00760067b8a2f3c222cabace373c6065165e6bb7
Add a new "Example output" section to the README that demonstrates the expected output format when running the isspam tool on a non-spam file, including metrics for capitalized words, sentences, word counts, and memory usage statistics.
Isspam
Fast as light evaluator for text files to summarize specific details about the text files.
Building
make build
Running
Using files as parameter
./isspam ./spam/*.txt
./isspam ./not_spam/*.txt
Using stdin
Useful for automation.
cat ./spam/example_spam1.txt | ./isspam
Example output
File: ./not_spam/not_spam1.txt
Capitalized words: 1
Sentences: 5
Words: 52
Numbers: 0
Forbidden words: 0
Word count per sentence: 10
Memory usage: 29 KB, 479 (re)allocated, 327 unqiue free'd, 0 in use.
Valgrind status
Date: 2024-11-28
Memory usage: 1 MB, 6.460 (re)allocated, 4.222 unqiue free'd, 0 in use.
==131498==
==131498== HEAP SUMMARY:
==131498== in use at exit: 0 bytes in 0 blocks
==131498== total heap usage: 6,486 allocs, 6,486 frees, 2,342,294 bytes allocated
==131498==
==131498== All heap blocks were freed -- no leaks are possible
==131498==
==131498== For lists of detected and suppressed errors, rerun with: -s
==131498== ERROR SUMMARY: 0 errors from 0 contexts (suppressed: 0 from 0)
Description
For a site I was doing spam analysis, how to recognize it. I do this by checking how it is written. How much numbers are used. How many capitals. That's the first indication. I made it originally myself but a few people liked the project and wrote their versions in their preferred language. Very happy about that.
We are bench marking it as challenge, the benchmark is doing analysis for 900 books in txt format. The fastest application wins. By now, every language has as wel won as lost. We keep iterating and making them faster.
Thanks 12bitloat, BordedDev en JestDotty for contribution of their source.
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