isabl-project-report

name	isabl-project-report
description	Generate a status report for an Isabl project. Use when summarizing project progress, identifying issues, or preparing updates.
tools	Read, Bash
model	inherit

Generating a Project Report

You are helping generate a status report for an Isabl project.

Checklist

Work through these steps systematically:

1. Get project info (title, description, team)
2. Count experiments by technique and category
3. Count analyses by status and application
4. Identify failures that need attention
5. Calculate storage usage
6. Generate summary with key metrics
7. List action items if any

Step 1: Get Project Info

import isabl_cli as ii

project = ii.get_instance("projects", PROJECT_PK)

print(f"Project: {project.title}")
print(f"Short title: {project.short_title}")
print(f"PI: {project.principal_investigator}")
print(f"Analyst: {project.analyst}")
print(f"Description: {project.description}")

Step 2: Count Experiments

from collections import Counter

experiments = ii.get_experiments(projects=PROJECT_PK)

# By technique
techniques = Counter(e.technique.method for e in experiments)
print("Experiments by technique:")
for tech, count in techniques.most_common():
    print(f"  {tech}: {count}")

# By sample category
categories = Counter(e.sample.category for e in experiments)
print("\nExperiments by category:")
for cat, count in categories.most_common():
    print(f"  {cat}: {count}")

print(f"\nTotal experiments: {len(experiments)}")

Step 3: Count Analyses

analyses = ii.get_analyses(projects=PROJECT_PK)

# By status
statuses = Counter(a.status for a in analyses)
print("Analyses by status:")
for status in ["SUCCEEDED", "FAILED", "STARTED", "STAGED", "CREATED"]:
    count = statuses.get(status, 0)
    print(f"  {status}: {count}")

# By application
apps = Counter(a.application.name for a in analyses)
print("\nAnalyses by application (top 10):")
for app, count in apps.most_common(10):
    print(f"  {app}: {count}")

print(f"\nTotal analyses: {len(analyses)}")

Step 4: Identify Failures

failed = ii.get_analyses(
    projects=PROJECT_PK,
    status="FAILED"
)

if failed:
    print(f"FAILED analyses ({len(failed)}):")
    for a in failed[:10]:  # Show first 10
        target = a.targets[0].system_id if a.targets else "N/A"
        print(f"  [{a.pk}] {a.application.name}: {target}")

    if len(failed) > 10:
        print(f"  ... and {len(failed) - 10} more")
else:
    print("No failed analyses!")

Step 5: Calculate Storage

# Get storage usage from project
print(f"Project storage: {project.storage_usage / 1e9:.2f} GB")

# Or calculate from analyses
total_storage = sum(a.storage_usage or 0 for a in analyses)
print(f"Total analysis storage: {total_storage / 1e9:.2f} GB")

Step 6: Generate Summary

Create a summary like this:

# Project Report: {project.title}

**Date**: {today}
**PI**: {project.principal_investigator}
**Analyst**: {project.analyst}

## Overview

| Metric | Count |
|--------|-------|
| Individuals | X |
| Samples | X |
| Experiments | X |
| Analyses | X |

## Analysis Status

| Status | Count | % |
|--------|-------|---|
| SUCCEEDED | X | X% |
| FAILED | X | X% |
| IN PROGRESS | X | X% |

## Top Applications

| Application | Succeeded | Failed |
|-------------|-----------|--------|
| MUTECT | X | X |
| BATTENBERG | X | X |

## Issues Requiring Attention

- X failed analyses need investigation
- [List specific failures if any]

## Storage

Total: X.XX GB

Step 7: Action Items

Based on the report, identify:

• Failed analyses to re-run or debug
• Missing analyses (samples without expected apps)
• Stale analyses (STARTED for too long)

Common Patterns

Find stale analyses (running too long)

from datetime import datetime, timedelta

stale_cutoff = datetime.now() - timedelta(days=7)

stale = ii.get_analyses(
    projects=PROJECT_PK,
    status="STARTED",
    modified__lt=stale_cutoff.isoformat()
)

if stale:
    print(f"Stale analyses (started > 7 days ago): {len(stale)}")

Find samples without a specific app

# All experiments in project
all_exps = set(e.pk for e in ii.get_experiments(projects=PROJECT_PK))

# Experiments with MUTECT analysis
mutect_exps = set()
for a in ii.get_analyses(projects=PROJECT_PK, application__name="MUTECT"):
    mutect_exps.update(t.pk for t in a.targets)

# Missing
missing = all_exps - mutect_exps
print(f"Experiments without MUTECT: {len(missing)}")

Export to CSV

import pandas as pd

data = []
for a in analyses:
    data.append({
        "pk": a.pk,
        "application": a.application.name,
        "status": a.status,
        "target": a.targets[0].system_id if a.targets else None,
        "created": a.created,
    })

df = pd.DataFrame(data)
df.to_csv("project_report.csv", index=False)