Pipedrive/Pipedrive_Get_all_notes.ipynb

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    "<img width=\"8%\" alt=\"Pipedrive.png\" src=\"https://raw.githubusercontent.com/jupyter-naas/awesome-notebooks/master/.github/assets/logos/Pipedrive.png\" style=\"border-radius: 15%\">"
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   "source": [
    "# Pipedrive - Get all notes\n",
    "<a href=\"https://bit.ly/3JyWIk6\">Give Feedback</a> | <a href=\"https://github.com/jupyter-naas/awesome-notebooks/issues/new?assignees=&labels=bug&template=bug_report.md&title=Pipedrive+-+Get+all+notes:+Error+short+description\">Bug report</a>"
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   "id": "1528c23e-d4b5-4dae-aedd-3e0c3de7a07e",
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   "source": [
    "**Tags:** #pipedrive #notes #get #snippet #api #v1 #python #csv #export"
   ]
  },
  {
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   "id": "0f5b4999-cf8f-429b-a3b5-60abd6f0b4cb",
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   "source": [
    "**Author:** [Florent Ravenel](https://www.linkedin.com/in/florent-ravenel/)"
   ]
  },
  {
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   "source": [
    "**Last update:** 2023-01-04 (Created: 2023-01-04)"
   ]
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   "source": [
    "**Description:** This notebook retrieves all notes with access to your Pipedrive account."
   ]
  },
  {
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   "id": "6a0004b2-eb12-4dc2-b721-6b482cab7439",
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   "source": [
    "**References:**\n",
    "- [Pipedrive API v1 Documentation](https://developers.pipedrive.com/docs/api/v1/Notes#getNotes)\n",
    "- [Pipedrive API Authentication](https://developers.pipedrive.com/docs/api/authentication)\n",
    "- [Get your Pipedrive API token](https://developers.pipedrive.com/docs/api/authentication)."
   ]
  },
  {
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   "id": "906e7461-ec7c-4efe-952b-79a2fcdf2b94",
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   "source": [
    "## Input"
   ]
  },
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   "source": [
    "### Import libraries"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "import requests\n",
    "import naas\n",
    "import pandas as pd\n",
    "from datetime import date"
   ]
  },
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   "id": "0ab0d130-cbec-438c-a188-8a0cb295da4e",
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   "source": [
    "### Setup variables\n",
    "- `api_token`: API token used to authenticate the request.\n",
    "- `file_path`: CSV file path to save data\n",
    "- `params`: query parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d6ffb591-6b88-43f6-95b7-a93de4040366",
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   "source": [
    "api_token = naas.secret.get(\"PIPEDRIVE_API_KEY\") or \"YOUR_API_TOKEN\"\n",
    "file_path = f\"{date.today().isoformat()}_export_pipedrive_notes.csv\"\n",
    "params = {\n",
    "    \"user_id\": None,\n",
    "    \"lead_id\": None,\n",
    "    \"deal_id\": None,\n",
    "    \"person_id\": None,\n",
    "    \"org_id\": None,\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "61a6835b-4526-4d1e-9e21-e2c9325f0206",
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   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "### Get all notes"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "# Flatten the nested dict\n",
    "def flatten_dict(d, parent_key='', sep='_'):\n",
    "    \"\"\"\n",
    "    Flattens a nested dictionary into a single level dictionary.\n",
    "\n",
    "    Args:\n",
    "        d (dict): A nested dictionary.\n",
    "        parent_key (str): Optional string to prefix the keys with.\n",
    "        sep (str): Optional separator to use between parent_key and child_key.\n",
    "\n",
    "    Returns:\n",
    "        dict: A flattened dictionary.\n",
    "    \"\"\"\n",
    "    items = []\n",
    "    for k, v in d.items():\n",
    "        new_key = f\"{parent_key}{sep}{k}\" if parent_key else k\n",
    "        if isinstance(v, dict):\n",
    "            items.extend(flatten_dict(v, new_key, sep=sep).items())\n",
    "        else:\n",
    "            items.append((new_key, v))\n",
    "    return dict(items)\n",
    "\n",
    "def get_all_notes(\n",
    "    api_token,\n",
    "    params,\n",
    "    start=0,\n",
    "    limit=100,\n",
    "):\n",
    "    # Init\n",
    "    data = []\n",
    "    \n",
    "    # Requests\n",
    "    while True:\n",
    "        api_url = f'https://api.pipedrive.com/v1/notes?api_token={api_token}&start={start}&limit={limit}'\n",
    "        res = requests.get(api_url, params)\n",
    "        res.raise_for_status()\n",
    "        if res.status_code == 200:\n",
    "            res_json = res.json()\n",
    "        else:\n",
    "            print(f'Failed to get all notes. Status code: {res.status_code}')\n",
    "            break\n",
    "            \n",
    "        # Clean data\n",
    "        if res_json.get(\"success\") and res_json.get('data') is not None:\n",
    "            for r in res_json.get('data'):\n",
    "                data.append(flatten_dict(r))\n",
    "            start += 100\n",
    "        else:\n",
    "            break\n",
    "    return pd.DataFrame(data)\n",
    "        \n",
    "df = get_all_notes(api_token, params)\n",
    "print(\"Notes:\", len(df))\n",
    "df.head(5)"
   ]
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   "id": "7c89f6ac-4231-46ea-81ba-3aa90bc46f3c",
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   "source": [
    "## Output"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca89baa8-b76c-4f9e-8d60-74fdfacf141d",
   "metadata": {
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   "source": [
    "### Save data to CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4e6814d5-bfeb-413a-a4e9-7d9c70c4d95b",
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   "outputs": [],
   "source": [
    "df.to_csv(file_path, index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e625e87-9a42-44a4-a872-9ab557638886",
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   "source": [
    " "
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