This project generates realistic fake sales data for a photography business using Python and the Faker library. Originally designed as a lightweight API and CSV generator using Flask, it was later ported to a Drupal module for integration into a dynamic sales dashboard.
To create believable and varied weekly photography sales data, supporting analytics dashboards, portfolio projects, and visualizations without relying on sensitive or real client data.
- Python 3
- Faker – for generating names, emails, locations, etc.
- Pandas – for CSV output
- Flask (optional) – to serve generated data via API endpoint (for early demos)
- Generates 2,000 rows of sales data
- Includes weighted categories:
- Wedding
- Portrait
- Event
- Real Estate
- Product
- Stock Photo License
- Assigns pricing ranges based on job type
- Dynamically creates:
- Purchase date (realistic day-of-week distribution)
- Shoot date and time (based on type)
- Customer name, email, city, region, and country
- Payment method
- Referral source
- Customer segment (with weights)
| Field | Description |
|---|---|
customer_name |
Random full name |
email |
Random email address |
industrytype |
Type of photography job |
purchasedate |
Simulated date of purchase |
month |
Purchase month (YYYY-MM) |
city, region, country |
Geographic metadata |
price_USD |
Estimated fee for the job |
payment_method |
How the job was paid |
referral_source |
Lead source (e.g. Instagram) |
customer_segment |
Type of buyer |
shoot_day |
Scheduled shoot day |
shoot_time |
Scheduled shoot time |
The generated data is saved to: root folder Can adjust as necessary for simplicity it is bundled as is.