retoor
b607207647
Introduce a global `total` counter incremented on each `analyze()` call, printing the file sequence number. Extend the analysis block to compute and display capitalized and forbidden word percentages when forbidden words exist. Add a new Python script `totals.py` that reads the application output and computes average percentages across all processed files.
Isspam
Fast as light evaluator for text files to summarize specific details about the text files.
Building
make build
Build with memory check (requires valgrind to be installed):
make valgrind
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: ./spam/example_spam3.txt
Capitalized words: 39
Sentences: 20
Words: 420
Numbers: 1
Forbidden words: 15
<0:recovery>
<1:techie>
<2:https>
<3:digital>
<4:hack>
<5://>
<6:com>
<7:@>
<8:crypto>
<9:bitcoin>
<10:whatsapp>
<11:cryptocurrency>
<12:stolen>
<13:contact>
<14:understanding>
Word count per sentence: 21
Memory usage: 1 MB, 6.460 (re)allocated, 4.222 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)