docs(examples:skip) Use dict for framework and datasets links (#3709)

adap · Jul 4, 2024 · 049d929 · 049d929
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diff --git a/dev/build-example-docs.py b/dev/build-example-docs.py
@@ -61,19 +61,65 @@
     "other": {"table": table_headers, "list": ""},
 }
 
+urls = {
+    # Frameworks
+    "Android": "https://www.android.com/",
+    "C++": "https://isocpp.org/",
+    "Docker": "https://www.docker.com/",
+    "JAX": "https://jax.readthedocs.io/en/latest/",
+    "Java": "https://www.java.com/",
+    "Keras": "https://keras.io/",
+    "Kotlin": "https://kotlinlang.org/",
+    "mlcube": "https://docs.mlcommons.org/mlcube/",
+    "MLX": "https://ml-explore.github.io/mlx/build/html/index.html",
+    "MONAI": "https://monai.io/",
+    "PEFT": "https://huggingface.co/docs/peft/index",
+    "Swift": "https://www.swift.org/",
+    "TensorFlowLite": "https://www.tensorflow.org/lite",
+    "fastai": "https://fast.ai/",
+    "lifelines": "https://lifelines.readthedocs.io/en/latest/index.html",
+    "lightning": "https://lightning.ai/docs/pytorch/stable/",
+    "numpy": "https://numpy.org/",
+    "opacus": "https://opacus.ai/",
+    "pandas": "https://pandas.pydata.org/",
+    "scikit-learn": "https://scikit-learn.org/",
+    "tabnet": "https://github.com/titu1994/tf-TabNet",
+    "tensorboard": "https://www.tensorflow.org/tensorboard",
+    "tensorflow": "https://www.tensorflow.org/",
+    "torch": "https://pytorch.org/",
+    "torchvision": "https://pytorch.org/vision/stable/index.html",
+    "transformers": "https://huggingface.co/docs/transformers/index",
+    "wandb": "https://wandb.ai/home",
+    "whisper": "https://huggingface.co/openai/whisper-tiny",
+    "xgboost": "https://xgboost.readthedocs.io/en/stable/",
+    # Datasets
+    "Adult Census Income": "https://www.kaggle.com/datasets/uciml/adult-census-income/data",
+    "Alpaca-GPT4": "https://huggingface.co/datasets/vicgalle/alpaca-gpt4",
+    "CIFAR-10": "https://huggingface.co/datasets/uoft-cs/cifar10",
+    "HIGGS": "https://archive.ics.uci.edu/dataset/280/higgs",
+    "IMDB": "https://huggingface.co/datasets/stanfordnlp/imdb",
+    "Iris": "https://scikit-learn.org/stable/auto_examples/datasets/plot_iris_dataset.html",
+    "MNIST": "https://huggingface.co/datasets/ylecun/mnist",
+    "MedNIST": "https://medmnist.com/",
+    "Oxford Flower-102": "https://www.robots.ox.ac.uk/~vgg/data/flowers/102/",
+    "SpeechCommands": "https://huggingface.co/datasets/google/speech_commands",
+    "Titanic": "https://www.kaggle.com/competitions/titanic",
+}
 
-def _convert_to_link(search_result):
-    if "|" in search_result:
-        if "," in search_result:
-            result = ""
-            for part in search_result.split(","):
-                result += f"{_convert_to_link(part)}, "
-            return result[:-2]
-
-        name, url = search_result.replace('"', "").split("|")
-        return f"`{name.strip()} <{url.strip()}>`_"
 
-    return search_result
+def _convert_to_link(search_result):
+    if "," in search_result:
+        result = ""
+        for part in search_result.split(","):
+            result += f"{_convert_to_link(part)}, "
+        return result[:-2]
+    else:
+        search_result = search_result.strip()
+        name, url = search_result, urls.get(search_result, None)
+        if url:
+            return f"`{name.strip()} <{url.strip()}>`_"
+        else:
+            return search_result
 
 
 def _read_metadata(example):
@@ -85,7 +131,7 @@ def _read_metadata(example):
         raise ValueError("Metadata block not found")
     metadata = metadata_match.group(1)
 
