testdata_generator¶

Generates synthetic Jira issue JSON files in Jira REST API format. The generated files can be processed directly by transform_data and are suitable for development, testing, and demonstrations without real Jira data.

Status: available (Beta)

Manuals¶

Language	Download
Deutsch (DE)	Benutzerhandbuch
English (EN)	User Manual
Română (RO)	Manual de Utilizator
Português (PT)	Manual do Utilizador
Français (FR)	Manuel d'utilisation

Interface¶

Testdata Generator GUI screenshot

Start¶

GUI¶

python -m testdata_generator

Or via the start script in the portable package:

Windows: TestdataGenerator.bat
macOS: TestdataGenerator.command
Linux: TestdataGenerator.sh

Command line¶

python -m testdata_generator \
    --workflow workflow_ART_A.txt \
    --project ART_A_GEN \
    --issues 200 \
    --seed 42 \
    --output ART_A_generated.json

Parameters¶

Parameter	Default	Description
`--scenario portfolio`	(none)	Generate the complete demo portfolio instead of a single JSON (see below)
`--workflow FILE`	(required without `--scenario`)	Workflow definition file
`--output FILE.json`	`<project>_generated.json`	Output file
`--project KEY`	`TEST`	Jira project key
`--issues N`	`100`	Number of issues to generate
`--from-date YYYY-MM-DD`	`2025-01-01`	Earliest creation date
`--to-date YYYY-MM-DD`	`2025-12-31`	Latest transition date
`--issue-types TYPE:W …`	`Feature:0.6 Bug:0.3 Enabler:0.1`	Issue types with weights
`--completion-rate FLOAT`	`0.7`	Fraction of closed issues (0–1)
`--todo-rate FLOAT`	`0.15`	Fraction of open issues in To Do stages (0–1)
`--backflow-prob FLOAT`	`0.1`	Probability of backward transitions (0–1)
`--seed INT`	(random)	Seed for reproducible output
`--mean-cycle-days FLOAT`	(none)	Target mean cycle time in days (lognormal)
`--std-cycle-days FLOAT`	(30 % of mean)	Standard deviation of cycle time
`--pattern PATTERN`	`none`	Flow anti-pattern: `none` / `triangle` / `flat_triangle` / `cluster` / `batch`
`--pi-duration-weeks INT`	`12`	PI cycle length in weeks (for `cluster`/`batch`)

Flow Patterns¶

Use --mean-cycle-days together with --pattern to simulate typical flow anti-patterns:

Pattern	Description
`none`	Random cycle time without shape (default)
`triangle`	Cycle time increases linearly over time — triangle shape in the scatter plot
`flat_triangle`	Like `triangle`, but the increase flattens toward the end (tanh)
`cluster`	Deliveries cluster in the last 2 weeks of each PI (Beta distribution)
`batch`	PI clustering with highly variable cycle time (0.1× to 3× mean)

# Triangle pattern with mean cycle time of 30 days
python -m testdata_generator \
    --workflow workflow.txt \
    --pattern triangle \
    --mean-cycle-days 30 \
    --std-cycle-days 10 \
    --output triangle.json

Portfolio scenario¶

GUI: the Demo portfolio section at the bottom of the window generates the complete scenario into a folder of your choice (the seed field is honoured, default 42) — and Open Portfolio Report renders the portfolio report and opens it in the browser. Two clicks from empty folder to a full portfolio evaluation, no command line needed.

Command line:

python -m testdata_generator --scenario portfolio --output demo/ --seed 42

Creates a complete, consistent demo portfolio in one step: two solutions with three ARTs each, including every artifact of the processing chain — workflow files, raw Jira JSON, IssueTimes/CFD/Transitions workbooks, two solution configs (Solution Beta with its own stage_map, schema 2), a ROAM risk register per solution (risks_alpha.json/risks_beta.json), an NFR/runway register per solution (nfr_alpha.json/nfr_beta.json), a capability map per solution (capabilities_alpha.json/capabilities_beta.json), a dependency register per solution (dependencies_alpha.json/dependencies_beta.json), a decision/assumption log per solution (decisions_alpha.json/decisions_beta.json), a portfolio config, a PI config, and a README describing the built-in stories. The data window is placed relative to the generation date so the portfolio report's quality traffic light rates the sources as current.

Built-in stories (deterministic per seed):

ART Alpha-3 is the outlier (~3× cycle time) — highlighted red in Solution Alpha's comparison report.
ART Beta-3 delivers weak data (no CFD, few started issues, data 60 days old) — confidence low in the quality table, coverage below 100 %.
Solution Beta pools via its own stage_map; Solution Alpha uses the default classification path.
ROAM board: both risk registers together hold nine risks; two owned risks are deliberately old (45/50 days) — the aging highlight fires.
NFR & runway: six NFRs and four runway elements; Beta's API NFR is violated and one runway element is an overdue gap — the dashboard shows red.
Capability map: six capabilities; Beta's data-insights capability is critical (weak source) and one Alpha capability has no contributing ART — flagged as uncovered.
Dependency heatmap: five dependencies; Alpha-1 → Alpha-3 is blocked and overdue (the outlier does not deliver), and Beta-1 → Alpha-1 is a cross-solution integration — visible in the portfolio report.
Decision log: three decisions and two assumptions; Alpha's stage-map decision supersedes an older one, and Beta's open assumption has passed its review date — flagged red as "review due".

The folder is directly usable: python -m portfolio demo/portfolio.json builds the portfolio report; the solution configs also work individually.

Workflow file¶

Same format as in transform_data:

CanonicalStageName:Alias1:Alias2
<First>StageName
<Closed>StageName

Output and further processing¶

# Generate
python -m testdata_generator --workflow workflow.txt --project ART_TEST --seed 1

# Process directly with transform_data
python -m transform_data ART_TEST_generated.json workflow.txt

The generated JSON file contains Jira changelog histories with status transitions along the defined workflow. transform_data processes them into IssueTimes.xlsx, CFD.xlsx, and Transitions.xlsx.

Direct report (GUI)¶

After a successful generation the "Create Report" button becomes active in the GUI. Clicking it runs transform_data and build_reports directly and opens a combined report (a single HTML page with all metrics) in the browser. The report covers the entire generated date range — no date filter.

Architecture¶

testdata_generator/
├── __main__.py          Dispatcher: GUI without arguments, CLI with arguments
├── cli.py               run_generate() + argparse CLI
├── generator.py         Core logic: issue simulation
├── scenario.py          Portfolio scenario (2 solutions × 3 ARTs, all artifacts)
└── workflow_parser.py   Re-export from transform_data.workflow

Tests¶

python -m pytest tests/testdata_generator/

Note: Random cycle time distribution¶

The generator ensures that completed issues close before the configured to-date. The creation date is sampled from a restricted window [from-date, latest_start] where latest_start leaves enough buffer for the maximum cycle time. This produces an evenly distributed, random point cloud in the Flow Time scatter plot rather than a descending diagonal (right-censoring artefact).