| import requests | |
| import pandas as pd | |
| import gradio as gr | |
| from huggingface_hub.hf_api import SpaceInfo | |
| path = f"https://huggingface.co/api/spaces" | |
| def get_hugging_learners_spaces(): | |
| r = requests.get(path) | |
| d = r.json() | |
| spaces = [SpaceInfo(**x) for x in d] | |
| blocks_spaces = {} | |
| for i in range(0,len(spaces)): | |
| if spaces[i].id.split('/')[0] == 'hugginglearners' and hasattr(spaces[i], 'likes') and spaces[i].id != 'hugginglearners/Hearts_Leaderboard' and spaces[i].id != 'hugginglearners/README': | |
| blocks_spaces[spaces[i].id]=spaces[i].likes | |
| df = pd.DataFrame( | |
| [{"Spaces_Name": Spaces, "likes": likes} for Spaces,likes in blocks_spaces.items()]) | |
| df = df.sort_values(by=['likes'],ascending=False) | |
| return df | |
| block = gr.Blocks() | |
| with block: | |
| gr.Markdown("""### Leaderboard of the most popular **fastai X Hugging Face Group** (the Hugging Learners) Spaces""") | |
| gr.Markdown("""Learn more, join and become a Hugging Learner. The instructions are <a href="https://huggingface.co/hugginglearners" target="_blank" style="text-decoration: underline">here.</a>""") | |
| with gr.Tabs(): | |
| with gr.TabItem("Leaderboard of spaces with the most hearts"): | |
| with gr.Row(): | |
| data = gr.outputs.Dataframe(type="pandas") | |
| with gr.Row(): | |
| data_run = gr.Button("Refresh") | |
| data_run.click(get_hugging_learners_spaces, inputs=None, outputs=data) | |
| block.load(get_hugging_learners_spaces, inputs=None, outputs=data) | |
| block.launch() |