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| import gradio as gr | |
| import pypistats | |
| from datetime import date | |
| from dateutil.relativedelta import relativedelta | |
| import pandas as pd | |
| pd.options.plotting.backend = "plotly" | |
| def get_plot(lib, time): | |
| data = pypistats.overall(lib, total=True, format="pandas") | |
| data = data.groupby("category").get_group("with_mirrors").sort_values("date") | |
| start_date = date.today() - relativedelta(months=int(time.split(" ")[0])) | |
| data = data[(data['date'] > str(start_date))] | |
| chart = data.plot(x="date", y="downloads") | |
| return chart | |
| with gr.Blocks() as demo: | |
| gr.Markdown( | |
| """ | |
| ## Pypi Download Stats π | |
| See live download stats for all of Hugging Face's open-source libraries π€ | |
| """) | |
| with gr.Row(): | |
| lib = gr.Dropdown(["transformers", "datasets", "huggingface-hub", "gradio", "accelerate", "optimum", "evaluate", "diffusers", "timm"], label="Library") | |
| time = gr.Dropdown(["3 months", "6 months", "9 months", "12 months"], label="Downloads over the last...") | |
| plt = gr.Plot() | |
| lib.change(get_plot, [lib, time], plt) | |
| time.change(get_plot, [lib, time], plt) | |
| demo.load(get_plot, [lib, time], plt) | |
| demo.launch() |