9967ea9a6c96a6f1db2f2271c388298d97d0df2a
Add curl to apt install list and install Rust nightly via rustup in the CI workflow. Update Makefile all target to include build_risspam before run_risspam, ensuring the Rust-based risspam binary is compiled before execution.
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: 2024-11-30
==58062==
==58062== HEAP SUMMARY:
==58062== in use at exit: 0 bytes in 0 blocks
==58062== total heap usage: 6,490 allocs, 6,490 frees, 2,343,156 bytes allocated
==58062==
==58062== All heap blocks were freed -- no leaks are possible
==58062==
==58062== For lists of detected and suppressed errors, rerun with: -s
==58062== 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.
486 MiB
Languages
Rust
73%
C++
12.9%
C
6.8%
Swift
3.4%
Python
2.2%
Other
1.6%