My commit

663_project1_check.ipynb

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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyMjOP9eeSmr0ii5DDNSNECG"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"markdown","source":["## Set up"],"metadata":{"id":"03_zGVdmtiwd"}},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"_ntkWenjsmjo","executionInfo":{"status":"ok","timestamp":1710373415823,"user_tz":420,"elapsed":310589,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"8a2faaf6-cc83-42c4-d95b-f379033f0af4"},"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m510.5/510.5 kB\u001b[0m \u001b[31m2.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m5.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m3.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m553.4 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hMounted at /content/drive\n","/content/drive/MyDrive/STA663\n","Git LFS initialized.\n","\n","    _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|\n","    _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|\n","    _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|\n","    _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|\n","    _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|\n","\n","    To login, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens .\n","Token: \n","Add token as git credential? (Y/n) Y\n","Token is valid (permission: write).\n","Your token has been saved in your configured git credential helpers (store).\n","Your token has been saved to /root/.cache/huggingface/token\n","Login successful\n","\u001b[90mgit version 2.34.1\u001b[0m\n","\u001b[90mgit-lfs/3.0.2 (GitHub; linux amd64; go 1.18.1)\u001b[0m\n","\n","You are about to create \u001b[1mdatasets/Johnnyeee/Yelpdata_663\u001b[0m\n","Proceed? [Y/n] n\n","Abort\n","fatal: destination path 'Yelpdata_663' already exists and is not an empty directory.\n","/content/drive/MyDrive/STA663/Yelpdata_663\n"]}],"source":["# Install the huggingface datasets library\n","!pip install datasets -q\n","\n","# Change to your work directory\n","from google.colab import drive\n","drive.mount('/content/drive')\n","%cd /content/drive/MyDrive/STA663\n","\n","# These are git commands, we will cover git more extensively in another class\n","!git config --global user.name \"Johnnyeee\"\n","!git config --global user.email \"yy413@duke.edu\"\n","!git config --global credential.helper store\n","!git lfs install\n","\n","# Log into huggingface\n","!huggingface-cli login\n","!huggingface-cli repo create Yelpdata_663 --type dataset\n","!git clone https://huggingface.co/datasets/Johnnyeee/Yelpdata_663\n","%cd Yelpdata_663"]},{"cell_type":"code","source":["# @title Save changes\n","\n","# You'll learn what this does in the future if you are\n","# not familiar with git\n","!git add -A\n","!git commit -m \"My commit\"\n","!git push"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"qqqPfv96su_F","executionInfo":{"status":"ok","timestamp":1710374035570,"user_tz":420,"elapsed":509055,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"ed807be3-24d7-4837-cb55-87c36e9d1061"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["fatal: cannot exec '.git/hooks/post-commit': Permission denied\n","[main e9e3ac1] My commit\n"," 3 files changed, 364 insertions(+), 1 deletion(-)\n"," rewrite README.md (100%)\n"," create mode 100644 Yelpdata_663.py\n"," create mode 100644 yelpdata.parquet\n","fatal: cannot exec '.git/hooks/pre-push': Permission denied\n","^C\n"]}]},{"cell_type":"markdown","source":["## Test if works"],"metadata":{"id":"WWnP1bZvtpJF"}},{"cell_type":"code","source":["# @title Test if your dataset works!\n","\n","!pip install datasets\n","\n","from datasets import load_dataset"],"metadata":{"id":"KohLXmZUtmcu"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["dataset = load_dataset(\"Johnnyeee/Yelpdata_663\", trust_remote_code=True)"],"metadata":{"id":"Fptgu8xwDIqW"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["next(iter((dataset['train'])))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"DVup69Ee7Sfo","executionInfo":{"status":"ok","timestamp":1708376478907,"user_tz":300,"elapsed":186,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"d90e0fab-84b1-4666-c401-8edc333c0727"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'business_id': 'YMOCOlONOae4zaiKImTnTQ',\n"," 'name': 'Reef Sushi & Sake',\n"," 'address': '50 N Sierra St, Ste 106',\n"," 'city': 'Reno',\n"," 'state': 'NV',\n"," 'postal_code': '89501',\n"," 'latitude': 39.52512741088867,\n"," 'longitude': -119.81383514404297,\n"," 'stars_x': 3.0,\n"," 'review_count': 743.0,\n"," 'is_open': 0.0,\n"," 'categories': 'Restaurants, Sushi Bars, Asian Fusion, Japanese',\n"," 'hours': \"{'Monday': '11:0-22:0', 'Tuesday': '11:0-22:0', 'Wednesday': '11:0-22:0', 'Thursday': '11:0-22:0', 'Friday': '11:0-22:0', 'Saturday': '11:0-22:0', 'Sunday': '11:0-22:0'}\",\n"," 'review_id': 'FmoRIwlNwx91QHLhplZOaA',\n"," 'user_id': 'rwu2uCpSf57BvNi3B42F4A',\n"," 'stars_y': 4.0,\n"," 'useful': 0.0,\n"," 'funny': 0.0,\n"," 'cool': 0.0,\n"," 'text': \"First time here.  Place looked clean and trendy. This place is very reasonbly price. Customers have the option to either order al la cart or all you can eat.  We (2 adults/4 kids)  came in on a Friday afternoon about 200pm,  we ordered the all you eat for the adults and kids meal for my kids.  Everything we ordered was very tasty.  The servers were very helpful.  My only complain is that the appetizers /sushi we ordered took quite some time to get to our table and some of the things we order didn't come at all.  I would also suggest that the wait staff tell you what it is that they are bringing since the menu does not have pictures of the sushi that is offered. \\n\\nOur lunch was about 2 hours long due to the long waits for our sushi.  I would definitely recommend this place to friends and fam.  Hopefully next time we come back service is a little faster.\",\n"," 'date': '2015-03-21 09:09:06',\n"," 'attributes': '{\\'Alcohol\\': \"u\\'full_bar\\'\", \\'RestaurantsDelivery\\': \\'False\\', \\'BusinessAcceptsCreditCards\\': \\'True\\', \\'HasTV\\': \\'True\\', \\'RestaurantsGoodForGroups\\': \\'True\\', \\'RestaurantsAttire\\': \"u\\'casual\\'\", \\'WiFi\\': \"\\'free\\'\", \\'OutdoorSeating\\': \\'True\\', \\'Caters\\': \\'True\\', \\'BusinessParking\\': \"{\\'garage\\': False, \\'street\\': True, \\'validated\\': False, \\'lot\\': False, \\'valet\\': False}\", \\'RestaurantsPriceRange2\\': \\'2\\', \\'BikeParking\\': \\'True\\', \\'GoodForKids\\': \\'True\\', \\'RestaurantsReservations\\': \\'True\\', \\'HappyHour\\': \\'True\\', \\'Ambience\\': \"{\\'touristy\\': False, \\'hipster\\': False, \\'romantic\\': False, \\'divey\\': False, \\'intimate\\': False, \\'trendy\\': True, \\'upscale\\': False, \\'classy\\': False, \\'casual\\': True}\", \\'GoodForMeal\\': \"{\\'dessert\\': False, \\'latenight\\': False, \\'lunch\\': True, \\'dinner\\': True, \\'brunch\\': False, \\'breakfast\\': False}\", \\'RestaurantsTakeOut\\': \\'True\\', \\'NoiseLevel\\': \"u\\'average\\'\"}'}"]},"metadata":{},"execution_count":28}]},{"cell_type":"code","source":["next(iter((dataset['test'])))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Ups2RaiB76iL","executionInfo":{"status":"ok","timestamp":1708376481764,"user_tz":300,"elapsed":186,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"662faba2-f653-4b58-ca20-1c567c7e2188"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'business_id': 'mabS8Eq8CLjMZdLl3V7GWA',\n"," 'name': \"Guido's