I'm a developer and I use Python scripts for parsing and converting large structured files. I have extensive experience parsing PDFs, xml, json, xlsx etc. I have been in love with Python for 9 years.

Alternatively, you can use an XML parser library or framework that can handle or ignore some errors and recover from them. For example, in Python, you can use the lxml or ElementTree modules to ...

But fear not, as Python provides tools and techniques to parse these files without exhausting your system's memory. When you load an entire CSV file into memory, especially if it's large ...

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I would like to process the record data from the demo in Python. I found the file "parseTLV.py", but seems that there is example script since it doesn't parse all data (just Detected Objects and Range ...

but haven't managed to translate this piece of code in python so far. I'm parsing the TLV like that : a = f"{int(tlv_length//4)}i" data = np.array(struct.unpack(a, data)) i = data[1::2] q = data[::2] ...

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