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Based on our record, Jupyter seems to be a lot more popular than iMDone. While we know about 205 links to Jupyter, we've tracked only 7 mentions of iMDone. 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.
Imdone is the closest option fitting your requirements, as it saves cards in a Markdown text format with special syntax. You can either have all cards in one text file, or individual files for each card. It's pretty flexible, and development is very active. Source: over 1 year ago
I work full time as an advising consultant and software engineer, so I really need to automate a lot my work on imdone. For starters, I use imdone to plan and manage releases of imdone. - Source: dev.to / about 2 years ago
I use Obsidian (or, rather, the single top-level directory of markdown files) for my customized GTD process. Essential to me are the Imdone app (https://imdone.io) and the Tasks community plugin. They work well together. Source: about 2 years ago
You can also try https://imdone.io. Source: over 2 years ago
I’m personally using imdone which is also note-centric and extremely flexible but has a steep learning curve. Source: over 2 years ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / 11 days ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / 22 days ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / 17 days ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 2 months ago
Note. Nowadays, there are many flavors of notebooks (Jupyter, VSCode, Databricks, etc.), but they’re all built on top of IPython. Therefore, the Magics developed should be reusable across environments. - Source: dev.to / 2 months ago
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