Original New York Style Pizza Downtown\",\n"," 'address': '235 N 5th St',\n"," 'city': 'Boise',\n"," 'state': 'ID',\n"," 'postal_code': '83702',\n"," 'latitude': 43.61501693725586,\n"," 'longitude': -116.19904327392578,\n"," 'stars_x': 4.5,\n"," 'review_count': 270.0,\n"," 'is_open': 1.0,\n"," 'categories': 'Italian, Salad, Pizza, Restaurants',\n"," 'hours': \"{'Monday': '0:0-0:0', 'Tuesday': '11:0-21:0', 'Wednesday': '11:0-21:0', 'Thursday': '11:0-21:0', 'Friday': '11:0-22:0', 'Saturday': '11:0-22:0', 'Sunday': '11:0-21:0'}\",\n"," 'review_id': 'xCG3Mgp_stuKQqgcdoWtFw',\n"," 'user_id': 'ekDxCpf9ZYTqtbr2XHyDEQ',\n"," 'stars_y': 5.0,\n"," 'useful': 0.0,\n"," 'funny': 0.0,\n"," 'cool': 0.0,\n"," 'text': 'Pretty darn good pizzas, definitely recommend over the chain stores. The white pizza is especially tasty.',\n"," 'date': '2015-01-15 18:15:22',\n"," 'attributes': '{\\'BikeParking\\': \\'True\\', \\'GoodForKids\\': \\'True\\', \\'Alcohol\\': \"u\\'beer_and_wine\\'\", \\'BusinessParking\\': \"{\\'garage\\': False, \\'street\\': True, \\'validated\\': False, \\'lot\\': False, \\'valet\\': False}\", \\'RestaurantsPriceRange2\\': \\'1\\', \\'RestaurantsReservations\\': \\'False\\', \\'HasTV\\': \\'False\\', \\'NoiseLevel\\': \"u\\'average\\'\", \\'RestaurantsGoodForGroups\\': \\'True\\', \\'WiFi\\': \"u\\'no\\'\", \\'BusinessAcceptsCreditCards\\': \\'True\\', \\'RestaurantsAttire\\': \"\\'casual\\'\", \\'OutdoorSeating\\': \\'True\\', \\'RestaurantsDelivery\\': \\'True\\', \\'Caters\\': \\'False\\', \\'RestaurantsTakeOut\\': \\'True\\', \\'RestaurantsTableService\\': \\'False\\', \\'GoodForMeal\\': \"{\\'dessert\\': False, \\'latenight\\': False, \\'lunch\\': True, \\'dinner\\': True, \\'brunch\\': False, \\'breakfast\\': False}\", \\'Ambience\\': \"{\\'touristy\\': False, \\'hipster\\': None, \\'romantic\\': False, \\'divey\\': None, \\'intimate\\': False, \\'trendy\\': False, \\'upscale\\': False, \\'classy\\': False, \\'casual\\': True}\", \\'WheelchairAccessible\\': \\'True\\'}'}"]},"metadata":{},"execution_count":29}]}]}

Lecture2&3.ipynb

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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyOibBjeE+j+tt0c+s7SXVqJ"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"p38hXaVqPusR","executionInfo":{"status":"ok","timestamp":1705441723997,"user_tz":300,"elapsed":17116,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"1d9af1f3-2d86-4f67-ba7e-b80fbd01c255"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting datasets\n","  Downloading datasets-2.16.1-py3-none-any.whl (507 kB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m507.1/507.1 kB\u001b[0m \u001b[31m2.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets) (3.13.1)\n","Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.23.5)\n","Requirement already satisfied: pyarrow>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (10.0.1)\n","Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets) (0.6)\n","Collecting dill<0.3.8,>=0.3.0 (from datasets)\n","  Downloading dill-0.3.7-py3-none-any.whl (115 kB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.3/115.3 kB\u001b[0m \u001b[31m9.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (1.5.3)\n","Requirement already satisfied: requests>=2.19.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.31.0)\n","Requirement already satisfied: tqdm>=4.62.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.1)\n","Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from datasets) (3.4.1)\n","Collecting multiprocess (from datasets)\n","  Downloading multiprocess-0.70.15-py310-none-any.whl (134 kB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m8.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: fsspec[http]<=2023.10.0,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n","Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.9.1)\n","Requirement already satisfied: huggingface-hub>=0.19.4 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.20.2)\n","Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (23.2)\n","Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.1)\n","Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (23.2.0)\n","Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.0.4)\n","Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.9.4)\n","Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.4.1)\n","Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n","Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.3)\n","Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.19.4->datasets) (4.5.0)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.3.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.6)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2.0.7)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2023.11.17)\n","Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2023.3.post1)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->datasets) (1.16.0)\n","Installing collected packages: dill, multiprocess, datasets\n","Successfully installed datasets-2.16.1 dill-0.3.7 multiprocess-0.70.15\n"]}],"source":["pip install datasets"]},{"cell_type":"code","source":["type(b'abc')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"s_fFmyZSQzYq","executionInfo":{"status":"ok","timestamp":1705442045074,"user_tz":300,"elapsed":97,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"cb4117e1-b364-4027-b15a-91a665adfcc5"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["bytes"]},"metadata":{},"execution_count":5}]},{"cell_type":"code","source":["type(True)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mIjPwj6jRHNs","executionInfo":{"status":"ok","timestamp":1705442363331,"user_tz":300,"elapsed":120,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"68f4d6bd-0064-4d2f-84bb-be2b39cc6a9c"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["bool"]},"metadata":{},"execution_count":11}]},{"cell_type":"code","source":["class Dog:\n","    def __init__(self,name,age):\n","        self.name=name\n","        self.age=age\n","    def bark(self):\n","        print(f'{self.name} is barking')\n","\n","d = Dog('Fido',3)\n","d.bark()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ahLFcJS7SUw_","executionInfo":{"status":"ok","timestamp":1705442369399,"user_tz":300,"elapsed":2,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"6343f352-988a-403e-be77-08116e5baa2d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Fido is barking\n"]}]},{"cell_type":"code","source":["class Dog:\n","    def __init__(self,name,age):\n","        self.name=name\n","        self.age=age\n","        print('A new dog is born!')\n","\n","    def bark(self):\n","        print(f'{self.name} is barking')\n","\n","d = Dog('Fido',3) #instance of this class\n","d.name = 'Apple'\n","d.bark()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"IX0DIMmNazxf","executionInfo":{"status":"ok","timestamp":1705444596914,"user_tz":300,"elapsed":100,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"78cc4454-c4d5-4a00-8d60-ac8d7fa5b9f7"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["A new dog is born!\n","Apple is barking\n"]}]},{"cell_type":"code","source":["class MyDataset:\n","    def __init__(self,name,age):\n","        self.name=name\n","        self.age=age\n","        print('A new dog is born!')