save

.github/workflows/deploy.yaml

@@ -0,0 +1,9 @@
+name: Deploy to GitHub Pages
+on:
+  push:
+    branches: [ "main", "master" ]
+  workflow_dispatch:
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    steps: [uses: fastai/workflows/quarto-ghp@master]

.github/workflows/test.yaml

@@ -0,0 +1,7 @@
+name: CI
+on:  [workflow_dispatch, pull_request, push]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps: [uses: fastai/workflows/nbdev-ci@master]

.gitignore

@@ -0,0 +1,151 @@
+_docs/
+_proc/
+
+*.bak
+.gitattributes
+.last_checked
+.gitconfig
+*.bak
+*.log
+*~
+~*
+_tmp*
+tmp*
+tags
+*.pkg
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+env/
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+.hypothesis/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# pyenv
+.python-version
+
+# celery beat schedule file
+celerybeat-schedule
+
+# SageMath parsed files
+*.sage.py
+
+# dotenv
+.env
+
+# virtualenv
+.venv
+venv/
+ENV/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+
+.vscode
+*.swp
+
+# osx generated files
+.DS_Store
+.DS_Store?
+.Trashes
+ehthumbs.db
+Thumbs.db
+.idea
+
+# pytest
+.pytest_cache
+
+# tools/trust-doc-nbs
+docs_src/.last_checked
+
+# symlinks to fastai
+docs_src/fastai
+tools/fastai
+
+# link checker
+checklink/cookies.txt
+
+# .gitconfig is now autogenerated
+.gitconfig
+
+# Quarto installer
+.deb
+.pkg
+
+# Quarto
+.quarto

LICENSE

@@ -0,0 +1,201 @@
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MANIFEST.in

@@ -0,0 +1,5 @@
+include settings.ini
+include LICENSE
+include CONTRIBUTING.md
+include README.md
+recursive-exclude * __pycache__

README.md

@@ -0,0 +1,27 @@
+nbdev-spaces-demo
+================
+
+<!-- WARNING: THIS FILE WAS AUTOGENERATED! DO NOT EDIT! -->
+
+This is a toy python library that lets you obtain the size of any
+Hugging Face dataset. For example, we can check the size of
+[tglcourse/CelebA-faces-cropped-128](https://huggingface.co/datasets/tglcourse/CelebA-faces-cropped-128)
+like so:
+
+``` python
+from nbdev_spaces_demo import hfsize 
+hfsize("tglcourse/CelebA-faces-cropped-128")
+```
+
+    '5.49 GB'
+
+We deploy this function using Gradio and Hugging Face spaces.
+
+## Using nbdev with Gradio
+
+Gradio and Hugging Face spaces is one of the easiest way to create and
+host apps. Gradio also allows you to prototype these apps in notebooks,
+which is excellent!
+
+We show you step-by-step instructions on how to deploy a Hugging Face
+gradio app from a notebook in this example.

