feat: add notebook init

Pennylane/Pennylane_List_all_categories.ipynb

@@ -0,0 +1,239 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1ec65662-8eb6-4a98-a16e-ffc3729252b6",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2021-02-23T14:22:16.610471Z",
+     "iopub.status.busy": "2021-02-23T14:22:16.610129Z",
+     "iopub.status.idle": "2021-02-23T14:22:16.627784Z",
+     "shell.execute_reply": "2021-02-23T14:22:16.626866Z",
+     "shell.execute_reply.started": "2021-02-23T14:22:16.610384Z"
+    },
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "<img width=\"8%\" alt=\"Pennylane.png\" src=\"https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/.github/assets/logos/Pennylane.png\" style=\"border-radius: 15%\">"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "hairy-interstate",
+   "metadata": {},
+   "source": [
+    "# Pennylane - List all categories"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "db03090b-015f-4b1b-8c7c-ba11f37d60b5",
+   "metadata": {},
+   "source": [
+    "**Tags:** #pennylane #list #categories #snippet"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c54c97eb-8d4d-417c-a402-7adf5327d7fb",
+   "metadata": {},
+   "source": [
+    "**Author:** [Florent Ravenel](https://www.linkedin.com/in/florent-ravenel/)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ed962863-54e5-48e4-aa48-877adeba86fc",
+   "metadata": {},
+   "source": [
+    "**Description:** This endpoint returns a list of categories."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fdcf05b5-17d7-4c11-88ec-f722cf264a7f",
+   "metadata": {},
+   "source": [
+    "## Input"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "75da13af-72c2-44b9-8c06-ed3bfa4700ac",
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2022-08-31T10:54:23.866665Z",
+     "iopub.status.busy": "2022-08-31T10:54:23.866431Z",
+     "iopub.status.idle": "2022-08-31T10:54:23.871270Z",
+     "shell.execute_reply": "2022-08-31T10:54:23.870705Z",
+     "shell.execute_reply.started": "2022-08-31T10:54:23.866641Z"
+    },
+    "tags": []
+   },
+   "source": [
+    "### Import libraries"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b5605c12-6814-4d98-99b0-aaaa4526014f",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "import pandas as pd\n",
+    "import naas_python #to use this lib create your account on naas.ai"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1b6ad1a8-308e-4778-963c-fc21d492a1a9",
+   "metadata": {},
+   "source": [
+    "### Setup variables"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "06d385f7-6b96-4e95-8721-b02ef7c52c83",
+   "metadata": {
+    "tags": [
+     "parameters"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "api_token = naas_python.secret.get(\"PENNYLANE_API_TOKEN\").value or \"YOUR_PENNYLANE_API_TOKEN\" # if you don't have a naas.ai account, add api_token as string"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e2b06c06-c20d-4d1a-a228-dca532603925",
+   "metadata": {},
+   "source": [
+    "## Model"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "14cd5a2a-8e0a-45f6-a31c-f487950db30d",
+   "metadata": {},
+   "source": [
+    "### List all categories"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4a62312c-53f7-4285-b1fd-5dde2592022c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "def list_all_catgories(\n",
+    "    api_token,\n",
+    "    per_page=50,\n",
+    "    sort=None,\n",
+    "    filter=None,\n",
+    "):\n",
+    "    url = \"https://app.pennylane.com/api/external/v1/categories\"\n",
+    "    headers = {\n",
+    "        \"Accept\": \"application/json\",\n",
+    "        \"Authorization\": f\"Bearer {api_token}\"\n",
+    "    }\n",
+    "    data = []\n",
+    "    page = 1\n",
+    "    while True:\n",
+    "        # Get data\n",
+    "        res_json = []\n",
+    "        params = {\n",
+    "            \"page\": page,\n",
+    "            \"per_page\": per_page,\n",
+    "        }\n",
+    "        res = requests.get(url, headers=headers, params=params)\n",
+    "        res.raise_for_status()\n",
+    "        if res.status_code == 200:\n",
+    "            result = res.json().get(\"categories\")\n",
+    "\n",
+    "        # Concat result\n",
+    "        if len(result) > 0:\n",
+    "            data += result\n",
+    "            page += 1\n",
+    "        else:\n",
+    "            break\n",
+    "    return data\n",
+    "\n",
+    "result = list_all_catgories(api_token)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "21da518a-e9a5-4655-87a2-52e005f31dbe",
+   "metadata": {},
+   "source": [
+    "## Output"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "08861687-49bb-4c65-83a3-a483a8c4b708",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "source": [
+    "### Display result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b123c08c-124a-44ac-bc44-fc72a7768434",
+   "metadata": {
+    "papermill": {},
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "df = pd.DataFrame(result)\n",
+    "print(\"Rows:\", len(df))\n",
+    "df.head(5)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "078e5821-d264-48b4-a1d1-7bfbc1c05490",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}