如何使用Python correclty创建JSON文件？

2024-04-16 23:13:10 发布

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我正试图用雅虎的财务数据创建一个JSON文件。 我可以解析网站上的所有数据。但不幸的是，我找不到正确创建JSON文件的方法。JSON对象似乎没有以正确的方式连接

有人知道如何解决这个问题吗

请查找以下代码：

#!/usr/bin/python
# -*- coding: utf-8 -*-
import urllib2
from bs4 import BeautifulSoup
import ssl
import json
import ast
import os
from urllib2 import Request, urlopen
import datetime

# For ignoring SSL certificate errors
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE

# Input from the user (temp. manually)
urls = [
    'https://finance.yahoo.com/quote/DB1.DE?p=DB1.DE'
    , 'https://finance.yahoo.com/quote/ALV.DE?p=ALV.DE&.tsrc=fin-srch'
    , 'https://finance.yahoo.com/quote/FME.DE?p=FME.DE'
    , 'https://finance.yahoo.com/quote/DBK.DE?p=DBK.DE'
]

# Making the website believe that you are accessing it using a Mozilla browser
for url in urls:
    req = Request(url, headers={'User-Agent': 'Mozilla/5.0'})
    webpage = urlopen(req).read()

# Creating a BeautifulSoup object of the HTML page for easy extraction of data.
    soup = BeautifulSoup(webpage, 'html.parser')
    html = soup.prettify('utf-8')
    world_ana_json = {}

    for h1 in soup.findAll('h1'):
        world_ana_json['TICKER'] = h1.text.strip()
    for span in soup.findAll('span',attrs={'class': 'Trsdu(0.3s) Trsdu(0.3s) Fw(b) Fz(36px) Mb(-4px) D(b)'}):
        world_ana_json['PRESENT_VALUE'] = span.text.strip()
    for div in soup.findAll('div', attrs={'class': 'D(ib) Va(t)'}):
        for span in div.findAll('span', recursive=False):
            world_ana_json['PRESENT_GROWTH'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'PREV_CLOSE-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['PREV_CLOSE'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'OPEN-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['OPEN'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'BID-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['BID'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'ASK-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['ASK'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'DAYS_RANGE-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['DAYS_RANGE'] = span.text.strip()
    for td in soup.findAll('td',attrs={'data-test': 'FIFTY_TWO_WK_RANGE-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['FIFTY_TWO_WK_RANGE'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'TD_VOLUME-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['TD_VOLUME'] = span.text.strip()
    for td in soup.findAll('td',attrs={'data-test': 'AVERAGE_VOLUME_3MONTH-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['AVERAGE_VOLUME_3MONTH'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'MARKET_CAP-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['MARKET_CAP'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'BETA_3Y-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['BETA_3Y'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'PE_RATIO-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['PE_RATIO'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'EPS_RATIO-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['EPS_RATIO'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'EARNINGS_DATE-value'}):
        world_ana_json['EARNINGS_DATE'] = []
        for span in td.findAll('span', recursive=False):
            world_ana_json['EARNINGS_DATE'].append(span.text.strip())
    for td in soup.findAll('td',attrs={'data-test': 'DIVIDEND_AND_YIELD-value'}):
        world_ana_json['DIVIDEND_AND_YIELD'] = td.text.strip()
    for td in soup.findAll('td',attrs={'data-test': 'EX_DIVIDEND_DATE-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['EX_DIVIDEND_DATE'] = span.text.strip()
    for td in soup.findAll('td',attrs={'data-test': 'ONE_YEAR_TARGET_PRICE-value' }):
        for span in td.findAll('span', recursive=False):
            world_ana_json['ONE_YEAR_TARGET_PRICE'] = span.text.strip()
    world_ana_json['PARSE_DATE'] = str(datetime.datetime.now())
    with open('world_ana_kpis.json', 'a') as outfile:
        json.dump(world_ana_json, outfile, indent=4)
    print world_ana_json
    print '----------Iteration complete.----------'

print '----------Extraction of data is complete. Check json file.----------'

