{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "22f3053f",
   "metadata": {},
   "outputs": [
    {
     "ename": "ArrowInvalid",
     "evalue": "Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file.",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mArrowInvalid\u001b[0m                              Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[2], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mdatasets\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mimport\u001b[39;00m load_dataset\n\u001b[1;32m      2\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mpandas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mas\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21;01mpd\u001b[39;00m\n\u001b[0;32m----> 3\u001b[0m train \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_parquet\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mcompositionality/exp_setting_2/experiment_1/train.parquet\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mengine\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mpyarrow\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[38;5;66;03m# test = pd.read_parquet('before-arc-parquet/generalization/exp_setting_4/experiment_1/test.parquet', engine='pyarrow')\u001b[39;00m\n\u001b[1;32m      5\u001b[0m \u001b[38;5;66;03m# test_ood = pd.read_parquet('before-arc-parquet/generalization/exp_setting_4/experiment_1/test_ood.parquet', engine='pyarrow')\u001b[39;00m\n\u001b[1;32m      6\u001b[0m  \n\u001b[1;32m      7\u001b[0m \u001b[38;5;66;03m# gen_exps3_exp2_test = load_dataset(\"yassinetb/cogitao-dev\", data_files={\"data\": \"sample_efficiency/exp_setting_1/experiment_1/test.parquet\"})\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;03m# print(gen_exps3_exp2_test[\"data\"][0].keys())\u001b[39;00m\n",
      "File \u001b[0;32m/opt/anaconda3/envs/daily/lib/python3.11/site-packages/pandas/io/parquet.py:667\u001b[0m, in \u001b[0;36mread_parquet\u001b[0;34m(path, engine, columns, storage_options, use_nullable_dtypes, dtype_backend, filesystem, filters, **kwargs)\u001b[0m\n\u001b[1;32m    664\u001b[0m     use_nullable_dtypes \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m    665\u001b[0m check_dtype_backend(dtype_backend)\n\u001b[0;32m--> 667\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mimpl\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    668\u001b[0m \u001b[43m    \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    669\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    670\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfilters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    671\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstorage_options\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstorage_options\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    672\u001b[0m \u001b[43m    \u001b[49m\u001b[43muse_nullable_dtypes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_nullable_dtypes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    673\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdtype_backend\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdtype_backend\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    674\u001b[0m \u001b[43m    \u001b[49m\u001b[43mfilesystem\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilesystem\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    675\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    676\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m/opt/anaconda3/envs/daily/lib/python3.11/site-packages/pandas/io/parquet.py:274\u001b[0m, in \u001b[0;36mPyArrowImpl.read\u001b[0;34m(self, path, columns, filters, use_nullable_dtypes, dtype_backend, storage_options, filesystem, **kwargs)\u001b[0m\n\u001b[1;32m    267\u001b[0m path_or_handle, handles, filesystem \u001b[38;5;241m=\u001b[39m _get_path_or_handle(\n\u001b[1;32m    268\u001b[0m     path,\n\u001b[1;32m    269\u001b[0m     filesystem,\n\u001b[1;32m    270\u001b[0m     storage_options\u001b[38;5;241m=\u001b[39mstorage_options,\n\u001b[1;32m    271\u001b[0m     mode\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrb\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m    272\u001b[0m )\n\u001b[1;32m    273\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 274\u001b[0m     pa_table \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mapi\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mparquet\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mread_table\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    275\u001b[0m \u001b[43m        \u001b[49m\u001b[43mpath_or_handle\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    276\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    277\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfilesystem\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilesystem\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    278\u001b[0m \u001b[43m        \u001b[49m\u001b[43mfilters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    279\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    280\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    281\u001b[0m     result \u001b[38;5;241m=\u001b[39m pa_table\u001b[38;5;241m.\u001b[39mto_pandas(\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mto_pandas_kwargs)\n\u001b[1;32m    283\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m manager \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124marray\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n",
      "File \u001b[0;32m/opt/anaconda3/envs/daily/lib/python3.11/site-packages/pyarrow/parquet/core.py:1774\u001b[0m, in \u001b[0;36mread_table\u001b[0;34m(source, columns, use_threads, schema, use_pandas_metadata, read_dictionary, memory_map, buffer_size, partitioning, filesystem, filters, ignore_prefixes, pre_buffer, coerce_int96_timestamp_unit, decryption_properties, thrift_string_size_limit, thrift_container_size_limit, page_checksum_verification)\u001b[0m\n\u001b[1;32m   1764\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;21mread_table\u001b[39m(source, \u001b[38;5;241m*\u001b[39m, columns\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, use_threads\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m,\n\u001b[1;32m   1765\u001b[0m                schema\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, use_pandas_metadata\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, read_dictionary\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   1766\u001b[0m                memory_map\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m, buffer_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m, partitioning\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mhive\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1770\u001b[0m                