🩺 EMR Logs Analyser CLI

A powerful command-line tool written in Go for parsing and analyzing EMR system logs — including Tomcat (Catalina) and OpenMRS (Log4j) logs.
It helps you extract insights, detect errors, and summarize patterns from large log files.

---

📋 Table of Contents

1. Overview
2. Features
3. Installation
4. Usage
5. Command Reference
6. Supported Log Formats
7. Filters
8. Examples
9. Using the Makefile
10. Development
11. Planned Enhancements

---

🧩 Overview

The EMR Logs Analyser helps health system administrators and developers quickly make sense of massive EMR server logs.
It supports both Tomcat (Catalina) and OpenMRS (Log4j) formats, with filtering and summary statistics built in.

---

✨ Features

✅ Parse and analyze Tomcat / Catalina logs
✅ Parse and analyze OpenMRS (Log4j / SLF4J) logs
✅ Apply filters for level, thread, class, IP, or status
✅ Generate summary statistics
✅ Handle large log files efficiently (stream-based reading)
✅ Export results to file
✅ Extensible architecture — easily add new log formats

---

⚙️ Installation

Clone the repository

git clone https://github.com/<your-username>/emr-logs-analyser.git
cd emr-logs-analyser

Build the binary

make build

The binary emr-logs-analyser will be created in the current directory.

---

🚀 Usage

You can run the tool directly with Go or via the compiled binary.

Run with Go

go run main.go analyse --logfile=logs/catalina.out --type=catalina --level=ERROR

Run compiled binary

./emr-logs-analyser analyse --logfile=logs/openmrs.log --type=openmrs --level=ERROR

---

🧭 Command Reference

analyse

Analyse EMR logs to extract useful information and insights.

Flags

Flag	Shorthand	Description	Example
--logfile	-f	Path to the log file to analyze	--logfile=catalina.out
--type	-t	Type of logs (catalina, apache, openmrs)	--type=catalina
--output	-o	Output file for analysis results	--output=stats.json
--stats		Display summary statistics	--stats

---

🧱 Supported Log Formats

🐱 Catalina / Tomcat Logs

03-Oct-2025 09:12:06.003 INFO [main] org.apache.catalina.startup.Catalina.start Server startup in [4234] milliseconds

🩺 OpenMRS (Log4j / SLF4J) Logs

WARN - SessionImpl.createCriteria(1837) |2025-10-04T08:45:59,974| HHH90000022: Hibernate's legacy org.hibernate.Criteria API is deprecated
ERROR - FlagServiceImpl.generateFlagsForPatient(113) |2025-10-04T08:45:59,985| Unable to test flag Eligible for HIV program on patient #7032

---

🎯 Filters

Filter	Type	Description	Example
--level	Catalina / OpenMRS	Filter by log level (INFO, WARN, ERROR)	--level=ERROR
--thread	Catalina	Filter by thread name	--thread=main
--class	Catalina / OpenMRS	Filter by class or package	--class=org.openmrs.module
--ip	Apache	Filter by IP address	--ip=192.168.1.1
--path	Apache	Filter by request path	--path=/api/patients
--status	Apache	Filter by HTTP status code	--status=500

---

💡 Examples

1. Analyze Catalina logs

./emr-logs-analyser analyse --logfile=logs/catalina.out --type=catalina --level=ERROR --stats

2. Analyze OpenMRS application logs

./emr-logs-analyser analyse --logfile=logs/openmrs.log --type=openmrs --level=WARN

3. Export statistics to JSON

./emr-logs-analyser analyse -f logs/catalina.out -t catalina -o stats.json --stats

---

🧰 Using the Makefile

The included Makefile provides shortcuts for common tasks:

build:      ## Build the binary
	go build -o emr-logs-analyser main.go

run:         ## Run the CLI with arguments
	./emr-logs-analyser $(ARGS)

help:        ## Show available make commands
	@grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | sort | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[36m%-30s\033[0m %s\n", $$1, $$2}'

Example usage:

make run ARGS="analyse --logfile=logs/openmrs.log --type=openmrs --level=ERROR --stats"

---

🧪 Development

Directory Structure

.
├── cmd/
│   └── analyse.go         # Cobra command definition
├── parser/
│   ├── apache_parser.go
│   ├── catalina_parser.go
│   └── openmrs_parser.go
├── analyser/
│   └── stats.go
├── main.go
└── Makefile

Run locally

go run main.go analyse --logfile=logs/catalina.out --type=catalina

---

🚀 Planned Enhancements

• Add progress tracking for large log files
• Add JSON / CSV export options
• Add REST API layer for frontend integration (React dashboard)
• Implement log correlation (linking errors to user actions)
• Add visual summary report generation (PDF)

---

👨‍💻 Author

Jabar Jeremy
Full-Stack Developer • Health Tech | Go | React | Kotlin | Cloud-Native Architect