-    title_match = re.search(r"^title:\s*(.+)$", metadata, re.MULTILINE)
+    title_match = re.search(r"^# (.+)$", content, re.MULTILINE)
     if not title_match:
         raise ValueError("Title not found in metadata")
     title = title_match.group(1).strip()
@@ -163,7 +209,7 @@ def _copy_images(example):
                 )
 
 
-def _add_all_entries(index_file):
+def _add_all_entries():
     examples_dir = os.path.join(ROOT, "examples")
     for example in sorted(os.listdir(examples_dir)):
         example_path = os.path.join(examples_dir, example)
@@ -211,7 +257,7 @@ def _main():
         )
         index_file.write(categories["other"]["table"])
 
-        _add_all_entries(index_file)
+        _add_all_entries()
 
         index_file.write(
             "\n.. toctree::\n  :maxdepth: 1\n  :caption: Quickstart\n  :hidden:\n\n"

diff --git a/examples/advanced-pytorch/README.md b/examples/advanced-pytorch/README.md
@@ -1,8 +1,7 @@
 ---
-title: Advanced Flower Example using PyTorch
 tags: [advanced, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [torch | https://pytorch.org/, torchvision | https://pytorch.org/vision/stable/index.html]
+dataset: [CIFAR-10]
+framework: [torch, torchvision]
 ---
 
 # Advanced Flower Example (PyTorch)

diff --git a/examples/advanced-tensorflow/README.md b/examples/advanced-tensorflow/README.md
@@ -1,8 +1,7 @@
 ---
-title: Advanced Flower Example using TensorFlow/Keras
 tags: [advanced, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [tensorflow | https://www.tensorflow.org/, Keras | https://keras.io/]
+dataset: [CIFAR-10]
+framework: [tensorflow, Keras]
 ---
 
 # Advanced Flower Example (TensorFlow/Keras)

diff --git a/examples/android-kotlin/README.md b/examples/android-kotlin/README.md
@@ -1,9 +1,7 @@
 ---
-title: Flower Android Example using Kotlin and TF Lite
-tags: [basic, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [Android | https://www.android.com/, Kotlin | https://kotlinlang.org/,
-  TensorFlowLite | https://www.tensorflow.org/lite]
+tags: [mobile, vision, sdk]
+dataset: [CIFAR-10]
+framework: [Android, Kotlin, TensorFlowLite]
 ---
 
 # Flower Android Client Example with Kotlin and TensorFlow Lite 2022

diff --git a/examples/android/README.md b/examples/android/README.md
@@ -1,9 +1,7 @@
 ---
-title: Flower Android Example using Java and TF Lite
-tags: [basic, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [Android | https://www.android.com/, Java | https://www.java.com/, TensorFlowLite
-      | https://www.tensorflow.org/lite]
+tags: [mobile, vision, sdk]
+dataset: [CIFAR-10]
+framework: [Android, Java, TensorFlowLite]
 ---
 
 # Flower Android Example (TensorFlowLite)

diff --git a/examples/app-pytorch/README.md b/examples/app-pytorch/README.md
@@ -1,8 +1,7 @@
 ---
-title: Example Flower App using PyTorch
 tags: [basic, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [torch | https://pytorch.org/, torchvision | https://pytorch.org/vision/stable/index.html]
+dataset: [CIFAR-10]
+framework: [torch, torchvision]
 ---
 
 # Flower App (PyTorch) 🧪

diff --git a/examples/app-secure-aggregation/README.md b/examples/app-secure-aggregation/README.md
@@ -1,8 +1,7 @@
 ---
-title: Example Flower App with Secure Aggregation
 tags: [basic, vision, fds]
 dataset: []
-framework: [numpy | https://numpy.org/]
+framework: [numpy]
 ---
 