thrift_container_size_limit\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   1771\u001b[0m                page_checksum_verification\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m):\n\u001b[1;32m   1773\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 1774\u001b[0m         dataset \u001b[38;5;241m=\u001b[39m \u001b[43mParquetDataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1775\u001b[0m \u001b[43m            \u001b[49m\u001b[43msource\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1776\u001b[0m \u001b[43m            \u001b[49m\u001b[43mschema\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mschema\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1777\u001b[0m \u001b[43m            \u001b[49m\u001b[43mfilesystem\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilesystem\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1778\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpartitioning\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpartitioning\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1779\u001b[0m \u001b[43m            \u001b[49m\u001b[43mmemory_map\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmemory_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1780\u001b[0m \u001b[43m            \u001b[49m\u001b[43mread_dictionary\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mread_dictionary\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1781\u001b[0m \u001b[43m            \u001b[49m\u001b[43mbuffer_size\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbuffer_size\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1782\u001b[0m \u001b[43m            \u001b[49m\u001b[43mfilters\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfilters\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1783\u001b[0m \u001b[43m            \u001b[49m\u001b[43mignore_prefixes\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mignore_prefixes\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1784\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpre_buffer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpre_buffer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1785\u001b[0m \u001b[43m            \u001b[49m\u001b[43mcoerce_int96_timestamp_unit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcoerce_int96_timestamp_unit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1786\u001b[0m \u001b[43m            \u001b[49m\u001b[43mdecryption_properties\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdecryption_properties\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1787\u001b[0m \u001b[43m            \u001b[49m\u001b[43mthrift_string_size_limit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mthrift_string_size_limit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1788\u001b[0m \u001b[43m            \u001b[49m\u001b[43mthrift_container_size_limit\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mthrift_container_size_limit\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1789\u001b[0m \u001b[43m            \u001b[49m\u001b[43mpage_checksum_verification\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mpage_checksum_verification\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1790\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1791\u001b[0m     \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mImportError\u001b[39;00m:\n\u001b[1;32m   1792\u001b[0m         \u001b[38;5;66;03m# fall back on ParquetFile for simple cases when pyarrow.dataset\u001b[39;00m\n\u001b[1;32m   1793\u001b[0m         \u001b[38;5;66;03m# module is not available\u001b[39;00m\n\u001b[1;32m   1794\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m filters \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
      "File \u001b[0;32m/opt/anaconda3/envs/daily/lib/python3.11/site-packages/pyarrow/parquet/core.py:1350\u001b[0m, in \u001b[0;36mParquetDataset.__init__\u001b[0;34m(self, path_or_paths, filesystem, schema, filters, read_dictionary, memory_map, buffer_size, partitioning, ignore_prefixes, pre_buffer, coerce_int96_timestamp_unit, decryption_properties, thrift_string_size_limit, thrift_container_size_limit, page_checksum_verification)\u001b[0m\n\u001b[1;32m   1346\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m single_file \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m   1347\u001b[0m     fragment \u001b[38;5;241m=\u001b[39m parquet_format\u001b[38;5;241m.\u001b[39mmake_fragment(single_file, filesystem)\n\u001b[1;32m   1349\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_dataset \u001b[38;5;241m=\u001b[39m ds\u001b[38;5;241m.\u001b[39mFileSystemDataset(\n\u001b[0;32m-> 1350\u001b[0m         [fragment], schema\u001b[38;5;241m=\u001b[39mschema \u001b[38;5;129;01mor\u001b[39;00m \u001b[43mfragment\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mphysical_schema\u001b[49m,\n\u001b[1;32m   1351\u001b[0m         \u001b[38;5;28mformat\u001b[39m\u001b[38;5;241m=\u001b[39mparquet_format,\n\u001b[1;32m   1352\u001b[0m         filesystem\u001b[38;5;241m=\u001b[39mfragment\u001b[38;5;241m.\u001b[39mfilesystem\n\u001b[1;32m   1353\u001b[0m     )\n\u001b[1;32m   1354\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m   1356\u001b[0m \u001b[38;5;66;03m# check partitioning to enable dictionary encoding\u001b[39;00m\n",
      "File \u001b[0;32m/opt/anaconda3/envs/daily/lib/python3.11/site-packages/pyarrow/_dataset.pyx:1473\u001b[0m, in \u001b[0;36mpyarrow._dataset.Fragment.physical_schema.__get__\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m/opt/anaconda3/envs/daily/lib/python3.11/site-packages/pyarrow/error.pxi:155\u001b[0m, in \u001b[0;36mpyarrow.lib.pyarrow_internal_check_status\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32m/opt/anaconda3/envs/daily/lib/python3.11/site-packages/pyarrow/error.pxi:92\u001b[0m, in \u001b[0;36mpyarrow.lib.check_status\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mArrowInvalid\u001b[0m: Could not open Parquet input source '<Buffer>': Parquet magic bytes not found in footer. Either the file is corrupted or this is not a parquet file."
     ]
    }
   ],
   "source": [
    "from datasets import load_dataset\n",
    "import pandas as pd\n",
    "train = pd.read_parquet('compositionality/exp_setting_2/experiment_1/train.parquet', engine='pyarrow')\n",
    "# test = pd.read_parquet('before-arc-parquet/generalization/exp_setting_4/experiment_1/test.parquet', engine='pyarrow')\n",
    "# test_ood = pd.read_parquet('before-arc-parquet/generalization/exp_setting_4/experiment_1/test_ood.parquet', engine='pyarrow')\n",
    " \n",
    "# gen_exps3_exp2_test = load_dataset(\"yassinetb/cogitao-dev\", data_files={\"data\": \"sample_efficiency/exp_setting_1/experiment_1/test.parquet\"})\n",
    "# print(gen_exps3_exp2_test[\"data\"][0].keys())"
   ]
  }
 ],
 "metadata": {
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