Metadata-Version: 2.4
Name: nsml-parser
Version: 0.1.0
Summary: NSML++: Neuro-Symbolic Memory Lattice for Intelligent Log Parsing
Home-page: https://github.com/catchmaurya/nsml-parser
Author: catchmaurya(catchmaurya@gmail.com) and NeuroBujandar
Author-email: catchmaurya@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-python
Dynamic: summary

# NSMLParser (Neuro-Symbolic Memory Lattice Parser)

NSMLParser is a lightweight, intelligent log parser designed to extract structured key-value fields from unstructured logs using a hybrid of fuzzy matching, positional reasoning, and heuristic inference. It includes:

- Fuzzy key correction
- Backfilled value inference
- Canonical semantic mapping
- Confidence scoring
- Lightweight tokenizer (no spaCy or heavy dependencies)

## Features

- ✅ Intelligent tokenization and parsing
- ✅ Fuzzy matching for variant key names (`case_number`, `casenum` → `caseNumber`)
- ✅ Heuristic inference for misplaced or missing key-value pairs
- ✅ Positional backtracking for unstructured logs
- ✅ Confidence scoring per field
- ✅ Designed to work without external APIs or heavyweight NLP libraries

## Example

```python
from nsml_parser import NSMLParser

parser = NSMLParser()

log = """Running HTTPS_PROXY='http://proxy.net:8080' /opt/radar/bin/apprise -consumers "FUNNYTEAM_AUDIT" -cluster "POD109" -product "blah-base" -sp "KP" -dc "MM" -caseNumber -release "rrrrr" -event "ERROR_RUNNING_PLSQL_TARGET" -eventTime "2023-06-09_04:31:04" -stage "some issue here" -status "FAILED" -type "ERROR" -source "ops0-release2-2-RR" "123456" --message "something" """

result = parser.parse(log)

print(result)
