%3BPNE%2C0%3B%2C1%3BTAX%2C0%3B%2C1%3BTAC%2C1%3B%2C1%3BTAE%2C0%3B%2C1%3BTAH%2C1%3B%2C1%3BTAM%2C0%3B%2C1%3BTAP%2C0%3B%2C1%3BTAT%2C0%3B+' + '=&Page=' + str(i)
    response = requests.get(url)
    response.raise_for_status()
    soup = BeautifulSoup(response.content, 'html.parser')

    hp_sol_data = soup.find_all('section', {'class':'solicitor'})

    for sol in hp_sol_data:
        try:
            addy = sol.contents[7].find_all('dd', {'class':'feature highlight'})[0].text
            locations.append(addy)
        except IndexError:
            locations.append('None Found')
        try:
            office_names = sol.contents[7].find_all('dd', {'class':'highlight'})[0].text
            offices.append(office_names.strip())
        except IndexError:
            offices.append('None Found')

    for link in soup.find_all('a', href=True):
        if link.get('href').startswith('/person/'):
            tags = (link.get('href'))

            url2 = 'http://solicitors.lawsociety.org.uk' + str(tags)
            r2 = requests.get(url2)
            soup = BeautifulSoup(r2.content, 'html.parser')

            s_data = soup.find_all('article', {'class':'solicitor solicitor-type-individual details'})

            for item in s_data:
                solicitor_names = (item.contents[3].find_all('h1')[0].text)
                names.append(solicitor_names)
                try:
                    role = (item.find_all('div', {'class':'panel-half'})[1].find('dd').get_text(''))
                    roles.append(role.strip())
                except IndexError:
                    roles.append('Role not specified')


tls_solicitors = pd.DataFrame({'Solicitor_Name': names, 'Role': roles, 'Office': offices,'Address': locations},
                         columns = ['Solicitor_Name', 'Office', 'Address', 'Role'])
law = tls_solicitors
newd = law['Role'].str.split('\n', n=3, expand = True)
#law['Primary_Role'] = newd[0]
#law['Secondary_Role'] = newd[1]
role_1 = newd[0]
role_2 = newd[1]
law.drop('Role', axis=1)

all_data = [{'name': names, 'office': offices, 'address': locations, 'primary_role': role_1, 'secondary_role': role_2}]

return all_data

Answer 1

...
{% for a in data %}
    <tr>
        <td>{{a.name}}</td>
        <td>{{a.office}}</td>
    </tr>
{% endfor %}
...

在这种情况下，您的数据应该是字典列表[{'name': 'some name', 'office': 'some office'}, ...]