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Based on our record, RegExr should be more popular than Jupyter. It has been mentiond 367 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.
Showcase and share: Easily embed UIs in Jupyter Notebook, Google Colab or share them on Hugging Face using a public link. - Source: dev.to / about 2 months ago
LangChain wasn’t designed in isolation — it was built in the data pipeline world, where every data engineer’s tool of choice was Jupyter Notebooks. Jupyter was an innovative tool, making pipeline programming easy to experiment with, iterate on, and debug. It was a perfect fit for machine learning workflows, where you preprocess data, train models, analyze outputs, and fine-tune parameters — all in a structured,... - Source: dev.to / 3 months ago
Leverage versatile resources to prototype and refine your ideas, such as Jupyter Notebooks for rapid iterations, Google Colabs for cloud-based experimentation, OpenAI’s API Playground for testing and fine-tuning prompts, and Anthropic's Prompt Engineering Library for inspiration and guidance on advanced prompting techniques. For frontend experimentation, tools like v0 are invaluable, providing a seamless way to... - Source: dev.to / 4 months ago
Lately I've been working on Langgraph4J which is a Java implementation of the more famous Langgraph.js which is a Javascript library used to create agent and multi-agent workflows by Langchain. Interesting note is that [Langchain.js] uses Javascript Jupyter notebooks powered by a DENO Jupiter Kernel to implement and document How-Tos. So, I faced a dilemma on how to use (or possibly simulate) the same approach in... - Source: dev.to / 8 months ago
One of the most convenient ways to play with datasets is to utilize Jupyter. If you are not familiar with this tool, do not worry. I will show how to use it to solve our problem. For local experiments, I like to use DataSpell by JetBrains, but there are services available online and for free. One of the most well-known services among data scientists is Kaggle. However, their notebooks don't allow you to make... - Source: dev.to / 11 months ago
However - here it becomes weird - when testing the original regex rule (the first one, without the \u00A0 part) on the same string in an interactive visualiser (https://regexr.com/ for instance), there is a match:. - Source: dev.to / 7 months ago
Learned regex in the 90's from the Perl documentation, or possibly one of the oreilly perl references. That was a time where printed language references were more convenient than searching the internet. Perl still includes a shell component for accessing it's documentation, that was invaluable in those ancient times. Perl's regex documentation is rather fantastic. `perldoc perlre` from your terminal. Or... - Source: Hacker News / 9 months ago
I read a lot on https://www.regular-expressions.info and experimented on https://rubular.com since I was also learning Ruby at the time. https://regexr.com is another good tool that breaks down your regex and matches. One of the things I remember being difficult at the beginning was the subtle differences between implementations, like `^` meaning "beginning of line" in Ruby (and others) but meaning "beginning of... - Source: Hacker News / 9 months ago
Mostly building things that needed complex RegEx, and debugging my regular expressions with https://regexr.com/. - Source: Hacker News / 9 months ago
For username: You are using the min() function to make sure the characters are not below three and, then the max() function checks that the characters are not beyond twenty-five. You also make use of Regex to make sure the username must contain only letters, numbers, and underscore. - Source: dev.to / 10 months ago
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
regular expressions 101 - Extensive regex tester and debugger with highlighting for PHP, PCRE, Python and JavaScript.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
rubular - A ruby based regular expression editor
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Expresso - The award-winning Expresso editor is equally suitable as a teaching tool for the beginning user of regular expressions or as a full-featured development environment for the experienced programmer with an extensive knowledge of regular expressions.