Spaces:
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import gradio as gr
import pandas as pd
import requests
from huggingface_hub.hf_api import SpaceInfo
path = f"https://huggingface.co/api/spaces"
def get_platzi_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] == "platzi"
and hasattr(spaces[i], "likes")
and spaces[i].id != "platzi/platzi-leaderboard"
and spaces[i].id != "platzi/README"
and spaces[i].id != "platzi/platzi-curso-streamlit-segmentacion-imagenes"
and spaces[i].id != "platzi/platzi-curso-gradio-asr"
and spaces[i].id != "platzi/platzi-curso-gradio-blocks"
and spaces[i].id != "platzi/platzi-curso-gradio-tf-clasificacion-imagenes"
and spaces[i].id != "platzi/platzi-curso-gradio-clasificacion-imagenes"
# and spaces[i].id != "platzi/platzi-curso-streamlit-butterfly-gan"
):
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 de los Spaces (demos) más populares creados por estudiantes del curso de **creación de demos de Platzi**."""
)
gr.Markdown(
"""Aprende más sobre el curso aquí y comparte para obtener más corazones 🤗.</a>"""
)
with gr.Tabs():
with gr.TabItem("Leaderboard de los Spaces con más corazones"):
with gr.Row():
data = gr.outputs.Dataframe(type="pandas")
with gr.Row():
data_run = gr.Button("Refrescar")
data_run.click(get_platzi_spaces, inputs=None, outputs=data)
block.load(get_platzi_spaces, inputs=None, outputs=data)
block.launch()
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