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DUMMY DATABASE
Mockaroo
DataConstruct
Data Creator
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Random Data
Dummy Database is built to solve a simple, yet annoying problem โ generating realistic test datasets quickly, without writing scripts or juggling Excel files.
Itโs designed for: - Developers needing dummy databases for prototyping & testing. - Analysts and BI specialists preparing demo dashboards. - QA engineers creating data scenarios for testing. - SQL learners who want practice datasets on demand.
What makes it special? - Create from simple tables to full relational databases with PK/FK. - 35+ data types including Numbers, Dates, Names, Booleans, etc. - Unique Event Sequences โ simulate user actions and workflows. - Advanced data controls โ outliers, nulls, repeats, distributions. - ERD visualization to map relationships. - Built-in PostgreSQL editor to query generated data. - Export as CSV, XLSX, SQL DDL, or full ZIP. - Free up to 10,000 records per table for registered users โ no paywalls or limits.
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DUMMY DATABASE's answer:
A free, all-in-one data generation platform that builds everything from simple tables to full relational databases with advanced controls, unique event sequences, ERD visualization, built-in SQL querying, and multiple export formats โ no limits, no paywalls.
DUMMY DATABASE's answer:
Unlike other data generators, DUMMY DATABASE gives you full relational database creation, unique event simulations, advanced control over every field, built-in SQL querying, and generous free limits โ so you can go from idea to test-ready data without restrictions, subscriptions, or hidden fees
DUMMY DATABASE's answer:
DUMMY DATABASE's answer:
Began as a project for myself to be able to have custom datasets for testing purpose I've decided that it could be useful for wider audience and finalized it as a full-stack web project
DUMMY DATABASE's answer:
Python, Flask, HTML, CSS, Bootstrap, Redis, PostgreSQL, JavaScript
Based on our record, Python seems to be more popular. It has been mentiond 299 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
137Foundry provides legacy modernization services that include dependency mapping as a foundational assessment phase. Prettier and ESLint are useful companion tools for enforcing code style consistency as the refactoring proceeds. Node.js and Python.org official documentation are authoritative references for understanding the import and module systems of those runtimes. - Source: dev.to / about 2 months ago
For Python codebases, tools like Python's built-in ast module and import analysis scripts can generate call graphs. For JavaScript, ESLint and module analysis tools serve a similar purpose. GitHub advanced search can help you find all internal references to a specific function across a large repository. - Source: dev.to / about 2 months ago
Import asyncio Import aiohttp From bs4 import BeautifulSoup Async def scrape_and_parse(url: str, session: aiohttp.ClientSession) -> dict: async with session.get(url) as response: html = await response.text() # BeautifulSoup parsing happens after the await โ no issue soup = BeautifulSoup(html, "html.parser") return { "url": url, "title": soup.title.string if soup.title... - Source: dev.to / 3 months ago
**_Beginner mistake to avoid_** - Writing SQL only inside DBeaver - Always save SQL files in VS Code and commit them **Using PostgreSQL with Python** _**What Python does here**_ Python talks to PostgreSQL and says: - โSave this dataโ - โGet this dataโ - PostgreSQL listens. Python works. _**Step 1: Install Python **_ - Download from https://python.org - During install, check Add Python to PATH Screenshot... - Source: dev.to / 6 months ago
Import time Import requests Import asyncio Import aiohttp Urls = [ 'https://example.com', 'https://httpbin.org/get', 'https://python.org' ] # Synchronous version Def sync_fetch(): for url in urls: response = requests.get(url) print(f"{url} fetched with {len(response.text)} characters") # Async version Async def async_fetch(): async with aiohttp.ClientSession() as session: ... - Source: dev.to / 9 months ago
JavaScript - Lightweight, interpreted, object-oriented language with first-class functions
Mockaroo - A realistic data generator to test your app
Java - A concurrent, class-based, object-oriented, language specifically designed to have as few implementation dependencies as possible
DataConstruct - We fake it till you make it!
C++ - Has imperative, object-oriented and generic programming features, while also providing the facilities for low level memory manipulation
Data Creator - Data generator that can create a table filled with pseudo-random content.
