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add notebook
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‎export_csv.ipynb‎

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@@ -2,28 +2,28 @@
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"cells": [
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{
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"cell_type": "code",
5-
"execution_count": 27,
5+
"execution_count": 64,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
12-
"shape: (8, 3)\n",
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"┌────────────────────┬───────┬──────────┐\n",
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"│ position ┆ hello ┆ world!!! │\n",
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"│ --- ┆ --- ┆ --- │\n",
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"│ array[f64, 3] ┆ i64 ┆ bool │\n",
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"╞════════════════════╪═══════╪══════════╡\n",
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"│ [-1.0, -1.0, -1.0] ┆ 42 ┆ true │\n",
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"│ [-1.0, -1.0, 1.0] ┆ 42 ┆ true │\n",
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"│ [-1.0, 1.0, -1.0] ┆ 42 ┆ true │\n",
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"│ [-1.0, 1.0, 1.0] ┆ 42 ┆ true │\n",
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"│ [1.0, -1.0, -1.0] ┆ 42 ┆ true │\n",
23-
"│ [1.0, -1.0, 1.0] ┆ 42 ┆ true │\n",
24-
"│ [1.0, 1.0, -1.0] ┆ 42 ┆ true │\n",
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"│ [1.0, 1.0, 1.0] ┆ 42 ┆ true │\n",
26-
"└────────────────────┴───────┴──────────┘\n"
12+
"shape: (8, 4)\n",
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"┌────────────────────┬───────┬──────────┬─────────────────────────────────┐\n",
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"│ position ┆ hello ┆ world!!! ┆ advanced │\n",
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"│ --- ┆ --- ┆ --- ┆ --- │\n",
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"│ array[f64, 3] ┆ i64 ┆ bool ┆ array[f64, 4] │\n",
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"╞════════════════════╪═══════╪══════════╪═════════════════════════════════╡\n",
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"│ [-1.0, -1.0, -1.0] ┆ 42 ┆ true ┆ [0.992774, 0.11234, … 0.016647… │\n",
19+
"│ [-1.0, -1.0, 1.0] ┆ 42 ┆ true ┆ [0.992774, 0.11234, … 0.016647… │\n",
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"│ [-1.0, 1.0, -1.0] ┆ 42 ┆ true ┆ [0.992774, 0.11234, … 0.016647… │\n",
21+
"│ [-1.0, 1.0, 1.0] ┆ 42 ┆ true ┆ [0.992774, 0.11234, … 0.016647… │\n",
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"│ [1.0, -1.0, -1.0] ┆ 42 ┆ true ┆ [0.992774, 0.11234, … 0.016647… │\n",
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"│ [1.0, -1.0, 1.0] ┆ 42 ┆ true ┆ [0.992774, 0.11234, … 0.016647… │\n",
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"│ [1.0, 1.0, -1.0] ┆ 42 ┆ true ┆ [0.992774, 0.11234, … 0.016647… │\n",
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"│ [1.0, 1.0, 1.0] ┆ 42 ┆ true ┆ [0.992774, 0.11234, … 0.016647… │\n",
26+
"└────────────────────┴───────┴──────────┴─────────────────────────────────┘\n"
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]
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}
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],
@@ -56,19 +56,99 @@
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},
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{
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"cell_type": "code",
59-
"execution_count": 24,
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"execution_count": 69,
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"metadata": {},
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"outputs": [
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{
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"ename": "ComputeError",
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"evalue": "datatype array[f64, 3] cannot be written to CSV\n\nConsider using JSON or a binary format.",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
68-
"\u001b[0;31mComputeError\u001b[0m Traceback (most recent call last)",
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"\u001b[0;32m/var/folders/0n/w5m51rrn71db4cvkds08wdg80000gn/T/ipykernel_10042/3097064528.py\u001b[0m in \u001b[0;36m?\u001b[0;34m()\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;31m# Write to temporary file\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0mtemp_dir\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtempfile\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgettempdir\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0mtemp_file\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mjoin\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtemp_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"mesh_attributes.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwrite_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtemp_file\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 8\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"CSV written to: {temp_file}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
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"\u001b[0;32m~/Library/Application Support/Blender/4.4/extensions/.local/lib/python3.11/site-packages/polars/dataframe/frame.py\u001b[0m in \u001b[0;36m?\u001b[0;34m(***failed resolving arguments***)\u001b[0m\n\u001b[1;32m 2990\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2991\u001b[0m \u001b[0;31m# Handle empty dict input\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2992\u001b[0m \u001b[0mstorage_options\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2993\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2994\u001b[0;31m self._df.write_csv(\n\u001b[0m\u001b[1;32m 2995\u001b[0m \u001b[0mfile\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2996\u001b[0m \u001b[0minclude_bom\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2997\u001b[0m \u001b[0minclude_header\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
71-
"\u001b[0;31mComputeError\u001b[0m: datatype array[f64, 3] cannot be written to CSV\n\nConsider using JSON or a binary format."