\n","\n","    def bark(self):\n","        print(f'{self.name} is barking')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"aCHLm8LfZ04z","executionInfo":{"status":"ok","timestamp":1705444557889,"user_tz":300,"elapsed":103,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"67f701fb-a48c-4fc2-913e-7b8154093e3d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Apple is barking\n"]}]},{"cell_type":"code","source":["from datasets import load_dataset\n","\n","dataset=load_dataset('zeroshot/twitter-financial-news-sentiment')"],"metadata":{"id":"tEsOTOMdPy5G"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["dataset"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"YrCqQWopQskH","executionInfo":{"status":"ok","timestamp":1705441947560,"user_tz":300,"elapsed":3,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"5f59c874-16fb-4db6-e81a-f272174631cc"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["DatasetDict({\n","    train: Dataset({\n","        features: ['text', 'label'],\n","        num_rows: 9543\n","    })\n","    validation: Dataset({\n","        features: ['text', 'label'],\n","        num_rows: 2388\n","    })\n","})"]},"metadata":{},"execution_count":4}]},{"cell_type":"code","source":["training_set = dataset['train']"],"metadata":{"id":"sQOWNGI8RYiM"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["training_set"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gBGqOlhjSEz5","executionInfo":{"status":"ok","timestamp":1705442409620,"user_tz":300,"elapsed":4,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"e4bf66d9-42d8-4119-89fb-fe50d8ec5b60"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Dataset({\n","    features: ['text', 'label'],\n","    num_rows: 9543\n","})"]},"metadata":{},"execution_count":14}]},{"cell_type":"code","source":["#tuple() = return keys: 'y'=0.5 ; 'y' is key"],"metadata":{"id":"MDMX_lcjTqSI"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["true_dictionary = {\n","    'train': [1,2,3,4],\n","    'validation': [1,2,'winner',4]\n","}\n","\n","true_dictionary['validation'][2]"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"zpBAcwaETxdN","executionInfo":{"status":"ok","timestamp":1705442924339,"user_tz":300,"elapsed":6,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"3487b57b-b30f-4677-8547-e392304c58dc"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'winner'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":21}]},{"cell_type":"code","source":["my_dataset = {\n","    'train' : dataset['train'],\n","    'validation': dataset['validation']\n","}"],"metadata":{"id":"3md_OTcTVCoY"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["my_dataset"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"BiqiAsv3VLHd","executionInfo":{"status":"ok","timestamp":1705443112269,"user_tz":300,"elapsed":3,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"615c97f4-3e3d-48c5-c7cd-b734778bc7c6"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["{'train': Dataset({\n","     features: ['text', 'label'],\n","     num_rows: 9543\n"," }),\n"," 'validation': Dataset({\n","     features: ['text', 'label'],\n","     num_rows: 2388\n"," })}"]},"metadata":{},"execution_count":24}]},{"cell_type":"code","source":["# path:str doesn't have to be str, just for annotation.\n","def my_load_datase(path:str) -> str:\n","  print('I do something with',path)\n","  print(path)\n","  return path"],"metadata":{"id":"7DfQm-y9WK04"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["my_load_datase('hello!')\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":71},"id":"stgiMo_AWQYt","executionInfo":{"status":"ok","timestamp":1705443705384,"user_tz":300,"elapsed":118,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"bd947972-ddaa-4842-9651-3edc084b0e7f"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["I do something with hello!\n","hello!\n"]},{"output_type":"execute_result","data":{"text/plain":["'hello!'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":45}]},{"cell_type":"code","source":["df = dataset['train'].to_pandas()"],"metadata":{"id":"q6xzMNIdWvnn"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["df.head()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":206},"id":"f44y0J_JbmkQ","executionInfo":{"status":"ok","timestamp":1705445069459,"user_tz":300,"elapsed":115,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"4a75a86e-899f-492c-d8bc-a6c1a95a4632"},"execution_count":null,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                                                text  label\n","0  $BYND - JPMorgan reels in expectations on Beyo...      0\n","1  $CCL $RCL - Nomura points to bookings weakness...      0\n","2  $CX - Cemex cut at Credit Suisse, J.P. Morgan ...      0\n","3  $ESS: BTIG Research cuts to Neutral https://t....      0\n","4  $FNKO - Funko slides after Piper Jaffray PT cu...      0"],"text/html":["\n","  <div id=\"df-5d357d6b-9c2b-40df-9339-eb6b227280a1\" class=\"colab-df-container\">\n","    <div>\n","<style scoped>\n","    .dataframe tbody tr th:only-of-type {\n","        vertical-align: middle;\n","    }\n","\n","    .dataframe tbody tr th {\n","        vertical-align: top;\n","    }\n","\n","    .dataframe thead th {\n","        text-align: right;\n","    }\n","</style>\n","<table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: right;\">\n","      <th></th>\n","      <th>text</th>\n","      <th>label</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>0</th>\n","      <td>$BYND - JPMorgan reels in expectations on Beyo...</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>1</th>\n","      <td>$CCL $RCL - Nomura points to bookings weakness...</td>\n","      <td>0</td>\n","    </tr>\n","    <tr>\n","      <th>2</th>\n","      <td>$CX - Cemex cut at Credit Suisse, J.P. 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This behaviour is the source of the following dependency conflicts.\n","llmx 0.0.15a0 requires cohere, which is not installed.\n","llmx 0.0.15a0 requires tiktoken, which is not installed.\n","tensorflow-probability 0.22.0 requires typing-extensions<4.6.0, but you have typing-extensions 4.9.0 which is incompatible.\u001b[0m\u001b[31m\n","\u001b[0mSuccessfully installed h11-0.14.0 httpcore-1.0.2 httpx-0.26.0 openai-1.8.0 typing-extensions-4.9.0\n"]}]},{"cell_type":"code","source":["from openai import OpenAI"],"metadata":{"id":"O2T0DAJDc3b-"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# https://huggingface.co/docs/datasets/v2.16.1/loading\n","# https://huggingface.co/docs/datasets/v2.16.1/en/package_reference/loading_methods#datasets.load_dataset\n","dataset = load_dataset(\"zeroshot/twitter-financial-news-sentiment\")\n","\n","df = dataset[\"train\"].to_pandas()"],"metadata":{"id":"FDevjxWxc3gB"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["print(df.iloc[0].text)"],"metadata":{"id":"aMHcoXuFc3jj"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["client = OpenAI(\n","    # https://platform.openai.com/docs/overview\n","    api_key=API_KEY,\n",")\n","\n","chat_completion = client.chat.completions.create(\n","    messages=[\n","        {\"role\": \"system\", \"content\": \"You are an API which extracts stock tickers from tweets. Only provide the ticker.