这是JSON结果：

{
    "TD_VOLUME": "684,446", 
    "MARKET_CAP": "24.882B", 
    "OPEN": "134.05", 
    "BID": "135.15 x 3500", 
    "AVERAGE_VOLUME_3MONTH": "849,271", 
    "PREV_CLOSE": "132.65", 
    "EARNINGS_DATE": [
        "Feb 13, 2018", 
        "Feb 19, 2018"
    ], 
    "DIVIDEND_AND_YIELD": "2.90 (2.19%)", 
    "EPS_RATIO": "5.47", 
    "PARSE_DATE": "2020-04-14 22:06:45.339815", 
    "PE_RATIO": "24.80", 
    "ASK": "135.10 x 14200", 
    "PRESENT_VALUE": "135.65", 
    "TICKER": "DB1.DE - Deutsche Borse AG", 
    "EX_DIVIDEND_DATE": "May 20, 2020", 
    "ONE_YEAR_TARGET_PRICE": "119.75"
}{
    "TD_VOLUME": "1,841,919", 
    "MARKET_CAP": "69.86B", 
    "OPEN": "168.72", 
    "BID": "167.66 x 214900", 
    "AVERAGE_VOLUME_3MONTH": "2,259,476", 
    "PREV_CLOSE": "164.88", 
    "EARNINGS_DATE": [
        "May 12, 2020"
    ], 
    "DIVIDEND_AND_YIELD": "9.60 (5.82%)", 
    "EPS_RATIO": "18.83", 
    "PARSE_DATE": "2020-04-14 22:06:46.592483", 
    "PE_RATIO": "8.91", 
    "ASK": "167.74 x 10000", 
    "PRESENT_VALUE": "167.70", 
    "TICKER": "ALV.DE - Allianz SE", 
    "EX_DIVIDEND_DATE": "May 07, 2020", 
    "ONE_YEAR_TARGET_PRICE": "213.69"
}{
    "TD_VOLUME": "912,856", 
    "MARKET_CAP": "19.246B", 
    "OPEN": "64.26", 
    "BID": "63.98 x 38700", 
    "AVERAGE_VOLUME_3MONTH": "1,293,817", 
    "PREV_CLOSE": "63.24", 
    "EARNINGS_DATE": [
        "May 06, 2020"
    ], 
    "DIVIDEND_AND_YIELD": "1.20 (1.90%)", 
    "EPS_RATIO": "3.96", 
    "PARSE_DATE": "2020-04-14 22:06:48.157705", 
    "PE_RATIO": "16.18", 
    "ASK": "64.04 x 105300", 
    "PRESENT_VALUE": "64.06", 
    "TICKER": "FME.DE - Fresenius Medical Care AG & Co. KGaA", 
    "EX_DIVIDEND_DATE": "May 20, 2020", 
    "ONE_YEAR_TARGET_PRICE": "80.61"
}{
    "TD_VOLUME": "15,877,455", 
    "MARKET_CAP": "12.828B", 
    "OPEN": "6.20", 
    "BID": "6.19 x 555100", 
    "AVERAGE_VOLUME_3MONTH": "25,845,616", 
    "PREV_CLOSE": "6.12", 
    "EARNINGS_DATE": [
        "Apr 29, 2020"
    ], 
    "DIVIDEND_AND_YIELD": "0.11 (1.82%)", 
    "EPS_RATIO": "-2.71", 
    "PARSE_DATE": "2020-04-14 22:06:49.821249", 
    "PE_RATIO": "N/A", 
    "ASK": "6.19 x 230000", 
    "PRESENT_VALUE": "6.21", 
    "TICKER": "DBK.DE - Deutsche Bank Aktiengesellschaft", 
    "EX_DIVIDEND_DATE": "May 24, 2019", 
    "ONE_YEAR_TARGET_PRICE": "N/A"
}