app.ipynb

@@ -0,0 +1,410 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8c68f03e-620c-46a9-a7ec-a6cde27043cd",
+   "metadata": {},
+   "source": [
+    "# Hugging Face Spaces\n",
+    "\n",
+    "> A demo of using nbdev with Hugging Face Spaces\n",
+    "\n",
+    "Hugging Face spaces require that your python script is named `app.py`, so your first cell should be this, which will make sure code is exported to a file named `app.py`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c3463e8e-454a-48b8-ae21-8308703d2275",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|default_exp app"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "96483373-4ae1-49b2-85ed-ceee8456df19",
+   "metadata": {},
+   "source": [
+    "# Create a Gradio-enabled Space on Hugging Face\n",
+    "\n",
+    "The first step is to create a space and select the appropriate sdk (which is Gradio in this example), per [these instructions](https://huggingface.co/docs/hub/spaces-overview#creating-a-new-space):"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b34d7ec6-69b8-48c4-a68b-fad6db3c2fab",
+   "metadata": {},
+   "source": [
+    "![](./create_space.png)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c25e8e7a-52d9-4305-a107-ba03e3d6a5f3",
+   "metadata": {},
+   "source": [
+    "After you are done creating the space, **clone the repo to the root of your nbdev project.**  In this example, I ran the command `git clone https://huggingface.co/spaces/hamel/hfspace_demo` from the root of this repository."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff26114c-329b-4a97-98b5-c652554b0114",
+   "metadata": {},
+   "source": [
+    "## Make an app with Gradio"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14a884fc-36e2-43ec-8e42-ca2903aaa4de",
+   "metadata": {},
+   "source": [
+    "Below, we will create a [gradio](https://gradio.app/) in a notebook and show you how to deploy it to [Hugging Face Spaces](https://huggingface.co/docs/hub/spaces).\n",
+    "\n",
+    "First, lets specify the libraries we need, which in this case are gradio, and the nbdev project which in this case is `nbdev_spaces_demo`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e5e5d597-19ad-46e5-81ad-8f646d8a1c21",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "import gradio as gr\n",
+    "from nbdev_spaces_demo import hfsize "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9ff9f84d-7744-46ad-80ed-2cf1fa6d0643",
+   "metadata": {},
+   "source": [
+    "As a reminder, `hfsize` can be used to check the size of a Hugging Face Dataset. For example, we can check the size of [tglcourse/CelebA-faces-cropped-128](https://huggingface.co/datasets/tglcourse/CelebA-faces-cropped-128) like so:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "95bc32b8-d8ff-4761-a2d7-0880c51d0a42",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'5.49 GB'"
+      ]
+     },
+     "execution_count": null,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hfsize(\"tglcourse/CelebA-faces-cropped-128\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cb13747b-ea48-4146-846d-deb9e855d32d",
+   "metadata": {},
+   "source": [
+    "You can construct a simple UI with the `gradio.interface` and then call the `launch` method of that interface to display a preview in a notebook.  This is a great way to test your app to see if it works"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7b20e2a1-b622-4970-9069-0202ce10a2ce",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7860\n",
+      "\n",
+      "To create a public link, set `share=True` in `launch()`.\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"500\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(<gradio.routes.App>, 'http://127.0.0.1:7860/', None)"
+      ]
+     },
+     "execution_count": null,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "#|export\n",
+    "iface = gr.Interface(fn=hfsize, inputs=gr.Text(value=\"tglcourse/CelebA-faces-cropped-128\"), outputs=\"text\")\n",
+    "iface.launch(width=500)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "59926b18-a9af-4387-9fcc-f88e588da577",
+   "metadata": {},
+   "source": [
+    "Note how running the `launch()` method in a notebook runs a webserver in the background.  Below, we call the `close()` method to close the webserver."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "39d7be72-9389-42cf-91b1-78e8f4bbd083",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Closing server running on port: 7860\n"
+     ]
+    }
+   ],
+   "source": [
+    "# this is only necessary in a notebook\n",
+    "iface.close()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "249b2cd7-3123-45bf-945f-882b8a964cf5",
+   "metadata": {},
+   "source": [
+    "## Converting This Notebook Into A Gradio App"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5c18ca6e-8de8-49e1-b95a-304070bbc171",
+   "metadata": {},
+   "source": [
+    "In order to host this code on Hugging Faces spaces, we need to do the following:\n",
+    "\n",
+    "1. Export parts of this notebook to a script named `app.py`\n",
+    "2. Create a `requirements.txt` file specifying all the dependencies of the gradio app which is inferred from `settings.ini`"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1971847f-8d70-429b-8dd2-292d3e329266",
+   "metadata": {},
+   "source": [
+    "We can achieve this with the below code, note how we are exporting the code to the `hfspace_demo/` directory, which is the repo we cloned in the first step."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6706d92c-5785-4f09-9773-b9a944c493a5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from nbdev.export import nb_export\n",