\"},\n","        {\"role\": \"user\", \"content\": df.iloc[0].text}\n","    ],\n","    model=\"gpt-3.5-turbo\",\n",")"],"metadata":{"id":"NyqgMq9Zc3m1","colab":{"base_uri":"https://localhost:8080/","height":250},"executionInfo":{"status":"error","timestamp":1705614540658,"user_tz":300,"elapsed":145,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"ad550488-f040-4e06-d1e0-0bdc831ec06c"},"execution_count":null,"outputs":[{"output_type":"error","ename":"NameError","evalue":"name 'API_KEY' is not defined","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)","\u001b[0;32m<ipython-input-4-3ce586a18164>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m client = OpenAI(\n\u001b[1;32m      2\u001b[0m     \u001b[0;31m# https://platform.openai.com/docs/overview\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0mapi_key\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mAPI_KEY\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      4\u001b[0m )\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mNameError\u001b[0m: name 'API_KEY' is not defined"]}]},{"cell_type":"code","source":["chat_completion.choices[0].message.content"],"metadata":{"id":"J7OnVqJJc3px"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["def get_tickers(text):\n","  client = OpenAI(\n","    api_key= \"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\",\n","  )\n","\n","  chat_completion = client.chat.completions.create(\n","      messages=[\n","          {\"role\": \"system\", \"content\": \"You are an API which extracts stock tickers from tweets. Only provide the ticker.\"},\n","          {\"role\": \"user\", \"content\": text}\n","      ],\n","      model=\"gpt-3.5-turbo\",\n","  )\n","\n","  return chat_completion.choices[0].message.content"],"metadata":{"id":"vQ3OTNtTcuQf"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["get_tickers()"],"metadata":{"id":"Ny1dlDH6rjMq","colab":{"base_uri":"https://localhost:8080/","height":381},"executionInfo":{"status":"error","timestamp":1705615026232,"user_tz":300,"elapsed":3133,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"a0f010f7-5edd-442b-f768-64c40ab67c91"},"execution_count":null,"outputs":[{"output_type":"error","ename":"RateLimitError","evalue":"Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mRateLimitError\u001b[0m                            Traceback (most recent call last)","\u001b[0;32m<ipython-input-10-92cf810a02f5>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_tickers\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m<ipython-input-8-49b396972038>\u001b[0m in \u001b[0;36mget_tickers\u001b[0;34m(text)\u001b[0m\n\u001b[1;32m      4\u001b[0m   )\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m   chat_completion = client.chat.completions.create(\n\u001b[0m\u001b[1;32m      7\u001b[0m       messages=[\n\u001b[1;32m      8\u001b[0m           \u001b[0;34m{\u001b[0m\u001b[0;34m\"role\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"system\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"content\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"You are an API which extracts stock tickers from tweets. Only provide the ticker.\"\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[0;32m/usr/local/lib/python3.10/dist-packages/openai/_utils/_utils.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    269\u001b[0m                         \u001b[0mmsg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mf\"Missing required argument: {quote(missing[0])}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    270\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 271\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    272\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    273\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m  \u001b[0;31m# type: ignore\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/resources/chat/completions.py\u001b[0m in \u001b[0;36mcreate\u001b[0;34m(self, messages, model, frequency_penalty, function_call, functions, logit_bias, logprobs, max_tokens, n, presence_penalty, response_format, seed, stop, stream, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m    646\u001b[0m         \u001b[0mtimeout\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mfloat\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0mhttpx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTimeout\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0mNotGiven\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mNOT_GIVEN\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    647\u001b[0m     ) -> ChatCompletion | Stream[ChatCompletionChunk]:\n\u001b[0;32m--> 648\u001b[0;31m         return self._post(\n\u001b[0m\u001b[1;32m    649\u001b[0m             \u001b[0;34m\"/chat/completions\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    650\u001b[0m             body=maybe_transform(\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/_base_client.py\u001b[0m in \u001b[0;36mpost\u001b[0;34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1165\u001b[0m             \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"post\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mjson_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mto_httpx_files\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfiles\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1166\u001b[0m         )\n\u001b[0;32m-> 1167\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mResponseT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcast_to\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mopts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstream\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream_cls\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstream_cls\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[0m\u001b[1;32m   1168\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1169\u001b[0m     def patch(\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/_base_client.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m    854\u001b[0m         \u001b[0mstream_cls\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0m_StreamT\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    855\u001b[0m     ) -> ResponseT | _StreamT:\n\u001b[0;32m--> 856\u001b[0;31m         return self._request(\n\u001b[0m\u001b[1;32m    857\u001b[0m             \u001b[0mcast_to\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcast_to\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    858\u001b[0m             \u001b[0moptions\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/_base_client.py\u001b[0m in \u001b[0;36m_request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m    930\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mretries\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_should_retry\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresponse\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    931\u001b[0m                 \u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\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[0;32m--> 932\u001b[0;31m                 return self._retry_request(\n\u001b[0m\u001b[1;32m    933\u001b[0m                     \u001b[0moptions\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    934\u001b[0m                     \u001b[0mcast_to\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/_base_client.py\u001b[0m in \u001b[0;36m_retry_request\u001b[0;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[1;32m    978\u001b[0m         \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    979\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 980\u001b[0;31m         return self._request(\n\u001b[0m\u001b[1;32m    981\u001b[0m             \u001b[0moptions\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    982\u001b[0m             \u001b[0mcast_to\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcast_to\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/_base_client.py\u001b[0m in \u001b[0;36m_request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m    