Tags： textinjsonfalseforworlddatadate
1条回答
网友
1楼 · 发布于 2024-04-16 23:13:10

当您在for循环中写入文件时，json对象之间没有“，”，所有json对象都应该在一个数组中

我已经修改了代码

#!/usr/bin/python
# -*- coding: utf-8 -*-
import urllib2
from bs4 import BeautifulSoup
import ssl
import json
import ast
import os
from urllib2 import Request, urlopen
import datetime

# For ignoring SSL certificate errors
ctx = ssl.create_default_context()
ctx.check_hostname = False
ctx.verify_mode = ssl.CERT_NONE

# Input from the user (temp. manually)
urls = [
    'https://finance.yahoo.com/quote/DB1.DE?p=DB1.DE'
    , 'https://finance.yahoo.com/quote/ALV.DE?p=ALV.DE&.tsrc=fin-srch'
    , 'https://finance.yahoo.com/quote/FME.DE?p=FME.DE'
    , 'https://finance.yahoo.com/quote/DBK.DE?p=DBK.DE'
]

output = []

# Making the website believe that you are accessing it using a Mozilla browser
for url in urls:
    req = Request(url, headers={'User-Agent': 'Mozilla/5.0'})
    webpage = urlopen(req).read()

# Creating a BeautifulSoup object of the HTML page for easy extraction of data.
    soup = BeautifulSoup(webpage, 'html.parser')
    html = soup.prettify('utf-8')
    world_ana_json = {}

    for h1 in soup.findAll('h1'):
        world_ana_json['TICKER'] = h1.text.strip()
    for span in soup.findAll('span',attrs={'class': 'Trsdu(0.3s) Trsdu(0.3s) Fw(b) Fz(36px) Mb(-4px) D(b)'}):
        world_ana_json['PRESENT_VALUE'] = span.text.strip()
    for div in soup.findAll('div', attrs={'class': 'D(ib) Va(t)'}):
        for span in div.findAll('span', recursive=False):
            world_ana_json['PRESENT_GROWTH'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'PREV_CLOSE-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['PREV_CLOSE'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'OPEN-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['OPEN'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'BID-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['BID'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'ASK-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['ASK'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'DAYS_RANGE-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['DAYS_RANGE'] = span.text.strip()
    for td in soup.findAll('td',attrs={'data-test': 'FIFTY_TWO_WK_RANGE-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['FIFTY_TWO_WK_RANGE'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'TD_VOLUME-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['TD_VOLUME'] = span.text.strip()
    for td in soup.findAll('td',attrs={'data-test': 'AVERAGE_VOLUME_3MONTH-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['AVERAGE_VOLUME_3MONTH'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'MARKET_CAP-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['MARKET_CAP'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'BETA_3Y-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['BETA_3Y'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'PE_RATIO-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['PE_RATIO'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'EPS_RATIO-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['EPS_RATIO'] = span.text.strip()
    for td in soup.findAll('td', attrs={'data-test': 'EARNINGS_DATE-value'}):
        world_ana_json['EARNINGS_DATE'] = []
        for span in td.findAll('span', recursive=False):
            world_ana_json['EARNINGS_DATE'].append(span.text.strip())
    for td in soup.findAll('td',attrs={'data-test': 'DIVIDEND_AND_YIELD-value'}):
        world_ana_json['DIVIDEND_AND_YIELD'] = td.text.strip()
    for td in soup.findAll('td',attrs={'data-test': 'EX_DIVIDEND_DATE-value'}):
        for span in td.findAll('span', recursive=False):
            world_ana_json['EX_DIVIDEND_DATE'] = span.text.strip()
    for td in soup.findAll('td',attrs={'data-test': 'ONE_YEAR_TARGET_PRICE-value' }):
        for span in td.findAll('span', recursive=False):
            world_ana_json['ONE_YEAR_TARGET_PRICE'] = span.text.strip()
    world_ana_json['PARSE_DATE'] = str(datetime.datetime.now())
    output.append(world_ana_json);

with open('world_ana_kpis.json', 'a') as outfile:
    json.dump(output, outfile, indent=4)

print '     Extraction of data is complete. Check json file.     '

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