 # Secure aggregation with Flower (the SecAgg+ protocol) 🧪

diff --git a/examples/custom-metrics/README.md b/examples/custom-metrics/README.md
@@ -1,8 +1,8 @@
 ---
 title: Example Flower App with Custom Metrics
 tags: [basic, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [tensorflow | https://www.tensorflow.org/]
+dataset: [CIFAR-10]
+framework: [tensorflow]
 ---
 
 # Flower Example using Custom Metrics

diff --git a/examples/custom-mods/README.md b/examples/custom-mods/README.md
@@ -1,8 +1,7 @@
 ---
-title: Example Flower App with Custom Mods
 tags: [mods, monitoring, app]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [wandb | https://wandb.ai/home, tensorboard | https://www.tensorflow.org/tensorboard]
+dataset: [CIFAR-10]
+framework: [wandb, tensorboard]
 ---
 
 # Using custom mods 🧪
@@ -214,7 +213,7 @@ app = fl.client.ClientApp(
     client_fn=client_fn,
     mods=[
         get_wandb_mod("Custom mods example"),
-     ],
+    ],
 )
 ```
 

diff --git a/examples/embedded-devices/README.md b/examples/embedded-devices/README.md
@@ -1,8 +1,7 @@
 ---
-title: Flower Embedded Devices Example
 tags: [basic, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10, MNIST | https://huggingface.co/datasets/ylecun/mnist]
-framework: [torch | https://pytorch.org/, tensorflow | https://www.tensorflow.org/]
+dataset: [CIFAR-10, MNIST]
+framework: [torch, tensorflow]
 ---
 
 # Federated Learning on Embedded Devices with Flower
@@ -187,7 +186,7 @@ If you are working on this tutorial on your laptop or desktop, it can host the F
 
 ## Running Embedded FL with Flower
 
-For this demo, we'll be using [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10](https://www.cs.toronto.edu/~kriz/cifar.html), a popular dataset for image classification comprised of 10 classes (e.g. car, bird, airplane) and a total of 60K `32x32` RGB images. The training set contains 50K images. The server will automatically download the dataset should it not be found in `./data`. The clients do the same. The dataset is by default split into 50 partitions (each to be assigned to a different client). This can be controlled with the `NUM_CLIENTS` global variable in the client scripts. In this example, each device will play the role of a specific user (specified via `--cid` -- we'll show this later) and therefore only do local training with that portion of the data. For CIFAR-10, clients will be training a MobileNet-v2/3 model.
+For this demo, we'll be using [CIFAR-10](https://www.cs.toronto.edu/~kriz/cifar.html), a popular dataset for image classification comprised of 10 classes (e.g. car, bird, airplane) and a total of 60K `32x32` RGB images. The training set contains 50K images. The server will automatically download the dataset should it not be found in `./data`. The clients do the same. The dataset is by default split into 50 partitions (each to be assigned to a different client). This can be controlled with the `NUM_CLIENTS` global variable in the client scripts. In this example, each device will play the role of a specific user (specified via `--cid` -- we'll show this later) and therefore only do local training with that portion of the data. For CIFAR-10, clients will be training a MobileNet-v2/3 model.
 
 You can run this example using MNIST and a smaller CNN model by passing flag `--mnist`. This is useful if you are using devices with a very limited amount of memory (e.g. RaspberryPi Zero) or if you want the training taking place on the embedded devices to be much faster (specially if these are CPU-only). The partitioning of the dataset is done in the same way.
 