+    "from nbdev.release import write_requirements\n",
+    "\n",
+    "app_dir = 'hfspace_demo/'\n",
+    "nb_export('app.ipynb', app_dir)\n",
+    "write_requirements(app_dir)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "662a58d6-a907-4a7f-962e-35859687a1e4",
+   "metadata": {},
+   "source": [
+    "We can vendor in our python library generated with nbdev (named `nbdev_spaces_demo`) into the directory as well like so:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "128b042e-7a8a-4485-94af-46e7efee8557",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from nbdev.config import get_config\n",
+    "!cp -r {str(get_config().lib_path)} {app_dir}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0182403f-d1d6-48c0-8e66-46aefb23a9ab",
+   "metadata": {},
+   "source": [
+    "<div>\n",
+    "<link rel=\"stylesheet\" href=\"https://gradio.s3-us-west-2.amazonaws.com/2.6.5/static/bundle.css\">\n",
+    "<div id=\"target\"></div>\n",
+    "<script src=\"https://gradio.s3-us-west-2.amazonaws.com/2.6.5/static/bundle.js\"></script>\n",
+    "<script>\n",
+    "launchGradioFromSpaces(\"abidlabs/question-answering\", \"#target\")\n",
+    "</script>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "84d5fd19-7880-459c-8382-b3574ed11141",
+   "metadata": {},
+   "source": [
+    "### Understanding what is generated"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0b783f0-cd5a-4092-b19c-8d05a978ce3c",
+   "metadata": {},
+   "source": [
+    "The contents of the hfspace_demo/ folder will contain these assets:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "a8d6b05f-1d17-4000-b82a-7fd4eb3092c5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "README.md         app.py            \u001b[1m\u001b[36mnbdev_spaces_demo\u001b[m\u001b[m requirements.txt\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls hfspace_demo/"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9ea562e7-b67a-45df-b822-2f4528a307c2",
+   "metadata": {},
+   "source": [
+    "Notice how the contents of app.py only contains the exported cells from this notebook:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4bae6a5c-58bc-4a0f-9aac-34c092150fdc",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\u001b[0;31m# AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0;31m# %% auto 0\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0m__all__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m'iface'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0;31m# %% ../app.ipynb 7\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0;32mimport\u001b[0m \u001b[0mgradio\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mgr\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0;32mfrom\u001b[0m \u001b[0mnbdev_spaces_demo\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mhfsize\u001b[0m \u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0;31m# %% ../app.ipynb 11\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0miface\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mgr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mInterface\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mhfsize\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mgr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mText\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mvalue\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"tglcourse/CelebA-faces-cropped-128\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutputs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"text\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\n",
+       "\u001b[0;34m\u001b[0m\u001b[0miface\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mlaunch\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwidth\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m500\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "%pycat hfspace_demo/app.py"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aadb4817-0671-4d05-9abc-d16776e2bec7",
+   "metadata": {},
+   "source": [
+    "Similarly, the contents of requirements.txt contain all dependencies listed in `settings.ini` from the `requirments` and `pip_requirements` fields (which in this case is just `fastcore`:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "831333c4-5e67-46fd-bd73-81a61cbcbd86",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "fastcore\n"
+     ]
+    }
+   ],
+   "source": [
+    "!cat hfspace_demo/requirements.txt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f15d9c78-1f55-449e-8058-9af1832367a0",
+   "metadata": {},
+   "source": [
+    "## Launching Your Gradio App\n",
+    "\n",
+    "To launch your gradio app, you need to commit the changes in the Hugging Face repo.  \n",
+    "\n",
+    "First, change directories to your huggingface repo (in this case its a directory called `hfspace_demo/`:\n",
+    "\n",
+    "`cd hfspace_demo`\n",
+    "\n",
+    "Then commit all changes\n",
+    "\n",
+    "```\n",
+    "git add -A; git commit -m \"Add application files\"; git push\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fa661f93-73b4-465a-9c22-cc38197505cb",
+   "metadata": {},
+   "source": [
+    "## Voilà!  Enjoy your Gradio App"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9b20ff94-6842-4078-9ec1-be740944e721",
+   "metadata": {},
+   "source": [
+    "After a couple of minutes, you will see your app published!  "
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

