AI agents that spec, build, test, and ship code โ with voice chat, deep GitHub integration, and zero LLM markup.
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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.
iPython DUMMY DATABASEDUMMY 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, iPython seems to be more popular. It has been mentiond 20 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.
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
As alluded to in Poetry2Nix Development Flake with Matplotlib GTK Support, Iโm currently in the process of getting my โnewโ python workflow up to speed. My second problem, after dependency and environment management, was that fancy REPLs like ipython or ptpython donโt jazz well with the standard comint based inferior python repl that comes with python-mode. One can basically only run ipython with the... - Source: dev.to / about 2 years ago
Third, if possible use a command line interpreter to test things out. I recommend ipython for this purpose. You can use your browser's developer console this way if you are learning Javascript. Source: over 3 years ago
IJulia is an interactive notebook environment powered by the Julia programming language. Its backend is integrated with that of the Jupyter environment. The interface is web-based, similar to the iPython notebook. It is open-source and cross-platform. - Source: dev.to / over 3 years ago
Also, take a look at installing iPthon to give you a much richer shell environment. This underpins Jupyter Notebooks, so is well known, proven and trusted. Source: over 3 years ago
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
Mockaroo - A realistic data generator to test your app
PyCharm - Python & Django IDE with intelligent code completion, on-the-fly error checking, quick-fixes, and much more...
DataConstruct - We fake it till you make it!
Spyder - The Scientific Python Development Environment
Data Creator - Data generator that can create a table filled with pseudo-random content.