Iterate through a html file and extract data to CSV file - python
I have searched high and low for a solution, but non have quite fit what I need to do.
I have an html page that is saved, as a file, lets call it sample.html and I need to extract recurring json data from it. An example file is as follows:
I need to get the info from these files regulary, so the amount of objects change every time, an object would be considered as "{"SpecificIdent":2588,"SpecificNum":29,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false}"
I need to get each of the values to a CSV file, with column headings being SpecificIdent, SpecificNum, Meter, Power, WPower, Snumber, isI. The associated data would be the rows from each.
I apologize if this is a basic question in Python, but I am pretty new to it and cannot fathom the best way to do this. Any assistance would be greatly appreciated.
Kind regards
A
<html><head><meta name="color-scheme" content="light dark"></head><body><pre style="word-wrap: break-word; white-space: pre-wrap;">[{"SpecificIdent":2588,"SpecificNum":29,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":3716,"SpecificNum":39,"Meter":1835,"Power":11240.0,"WPower":null,"SNumber":"0703-403548","isI":false},{"SpecificIdent":6364,"SpecificNum":27,"Meter":7768,"Power":29969.0,"WPower":null,"SNumber":"467419","isI":false},{"SpecificIdent":6583,"SpecificNum":51,"Meter":7027,"Power":36968.0,"WPower":null,"SNumber":"JE1449-521248","isI":false},{"SpecificIdent":6612,"SpecificNum":57,"Meter":12828,"Power":53918.0,"WPower":null,"SNumber":"JE1509-534327","isI":false},{"SpecificIdent":7139,"SpecificNum":305,"Meter":6264,"Power":33101.0,"WPower":null,"SNumber":"JE1449-521204","isI":false},{"SpecificIdent":7551,"SpecificNum":116,"Meter":0,"Power":21569.0,"WPower":null,"SNumber":"JE1449-521252","isI":false},{"SpecificIdent":7643,"SpecificNum":56,"Meter":7752,"Power":40501.0,"WPower":null,"SNumber":"JE1449-521200","isI":false},{"SpecificIdent":8653,"SpecificNum":49,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":9733,"SpecificNum":142,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":10999,"SpecificNum":20,"Meter":7723,"Power":6987.0,"WPower":null,"SNumber":"JE1608-625534","isI":false},{"SpecificIdent":12086,"SpecificNum":24,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":14590,"SpecificNum":35,"Meter":394,"Power":10941.0,"WPower":null,"SNumber":"BN1905-944799","isI":false},{"SpecificIdent":14954,"SpecificNum":100,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"517163","isI":false},{"SpecificIdent":14995,"SpecificNum":58,"Meter":0,"Power":38789.0,"WPower":null,"SNumber":"JE1444-511511","isI":false},{"SpecificIdent":15245,"SpecificNum":26,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"430149","isI":false},{"SpecificIdent":18824,"SpecificNum":55,"Meter":8236,"Power":31358.0,"WPower":null,"SNumber":"0703-310839","isI":false},{"SpecificIdent":20745,"SpecificNum":41,"Meter":0,"Power":60963.0,"WPower":null,"SNumber":"JE1447-517260","isI":false},{"SpecificIdent":31584,"SpecificNum":11,"Meter":0,"Power":3696.0,"WPower":null,"SNumber":"467154","isI":false},{"SpecificIdent":32051,"SpecificNum":40,"Meter":7870,"Power":13057.0,"WPower":null,"SNumber":"JE1608-625593","isI":false},{"SpecificIdent":32263,"SpecificNum":4,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":33137,"SpecificNum":132,"Meter":5996,"Power":26650.0,"WPower":null,"SNumber":"459051","isI":false},{"SpecificIdent":33481,"SpecificNum":144,"Meter":4228,"Power":16136.0,"WPower":null,"SNumber":"JE1603-617807","isI":false},{"SpecificIdent":33915,"SpecificNum":145,"Meter":5647,"Power":3157.0,"WPower":null,"SNumber":"JE1518-549610","isI":false},{"SpecificIdent":36051,"SpecificNum":119,"Meter":2923,"Power":12249.0,"WPower":null,"SNumber":"135493","isI":false},{"SpecificIdent":37398,"SpecificNum":21,"Meter":58,"Power":5540.0,"WPower":null,"SNumber":"BN1925-982761","isI":false},{"SpecificIdent":39024,"SpecificNum":50,"Meter":7217,"Power":38987.0,"WPower":null,"SNumber":"JE1445-511599","isI":false},{"SpecificIdent":39072,"SpecificNum":59,"Meter":5965,"Power":32942.0,"WPower":null,"SNumber":"JE1449-521199","isI":false},{"SpecificIdent":40601,"SpecificNum":9,"Meter":0,"Power":59655.0,"WPower":null,"SNumber":"JE1447-517150","isI":false},{"SpecificIdent":40712,"SpecificNum":37,"Meter":0,"Power":5715.0,"WPower":null,"SNumber":"JE1502-525840","isI":false},{"SpecificIdent":41596,"SpecificNum":53,"Meter":8803,"Power":60669.0,"WPower":null,"SNumber":"JE1503-527155","isI":false},{"SpecificIdent":50276,"SpecificNum":30,"Meter":2573,"Power":4625.0,"WPower":null,"SNumber":"JE1545-606334","isI":false},{"SpecificIdent":51712,"SpecificNum":69,