hfspace_demo

@@ -0,0 +1 @@
+Subproject commit 4b24ff04a9705aaaf5a62a209ab654394e665b20

nbdev_spaces_demo/__init__.py

@@ -0,0 +1,3 @@
+__version__ = "0.0.1"
+
+from .size import hfsize

nbdev_spaces_demo/_modidx.py

@@ -0,0 +1,8 @@
+# Autogenerated by nbdev
+
+d = { 'settings': { 'branch': 'master',
+                'doc_baseurl': '/nbdev-spaces-demo',
+                'doc_host': 'https://fastai.github.io',
+                'git_url': 'https://github.com/fastai/nbdev-spaces-demo',
+                'lib_path': 'nbdev_spaces_demo'},
+  'syms': {'nbdev_spaces_demo.size': {'nbdev_spaces_demo.size.hfsize': ('size.html#hfsize', 'nbdev_spaces_demo/size.py')}}}

nbdev_spaces_demo/size.py

@@ -0,0 +1,15 @@
+# AUTOGENERATED! DO NOT EDIT! File to edit: ../nbs/size.ipynb.
+
+# %% auto 0
+__all__ = ['hfsize']
+
+# %% ../nbs/size.ipynb 2
+from fastcore.net import urljson, HTTPError
+
+def hfsize(repo:str):
+    "Returns the size in GB of a HuggingFace Dataset."
+    url = f'https://huggingface.co/api/datasets/{repo}'
+    try: resp = urljson(f'{url}/treesize/main')
+    except HTTPError: return f'Did not find repo: {url}'
+    gb = resp['size'] / 1e9
+    return f'{gb:.2f} GB'

nbs/_quarto.yml

@@ -0,0 +1,20 @@
+project:
+  type: website
+
+format:
+  html:
+    theme: cosmo
+    css: styles.css
+    toc: true
+
+website:
+  twitter-card: true
+  open-graph: true
+  repo-actions: [issue]
+  navbar:
+    background: primary
+    search: true
+  sidebar:
+    style: floating
+
+metadata-files: [nbdev.yml, sidebar.yml]

nbs/index.ipynb

@@ -0,0 +1,75 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# nbdev-spaces-demo\n",
+    "\n",
+    "> A demo of how to create a Hugging Face Space with gradio within a nbdev project."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This is a toy python library that lets you obtain the size of any Hugging Face dataset.  For example, we can check the size of [tglcourse/CelebA-faces-cropped-128](https://huggingface.co/datasets/tglcourse/CelebA-faces-cropped-128) like so:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'5.49 GB'"
+      ]
+     },
+     "execution_count": null,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from nbdev_spaces_demo import hfsize \n",
+    "hfsize(\"tglcourse/CelebA-faces-cropped-128\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We deploy this function using Gradio and Hugging Face spaces."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Using nbdev with Gradio\n",
+    "\n",
+    "Gradio and Hugging Face spaces is one of the easiest way to create and host apps. Gradio also allows you to prototype these apps in notebooks, which is excellent!  \n",
+    "\n",
+    "We show you step-by-step instructions on how to deploy a Hugging Face gradio app from a notebook in this example."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

nbs/nbdev.yml

@@ -0,0 +1,9 @@
+project:
+  output-dir: _docs
+
+website:
+  title: "nbdev-spaces-demo"
+  site-url: "https://fastai.github.io/nbdev-spaces-demo"
+  description: "A demo of how to create a Hugging Face Space with gradio within a nbdev project."
+  repo-branch: master
+  repo-url: "https://github.com/fastai/nbdev-spaces-demo"

nbs/size.ipynb

@@ -0,0 +1,94 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# size\n",
+    "> Determine the size of a Hugging Face Dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#| default_exp size"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#|export\n",
+    "from fastcore.net import urljson, HTTPError\n",
+    "\n",
+    "def hfsize(repo:str):\n",
+    "    \"Returns the size in GB of a HuggingFace Dataset.\"\n",
+    "    url = f'https://huggingface.co/api/datasets/{repo}'\n",
+    "    try: resp = urljson(f'{url}/treesize/main')\n",
+    "    except HTTPError: return f'Did not find repo: {url}'\n",
+    "    gb = resp['size'] / 1e9\n",
+    "    return f'{gb:.2f} GB'"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`size` take as an input a [Hugging Face Dataset](https://huggingface.co/docs/datasets/index) repo and returns the total size in GB of the data.\n",
+    "\n",
+    "For example, we can check the size of [tglcourse/CelebA-faces-cropped-128](https://huggingface.co/datasets/tglcourse/CelebA-faces-cropped-128) like so:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'5.49 GB'"
+      ]
+     },
+     "execution_count": null,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "hfsize(\"tglcourse/CelebA-faces-cropped-128\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#| hide\n",
+    "import nbdev; nbdev.nbdev_export()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

nbs/styles.css

@@ -0,0 +1,37 @@
+.cell {
+  margin-bottom: 1rem;
+}
+
+.cell > .sourceCode {
+  margin-bottom: 0;
+}
+
+.cell-output > pre {
+  margin-bottom: 0;
+}
+
+.cell-output > pre, .cell-output > .sourceCode > pre, .cell-output-stdout > pre {
+  margin-left: 0.8rem;
+  margin-top: 0;
+  background: none;
+  border-left: 2px solid lightsalmon;
+  border-top-left-radius: 0;
+  border-top-right-radius: 0;
+}
+
+.cell-output > .sourceCode {
+  border: none;
+}
+
+.cell-output > .sourceCode {
+  background: none;
+  margin-top: 0;
+}
+
+div.description {
+  padding-left: 2px;
+  padding-top: 5px;
+  font-style: italic;
+  font-size: 135%;
+  opacity: 70%;
+}