diff --git a/examples/federated-kaplan-meier-fitter/README.md b/examples/federated-kaplan-meier-fitter/README.md
@@ -1,9 +1,7 @@
 ---
-title: Flower Example using KaplanMeierFitter
 tags: [estimator, medical]
-dataset: [Waltons | 
-      https://lifelines.readthedocs.io/en/latest/lifelines.datasets.html#lifelines.datasets.load_waltons]
-framework: [lifelines | https://lifelines.readthedocs.io/en/latest/index.html]
+dataset: [Waltons]
+framework: [lifelines]
 ---
 
 # Flower Example using KaplanMeierFitter

diff --git a/examples/fl-dp-sa/README.md b/examples/fl-dp-sa/README.md
@@ -1,8 +1,7 @@
 ---
-title: Example of Flower App with DP and SA
 tags: [basic, vision, fds]
-dataset: [MNIST | https://huggingface.co/datasets/ylecun/mnist]
-framework: [torch | https://pytorch.org/, torchvision | https://pytorch.org/vision/stable/index.html]
+dataset: [MNIST]
+framework: [torch, torchvision]
 ---
 
 # Example of Flower App with DP and SA

diff --git a/examples/fl-tabular/README.md b/examples/fl-tabular/README.md
@@ -1,8 +1,7 @@
 ---
-title: Flower Example on Adult Census Income Tabular Dataset
 tags: [basic, tabular, fds]
-dataset: [Adult Census Income | https://www.kaggle.com/datasets/uciml/adult-census-income/data]
-framework: [scikit-learn | https://scikit-learn.org/, torch | https://pytorch.org/]
+dataset: [Adult Census Income]
+framework: [scikit-learn, torch]
 ---
 
 # Flower Example on Adult Census Income Tabular Dataset

diff --git a/examples/flower-authentication/README.md b/examples/flower-authentication/README.md
@@ -1,8 +1,7 @@
 ---
-title: Flower Example with Authentication
 tags: [advanced, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [torch | https://pytorch.org/, torchvision | https://pytorch.org/vision/stable/index.html]
+dataset: [CIFAR-10]
+framework: [torch, torchvision]
 ---
 
 # Flower Authentication with PyTorch 🧪

diff --git a/examples/flower-in-30-minutes/README.md b/examples/flower-in-30-minutes/README.md
@@ -1,8 +1,7 @@
 ---
-title: 30-minute tutorial running Flower simulation with PyTorch
 tags: [colab, vision, simulation]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [torch | https://pytorch.org/]
+dataset: [CIFAR-10]
+framework: [torch]
 ---
 
 # 30-minute tutorial running Flower simulation with PyTorch

diff --git a/examples/flower-simulation-step-by-step-pytorch/README.md b/examples/flower-simulation-step-by-step-pytorch/README.md
@@ -1,8 +1,7 @@
 ---
-title: Flower Simulation Step-by-Step
 tags: [basic, vision, simulation]
-dataset: [MNIST | https://huggingface.co/datasets/ylecun/mnist]
-framework: [torch | https://pytorch.org/]
+dataset: [MNIST]
+framework: [torch]
 ---
 
 # Flower Simulation Step-by-Step

diff --git a/examples/flower-via-docker-compose/README.md b/examples/flower-via-docker-compose/README.md
@@ -1,8 +1,8 @@
 ---
 title: Leveraging Flower and Docker for Device Heterogeneity Management in FL
 tags: [deployment, vision, tutorial]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [Docker | https://www.docker.com/, tensorflow | https://www.tensorflow.org/]
+dataset: [CIFAR-10]
+framework: [Docker, tensorflow]
 ---
 
 # Leveraging Flower and Docker for Device Heterogeneity Management in Federated Learning

diff --git a/examples/ios/README.md b/examples/ios/README.md
@@ -1,8 +1,7 @@
 ---
-title: Simple Flower Example on iOS
-tags: [mobile, vision, fds]