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":56140,"SpecificNum":10,"Meter":5169,"Power":26659.0,"WPower":null,"SNumber":"JE1547-609024","isI":false},{"SpecificIdent":56362,"SpecificNum":6,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":58892,"SpecificNum":113,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":65168,"SpecificNum":5,"Meter":12739,"Power":55833.0,"WPower":null,"SNumber":"JE1449-521284","isI":false},{"SpecificIdent":65255,"SpecificNum":60,"Meter":5121,"Power":27784.0,"WPower":null,"SNumber":"JE1449-521196","isI":false},{"SpecificIdent":65665,"SpecificNum":47,"Meter":11793,"Power":47576.0,"WPower":null,"SNumber":"JE1509-534315","isI":false},{"SpecificIdent":65842,"SpecificNum":8,"Meter":10783,"Power":46428.0,"WPower":null,"SNumber":"JE1509-534401","isI":false},{"SpecificIdent":65901,"SpecificNum":22,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":65920,"SpecificNum":17,"Meter":9316,"Power":38242.0,"WPower":null,"SNumber":"JE1509-534360","isI":false},{"SpecificIdent":66119,"SpecificNum":43,"Meter":12072,"Power":52157.0,"WPower":null,"SNumber":"JE1449-521259","isI":false},{"SpecificIdent":70018,"SpecificNum":34,"Meter":11172,"Power":49706.0,"WPower":null,"SNumber":"JE1449-521285","isI":false},{"SpecificIdent":71388,"SpecificNum":54,"Meter":6947,"Power":36000.0,"WPower":null,"SNumber":"JE1445-512406","isI":false},{"SpecificIdent":71892,"SpecificNum":36,"Meter":15398,"Power":63691.0,"WPower":null,"SNumber":"JE1447-517256","isI":false},{"SpecificIdent":72600,"SpecificNum":38,"Meter":14813,"Power":62641.0,"WPower":null,"SNumber":"JE1447-517189","isI":false},{"SpecificIdent":73645,"SpecificNum":2,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":77208,"SpecificNum":28,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":77892,"SpecificNum":15,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false},{"SpecificIdent":78513,"SpecificNum":31,"Meter":6711,"Power":36461.0,"WPower":null,"SNumber":"JE1445-511601","isI":false},{"SpecificIdent":79531,"SpecificNum":18,"Meter":0,"Power":0.0,"WPower":null,"SNumber":"","isI":false}]</pre></body></html>
I have tried examples from bs4, jsontoxml, and others, but I am sure there is a simple way to iterate and extract this?
I would harness python's standard library following way
import csv
import json
from html.parser import HTMLParser
class MyHTMLParser(HTMLParser):
def handle_data(self, data):
if data.strip():
self.data = data
parser = MyHTMLParser()
with open("sample.html","r") as f:
parser.feed(f.read())
with open('sample.csv', 'w', newline='') as csvfile:
fieldnames = ['SpecificIdent', 'SpecificNum', 'Meter', 'Power', 'WPower', 'SNumber', 'isI']
writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
writer.writeheader()
writer.writerows(json.loads(parser.data))
which creates file starting with following lines
SpecificIdent,SpecificNum,Meter,Power,WPower,SNumber,isI
2588,29,0,0.0,,,False
3716,39,1835,11240.0,,0703-403548,False
6364,27,7768,29969.0,,467419,False
6583,51,7027,36968.0,,JE1449-521248,False
6612,57,12828,53918.0,,JE1509-534327,False
7139,305,6264,33101.0,,JE1449-521204,False
7551,116,0,21569.0,,JE1449-521252,False
7643,56,7752,40501.0,,JE1449-521200,False
8653,49,0,0.0,,,False
Disclaimer: this assumes JSON array you want is last text element which is not empty (i.e. contain at least 1 non-whitespace character).
There is a python library, called BeautifulSoup, that you could utilize to parse the whole HTML file:
# pip install bs4
from bs4 import BeautifulSoup
html = BeautifulSoup(your-html)
From here on, you can perform any actions upon the html. In your case, you just need to find the <pre> element, and get its contents. This can be achieved easily:
pre = html.body.find('pre')
text = pre.text
Finally, you need to parse the text, which it seems is JSON. You can do with Python's internal json library:
import json
result = json.loads(text)
Now, we need to convert this to a CSV file. This could be done, using the csv library:
import csv
with open('GFG', 'w') as f:
writer = csv.DictWriter(f, fieldnames=[
"SpecificIdent",
"SpecificNum",
"Meter",
"Power",
"WPower",
"SNumber",
"isI"
])
writer.writeheader()
writer.writerows(result)
Finally, your code should look something like this:
from bs4 import BeautifulSoup
import json
import csv
with open('raw.html', 'r') as f:
raw = f.read()
html = BeautifulSoup(raw)
pre = html.body.find('pre')
text = pre.text
result = json.loads(text)
with open('result.csv', 'w') as f:
writer = csv.DictWriter(f, fieldnames=[
"SpecificIdent",
"SpecificNum",
"Meter",
"Power",
"WPower",
"SNumber",
"isI"
])
writer.writeheader()
writer.writerows(result)
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