930\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mretries\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m0\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_should_retry\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresponse\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    931\u001b[0m                 \u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclose\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[0;32m--> 932\u001b[0;31m                 return self._retry_request(\n\u001b[0m\u001b[1;32m    933\u001b[0m                     \u001b[0moptions\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    934\u001b[0m                     \u001b[0mcast_to\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/_base_client.py\u001b[0m in \u001b[0;36m_retry_request\u001b[0;34m(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)\u001b[0m\n\u001b[1;32m    978\u001b[0m         \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    979\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 980\u001b[0;31m         return self._request(\n\u001b[0m\u001b[1;32m    981\u001b[0m             \u001b[0moptions\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    982\u001b[0m             \u001b[0mcast_to\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcast_to\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;32m/usr/local/lib/python3.10/dist-packages/openai/_base_client.py\u001b[0m in \u001b[0;36m_request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m    945\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    946\u001b[0m             \u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Re-raising status error\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 947\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_status_error_from_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    948\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    949\u001b[0m         return self._process_response(\n","\u001b[0;31mRateLimitError\u001b[0m: Error code: 429 - {'error': {'message': 'You exceeded your current quota, please check your plan and billing details. For more information on this error, read the docs: https://platform.openai.com/docs/guides/error-codes/api-errors.', 'type': 'insufficient_quota', 'param': None, 'code': 'insufficient_quota'}}"]}]},{"cell_type":"code","source":["def get_ticket_dummy(text: str) -> str:\n","  raise ValueError (\"Needs to be a string\")\n","  return \"the stock ticker\""],"metadata":{"id":"QqktCzdTkWe6"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["get_ticket_dummy('$nvda going strong!')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":268},"id":"Azt0unVglTc9","executionInfo":{"status":"error","timestamp":1705615136769,"user_tz":300,"elapsed":127,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"4dd5123f-dafc-4022-8ad3-0defc50eb880"},"execution_count":null,"outputs":[{"output_type":"error","ename":"ValueError","evalue":"Needs to be a string","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)","\u001b[0;32m<ipython-input-14-9436908cf828>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_ticket_dummy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'$nvda going strong!'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m<ipython-input-12-3c692c303b52>\u001b[0m in \u001b[0;36mget_ticket_dummy\u001b[0;34m(text)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_ticket_dummy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m   \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"Needs to be a string\"\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      3\u001b[0m   \u001b[0;32mreturn\u001b[0m \u001b[0;34m\"the stock ticker\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Needs to be a string"]}]},{"cell_type":"code","source":["def get_ticket_dummy(text: str) -> str:\n","  if type(text) is not str:\n","    raise ValueError (\"Needs to be a string\")\n","  return \"the stock ticker\""],"metadata":{"id":"VC2dwZizlZY5"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["get_ticket_dummy(10)"],"metadata":{"id":"BrgTdxkwlqKa","executionInfo":{"status":"error","timestamp":1705615214394,"user_tz":300,"elapsed":126,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"f2b06dac-df36-4c29-b62d-5e82466b1019","colab":{"base_uri":"https://localhost:8080/","height":286}},"execution_count":null,"outputs":[{"output_type":"error","ename":"ValueError","evalue":"Needs to be a string","traceback":["\u001b[0;31m---------------------------------------------------------------------------\u001b[0m","\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)","\u001b[0;32m<ipython-input-16-d5947b92d53d>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mget_ticket_dummy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m","\u001b[0;32m<ipython-input-15-9b45e6dc05cc>\u001b[0m in \u001b[0;36mget_ticket_dummy\u001b[0;34m(text)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mget_ticket_dummy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m   \u001b[0;32mif\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtext\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m     \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"Needs to be a string\"\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      4\u001b[0m   \u001b[0;32mreturn\u001b[0m \u001b[0;34m\"the stock ticker\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n","\u001b[0;31mValueError\u001b[0m: Needs to be a string"]}]},{"cell_type":"markdown","source":["Lecture3"],"metadata":{"id":"LYysqhwudGfA"}},{"cell_type":"code","source":["def my_decorator(func):\n","  print('I have decorated the function')\n","  return func\n","\n","@my_decorator\n","def say_something():\n","  print('hello')\n"],"metadata":{"id":"xlucUq1BlsWW","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1706049246928,"user_tz":300,"elapsed":138,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"c3a972c0-729b-406d-8f03-918d8718a4e3"},"execution_count":2,"outputs":[{"output_type":"stream","name":"stdout","text":["I have decorated the function\n"]}]},{"cell_type":"code","source":["my_decorator(say_something)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"XkxcxaZiekT6","executionInfo":{"status":"ok","timestamp":1706049589176,"user_tz":300,"elapsed":116,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"b718f5a1-91ec-441c-b630-7442243c0aa6"},"execution_count":12,"outputs":[{"output_type":"stream","name":"stdout","text":["I have decorated the function\n"]},{"output_type":"execute_result","data":{"text/plain":["<function __main__.say_something()>"]},"metadata":{},"execution_count":12}]},{"cell_type":"code","source":["say_something = my_decorator(say_something)\n","#same as above"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"tbnVCWGXdwRC","executionInfo":{"status":"ok","timestamp":1706049583152,"user_tz":300,"elapsed":109,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"3fc8bf1f-4e9f-482b-cf50-ac9a39081f0b"},"execution_count":11,"outputs":[{"output_type":"stream","name":"stdout","text":["I have decorated the function\n"]}]},{"cell_type":"code","source":["say_something()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"ArgRpSMeeMD3","executionInfo":{"status":"ok","timestamp":1706049460723,"user_tz":300,"elapsed":4,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"1f16aba3-fe50-4d94-8876-7ea060ae2085"},"execution_count":6,"outputs":[{"output_type":"stream","name":"stdout","text":["hello\n"]}]},{"cell_type":"code","source":["---"],"metadata":{"id":"CAEPy6pofb26"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["def