lxml VS opencv-python

lxml

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.

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.

Seriously, use LXML.

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.

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.

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.

Have you ever felt like your photos needed a little extra touch to stand out? Well, get ready because we're about to learn a cool Python trick! We're going to take ordinary photos and turn them into awesome pencil sketches using Python and OpenCV. This will make your pictures look like they were drawn by hand!

There are several modules that would allow you to process images in Python. Two of the perhaps most famous ones are PIL (https://pypi.org/project/Pillow/, also known as pillow), and opencv (https://pypi.org/project/opencv-python/).

Classifying images with trained model by using OpenCV and Teachable Machine packages

opencv-python: OpenCV for Python

Tool: Data collected using Python opencv, and a rudimentary OCR built from scratch. Graphic created with Microsoft Excel.

cv2: https://pypi.org/project/opencv-python/

I would try installing opencv-python on its own to see if you can learn more: https://pypi.org/project/opencv-python/

I've been googling and reading for a while but I'm very unsure about which tools I need, which tools will help me achieve what I want the easiest way. What about (pylivestream)[https://pypi.org/project/pylivestream/] for example? Will this do the job for me? What about a lower level approach including (pyopencv)[https://pypi.org/project/opencv-python/]? What about a higher level approach using (vidgear)[https://github.com/abhiTronix/vidgear], which seems promising but I don't feel confident in assessing if it's the tool I really need?

This is likely to be buggy and frustrating, and it's very likely that you'll need to use OpenCV to preprocess the screenshot. Not my idea of a good time!