Initial commit

.github/workflows/main.yml

@@ -2,8 +2,9 @@ name: Sync to Hugging Face hub
 on:
   push:
     branches: [main]
-
-  # to run this workflow manually from the Actions tab
+  pull_request:
+    branches: [main]
+      # to run this workflow manually from the Actions tab
   workflow_dispatch:
 
 jobs:
@@ -16,6 +17,8 @@ jobs:
         with:
           filesizelimit: 10485760 # this is 10MB so we can sync to HF Spaces
 
+
+
   sync-to-hub:
     runs-on: ubuntu-latest
     steps:
@@ -25,5 +28,5 @@ jobs:
       - name: Push to hub
         env:
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
-        run: git push --force https://HF_USERNAME:$HF_TOKEN@huggingface.co/spaces/versus666/uplift_lab main && git push https://HF_USERNAME:$HF_TOKEN@huggingface.co/spaces/versus666/uplift_lab main
-    needs: check_files
+        run: git push --force https://HF_USERNAME:$HF_TOKEN@huggingface.co/spaces/versus666/uplift_lab main
+    needs: check_files

README.md

@@ -1,8 +1,10 @@
+
+
 ---
-title: Uplift
-emoji: 👀
-colorFrom: pink
-colorTo: yellow
+title: Uplift lab
+emoji: 🚀
+colorFrom: blue
+colorTo: green
 sdk: streamlit
 sdk_version: 1.10.0
 app_file: src/app.py

src/app.py

@@ -1,11 +1,9 @@
-import catboost
 import pandas as pd
-import os
+
 from sklift.metrics import uplift_at_k, uplift_by_percentile, qini_auc_score, qini_curve, uplift_curve
 from sklift.viz import plot_qini_curve, plot_uplift_curve
-from sklift.models import SoloModel, TwoModels, ClassTransformation
+
 import streamlit as st
-import catboost
 
 import tools
 

src/tools.py

@@ -1,16 +1,9 @@
-from typing import Any
-
 import pandas as pd
-import numpy as np
 from sklearn.model_selection import train_test_split
 from sklift.datasets import fetch_hillstrom
-from sklift.metrics import uplift_at_k, uplift_by_percentile, weighted_average_uplift
-from sklift.viz import plot_uplift_by_percentile
-from catboost import CatBoostClassifier
-import sklearn
+from sklift.metrics import weighted_average_uplift
 import streamlit as st
 import plotly.express as px
-import plotly.graph_objects as go
 
 
 def test():
@@ -18,7 +11,7 @@ def test():
 
 
 @st.experimental_memo
-def get_data() -> tuple[Any, Any, Any]:
+def get_data():
 	# получаем датасет
 	dataset = fetch_hillstrom(target_col='visit')
 	dataset, target, treatment = dataset['data'], dataset['target'], dataset['treatment']
@@ -34,7 +27,7 @@ def get_data() -> tuple[Any, Any, Any]:
 
 
 @st.experimental_memo
-def data_split(data: pd.DataFrame, treatment: pd.DataFrame, target: pd.DataFrame) -> tuple[Any, Any, Any, Any, Any, Any]:
+def data_split(data: pd.DataFrame, treatment: pd.DataFrame, target: pd.DataFrame):
 	# склеиваем threatment и target для дальнейшей стратификации по ним
 	stratify_cols = pd.concat([treatment, target], axis=1)
 	# сплитим датасет