-dataset: [MNIST | https://huggingface.co/datasets/ylecun/mnist]
-framework: [Swift | https://www.swift.org/]
+tags: [mobile, vision, sdk]
+dataset: [MNIST]
+framework: [Swift]
 ---
 
 # FLiOS - A Flower SDK for iOS Devices with Example

diff --git a/examples/llm-flowertune/README.md b/examples/llm-flowertune/README.md
@@ -1,8 +1,8 @@
 ---
 title: Federated LLM Fine-tuning with Flower
 tags: [llm, nlp, LLama2]
-dataset: [Alpaca-GPT4 | https://huggingface.co/datasets/vicgalle/alpaca-gpt4]
-framework: [PEFT | https://huggingface.co/docs/peft/index, torch | https://pytorch.org/]
+dataset: [Alpaca-GPT4]
+framework: [PEFT, torch]
 ---
 
 # LLM FlowerTune: Federated LLM Fine-tuning with Flower

diff --git a/examples/opacus/README.md b/examples/opacus/README.md
@@ -1,8 +1,7 @@
 ---
-title: Sample-Level Differential Privacy using Opacus
 tags: [dp, security, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [opacus | https://opacus.ai/, torch | https://pytorch.org/]
+dataset: [CIFAR-10]
+framework: [opacus, torch]
 ---
 
 # Training with Sample-Level Differential Privacy using Opacus Privacy Engine

diff --git a/examples/pytorch-federated-variational-autoencoder/README.md b/examples/pytorch-federated-variational-autoencoder/README.md
@@ -1,8 +1,7 @@
 ---
-title: Federated Variational Autoencoder using Pytorch
 tags: [basic, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [torch | https://pytorch.org/, torchvision | https://pytorch.org/vision/stable/index.html]
+dataset: [CIFAR-10]
+framework: [torch, torchvision]
 ---
 
 # Flower Example for Federated Variational Autoencoder using Pytorch

diff --git a/examples/pytorch-from-centralized-to-federated/README.md b/examples/pytorch-from-centralized-to-federated/README.md
@@ -1,8 +1,7 @@
 ---
-title: PyTorch, From Centralized To Federated
 tags: [basic, vision, fds]
-dataset: [CIFAR-10 | https://huggingface.co/datasets/uoft-cs/cifar10]
-framework: [torch | https://pytorch.org/]
+dataset: [CIFAR-10]
+framework: [torch]
 ---
 
 # PyTorch: From Centralized To Federated

diff --git a/examples/quickstart-cpp/README.md b/examples/quickstart-cpp/README.md
@@ -1,8 +1,7 @@
 ---
-title: Simple Flower Example using C++
 tags: [quickstart, linear regression, tabular]
 dataset: [Synthetic]
-framework: [C++ | https://isocpp.org/]
+framework: [C++]
 ---
 
 # Flower Clients in C++ (under development)

diff --git a/examples/quickstart-fastai/README.md b/examples/quickstart-fastai/README.md
@@ -1,8 +1,7 @@
 ---
-title: Simple Flower Example using fastai
 tags: [quickstart, vision]
-dataset: [MNIST | https://huggingface.co/datasets/ylecun/mnist]
-framework: [fastai | https://fast.ai]
+dataset: [MNIST]
+framework: [fastai]
 ---
 
 # Flower Example using fastai

diff --git a/examples/quickstart-huggingface/README.md b/examples/quickstart-huggingface/README.md
@@ -1,8 +1,7 @@
 ---
-title: Flower Transformers Example using HuggingFace
 tags: [quickstart, llm, nlp, sentiment]
-dataset: [IMDB | https://huggingface.co/datasets/stanfordnlp/imdb]
-framework: [transformers | https://huggingface.co/docs/transformers/index]
+dataset: [IMDB]
+framework: [transformers]
 ---
 
 # Federated HuggingFace Transformers using Flower and PyTorch

diff --git a/examples/quickstart-jax/README.md b/examples/quickstart-jax/README.md
@@ -1,8 +1,7 @@
 ---
-title: Simple Flower Example using Jax
 tags: [quickstart, linear regression]
 dataset: [Synthetic]
-framework: [JAX | https://jax.readthedocs.io/en/latest/]
+framework: [JAX]
 ---
 
 # JAX: From Centralized To Federated