memory_profiler
lxml
memory_profiler | lxml | |
---|---|---|
6 | 17 | |
4,222 | 2,573 | |
0.6% | 0.8% | |
3.7 | 9.6 | |
7 days ago | 7 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
memory_profiler
- Ask HN: C/C++ developer wanting to learn efficient Python
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8 Most Popular Python HTML Web Scraping Packages with Benchmarks
memory_profiler
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Check Python Memory Usage
pythonprofilers/memory_profiler: Monitor Memory usage of Python code
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Profiling and Analyzing Performance of Python Programs
# https://github.com/pythonprofilers/memory_profiler pip install memory_profiler psutil # psutil is needed for better memory_profiler performance python -m memory_profiler some-code.py Filename: some-code.py Line # Mem usage Increment Occurrences Line Contents ============================================================ 15 39.113 MiB 39.113 MiB 1 @profile 16 def memory_intensive(): 17 46.539 MiB 7.426 MiB 1 small_list = [None] * 1000000 18 122.852 MiB 76.312 MiB 1 big_list = [None] * 10000000 19 46.766 MiB -76.086 MiB 1 del big_list 20 46.766 MiB 0.000 MiB 1 return small_list
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Profiling Python code with memory_profiler
What do you do when your Python program is using too much memory? How do you find the spots in your code with memory allocation, especially in large chunks? It turns out that there is not usually an easy answer to these question, but a number of tools exist that can help you figure out where your code is allocating memory. In this article, I’m going to focus on one of them, memory_profiler.
- What Is Your Favorite Profilerperformance Tool
lxml
-
8 Most Popular Python HTML Web Scraping Packages with Benchmarks
lxml
- Looking for someone to web scrape housing data needed research. Will pay you for your work!!
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13 ways to scrape any public data from any website
Parsel is a library build to extract data from XML/HTML documents with XPath and CSS selectors support, and could be combined with regular expressions. It's usees lxml parser under the hood by default.
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lazy and fast .mpd file parser - for video streaming
So, now that I no longer work in that industry, and I had some free time, I created a lazy parsing package using lxml instead of the xml parser in the standard library, which can help people who want to have a python only parsing solution.
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Guide to working with fancier XML documents with python?
Seriously, use LXML.
- There is framework for everything.
- how to find text in website ?
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Parsing XML file deletes whitespace. How to avoid it?
I got curious about this now so I did some tests on my own, and it appears that the XML parser implementation in Python does indeed strip all newline characters from attributes. Whether this is according to XML standard I do not know; I also briefly tried an alternative XML implementation for Python and it behaves the same, so I would assume that this is standard behavior, but I'm not knowledgable enough about XML to say for certain.
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Use case for ETL over ELT?
I use lxml for the XML parsing and pyodbc as the ODBC library. We have a small team so I just keep it as simple as possible: 1. A cursor yields the XML documents from a SQL query as a stream 2. A generator function parses the XML document and yields the rows (you could parallelize this step) 3. Stream each of the resulting rows to a single CSV file 4. Scoop up the resulting CSV file into the target database (usually with the DB engine's loader; bulk insert isn't so fast over ODBC) It ends up being a straight forward, low-overhead approach.
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CompactLogix: Implementing HTTP requests & XML Data Transfer via TCP/IP
If that sounds too weird maybe take a look at pycomm3, python also has lxml as well as requests. You could write a script that retrieves the data from the clx using the appropriate pycomm3 driver for cplx and then do xml things with the data using lxml and transmit the data over http using requests.
What are some alternatives?
py-spy - Sampling profiler for Python programs
xmltodict - Python module that makes working with XML feel like you are working with JSON
line_profiler
selectolax - Python binding to Modest and Lexbor engines (fast HTML5 parser with CSS selectors).
profiling
html5lib - Standards-compliant library for parsing and serializing HTML documents and fragments in Python
pyflame
untangle - Converts XML to Python objects
Laboratory - Achieving confident refactoring through experimentation with Python 2.7 & 3.3+
bleach - Bleach is an allowed-list-based HTML sanitizing library that escapes or strips markup and attributes
filprofiler - A Python memory profiler for data processing and scientific computing applications
pyquery - A jquery-like library for python