from typing import List, Dict
import httpx
import gradio as gr
import pandas as pd
async def get_splits(dataset_name: str) -> Dict[str, List[Dict]]:
URL = f"https://datasets-server.huggingface.co/splits?dataset={dataset_name}"
async with httpx.AsyncClient() as session:
response = await session.get(URL)
return response.json()
async def get_valid_datasets() -> Dict[str, List[str]]:
URL = f"https://datasets-server.huggingface.co/valid"
async with httpx.AsyncClient() as session:
response = await session.get(URL)
datasets = response.json()["valid"]
return gr.Dropdown.update(choices=datasets, value="glue")
async def get_first_rows(dataset: str, config: str, split: str) -> Dict[str, Dict[str, List[Dict]]]:
URL = f"https://datasets-server.huggingface.co/first-rows?dataset={dataset}&config={config}&split={split}"
async with httpx.AsyncClient() as session:
response = await session.get(URL)
return response.json()
def get_df_from_rows(api_output):
return pd.DataFrame([row["row"] for row in api_output["rows"]])
async def update_configs(dataset_name: str):
splits = await get_splits(dataset_name)
all_configs = sorted(set([s["config"] for s in splits["splits"]]))
return (gr.Dropdown.update(choices=all_configs, value=all_configs[0]),
splits)
async def update_splits(config_name: str, state: gr.State):
splits_for_config = sorted(set([s["split"] for s in state["splits"] if s["config"] == config_name]))
dataset_name = state["splits"][0]["dataset"]
dataset = await update_dataset(splits_for_config[0], config_name, dataset_name)
return (gr.Dropdown.update(choices=splits_for_config, value=splits_for_config[0]), dataset)
async def update_dataset(split_name: str, config_name: str, dataset_name: str):
rows = await get_first_rows(dataset_name, config_name, split_name)
df = get_df_from_rows(rows)
return df
# Guido von Roissum: https://www.youtube.com/watch?v=-DVyjdw4t9I
# Guido says indentation style in python helps readability. Emoji's do too: https://www.kaggle.com/datasets/subinium/emojiimage-dataset
# four spaces was a compromise. Google style guide (2 spaces) Harder at a glance to understand code. 8 spaces is a whole tab stop. after inddent levels you have little room left.
with gr.Blocks() as demo:
gr.Markdown("
🥫Datasets🎨
")
gr.Markdown("""Curated Datasets:
Kaggle.
NLM UMLS.
LOINC.
ICD10 Diagnosis.
ICD11.
Papers,Code,Datasets for SOTA in Medicine.
CMS Downloads.
CMS CPT and HCPCS Procedures and Services """)
splits_data = gr.State()
with gr.Row():
dataset_name = gr.Dropdown(label="Dataset")
config = gr.Dropdown(label="Subset")
split = gr.Dropdown(label="Split")
with gr.Row():
dataset = gr.DataFrame(wrap=True)
demo.load(get_valid_datasets, inputs=None, outputs=[dataset_name])
dataset_name.change(update_configs, inputs=[dataset_name], outputs=[config, splits_data])
config.change(update_splits, inputs=[config, splits_data], outputs=[split, dataset])
split.change(update_dataset, inputs=[split, config, dataset_name], outputs=[dataset])
demo.launch(debug=True)
# original: https://huggingface.co/spaces/freddyaboulton/dataset-viewer -- Freddy thanks! Your examples are the best.
# playlist on Gradio and Mermaid: https://www.youtube.com/watch?v=o7kCD4aWMR4&list=PLHgX2IExbFosW7hWNryq8hs2bt2aj91R-
# Link to Mermaid model and code: [![](https://mermaid.ink/img/pako:eNp1U8mO2zAM_RXCZ-eQpZccCmSZTIpOMQESIAdnDrRMx0JkydXSNDOYfy_lpUgD1AfBfnx8fCTlj0SYgpJ5UipzFRVaD4flSQM_YjwafcVJ9-FCfrbYVGA0ZQeLUkt9futiOM72pEh4QFijR9iTf2tzsx3Z0ti6hxslvb_Lm0TSNPvBDhQsg1TFXXAag7NBef_9hdDqFA6knbEbdgvGwu7mjRXVkDOLOV-yNXmytdQEsoROvTfi4EhK9XTSxUNz_mo4uVHm1lPyce-uR1k_n2RHymHRNPAvNXaTT7NVZYwjeDECVbS4UiYUAyc2lc-yFoPXxkujHaAl2G54PCjIpfBssZAGtsZ5KlLYkjWXkMLiuOfjPVhiymr3_x4qS7wicneTFuMW6Gdxlb6Cb7oJvt1LbEpMso08sza8MnqskA9jL27Ij72Jafb0G-tGkQNTdgKOy_XcFP5GDxFbWsJLV3FQid2LWfZsfpHVqAXBCBYa1e2dAHUBu5Ar6dgby0ghPWxQWk2Oh_L0M0h_S2Ep0YHUrXFHXD_msefo5XEkfFWBK8atdkA7mgfoalpATJI0qfnWoCz4b_iI0VPiK6rplMz5taASg_Kn5KQ_mYrBm_1Ni2TubaA0CU2BntYSeQl1Mi9ROfr8A8FBGds?type=png)](https://mermaid.live/edit#pako:eNp1U8mO2zAM_RXCZ-eQpZccCmSZTIpOMQESIAdnDrRMx0JkydXSNDOYfy_lpUgD1AfBfnx8fCTlj0SYgpJ5UipzFRVaD4flSQM_YjwafcVJ9-FCfrbYVGA0ZQeLUkt9futiOM72pEh4QFijR9iTf2tzsx3Z0ti6hxslvb_Lm0TSNPvBDhQsg1TFXXAag7NBef_9hdDqFA6knbEbdgvGwu7mjRXVkDOLOV-yNXmytdQEsoROvTfi4EhK9XTSxUNz_mo4uVHm1lPyce-uR1k_n2RHymHRNPAvNXaTT7NVZYwjeDECVbS4UiYUAyc2lc-yFoPXxkujHaAl2G54PCjIpfBssZAGtsZ5KlLYkjWXkMLiuOfjPVhiymr3_x4qS7wicneTFuMW6Gdxlb6Cb7oJvt1LbEpMso08sza8MnqskA9jL27Ij72Jafb0G-tGkQNTdgKOy_XcFP5GDxFbWsJLV3FQid2LWfZsfpHVqAXBCBYa1e2dAHUBu5Ar6dgby0ghPWxQWk2Oh_L0M0h_S2Ep0YHUrXFHXD_msefo5XEkfFWBK8atdkA7mgfoalpATJI0qfnWoCz4b_iI0VPiK6rplMz5taASg_Kn5KQ_mYrBm_1Ni2TubaA0CU2BntYSeQl1Mi9ROfr8A8FBGds)