goodbye():\n","  return 'bye'\n","\n","def my_decorator(func):\n","  print('I have decorated the function')\n","  return goodbye\n","\n","def hello():\n","  print('hello')\n","\n","\n","what_is_this = my_decorator(hello)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gVsOIpLDfd5s","executionInfo":{"status":"ok","timestamp":1706049912068,"user_tz":300,"elapsed":133,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"9b514c31-77b9-4c38-8757-7de6c06c6ad4"},"execution_count":15,"outputs":[{"output_type":"stream","name":"stdout","text":["I have decorated the function\n"]}]},{"cell_type":"code","source":["def goodbye():\n","  return 'bye'\n","\n","def my_decorator(func):\n","  print('I have decorated the function')\n","  return goodbye\n","\n","@my_decorator\n","def hello():\n","  print('hello')\n","\n","hello()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":53},"id":"a7rHnQWwhHqz","executionInfo":{"status":"ok","timestamp":1706050690195,"user_tz":300,"elapsed":6,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"e8629089-728f-4922-86b0-3e5395086947"},"execution_count":28,"outputs":[{"output_type":"stream","name":"stdout","text":["I have decorated the function\n"]},{"output_type":"execute_result","data":{"text/plain":["'bye'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":28}]},{"cell_type":"code","source":["hello()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"LjLdoxDLhOf9","executionInfo":{"status":"ok","timestamp":1706050254134,"user_tz":300,"elapsed":6,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"47b51e29-ac82-49e9-8c9d-aeb1ec703c41"},"execution_count":21,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'bye'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":21}]},{"cell_type":"code","source":["what_is_this()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"qP8X_L3qfwdN","executionInfo":{"status":"ok","timestamp":1706050001611,"user_tz":300,"elapsed":4,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"921b86aa-b18f-49ac-e211-43daf7d37b22"},"execution_count":17,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'bye'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":17}]},{"cell_type":"code","source":["x = goodbye\n","y=x\n","y()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"id":"uMBh-64zgbyB","executionInfo":{"status":"ok","timestamp":1706050055988,"user_tz":300,"elapsed":5,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"109aa117-9444-4066-e5cc-478c1e51d8c9"},"execution_count":19,"outputs":[{"output_type":"execute_result","data":{"text/plain":["'bye'"],"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"}},"metadata":{},"execution_count":19}]}]}

yelp_dataset.ipynb

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+{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"provenance":[],"toc_visible":true,"machine_shape":"hm","authorship_tag":"ABX9TyNCjdoNZhish6uzw3kOYuO+"},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"}},"cells":[{"cell_type":"code","execution_count":null,"metadata":{"id":"9m84JFrYlumk","executionInfo":{"status":"ok","timestamp":1708367355834,"user_tz":300,"elapsed":17348,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"3825a409-1170-4544-ab94-655a56075d2a"},"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting datasets\n","  Downloading datasets-2.17.1-py3-none-any.whl (536 kB)\n","\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m536.7/536.7 kB\u001b[0m \u001b[31m3.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25hRequirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages 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already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.19.4->datasets) (4.9.0)\n","Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.3.2)\n","Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (3.6)\n","Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2.0.7)\n","Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.19.0->datasets) (2024.2.2)\n","Requirement already satisfied: python-dateutil>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n","Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2023.4)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.1->pandas->datasets) (1.16.0)\n","Installing collected packages: pyarrow, dill, multiprocess, datasets\n","  Attempting uninstall: pyarrow\n","    Found existing installation: pyarrow 10.0.1\n","    Uninstalling pyarrow-10.0.1:\n","      Successfully uninstalled pyarrow-10.0.1\n","\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n","ibis-framework 7.1.0 requires pyarrow<15,>=2, but you have pyarrow 15.0.0 which is incompatible.\u001b[0m\u001b[31m\n","\u001b[0mSuccessfully installed datasets-2.17.1 dill-0.3.8 multiprocess-0.70.16 pyarrow-15.0.0\n"]}],"source":["# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.\n","#\n","# Licensed under the Apache License, Version 2.0 (the \"License\");\n","# you may not use this file except in compliance with the License.\n","# You may obtain a copy of the License at\n","#\n","#     http://www.apache.org/licenses/LICENSE-2.0\n","#\n","# Unless required by applicable law or agreed to in writing, software\n","# distributed under the License is distributed on an \"AS IS\" BASIS,\n","# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n","# See the License for the specific language governing permissions and\n","# limitations under the License.\n","# TODO: Address all TODOs and remove all explanatory comments\n","\"\"\"TODO: Add a description here.\"\"\"\n","\n","!pip install datasets\n","\n","import csv\n","import json\n","import os\n","from typing import List\n","import datasets\n","import logging\n","\n","# TODO: Add BibTeX citation\n","# Find for instance the citation on arxiv or on the dataset repo/website\n","_CITATION = \"\"\"\\\n","@InProceedings{huggingface:dataset,\n","title = {A great new dataset},\n","author={huggingface, Inc.\n","},\n","year={2020}\n","}\n","\"\"\"\n","\n","# TODO: Add description of the dataset here\n","# You can copy an official description\n","_DESCRIPTION = \"\"\"\\\n","This new dataset is designed to solve this great NLP task and is crafted with a lot of care.\n","\"\"\"\n","\n","# TODO: Add a link to an official homepage for the dataset here\n","_HOMEPAGE = \"https://www.yelp.com/dataset/download\"\n","\n","# TODO: Add the licence for the dataset here if you can find it\n","_LICENSE = \"\"\n","\n"]},{"cell_type":"code","source":["import json\n","import datasets\n","\n","class YelpDataset(datasets.GeneratorBasedBuilder):\n","    \"\"\"Yelp Dataset focusing on restaurant reviews.\"\"\"\n","\n","    VERSION = datasets.Version(\"1.1.0\")\n","\n","    BUILDER_CONFIGS = [\n","        datasets.BuilderConfig(name=\"restaurants\", version=VERSION, description=\"This part of my dataset covers a wide range of restaurants\"),\n","    ]\n","\n","    DEFAULT_CONFIG_NAME = \"restaurants\"\n","\n","    _URL = \"https://yelpdata.s3.us-west-2.amazonaws.com/\"\n","    _URLS = {\n","        \"business\": _URL + \"yelp_academic_dataset_business.json\",\n","        \"review\": _URL + \"yelp_academic_dataset_review.json\",\n","    }\n","\n","    def _info(self):\n","        return datasets.DatasetInfo(\n","            description=_DESCRIPTION,\n","            features=datasets.Features(\n","                {\n","                    \"business_id\": datasets.Value(\"string\"),\n","                    \"name\": datasets.Value(\"string\"),\n","                    \"categories\": datasets.Value(\"string\"),\n","                    \"review_id\": datasets.Value(\"string\"),\n","                    \"user_id\": datasets.Value(\"string\"),\n","                    \"stars\": datasets.Value(\"float\"),\n","                    \"text\": datasets.Value(\"string\"),\n","                    \"date\": datasets.Value(\"string\"),\n","                }\n","            ),\n","            supervised_keys=None,\n","            homepage=\"https://www.yelp.com/dataset/download\",\n","            citation=_CITATION,\n","        )\n","\n","    def _split_generators(self, dl_manager: datasets.DownloadManager):\n","        \"\"\"Returns SplitGenerators.