v1

_test.ipynb

@@ -0,0 +1,77 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 64,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['工作表1', 'Sheet1']"
+      ]
+     },
+     "execution_count": 64,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "\n",
+    "res = list()\n",
+    "\n",
+    "plain = pd.ExcelFile('TestA.xlsx')\n",
+    "for sheet_name in plain.sheet_names:\n",
+    "    df1 = pd.read_excel('TestA.xlsx', sheet_name=sheet_name)\n",
+    "    df2 = pd.read_excel('TestB.xlsx', sheet_name=sheet_name)\n",
+    "\n",
+    "    comparison_values = df1.values == df2.values\n",
+    "    comparison_values\n",
+    "\n",
+    "    rows,cols=np.where(comparison_values==False)\n",
+    "\n",
+    "    for item in zip(rows,cols):\n",
+    "        df1.iloc[item[0], item[1]] = '{} --> {}'.format(df1.iloc[item[0], item[1]],df2.iloc[item[0], item[1]])\n",
+    "    \n",
+    "    res.append(df1)\n",
+    "    # df1.to_excel('new.xlsx', sheet_name=sheet_name)\n",
+    "    \n",
+    "\n",
+    "with pd.ExcelWriter('new.xlsx') as writer:\n",
+    "    for index in range(len(res)):\n",
+    "        res[index].to_excel(writer, sheet_name=plain.sheet_names[index])\n",
+    "\n",
+    "pd.ExcelFile('new.xlsx').sheet_names"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.9.0 64-bit",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.0"
+  },
+  "orig_nbformat": 4,
+  "vscode": {
+   "interpreter": {
+    "hash": "fdf377d643bc1cb065454f0ad2ceac75d834452ecf289e7ba92c6b3f59a7cee1"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

app.py

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+import gradio as gr
+from gensim import models
+
+import pandas as pd
+import numpy as np
+
+#multiple inputs are passed as arguments for the same function greet
+def greet(file1, file2):
+    res = list()
+
+    plain = pd.ExcelFile(file1)
+    for sheet_name in plain.sheet_names:
+        df1 = pd.read_excel(file1, sheet_name=sheet_name)
+        df2 = pd.read_excel(file2, sheet_name=sheet_name)
+        comparison_values = df1.values == df2.values
+        rows,cols=np.where(comparison_values==False)
+        for item in zip(rows,cols):
+            df1.iloc[item[0], item[1]] = '{} --> {}'.format(df1.iloc[item[0], item[1]],df2.iloc[item[0], item[1]])
+        res.append(df1)
+        
+    with pd.ExcelWriter('new.xlsx') as writer:
+        for index in range(len(res)):
+            res[index].to_excel(writer, sheet_name=plain.sheet_names[index])
+
+    return 'new.xlsx'
+
+# iface = gr.Interface(fn=greet, inputs=["file", "file", gr.inputs.Textbox(placeholder="Enter Question here...")], outputs="text")
+iface = gr.Interface(fn=greet, inputs=['file', 'file'], outputs="file")
+iface.launch(share=True)