IP | Country | PORT | ADDED |
---|---|---|---|
50.169.222.243 | us | 80 | 12 minutes ago |
115.22.22.109 | kr | 80 | 12 minutes ago |
50.174.7.152 | us | 80 | 12 minutes ago |
50.171.122.27 | us | 80 | 12 minutes ago |
50.174.7.162 | us | 80 | 12 minutes ago |
47.243.114.192 | hk | 8180 | 12 minutes ago |
72.10.160.91 | ca | 29605 | 12 minutes ago |
218.252.231.17 | hk | 80 | 12 minutes ago |
62.99.138.162 | at | 80 | 12 minutes ago |
50.217.226.41 | us | 80 | 12 minutes ago |
50.174.7.159 | us | 80 | 12 minutes ago |
190.108.84.168 | pe | 4145 | 12 minutes ago |
50.169.37.50 | us | 80 | 12 minutes ago |
50.223.246.238 | us | 80 | 12 minutes ago |
50.223.246.239 | us | 80 | 12 minutes ago |
50.168.72.116 | us | 80 | 12 minutes ago |
72.10.160.174 | ca | 3989 | 12 minutes ago |
72.10.160.173 | ca | 32677 | 12 minutes ago |
159.203.61.169 | ca | 8080 | 12 minutes ago |
209.97.150.167 | us | 3128 | 12 minutes ago |
Simple tool for complete proxy management - purchase, renewal, IP list update, binding change, upload lists. With easy integration into all popular programming languages, PapaProxy API is a great choice for developers looking to optimize their systems.
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You need to open the settings menu, go to "Data and disk", and then - "Proxy settings". There you can enter the address, port number of the intermediate server, as well as username and password for authorization (if necessary).
Yes, you can speed up XML parsing using Python's ElementTree module by following some optimization techniques. Here are a few tips
1. Use Iterative Parsing (iterparse)
Instead of using ElementTree.parse(), consider using ElementTree.iterparse() for iterative parsing. It allows you to process the XML tree element by element, reducing memory usage compared to parsing the entire tree at once.
import xml.etree.ElementTree as ET
for event, element in ET.iterparse('your_file.xml'):
# Process the element here
pass
2. Use a Streaming Parser
ElementTree is a tree-based parser, but for large XML files, consider using a streaming parser like xml.sax or lxml. Streaming parsers read the XML file sequentially, avoiding the need to load the entire document into memory.
import xml.sax
class MyHandler(xml.sax.ContentHandler):
def startElement(self, name, attrs):
# Process the start of an element
def endElement(self, name):
# Process the end of an element
parser = xml.sax.make_parser()
handler = MyHandler()
parser.setContentHandler(handler)
parser.parse('your_file.xml')
3. Disable DTD Loading
If your XML file doesn't require DTD (Document Type Definition) validation, you can disable it to speed up parsing. DTD validation can introduce overhead.
parser = ET.XMLParser()
parser.entity = {}
tree = ET.parse('your_file.xml', parser=parser)
4. Use a Faster Parser (lxml)
Consider using the lxml library, which is known for being faster than the built-in ElementTree. Install it using:
pip install lxml
Then, use it in your code:
from lxml import etree
tree = etree.parse('your_file.xml')
5. Use a Subset of Data
If you don't need the entire XML document, parse only the subset of data that you need. This reduces the amount of data being processed.
6. Profile Your Code
Use profiling tools like cProfile to identify bottlenecks in your code. This will help you focus on optimizing specific parts of your XML processing logic.
In simple terms, it is a logically separated part of the main local or public network. It is through it that many users can use a proxy through a single server at the same time. Each connection is allocated to a separate subnet.
A proxy is just used to bypass torrent download blocking through your ISP's network. Separately, the proxy server can block the host, that is, the owner of the site where the torrent files are posted. But it happens mostly due to malicious violations of the rules for using such a resource (for example, "cheating" rating).
A reverse proxy is mainly used by administrators and is responsible for balancing workload and high availability. The reverse proxy redirects received requests to one of its web servers. From the outside it is completely invisible and looks as if all required resources are concentrated directly in the proxy.
What else…