Processing Text Files with Python: Earning $50K Continued
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Chapter 1: Introduction to Text File Processing
In a previous article, I discussed the use of Optical Character Recognition (OCR) with Python, which contributed to my journey of earning approximately $50K. However, this endeavor encompasses several components and extends beyond merely extracting data from PDF documents. I’m sharing my experience because I encountered challenges while attempting to read over a million text files to locate specific strings.
Section 1.1: Understanding Encoding Issues
Historically, I relied on UTF-8 encoding, which functioned adequately for my needs. However, it turned out that the encoding associated with my files was different. The following code snippet illustrates my initial approach:
with open(files[0], encoding='utf-8') as f:
content = f.read()
Executing this code resulted in a UnicodeDecodeError:
UnicodeDecodeError: 'utf-8' codec can't decode byte 0x99 in position 139: invalid start byte
To determine the correct encoding, I utilized the chardet library and ran this code:
import chardet
with open(files[0], 'rb') as file:
print(chardet.detect(file.read()))
In my case, the output indicated:
{'encoding': 'Windows-1252', 'confidence': 0.73, 'language': ''}
Thus, the correct encoding for reading my files was identified as Windows-1252. Interestingly, the first run suggested Windows-1251, which might also work, but UTF-8 was definitely unsuitable.
Section 1.2: Final Thoughts
This brief entry aims to provide additional clarity on overcoming this issue. It’s worth noting that Python’s error messages can sometimes be misleading, and relying solely on Stack Overflow may not always guide you correctly. I hope this information aids you in similar tasks or projects.
Chapter 2: Additional Resources and Community Engagement
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