Update app.py

app.py

@@ -1,14 +1,15 @@
 import gradio as gr
 import pandas as pd
-from huggingface_hub.hf_api import create_repo, upload_file
+from huggingface_hub.hf_api import create_repo, upload_file, HfApi
 from huggingface_hub.repository import Repository
 import subprocess
 import os
 import tempfile
 import sweetviz as sv
 
-def analyze_datasets(dataset, dataset_name, username, token, column=None, pairwise="off"):
+def analyze_datasets(dataset, dataset_name,  token, column=None, pairwise="off"):
     df = pd.read_csv(dataset.name)
+    username = HfApi().whoami(token=token)["name"]
     if column is not None:
         analyze_report = sv.analyze(df, target_feat=column, pairwise_analysis=pairwise)
     else:
@@ -24,9 +25,10 @@ def analyze_datasets(dataset, dataset_name, username, token, column=None, pairwi
 
     return f"Your dataset report will be ready at {repo_url}"
 
-def compare_column_values(dataset, dataset_name, username, token, column, category):
+def compare_column_values(dataset, dataset_name, token, column, category):
 
     df = pd.read_csv(dataset.name)
+    username = HfApi().whoami(token=token)["name"]
     arr = df[column].unique()
     arr = list(arr[arr != column])
     compare_report = sv.compare_intra(df, df[column] == category, arr[0])
@@ -42,10 +44,11 @@ def compare_column_values(dataset, dataset_name, username, token, column, catego
 
     return f"Your dataset report will be ready at {repo_url}"
 
-def compare_dataset_splits(dataset, dataset_name, username, token, splits):
+def compare_dataset_splits(dataset, dataset_name,  token, splits):
     df = pd.read_csv(dataset.name)
     train = df.sample(frac=splits)
     test = df.loc[df.index.difference(train.index)]
+    username = HfApi().whoami(token=token)["name"]
 
     compare_report = sv.compare([train, "Training Data"], [test, "Test Data"])
     compare_report.show_html('index.html', open_browser=False)
@@ -75,15 +78,14 @@ with gr.Blocks() as demo:
                     column = gr.Text(label = "Compare dataset against a target variable (Optional)")
                     pairwise = gr.Radio(["off", "on"], label = "Enable pairwise analysis")
                     token = gr.Textbox(label = "Your Hugging Face Token")
-                    username = gr.Textbox(label = "Your Hugging Face User Name")
                     dataset_name = gr.Textbox(label = "Dataset Name")
-                    pushing_desc = gr.Markdown("This app needs your Hugging Face Hub user name, token and a unique name for your dataset report.")
+                    pushing_desc = gr.Markdown("This app needs your Hugging Face Hub token and a unique name for your dataset report.")
                     inference_run = gr.Button("Infer")
                     inference_progress = gr.StatusTracker(cover_container=True)
                 outcome = gr.outputs.Textbox()
                 inference_run.click(
                     analyze_datasets,
-                    inputs=[dataset, dataset_name, username, token, column, pairwise],
+                    inputs=[dataset, dataset_name, token, column, pairwise],
                     outputs=outcome,
                     status_tracker=inference_progress,
                 )
@@ -94,9 +96,8 @@ with gr.Blocks() as demo:
                     description = gr.Markdown("Split a dataset and compare splits. You need to give a fraction, e.g. 0.8.")
                     dataset = gr.File(label = "Dataset")
                     split_ratio = gr.Number(label = "Split Ratios")
-                    pushing_desc = gr.Markdown("This app needs your Hugging Face Hub user name, token and a unique name for your dataset report.")
+                    pushing_desc = gr.Markdown("This app needs your Hugging Face Hub token and a unique name for your dataset report.")
                     token = gr.Textbox(label = "Your Hugging Face Token")
-                    username = gr.Textbox(label = "Your Hugging Face User Name")
                     dataset_name = gr.Textbox(label = "Dataset Name")
                     inference_run = gr.Button("Infer")
                     inference_progress = gr.StatusTracker(cover_container=True)
@@ -104,7 +105,7 @@ with gr.Blocks() as demo:
                 outcome = gr.outputs.Textbox()
                 inference_run.click(
                     compare_dataset_splits,
-                    inputs=[dataset, dataset_name, username, token, split_ratio],
+                    inputs=[dataset, dataset_name, token, split_ratio],
                     outputs=outcome,
                     status_tracker=inference_progress,
                 )
@@ -117,9 +118,8 @@ with gr.Blocks() as demo:
                     dataset = gr.File(label = "Dataset")
                     column = gr.Text(label = "Enter column:")
                     category = gr.Text(label = "Enter category:")
-                    pushing_desc = gr.Markdown("This app needs your Hugging Face Hub user name, token and a unique name for your dataset report.")
+                    pushing_desc = gr.Markdown("This app needs your Hugging Face Hub token and a unique name for your dataset report.")
                     token = gr.Textbox(label = "Your Hugging Face Token")
-                    username = gr.Textbox(label = "Your Hugging Face User Name")
                     dataset_name = gr.Textbox(label = "Dataset Name")
                     inference_run = gr.Button("Run Analysis")
                     inference_progress = gr.StatusTracker(cover_container=True)
@@ -127,7 +127,7 @@ with gr.Blocks() as demo:
                 outcome = gr.outputs.Textbox()
                 inference_run.click(
                     compare_column_values,
-                    inputs=[dataset, dataset_name, username, token, column, category ],
+                    inputs=[dataset, dataset_name, token, column, category ],
                     outputs=outcome,
                     status_tracker=inference_progress,
                 )