\"\"\"\n","        downloaded_files = dl_manager.download_and_extract(self._URLS)\n","\n","        return [\n","            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={\"business_path\": downloaded_files[\"business\"], \"review_path\": downloaded_files[\"review\"], \"split\": \"train\"}),\n","            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={\"business_path\": downloaded_files[\"business\"], \"review_path\": downloaded_files[\"review\"], \"split\": \"test\"}),\n","        ]\n","\n","    def _generate_examples(self, business_path, review_path, split):\n","        \"\"\"Yields examples as (key, example) tuples.\"\"\"\n","\n","        # Load businesses and filter for restaurants\n","        with open(business_path, encoding=\"utf-8\") as f:\n","            businesses = {}\n","            for line in f:\n","                business = json.loads(line)\n","                if business.get(\"categories\") and \"Restaurants\" in business[\"categories\"]:\n","                    businesses[business['business_id']] = business\n","\n","        # Generate examples\n","        with open(review_path, encoding=\"utf-8\") as f:\n","            for line in f:\n","                review = json.loads(line)\n","                business_id = review['business_id']\n","                if business_id in businesses:\n","                    yield review['review_id'], {\n","                        \"business_id\": business_id,\n","                        \"name\": businesses[business_id]['name'],\n","                        \"categories\": businesses[business_id]['categories'],\n","                        \"review_id\": review['review_id'],\n","                        \"user_id\": review['user_id'],\n","                        \"stars\": review['stars'],\n","                        \"text\": review['text'],\n","                        \"date\": review['date'],\n","                    }\n"],"metadata":{"id":"U8wXinbsScRt","executionInfo":{"status":"ok","timestamp":1710285488659,"user_tz":420,"elapsed":217,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}}},"execution_count":4,"outputs":[]},{"cell_type":"markdown","source":["# New Version"],"metadata":{"id":"mZy6UxI-LroL"}},{"cell_type":"code","source":["!pip install datasets"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"veKI9DfyQ70-","executionInfo":{"status":"ok","timestamp":1710273849091,"user_tz":420,"elapsed":1033,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}},"outputId":"9ea5357e-3acc-4c0e-bd8c-f0e041d7743c"},"execution_count":1,"outputs":[{"output_type":"stream","name":"stdout","text":["Installing collected packages: xxhash, dill, multiprocess, datasets\n","Successfully installed datasets-2.18.0 dill-0.3.8 multiprocess-0.70.16 xxhash-3.4.1\n"]}]},{"cell_type":"code","source":["# -*- coding: utf-8 -*-\n","\"\"\"yelp_dataset.ipynb\n","\n","Automatically generated by Colaboratory.\n","\n","Original file is located at\n","    https://colab.research.google.com/drive/14UtK4YCjMSx4cVbUb9NBRHviWZg07dtY\n","\"\"\"\n","\n","# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.\n","#\n","# Licensed under the Apache License, Version 2.0 (the \"License\");\n","# you may not use this file except in compliance with the License.\n","# You may obtain a copy of the License at\n","#\n","#     http://www.apache.org/licenses/LICENSE-2.0\n","#\n","# Unless required by applicable law or agreed to in writing, software\n","# distributed under the License is distributed on an \"AS IS\" BASIS,\n","# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n","# See the License for the specific language governing permissions and\n","# limitations under the License.\n","# TODO: Address all TODOs and remove all explanatory comments\n","\"\"\"TODO: Add a description here.\"\"\"\n","\n","\n","import csv\n","import json\n","import os\n","from typing import List\n","import datasets\n","import logging\n","\n","# TODO: Add BibTeX citation\n","# Find for instance the citation on arxiv or on the dataset repo/website\n","_CITATION = \"\"\"\\\n","@InProceedings{huggingface:dataset,\n","title = {A great new dataset},\n","author={huggingface, Inc.\n","},\n","year={2020}\n","}\n","\"\"\"\n","\n","# TODO: Add description of the dataset here\n","# You can copy an official description\n","_DESCRIPTION = \"\"\"\\\n","This dataset encompasses a wealth of information from the Yelp platform,\n"," detailing user reviews, business ratings, and operational specifics across a diverse array of local establishments.\n","\"\"\"\n","\n","# TODO: Add a link to an official homepage for the dataset here\n","_HOMEPAGE = \"https://www.yelp.com/dataset/download\"\n","\n","# TODO: Add the licence for the dataset here if you can find it\n","_LICENSE = \"https://s3-media0.fl.yelpcdn.com/assets/srv0/engineering_pages/f64cb2d3efcc/assets/vendor/Dataset_User_Agreement.pdf\"\n","\n","# TODO: Add link to the official dataset URLs here\n","# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.\n","# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)\n","_URL = \"https://yelpdata.s3.us-west-2.amazonaws.com/\"\n","_URLS = {\n","    \"business\": _URL + \"yelp_academic_dataset_business.json\",\n","    \"review\": _URL + \"yelp_academic_dataset_review.json\",\n","}\n","# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case\n","class YelpDataset(datasets.GeneratorBasedBuilder):\n","    \"\"\"TODO: Short description of my dataset.\"\"\"\n","\n","    _URLS = _URLS\n","    VERSION = datasets.Version(\"1.1.0\")\n","\n","    def _info(self):\n","      return datasets.DatasetInfo(\n","          description=_DESCRIPTION,\n","          features=datasets.Features(\n","              {\n","                  \"business_id\": datasets.Value(\"string\"),\n","                  \"name\": datasets.Value(\"string\"),\n","                  \"address\": datasets.Value(\"string\"),\n","                  \"city\": datasets.Value(\"string\"),\n","                  \"state\": datasets.Value(\"string\"),\n","                  \"postal_code\": datasets.Value(\"string\"),\n","                  \"latitude\": datasets.Value(\"float\"),\n","                  \"longitude\": datasets.Value(\"float\"),\n","                  \"stars_x\": datasets.Value(\"float\"),\n","                  \"review_count\": datasets.Value(\"float\"),\n","                  \"is_open\": datasets.Value(\"float\"),\n","                  \"categories\": datasets.Value(\"string\"),\n","                  \"hours\": datasets.Value(\"string\"),\n","                  \"review_id\": datasets.Value(\"string\"),\n","                  \"user_id\": datasets.Value(\"string\"),\n","                  \"stars_y\": datasets.Value(\"float\"),\n","                  \"useful\": datasets.Value(\"float\"),\n","                  \"funny\": datasets.Value(\"float\"),\n","                  \"cool\": datasets.Value(\"float\"),\n","                  \"text\": datasets.Value(\"string\"),\n","                  \"date\": datasets.Value(\"string\"),\n","                  \"attributes\": datasets.Value(\"string\"),\n","              }),\n","          # No default supervised_keys (as we have to pass both question\n","          # and context as input).