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@@ -32,19 +32,19 @@ The great part about this Databook is that the usage of the code is explained wi
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There are four ways to run this code. With **Binder**, with **Thebe**, **Dandihub**, or **Locally**.
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### Binder
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Binder can be used to setup the environment with [repo2docker](https://github.com/jupyterhub/repo2docker) and then execute the code in an instance of JupyterHub where the kernel is run. JupyterHub offers a lot of utilities for interacting with Jupyter notebooks and the environment. A given notebook can be launched in Binder by hovering over the `Launch` button in the top-right and selecting `Binder`. Occasionally, Binder will have to rebuild the environment before starting JupyterLab, which can take many minutes.
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Binder will automatically setup the environment with [repo2docker](https://github.com/jupyterhub/repo2docker) and then execute the code in an instance of JupyterHub where the kernel is run. JupyterHub offers a lot of utilities for interacting with Jupyter notebooks and the environment. A given notebook can be launched in Binder by hovering over the `Launch` button in the top-right and selecting `Binder`. Occasionally, Binder will have to rebuild the environment before starting JupyterLab, which can take many minutes.
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### Thebe
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[Thebe](https://github.com/executablebooks/thebe) uses Binder in the backend to prepare the environment and run the kernel. It allows users to run notebooks embedded directly within the Databook's web UI. It can be used by hovering over the `Launch` button in the top-right of a notebook and selecting `Live Code`. Thebe is a work-in-progress project and has room for improvement. It is also worth noting that, like Binder, starting the Jupyter Kernel can sometimes take many minutes.
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### Dandihub
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[Dandihub](https://hub.dandiarchive.org/) is an instance of JupyterHub hosted by DANDI. Dandihub does not automatically reproduce the environment required for these notebooks, but importantly, Dandihub allows for persistent storage of your files, so you can leave your work and come back to it later. In order to run notebooks on Dandihub, you must sign in with your github account. To set up the correct environment on Dandihub, open a `terminal` tab and navigate to the directory `openscope_databook` and run the command
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[Dandihub](https://hub.dandiarchive.org/) is an instance of JupyterHub hosted by DANDI. Dandihub does not automatically reproduce the environment required for these notebooks, but importantly, Dandihub allows for persistent storage of your files, so you can leave your work and come back to it later. It can be used by hovering over the `Launch` button in the top-right of a notebook and selecting `JupyterHub`. In order to run notebooks on Dandihub, you must sign in with your Github account. To set up the correct environment on Dandihub, open a `terminal` tab, navigate to the directory `openscope_databook` and run the command
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```
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pip install -r requirements.txt --user
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pip install -r .binder/requirements.txt --user
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```
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### Locally
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You can download an individual notebook by pressing the `Download` button in the top-right and selecting `.ipynb`. Alternatively, you can clone the repo to your machine and access the files there. The repo can be found by hovering over the the `Github` button in the top-right and selecting `repository`. When run locally, the environment can be replicated with our [requirements.txt](https://github.com/AllenInstitute/openscope_databook/blob/main/requirements.txt) file using the command
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You can download an individual notebook by pressing the `Download` button in the top-right and selecting `.ipynb`. Alternatively, you can clone the repo to your machine and access the files there. The repo can be found by hovering over the the `Github` button in the top-right and selecting `repository`. When run locally, the environment can be replicated with our [requirements.txt](https://github.com/AllenInstitute/openscope_databook/blob/main/.binder/requirements.txt) file using the command
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