JSM Ticket Analytics Export

Jira's 1,000-row export cap, ignored.

jsm-export pulls every Jira Service Management ticket through the REST API — not the first 1,000 the UI hands you — and writes clean CSV + JSON datasets plus an audit manifest you can drop straight into a spreadsheet or a data pipeline. API credentials live in your OS keychain, never in plaintext.

# 1. Install
pip install jsm-ticket-analytics-export

# 2. Point it at your Jira Cloud instance, then store your API token in the OS keychain
export JSM_JIRA_INSTANCE="https://your-org.atlassian.net"
export JSM_PROJECT_KEY="SUPPORT"
jsm-export-setup            # prompts for your Jira email + API token (one time)

# 3. Export last month's tickets to ~/Analytics/JSM/
jsm-export

Sample output

A single run writes three files. Real numbers — the run below pulled 1,287 tickets, well past Jira's native 1,000-row ceiling.

~/Analytics/JSM/2026-02.csv

ticket_id,summary,url,issue_type,priority,labels,components,status,resolution,resolution_time_days,assignee,assignee_email,reporter,reporter_email,division,manager,created_date,updated_date,resolved_date,sla_breached,sla_time_to_resolution_mins
SUPPORT-1042,VPN drops every 30 minutes on remote desktop,https://your-org.atlassian.net/browse/SUPPORT-1042,Incident,High,network|vpn,Connectivity,Done,Fixed,2.4,Alex Rivera,alex.rivera@example.com,Jordan Lee,jordan.lee@example.com,Infrastructure,Dana Kim,2026-02-03T09:14:00.000-0800,2026-02-05T16:30:00.000-0800,2026-02-05T16:30:00.000-0800,false,3456
SUPPORT-1043,New hire laptop provisioning request,https://your-org.atlassian.net/browse/SUPPORT-1043,Service Request,Medium,onboarding,Hardware,In Progress,,,Sam Park,sam.park@example.com,Priya Nair,priya.nair@example.com,People Ops,Dana Kim,2026-02-04T11:02:00.000-0800,2026-02-04T11:20:00.000-0800,,,

~/Analytics/JSM/2026-02.json (one object per ticket)

[
  {
    "ticket_id": "SUPPORT-1042",
    "summary": "VPN drops every 30 minutes on remote desktop",
    "url": "https://your-org.atlassian.net/browse/SUPPORT-1042",
    "issue_type": "Incident",
    "priority": "High",
    "labels": ["network", "vpn"],
    "components": ["Connectivity"],
    "status": "Done",
    "resolution": "Fixed",
    "resolution_time_days": 2.4,
    "assignee": "Alex Rivera",
    "assignee_email": "alex.rivera@example.com",
    "reporter": "Jordan Lee",
    "reporter_email": "jordan.lee@example.com",
    "division": "Infrastructure",
    "manager": "Dana Kim",
    "created_date": "2026-02-03T09:14:00.000-0800",
    "updated_date": "2026-02-05T16:30:00.000-0800",
    "resolved_date": "2026-02-05T16:30:00.000-0800",
    "sla_breached": false,
    "sla_time_to_resolution_mins": 3456
  }
]

~/Analytics/JSM/2026-02-manifest.json (audit trail for every run)

{
  "run_date": "2026-03-01T06:00:03.481519+00:00",
  "date_range_start": "2026-02-01T08:02:11.000-0800",
  "date_range_end": "2026-02-28T17:45:52.000-0800",
  "row_count": 1287,
  "jql_query": "project = SUPPORT AND created >= \"2026-02-01\" AND created < \"2026-03-01\" ORDER BY created ASC",
  "fields_exported": ["ticket_id", "summary", "url", "issue_type", "priority", "..."],
  "custom_fields_resolved": { "Division": "customfield_10042", "Manager": "customfield_10071" },
  "output_files": [
    "~/Analytics/JSM/2026-02.csv",
    "~/Analytics/JSM/2026-02.json",
    "~/Analytics/JSM/2026-02-manifest.json"
  ],
  "errors": [],
  "duration_seconds": 42.17
}

---

Why

Jira's built-in CSV export silently truncates at 1,000 rows. For any team with real ticket volume, that makes monthly metrics, quarterly briefs, and division-level breakdowns impossible without manual stitching. jsm-export paginates the REST API so you get the whole dataset, every time, in a format that's ready for analysis.

Features

• Unlimited export — paginates the Jira REST API to retrieve every ticket regardless of volume
• Monthly file splits — backfill mode automatically partitions output by year-month
• Dual output formats — CSV for Excel/Sheets and JSON for downstream pipelines
• Secure credentials — API token stored in the OS keychain via keyring, never in config files or environment dumps
• Dynamic custom fields — resolves custom field IDs by name at runtime, so it survives Jira schema changes
• Audit manifests — every run records row counts, field coverage, the exact JQL used, and timing

Usage

# Export the previous calendar month (default)
jsm-export

# Export a specific month
jsm-export --month 2026-02

# Export everything created since a date
jsm-export --since 2026-01-15

# Backfill all history, split into monthly files under ~/Analytics/JSM/
jsm-export --backfill

# Dry run — paginate and count tickets without writing files
jsm-export --dry-run --month 2026-02

# Verbose (DEBUG) logging
jsm-export --verbose

Configuration

The tool reads non-secret settings from environment variables:

Variable	Required	Description	Example
JSM_JIRA_INSTANCE	yes	Base URL of your Jira Cloud instance	https://your-org.atlassian.net
JSM_PROJECT_KEY	yes	Project key to export	SUPPORT
JSM_OUTPUT_DIR	no	Output directory (default ~/Analytics/JSM/)	~/exports/jsm

Credentials (your Jira email and an API token) are not environment variables — run jsm-export-setup once to store them in the OS keychain.

Requirements

• Python 3.11+
• A Jira Cloud instance with REST API read access
• An OS keychain backend supported by keyring (macOS Keychain works out of the box)

How it works

1. Authenticate — validates your token against /rest/api/3/myself
2. Resolve fields — looks up custom field IDs (e.g. Division, Manager, SLA) by name from /rest/api/3/field
3. Build JQL — constructs a date-scoped query for the requested window
4. Paginate — walks /rest/api/3/search with a startAt cursor, rate-limited and retry-wrapped, until every ticket is fetched
5. Transform & write — flattens each ticket to one row, then writes CSV, JSON, and a manifest

Scheduling

To run automatically (e.g. on the 1st of each month), wrap jsm-export --month auto in your platform's scheduler. A macOS launchd template is included — see RELEASE.md and copy the template to ~/Library/LaunchAgents/, editing the paths for your environment.

Development

git clone https://github.com/saagpatel/JSMTicketAnalyticsExport
cd JSMTicketAnalyticsExport
uv sync --all-groups      # create the venv and install deps + dev tools
uv run pytest             # run the test suite
uv build                  # build sdist + wheel into dist/

License

MIT © Saag Patel