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Merge pull request #2570 from jupyter-naas/2569-pennylane-invoices-in…
…tegration feat: add Pennylane integration
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{ | ||
"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 | ||
} |
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