leo-claude-mktplace/plugins/data-seed/skills/faker-patterns.md

name, description

name	description
faker-patterns	Realistic data generation patterns using faker providers with locale awareness

Faker Patterns

Purpose

Map schema column types and naming conventions to appropriate faker data generators. This skill ensures generated test data is realistic, locale-aware, and respects type constraints.

---

Column Name to Provider Mapping

Use column name heuristics to select the most realistic faker provider:

Column Name Pattern	Faker Provider	Example Output
*name, first_name	faker.name() / faker.first_name()	"Alice Johnson"
*last_name, surname	faker.last_name()	"Rodriguez"
*email	faker.email()	"alice@example.com"
*phone*, *tel*	faker.phone_number()	"+1-555-0123"
*address*, *street*	faker.street_address()	"742 Evergreen Terrace"
*city	faker.city()	"Toronto"
*state*, *province*	faker.state()	"Ontario"
*country*	faker.country()	"Canada"
*zip*, *postal*	faker.postcode()	"M5V 2H1"
*url*, *website*	faker.url()	"https://example.com"
*company*, *org*	faker.company()	"Acme Corp"
*title*, *subject*	faker.sentence(nb_words=5)	"Updated quarterly report summary"
*description*, *bio*, *body*	faker.paragraph()	Multi-sentence text
*created*, *updated*, *_at	faker.date_time_between(start_date='-2y')	"2024-06-15T10:30:00"
*date*, *dob*, *birth*	faker.date_of_birth(minimum_age=18)	"1990-03-22"
*price*, *amount*, *cost*	faker.pydecimal(min_value=0.01, max_value=9999.99)	49.99
*quantity*, *count*	faker.random_int(min=1, max=100)	7
*status*	Random from enum or ["active", "inactive", "pending"]	"active"
*uuid*, *guid*	faker.uuid4()	"550e8400-e29b-41d4-a716-446655440000"
*ip*, *ip_address*	faker.ipv4()	"192.168.1.42"
*color*, *colour*	faker.hex_color()	"#3498db"
*password*, *hash*	faker.sha256()	Hash string (never plaintext)
*image*, *avatar*, *photo*	faker.image_url()	"https://picsum.photos/200"
*slug*	faker.slug()	"updated-quarterly-report"
*username*, *login*	faker.user_name()	"alice_johnson42"

Type Fallback Mapping

When column name does not match any pattern, fall back to type-based generation:

Canonical Type	Generator
string	faker.pystr(max_chars=max_length)
integer	faker.random_int(min=0, max=2147483647)
float	faker.pyfloat(min_value=0, max_value=10000)
decimal	faker.pydecimal(left_digits=precision-scale, right_digits=scale)
boolean	faker.pybool()
datetime	faker.date_time_between(start_date='-2y', end_date='now')
date	faker.date_between(start_date='-2y', end_date='today')
uuid	faker.uuid4()
json	{"key": faker.word(), "value": faker.sentence()}

Locale Support

Supported locales affect names, addresses, phone formats, and postal codes:

Locale	Names	Addresses	Phone	Currency
en_US	English names	US addresses	US format	USD
en_CA	English names	Canadian addresses	CA format	CAD
en_GB	English names	UK addresses	UK format	GBP
pt_BR	Portuguese names	Brazilian addresses	BR format	BRL
fr_FR	French names	French addresses	FR format	EUR
de_DE	German names	German addresses	DE format	EUR
ja_JP	Japanese names	Japanese addresses	JP format	JPY
es_ES	Spanish names	Spanish addresses	ES format	EUR

Default locale: en_US. Override per-profile or per-command with --locale.

Edge Case Values

Include at configurable ratio (default 10%):

Type	Edge Cases
string	Empty string "", max-length string, unicode characters, emoji, SQL special chars '; DROP TABLE --
integer	0, -1, MAX_INT, MIN_INT
float	0.0, -0.0, very small (0.0001), very large (999999.99)
date	Today, yesterday, epoch (1970-01-01), leap day (2024-02-29)
boolean	null (if nullable)
email	Plus-addressed user+tag@example.com, long domain, subdomain email