settings.ini

@@ -0,0 +1,42 @@
+[DEFAULT]
+# All sections below are required unless otherwise specified.
+# See https://github.com/fastai/nbdev/blob/master/settings.ini for examples.
+
+### Python library ###
+repo = nbdev-spaces-demo
+lib_name = %(repo)s
+version = 0.0.1
+min_python = 3.7
+license = apache2
+
+### nbdev ###
+doc_path = _docs
+lib_path = nbdev_spaces_demo
+nbs_path = nbs
+recursive = True
+tst_flags = notest
+put_version_in_init = True
+
+### Docs ###
+branch = master
+custom_sidebar = False
+doc_host = https://%(user)s.github.io
+doc_baseurl = /%(repo)s
+git_url = https://github.com/%(user)s/%(repo)s
+title = %(lib_name)s
+
+### PyPI ###
+audience = Developers
+author = Hamel Husain
+author_email = [email protected]
+copyright = 2022 onwards, %(author)s
+description = A demo of how to create a Hugging Face Space with gradio within a nbdev project.
+keywords = nbdev jupyter notebook python
+language = English
+status = 3
+user = fastai
+
+### Optional ###
+requirements = fastcore
+dev_requirements = gradio
+# console_scripts =

setup.py

@@ -0,0 +1,57 @@
+from pkg_resources import parse_version
+from configparser import ConfigParser
+import setuptools
+assert parse_version(setuptools.__version__)>=parse_version('36.2')
+
+# note: all settings are in settings.ini; edit there, not here
+config = ConfigParser(delimiters=['='])
+config.read('settings.ini')
+cfg = config['DEFAULT']
+
+cfg_keys = 'version description keywords author author_email'.split()
+expected = cfg_keys + "lib_name user branch license status min_python audience language".split()
+for o in expected: assert o in cfg, "missing expected setting: {}".format(o)
+setup_cfg = {o:cfg[o] for o in cfg_keys}
+
+licenses = {
+    'apache2': ('Apache Software License 2.0','OSI Approved :: Apache Software License'),
+    'mit': ('MIT License', 'OSI Approved :: MIT License'),
+    'gpl2': ('GNU General Public License v2', 'OSI Approved :: GNU General Public License v2 (GPLv2)'),
+    'gpl3': ('GNU General Public License v3', 'OSI Approved :: GNU General Public License v3 (GPLv3)'),
+    'bsd3': ('BSD License', 'OSI Approved :: BSD License'),
+}
+statuses = [ '1 - Planning', '2 - Pre-Alpha', '3 - Alpha',
+    '4 - Beta', '5 - Production/Stable', '6 - Mature', '7 - Inactive' ]
+py_versions = '3.6 3.7 3.8 3.9 3.10'.split()
+
+requirements = cfg.get('requirements','').split()
+if cfg.get('pip_requirements'): requirements += cfg.get('pip_requirements','').split()
+min_python = cfg['min_python']
+lic = licenses.get(cfg['license'].lower(), (cfg['license'], None))
+dev_requirements = (cfg.get('dev_requirements') or '').split()
+
+setuptools.setup(
+    name = cfg['lib_name'],
+    license = lic[0],
+    classifiers = [
+        'Development Status :: ' + statuses[int(cfg['status'])],
+        'Intended Audience :: ' + cfg['audience'].title(),
+        'Natural Language :: ' + cfg['language'].title(),
+    ] + ['Programming Language :: Python :: '+o for o in py_versions[py_versions.index(min_python):]] + (['License :: ' + lic[1] ] if lic[1] else []),
+    url = cfg['git_url'],
+    packages = setuptools.find_packages(),
+    include_package_data = True,
+    install_requires = requirements,
+    extras_require={ 'dev': dev_requirements },
+    dependency_links = cfg.get('dep_links','').split(),
+    python_requires  = '>=' + cfg['min_python'],
+    long_description = open('README.md').read(),
+    long_description_content_type = 'text/markdown',
+    zip_safe = False,
+    entry_points = {
+        'console_scripts': cfg.get('console_scripts','').split(),
+        'nbdev': [f'{cfg.get("lib_path")}={cfg.get("lib_path")}._modidx:d']
+    },
+    **setup_cfg)
+
+