urllib | Request HTTP URLs in a complex world | HTTP library
kandi X-RAY | urllib Summary
kandi X-RAY | urllib Summary
Request HTTP URLs in a complex world — basic and digest authentication, redirections, cookies, timeout and more.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of urllib
urllib Key Features
urllib Examples and Code Snippets
from urllib import request
from bs4 import BeautifulSoup
import re
class ThemeSpider(object):
def __init__(self, theme_url,judge_url):
self.theme_url = theme_url
self.judge_url = judge_url
def getLinkList(self):
resp
import https from 'https';
import { CookieJar } from 'tough-cookie';
import { HttpsCookieAgent } from 'http-cookie-agent';
const jar = new CookieJar();
const agent = new HttpsCookieAgent({ jar });
https.get('https://example.com', { agent }, (res) =
\b(19|20)\d{2}\b
import re
import urllib.request
import operator
# Download wiki page
url = "https://en.wikipedia.org/wiki/Diplomatic_history_of_World_War_II"
html = urllib.request.urlopen(url).read()
# Find all mentioned years in the 20th or 21st
import numpy as np
import urllib
import cv2
def url_to_image(url):
resp = urllib.urlopen(url)
image = np.asarray(bytearray(resp.read()), dtype="uint8")
image = cv2.imdecode(image, cv2.IMREAD_COLOR)
return image
import geopandas as gpd
import requests, io
from pathlib import Path
from zipfile import ZipFile, BadZipFile
import urllib
import fiona
url = "https://hepgis.fhwa.dot.gov/fhwagis/AltFuels_Rounds1-5_2021-05-25.zip"
try:
gdf = gpd.read
import geopandas as gpd
import shapely.geometry
import numpy as np
import plotly.express as px
import requests
from pathlib import Path
from zipfile import ZipFile
import urllib
import pandas as pd
# fmt: off
# download boundaries
url = "
import urllib
from sqlalchemy import create_engine
server = 'serverName\instanceName,port' # to specify an alternate port
database = 'mydb'
username = 'myusername'
password = 'mypassword'
params = urllib.parse.quote_plus('DRIVER={ODBC
import boto3
import urllib
DESTINATION_BUCKET = 'bucket2'
def lambda_handler(event, context):
s3_client = boto3.client('s3')
# Get the bucket and object key from the Event
for record in event['Records']:
source_
from django.urls import resolve, reverse
import urllib
def drop_get_param(request, param):
'helpful for redirecting while dropping a specific parameter'
resolution = resolve(request.path_info) #simulate resolving the request
new_pa
import boto3
import urllib
def lambda_handler(event, context):
s3_client = boto3.client('s3')
bucket = event['Records'][0]['s3']['bucket']['name']
key = urllib.parse.unquote_plus(event['Records'][0]['s3']['object']['k
Community Discussions
Trending Discussions on urllib
QUESTION
I'm trying to use BS4 to parse through the HTML for an about page on a youtube channel so I can scrape the number of channel views. Below is the code to scrape the channel views (located in the 'yt-formatted-string') and also the whole right column of the page. Both lines of code return either an empty list and a "None" value for the findAll() and find() functions, respectively.
I read another thread saying I may be receiving an empty list or "None" value because the page is accessing an API to get the total channel views to count and the values aren't actually in the HTML I'm parsing.
I know I could access much of this info through the Youtube API, but I want to iterate this code over multiple channels that are not my own. Moreover, I want to understand how to use BS4 to its full extent so I can replicate this process on an Instagram page or Facebook page.
Should I be using a different library that isn't BS4? Is what I'm looking to accomplish even possible?
My CODE
...ANSWER
Answered 2021-Jun-15 at 20:43YouTube is loaded dynamically, therefore urlib
won't support it.
However, the data is available in JSON format on the website. You can convert this data to a Python dictionary (dict
) using the built-in json
library.
This example is using the URL you have provided: https://www.youtube.com/c/Rozziofficial/about, you can change the channel name, it will work for all channels.
Here's an example using requests
, you can use urlib
instead:
QUESTION
So, I'm a very amateur python programmer but hope all I'll explain makes sense.
I want to scrape a type of Financial document called "10-K". I'm just interested in a little part of the whole document. An example of the URL I try to scrape is: https://www.sec.gov/Archives/edgar/data/320193/0000320193-20-000096.txt
Now, if I download this document as a .txt, It "only" weights 12mb. So for my ignorance doesn't make much sense this takes 1-2 min to .read()
(even I got a decent PC).
The original code I was using:
...ANSWER
Answered 2021-Jun-13 at 18:07The time it takes to read a document over the internet is really not related to the speed of your computer, at least in most cases. The most important determinant is the speed of your internet connection. Another important determinant is the speed with which the remote server responds to your request, which will depend in part on how many other requests the remote server is currently trying to handle.