\n","          supervised_keys=None,\n","          homepage=\"https://www.yelp.com/dataset/download\",\n","          citation=_CITATION,\n","      )\n","\n","    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:\n","      urls_to_download = self._URLS\n","      downloaded_files = dl_manager.download_and_extract(urls_to_download)\n","\n","      return [\n","          datasets.SplitGenerator(name=datasets.Split.BUSINESS, gen_kwargs={\"filepath\": downloaded_files[\"business\"]}),\n","          datasets.SplitGenerator(name=datasets.Split.REVIEW, gen_kwargs={\"filepath\": downloaded_files[\"review\"]}),\n","      ]\n","\n","\n","    def _generate_examples(self, filepath):\n","        \"\"\"This function returns the examples in the raw (text) form.\"\"\"\n","        logging.info(\"generating examples from = %s\", filepath)\n","        with open(filepath, encoding=\"utf-8\") as csv_file:\n","            reader = csv.DictReader(csv_file)\n","            for i, row in enumerate(reader):\n","                # Handle missing values for float fields\n","                for key, value in row.items():\n","                    if value == '':\n","                        # Assuming all fields that can be empty are floats; adjust as needed\n","                        row[key] = None\n","                yield i, row\n","\n"],"metadata":{"id":"8pQKwMXBF0qZ","executionInfo":{"status":"ok","timestamp":1710273885042,"user_tz":420,"elapsed":1821,"user":{"displayName":"Johnny Ye","userId":"16268450102215689935"}}},"execution_count":2,"outputs":[]},{"cell_type":"markdown","source":["# Old Version"],"metadata":{"id":"BKXLWWM9RvxH"}},{"cell_type":"code","source":["# -*- coding: utf-8 -*-\n","\"\"\"yelp_dataset.ipynb\n","\n","Automatically generated by Colaboratory.\n","\n","Original file is located at\n","    https://colab.research.google.com/drive/14UtK4YCjMSx4cVbUb9NBRHviWZg07dtY\n","\"\"\"\n","\n","# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.\n","#\n","# Licensed under the Apache License, Version 2.0 (the \"License\");\n","# you may not use this file except in compliance with the License.\n","# You may obtain a copy of the License at\n","#\n","#     http://www.apache.org/licenses/LICENSE-2.0\n","#\n","# Unless required by applicable law or agreed to in writing, software\n","# distributed under the License is distributed on an \"AS IS\" BASIS,\n","# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n","# See the License for the specific language governing permissions and\n","# limitations under the License.\n","# TODO: Address all TODOs and remove all explanatory comments\n","\"\"\"TODO: Add a description here.\"\"\"\n","\n","\n","import csv\n","import json\n","import os\n","from typing import List\n","import datasets\n","import logging\n","\n","# TODO: Add BibTeX citation\n","# Find for instance the citation on arxiv or on the dataset repo/website\n","_CITATION = \"\"\"\\\n","@InProceedings{huggingface:dataset,\n","title = {A great new dataset},\n","author={huggingface, Inc.\n","},\n","year={2020}\n","}\n","\"\"\"\n","\n","# TODO: Add description of the dataset here\n","# You can copy an official description\n","_DESCRIPTION = \"\"\"\\\n","This new dataset is designed to solve this great NLP task and is crafted with a lot of care.\n","\"\"\"\n","\n","# TODO: Add a link to an official homepage for the dataset here\n","_HOMEPAGE = \"https://www.yelp.com/dataset/download\"\n","\n","# TODO: Add the licence for the dataset here if you can find it\n","_LICENSE = \"\"\n","\n","# TODO: Add link to the official dataset URLs here\n","# The HuggingFace Datasets library doesn't host the datasets but only points to the original files.\n","# This can be an arbitrary nested dict/list of URLs (see below in `_split_generators` method)\n","_URL = \"https://yelpdata.s3.us-west-2.amazonaws.com/\"\n","_URLS = {\n","    \"train\": _URL + \"yelp_train.csv\",\n","    \"test\": _URL + \"yelp_test.csv\",\n","}\n","# TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case\n","class YelpDataset(datasets.GeneratorBasedBuilder):\n","    \"\"\"TODO: Short description of my dataset.\"\"\"\n","\n","    _URLS = _URLS\n","    VERSION = datasets.Version(\"1.1.0\")\n","\n","    def _info(self):\n","      return datasets.DatasetInfo(\n","          description=_DESCRIPTION,\n","          features=datasets.Features(\n","              {\n","                  \"business_id\": datasets.Value(\"string\"),\n","                  \"name\": datasets.Value(\"string\"),\n","                  \"address\": datasets.Value(\"string\"),\n","                  \"city\": datasets.Value(\"string\"),\n","                  \"state\": datasets.Value(\"string\"),\n","                  \"postal_code\": datasets.Value(\"string\"),\n","                  \"latitude\": datasets.Value(\"float\"),\n","                  \"longitude\": datasets.Value(\"float\"),\n","                  \"stars_x\": datasets.Value(\"float\"),\n","                  \"review_count\": datasets.Value(\"float\"),\n","                  \"is_open\": datasets.Value(\"float\"),\n","                  \"categories\": datasets.Value(\"string\"),\n","                  \"hours\": datasets.Value(\"string\"),\n","                  \"review_id\": datasets.Value(\"string\"),\n","                  \"user_id\": datasets.Value(\"string\"),\n","                  \"stars_y\": datasets.Value(\"float\"),\n","                  \"useful\": datasets.Value(\"float\"),\n","                  \"funny\": datasets.Value(\"float\"),\n","                  \"cool\": datasets.Value(\"float\"),\n","                  \"text\": datasets.Value(\"string\"),\n","                  \"date\": datasets.Value(\"string\"),\n","                  \"attributes\": datasets.Value(\"string\"),\n","              }),\n","          # No default supervised_keys (as we have to pass both question\n","          # and context as input).\n","          supervised_keys=None,\n","          homepage=\"https://www.yelp.com/dataset/download\",\n","          citation=_CITATION,\n","      )\n","\n","    def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:\n","      urls_to_download = self._URLS\n","      downloaded_files = dl_manager.download_and_extract(urls_to_download)\n","\n","      return [\n","          datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={\"filepath\": downloaded_files[\"train\"]}),\n","          datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={\"filepath\": downloaded_files[\"test\"]}),\n","      ]\n","\n","\n","    def _generate_examples(self, filepath):\n","        \"\"\"This function returns the examples in the raw (text) form.\"\"\"\n","        logging.info(\"generating examples from = %s\", filepath)\n","        with open(filepath, encoding=\"utf-8\") as csv_file:\n","            reader = csv.DictReader(csv_file)\n","            for i, row in enumerate(reader):\n","                # Handle missing values for float fields\n","                for key, value in row.items():\n","                    if value == '':\n","                        # Assuming all fields that can be empty are floats; adjust as needed\n","                        row[key] = None\n","                yield i, row\n","\n"],"metadata":{"id":"Kxsu_aqZRy11"},"execution_count":null,"outputs":[]}]}