63+
"name": "stdout",
64+
"output_type": "stream",
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"text": [
66+
"Column dtypes: [Array(Float64, shape=(3,)), Int64, Boolean, Array(Float64, shape=(4,))]\n",
67+
"Array column found: position with dtype Array(Float64, shape=(3,))\n",
68+
"Array column found: advanced with dtype Array(Float64, shape=(4,))\n",
69+
"Array columns: ['position', 'advanced']\n",
70+
"DataFrame after expansion:\n",
71+
"shape: (8, 9)\n",
72+
"┌───────────┬───────────┬───────────┬───────┬───┬───────────┬───────────┬───────────┬───────────┐\n",
73+
"│ position1 ┆ position2 ┆ position3 ┆ hello ┆ … ┆ advanced1 ┆ advanced2 ┆ advanced3 ┆ advanced4 │\n",
74+
"│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n",
75+
"│ f64 ┆ f64 ┆ f64 ┆ i64 ┆ ┆ f64 ┆ f64 ┆ f64 ┆ f64 │\n",
76+
"╞═══════════╪═══════════╪═══════════╪═══════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n",
77+
"│ -1.0 ┆ -1.0 ┆ -1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
78+
"│ -1.0 ┆ -1.0 ┆ 1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
79+
"│ -1.0 ┆ 1.0 ┆ -1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
80+
"│ -1.0 ┆ 1.0 ┆ 1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
81+
"│ 1.0 ┆ -1.0 ┆ -1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
82+
"│ 1.0 ┆ -1.0 ┆ 1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
83+
"│ 1.0 ┆ 1.0 ┆ -1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
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"│ 1.0 ┆ 1.0 ┆ 1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
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"└───────────┴───────────┴───────────┴───────┴───┴───────────┴───────────┴───────────┴───────────┘\n"
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]
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}
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],
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"source": [
90+
"# Check dtypes and expand array columns\n",
91+
"dtypes = df.dtypes\n",
92+
"print(\"Column dtypes:\", dtypes)\n",
93+
"\n",
94+
"# Get columns that are arrays and expand them\n",
95+
"array_columns = []\n",
96+
"expanded_df = df.clone()\n",
97+
"\n",
98+
"for i, dtype in enumerate(dtypes):\n",
99+
" col_name = df.columns[i]\n",
100+
" if str(dtype).startswith('Array'):\n",
101+
" array_columns.append(col_name)\n",
102+
" print(f\"Array column found: {col_name} with dtype {dtype}\")\n",
103+
" \n",
104+
" # Get the array length from the first non-null value\n",
105+
" first_array = expanded_df.select(pl.col(col_name)).item(0, 0)\n",
106+
" array_length = len(first_array)\n",
107+
" \n",
108+
" # Expand array into separate columns with indexed names\n",
109+
" for j in range(array_length):\n",
110+
" expanded_df = expanded_df.with_columns([\n",
111+
" pl.col(col_name).arr.get(j).alias(f\"{col_name}{j+1}\")\n",
112+
" ])\n",
113+
" # Drop the original array column\n",
114+
" expanded_df = expanded_df.drop(col_name)\n",
115+
"\n",
116+
"# Reorder columns to place position columns first\n",
117+
"position_columns = [col for col in expanded_df.columns if col.startswith('position')]\n",
118+
"other_columns = [col for col in expanded_df.columns if not col.startswith('position')]\n",
119+
"column_order = position_columns + other_columns\n",
120+
"expanded_df = expanded_df.select(column_order)\n",
121+
"\n",
122+
"print(\"Array columns:\", array_columns)\n",
123+
"print(\"DataFrame after expansion:\")\n",
124+
"print(expanded_df)"
125+
]
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},
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{
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"cell_type": "code",
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"execution_count": 71,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"CSV written to: /var/folders/0n/w5m51rrn71db4cvkds08wdg80000gn/T/mesh_attributes.csv\n",
137+
"shape: (8, 9)\n",
138+
"┌───────────┬───────────┬───────────┬───────┬───┬───────────┬───────────┬───────────┬───────────┐\n",
139+
"│ position1 ┆ position2 ┆ position3 ┆ hello ┆ … ┆ advanced1 ┆ advanced2 ┆ advanced3 ┆ advanced4 │\n",
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"│ --- ┆ --- ┆ --- ┆ --- ┆ ┆ --- ┆ --- ┆ --- ┆ --- │\n",
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"│ f64 ┆ f64 ┆ f64 ┆ i64 ┆ ┆ f64 ┆ f64 ┆ f64 ┆ f64 │\n",
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"╞═══════════╪═══════════╪═══════════╪═══════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n",
143+
"│ -1.0 ┆ -1.0 ┆ -1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
144+
"│ -1.0 ┆ -1.0 ┆ 1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
145+
"│ -1.0 ┆ 1.0 ┆ -1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
146+
"│ -1.0 ┆ 1.0 ┆ 1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
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"│ 1.0 ┆ -1.0 ┆ -1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
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"│ 1.0 ┆ -1.0 ┆ 1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
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"│ 1.0 ┆ 1.0 ┆ -1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
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"│ 1.0 ┆ 1.0 ┆ 1.0 ┆ 42 ┆ … ┆ 0.992774 ┆ 0.11234 ┆ 0.038769 ┆ 0.016647 │\n",
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"└───────────┴───────────┴───────────┴───────┴───┴───────────┴───────────┴───────────┴───────────┘\n"
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]
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}
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],
@@ -79,9 +159,9 @@
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"# Write to temporary file\n",
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"temp_dir = tempfile.gettempdir()\n",
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"temp_file = os.path.join(temp_dir, \"mesh_attributes.csv\")\n",
82-
"df.write_csv(temp_file)\n",
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"expanded_df.write_csv(temp_file)\n",
83163
"print(f\"CSV written to: {temp_file}\")\n",
84-
"print(df)"
164+
"print(expanded_df)"
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]
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},
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{

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