It's also possible that the slow-down is not due to either of the above causes, but rather to measures taken by the remote server to limit scraping or to avoid congestion. It's very common for servers to deliberately reduce responsiveness to clients which make frequent requests, or even to deny the requests entirely. Or to reduce the speed of data transmission to everyone, which is another way of controlling server load. In that case, there's not much you're going to be able to do to speed up reading the requests.
From my machine, it takes a bit under 30 seconds to download the 12MB document. Since I'm in Perú it's possible that the speed of the internet connection is a factor, but I suspect that it's not the only issue. However, the data transmission does start reasonably quickly.
If the problem were related to the speed of data transfer between your machine and the server, you could speed things up by using a streaming parser (a phrase you can search for). A streaming parser reads its input in small chunks and assembles them on the fly into tokens, which is basically what you are trying to do. But the streaming parser will deal transparently with the most difficult part, which is to avoid tokens being split between two chunks. However, the nature of the SEC document, which taken as a whole is not very pure HTML, might make it difficult to use standard tools.
Since the part of the document you want to analyse is well past the middle, at least in the example you presented, you won't be able to reduce the download time by much. But that might still be worthwhile.
The basic approach you describe is workable, but you'll need to change it a bit in order to cope with the search strings being split between chunks, as you noted. The basic idea is to append successive chunks until you find the string, rather than just looking at them one at a time.
I'd suggest first identifying the entire document and then deciding whether it's the document you want. That reduces the search issue to a single string, the document terminator (\n\n
; the newlines are added to reduce the possibility of false matches).
Here's a very crude implementation, which I suggest you take as an example rather than just copying it into your program. The function docs
yields successive complete documents from a url; the caller can use that to select the one they want. (In the sample code, the first matching document is used, although there are actually two matches in the complete file. If you want all matches, then you will have to read the entire input, in which case you won't have any speed-up at all, although you might still have some savings from not having to parse everything.)
QUESTION
I am having trouble with specific links with urllib. Below is the code sample I use:
...ANSWER
Answered 2021-Jun-13 at 15:32Try using. You will get the response. Certain websites are secured and only respond to certain user-agents only.
QUESTION
import urllib.request
import pandas as pd
# Url file Website
url = 'https://......CSV'
# Download file
urllib.request.urlretrieve(
url, "F:\.....A.CSV")
csvFilePath = "F:\.....A.CSV"
df = pd.read_csv(csvFilePath, sep='\t')
rows=[0,1,2,3]
df2 = df.drop(rows, axis=0, inplace=True)
df.to_csv(
r'F:\....New_A.CSV')
...ANSWER
Answered 2021-Jun-13 at 14:40Replace:
QUESTION
I want the text from the li tag that is the specification of the product but when i am searching using driver.find_element_by_css_selector
it gives the error as path cannot find .So not able to get the text .
ANSWER
Answered 2021-Jun-13 at 08:49There are anti-scraping measures. If those do not affect you then you can use css classes to target the li elements to loop over, and the title/values for each specification:
QUESTION
I want to scrape the rating and all the reviews on the page .But not able to find the path .
...ANSWER
Answered 2021-Jun-13 at 04:51Perhaps there is a problem with your path? (apologies I'm not on windows to test). From memory, Windows paths use \
characters instead of /
. Additionally, you may need two backticks after the drive path (C:\\
).
c:\\Users\91940\AppData\Local\...
QUESTION
I am trying to web scrape a government public page that contains speeches and biography of ministers. At the end I would like a dictionary like this:
...ANSWER
Answered 2021-Jun-13 at 02:24Based on the provided target data structure above, you appear to be using a dictionary. It isn't clear what you would like your keys to be so I would probably suggest using a list/array.
I would suggest a slightly different way to dissect the problem.One potential implementation would be to iterate over each row (paragraph
of the table (div
data
array one index at a time.
From here, if the link(s) are present you could then query the external data source (or read from a different location on the page) to collect the respective data. In the example below, I choose to do this in a different iteration of data to help make the code a bit more readable.
I have not used the BeautifulSoap4 library before. I apologise if my solution isn't the most elegant regarding the libraries usage.
QUESTION
FIX FOR THIS ISSUE:
...ANSWER
Answered 2021-Jun-13 at 00:22EDIT:
Minimal working code based on @Weeble answer.
It uses yarl
with encoded=True
to stop requoting %3A
to :
QUESTION
I have search the specific brand Samsung , for this number of products are search ,I just wanted to scrape all the href from the of the search products with the product name .
...ANSWER
Answered 2021-Jun-12 at 11:12Couple of things. You are trying to mix bs4 syntax with selenium which is causing your current error. Additionally, you are targeting potentially dynamic values. Finally, there are anti-scraping measures which may later impact on your work.
Ignoring the last, a more robust, syntax appropriate version, might be:
QUESTION
I am working on a REST API and using python. say for a get request ( sample below), I am assuming , anyone who makes a call will URL encode the URL, what is the correct way to decode and read query parameters in python?
'https://someurl.com/query_string_params?id=1&type=abc'
...ANSWER
Answered 2021-Jun-11 at 08:21Here's an example of how to split a URL and get the query parameters:
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