{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 7440/7440 [02:42<00:00, 45.75it/s] \n"
     ]
    }
   ],
   "source": [
    "import json\n",
    "import os\n",
    "from tqdm import tqdm\n",
    "from pathlib import Path\n",
    "\n",
    "\n",
    "split = \"train\" # \"test\", \"eval\"\n",
    "\n",
    "def load_json_files(filepath):\n",
    "    with open(filepath, 'r') as f:\n",
    "        data = json.load(f)\n",
    "    return data\n",
    "\n",
    "\n",
    "folders = [os.path.join('dataset', split, f) for f in os.listdir('dataset/'+ split )]\n",
    "data = []\n",
    "for folderpath in tqdm(folders):\n",
    "    if not os.path.isdir(folderpath):\n",
    "        continue\n",
    "    files = [os.path.join(folderpath, f) for f in os.listdir(folderpath)]\n",
    "    for filepath in files:\n",
    "        if filepath.endswith('.json'):\n",
    "            \n",
    "            data.append({\"id\": str(Path(filepath).stem), **load_json_files(filepath)})\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 624022/624022 [00:11<00:00, 53122.61it/s]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "results = []\n",
    "for item in tqdm(data):\n",
    "    # Focal class\n",
    "    focal_class = \"class\" + \" \" + item[\"focal_class\"][\"identifier\"]\n",
    "\n",
    "    if item[\"focal_class\"][\"superclass\"]:\n",
    "        focal_class += \" \" + item[\"focal_class\"][\"superclass\"]\n",
    "\n",
    "    if item[\"focal_class\"][\"interfaces\"]:\n",
    "        focal_class += \" \" + item[\"focal_class\"][\"interfaces\"]\n",
    "\n",
    "    focal_class += \" {\"\n",
    "\n",
    "    indent = item[\"focal_method\"][\"body\"].split(\"\\n\")[-1][:-1]\n",
    "\n",
    "    # Focal method\n",
    "    focal_method = indent + item[\"focal_method\"][\"body\"]\n",
    "\n",
    "    # Constructors\n",
    "    constructors = []\n",
    "    for method in item[\"focal_class\"][\"methods\"]:\n",
    "        if method[\"constructor\"]:\n",
    "            constructor = indent + method[\"full_signature\"] + \";\"\n",
    "            constructors.append(constructor)\n",
    "\n",
    "    # Methods\n",
    "    methods = []\n",
    "    for method in item[\"focal_class\"][\"methods\"]:\n",
    "        if item[\"focal_method\"][\"full_signature\"] == method[\"full_signature\"]:\n",
    "            continue\n",
    "        #if method[\"testcase\"]:\n",
    "        #    continue\n",
    "\n",
    "        if not method[\"constructor\"]:\n",
    "            method_code = indent + method[\"full_signature\"] + \";\"\n",
    "            methods.append(method_code)\n",
    "\n",
    "    # Fields\n",
    "    fields = []\n",
    "    for field in item[\"focal_class\"][\"fields\"]:\n",
    "        field_code = indent\n",
    "        field_code += field[\"modifier\"] + \" \" + field[\"type\"] + \" \" + field[\"var_name\"] + \";\"\n",
    "        fields.append(field_code)\n",
    "\n",
    "\n",
    "    # TEST\n",
    "    # Test class\n",
    "    test_class = \"class\" + \" \" + item[\"test_class\"][\"identifier\"]\n",
    "\n",
    "    if item[\"test_class\"][\"superclass\"]:\n",
    "        test_class += \" \" + item[\"focal_class\"][\"superclass\"]\n",
    "\n",
    "    if item[\"test_class\"][\"interfaces\"]:\n",
    "        test_class += \" \" + item[\"focal_class\"][\"interfaces\"]\n",
    "\n",
    "    test_class += \" {\"\n",
    "\n",
    "    indent = item[\"test_case\"][\"body\"].split(\"\\n\")[-1][:-1]\n",
    "    # Test case\n",
    "    fields = []\n",
    "    for field in item[\"test_class\"][\"fields\"]:\n",
    "        field_code = indent\n",
    "        field_code += field[\"modifier\"] + \" \" + field[\"type\"] + \" \" + field[\"var_name\"] + \";\"\n",
    "        fields.append(field_code)\n",
    "    test_case = indent + item[\"test_case\"][\"body\"]\n",
    "\n",
    "    d = {\n",
    "        'id': item['id'],\n",
    "        't': test_case,\n",
    "        't_tc': \"\\n\\n\".join(filter(None, [test_class, \"\\n\".join(fields), test_case, \"}\"])),\n",
    "        'fm': focal_method,\n",
    "        'fm_fc': \"\\n\\n\".join(filter(None, [focal_class, focal_method, \"}\"])),\n",
    "        'fm_fc_c': \"\\n\\n\".join(filter(None, [focal_class, focal_method, \"\\n\".join(constructors), \"}\"])),\n",
    "        'fm_fc_c_m': \"\\n\\n\".join(filter(None, [focal_class, focal_method, \"\\n\".join(constructors), \"\\n\".join(methods), \"}\"])),\n",
    "        'fm_fc_c_m_f': \"\\n\\n\".join(filter(None, [focal_class, focal_method, \"\\n\".join(constructors), \"\\n\".join(methods), \"\\n\".join(fields), \"}\"])),\n",
    "    }\n",
    "    results.append(d)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# sort by id\n",
    "results_sorted = sorted(results, key=lambda k: int(k['id']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datasets import Dataset\n",
    "train_dataset = Dataset.from_list(results_sorted)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datasets import DatasetDict\n",
    "\n",
    "dataset_dict = DatasetDict({'train': train_dataset, 'test': test_dataset, 'validation': eval_dataset})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Creating parquet from Arrow format: 100%|██████████| 57/57 [00:00<00:00, 134.38ba/s]\n",
      "Creating parquet from Arrow format: 100%|██████████| 57/57 [00:00<00:00, 143.75ba/s]\n",
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      "Creating parquet from Arrow format: 100%|██████████| 57/57 [00:00<00:00, 145.44ba/s]\n",
      "Uploading the dataset shards: 100%|██████████| 11/11 [01:26<00:00,  7.90s/it]\n",
      "Creating parquet from Arrow format: 100%|██████████| 40/40 [00:00<00:00, 155.49ba/s]\n",
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      "Uploading the dataset shards: 100%|██████████| 2/2 [00:11<00:00,  5.58s/it]\n",
      "Creating parquet from Arrow format: 100%|██████████| 40/40 [00:00<00:00, 145.22ba/s]\n",
      "Creating parquet from Arrow format: 100%|██████████| 40/40 [00:00<00:00, 139.08ba/s]\n",
      "Uploading the dataset shards: 100%|██████████| 2/2 [00:12<00:00,  6.28s/it]\n",
      "README.md: 100%|██████████| 21.0/21.0 [00:00<00:00, 8.60kB/s]\n"
     ]
    }
   ],
   "source": [
    "dataset_dict.push_to_hub('andstor/methods2test')"
   ]
  }
 ],
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