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@@ -17,6 +17,9 @@ | |
| }, | ||
| { | ||
| "path": ".." | ||
| }, | ||
| { | ||
| "path": "../../dora-back" | ||
| } | ||
| ] | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,199 @@ | ||
| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "%pip install -e ../../../pipeline\n", | ||
| "%pip install -e ../../../../data-inclusion-schema\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import os\n", | ||
| "\n", | ||
| "import dotenv\n", | ||
| "import pandas as pd\n", | ||
| "\n", | ||
| "from data_inclusion.scripts.tasks import grist\n", | ||
| "from data_inclusion import schema" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "dotenv.load_dotenv(dotenv.find_dotenv())\n", | ||
| "\n", | ||
| "GRIST_API_TOKEN = os.environ[\"GRIST_API_TOKEN\"]\n", | ||
| "GRIST_API_URL = \"https://grist.incubateur.net/api\"\n", | ||
| "WORKSPACE_ID = \"27\"\n", | ||
| "DOCUMENT_NAME = \"template\"" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "grist_client = grist.GristClient(base_url=GRIST_API_URL, token=GRIST_API_TOKEN)\n", | ||
| "\n", | ||
| "document_id = grist_client.create_document(\n", | ||
| " workspace_id=WORKSPACE_ID, document_name=DOCUMENT_NAME\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "for referentiel in [\n", | ||
| " \"frais\",\n", | ||
| " \"labels_nationaux\",\n", | ||
| " \"modes_accueil\",\n", | ||
| " \"modes_orientation_accompagnateur\",\n", | ||
| " \"modes_orientation_beneficiaire\",\n", | ||
| " \"profils\",\n", | ||
| " \"thematiques\",\n", | ||
| " \"typologies_de_services\",\n", | ||
| " \"typologies_de_structures\",\n", | ||
| " \"zones_de_diffusion_types\",\n", | ||
| "]:\n", | ||
| " table_id = grist_client.create_table(\n", | ||
| " document_id=document_id,\n", | ||
| " table_name=referentiel.capitalize(),\n", | ||
| " columns=[\n", | ||
| " {\"id\": \"value\", \"fields\": {\"label\": \"valeur\", \"type\": \"Text\"}},\n", | ||
| " {\"id\": \"label\", \"fields\": {\"label\": \"label\", \"type\": \"Text\"}},\n", | ||
| " ],\n", | ||
| " )\n", | ||
| "\n", | ||
| " referentiel_df = pd.read_csv(\n", | ||
| " f\"../../../pipeline/dbt/seeds/schema/{referentiel}.csv\",\n", | ||
| " dtype=str,\n", | ||
| " )\n", | ||
| "\n", | ||
| " # attention: pas idempotent\n", | ||
| "\n", | ||
| " grist_client.add_records(\n", | ||
| " document_id=document_id,\n", | ||
| " table_id=table_id,\n", | ||
| " records=[\n", | ||
| " {\"fields\": value_dict}\n", | ||
| " for value_dict in referentiel_df[[\"value\", \"label\"]].to_dict(\n", | ||
| " orient=\"records\"\n", | ||
| " )\n", | ||
| " ],\n", | ||
| " )" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "import re\n", | ||
| "\n", | ||
| "\n", | ||
| "def get_column_type(field) -> str:\n", | ||
| " match_referentiel = re.search(\n", | ||
| " r\"data_inclusion.schema.(?P<referentiel>\\w+)\", str(field.annotation)\n", | ||
| " )\n", | ||
| "\n", | ||
| " if match_referentiel is not None:\n", | ||
| " return \"Ref:\" + match_referentiel.group(\"referentiel\").capitalize()\n", | ||
| " elif \"float\" in str(field.annotation):\n", | ||
| " return \"Numeric\"\n", | ||
| " elif \"bool\" in str(field.annotation):\n", | ||
| " return \"Bool\"\n", | ||
| " elif \"date\" in str(field.annotation):\n", | ||
| " return \"DateTime:Europe/Paris\"\n", | ||
| "\n", | ||
| " return \"Text\"" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "grist_columns = [\n", | ||
| " {\n", | ||
| " \"id\": field_name,\n", | ||
| " \"fields\": {\n", | ||
| " \"label\": field_name,\n", | ||
| " \"type\": get_column_type(field_info),\n", | ||
| " # \"visibleCol\": TODO\n", | ||
| " },\n", | ||
| " }\n", | ||
| " for field_name, field_info in schema.Structure.model_fields.items()\n", | ||
| "]\n", | ||
| "\n", | ||
| "grist_client.create_table(\n", | ||
| " document_id=document_id,\n", | ||
| " table_name=\"Structures\",\n", | ||
| " columns=grist_columns,\n", | ||
| ")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": {}, | ||
| "outputs": [], | ||
| "source": [ | ||
| "grist_columns = [\n", | ||
| " {\n", | ||
| " \"id\": field_name,\n", | ||
| " \"fields\": {\n", | ||
| " \"label\": field_name,\n", | ||
| " \"type\": get_column_type(field_info),\n", | ||
| " # \"visibleCol\": TODO\n", | ||
| " },\n", | ||
| " }\n", | ||
| " for field_name, field_info in schema.Service.model_fields.items()\n", | ||
| "]\n", | ||
| "\n", | ||
| "grist_client.create_table(\n", | ||
| " document_id=document_id,\n", | ||
| " table_name=\"Services\",\n", | ||
| " columns=grist_columns,\n", | ||
| ")\n" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": ".venv", | ||
| "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": "3.10.11" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 2 | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,3 @@ | ||
| structures | ||
| services | ||
| *.html |
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