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+{
+  "cells": [
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "3XEk4VVi483l"
+      },
+      "source": [
+        "## Table of Contents\n",
+        "* 1 - [Access data from a web browser](#section-1)\n",
+        "* 2 - [Access data using Tiled's Python client](#section-2)\n",
+        "    * 2.1 - [Setup kernel and required dependencies](#section-21)\n",
+        "    * 2.2 - [Read and download data](#section-22)\n",
+        "    * 2.3 - [Visualization and data analysis](#section-23)\n",
+        "    * 2.4 - [Log into an Authenticated Tiled Server](#section-24)\n",
+        "\n",
+        "Note that the output of this notebook was generated using [Google Colab](https://colab.research.google.com/).\n",
+        "\n"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "t2YtaEtj6w35"
+      },
+      "source": [
+        "## <a id='section-1'>1 - Access data from a web browser</a>\n",
+        "\n",
+        "Click the first tab on https://aimm.lbl.gov/"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "C0aLBAhQ7qr2"
+      },
+      "source": [
+        "## <a id='section-2'>2 - Access data using Tiled's Python client</a>\n",
+        "### <a id='section-21'>2.1 - Setup kernel and required dependencies</a>\n",
+        "**Tiled** is a data access service for data-aware portals and data science tools. Tiled has a Python client and integrates naturally with Python data science libraries, but nothing about the service is Python-specific; it also works from a web browser or any Internet-connected program.\n",
+        "\n",
+        "You can find a detailed **Tiled** document here: https://blueskyproject.io/tiled/tutorials/installation.html"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "611FyYOCruGJ",
+        "outputId": "8a484589-7e67-4455-b005-411ae02a32af"
+      },
+      "outputs": [],
+      "source": [
+        "# Install Tiled from PyPI using pip\n",
+        "!pip install \"tiled[client]\""
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "jLZMR8gjODEP"
+      },
+      "source": [
+        "### <a id='section-22'>2.2 - Read and download data</a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "BdoABDMurx5L"
+      },
+      "outputs": [],
+      "source": [
+        "# connect with client\n",
+        "from tiled.client import from_uri\n",
+        "\n",
+        "client = from_uri(\"https://aimm.lbl.gov\")"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "KSfWXEsWr9Qz",
+        "outputId": "503a80c1-46fe-4e09-9f7a-2f79c798b422"
+      },
+      "outputs": [],
+      "source": [
+        "client"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "liNBeFEV_Dow"
+      },
+      "source": [
+        "`client` holds a nested structure of data. Conceptually, it corresponds well to a directory of files or hierarchical structure like an HDF5 file or XML file.\n",
+        "\n",
+        "Tiled provides a utility for visualizing a nested structure. Each (sub)tree displays the names of a couple of its entries—up to however many fit on one line.\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "pAjnGK5m_C66",
+        "outputId": "4064d3d3-885d-4cbf-bd3e-f3a05a1859f3"
+      },
+      "outputs": [],
+      "source": [
+        "from tiled.utils import tree\n",
+        "tree(client)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9dG8jxIb_ZkQ"
+      },
+      "source": [
+        "`Containers` act like (nested) mappings in Python. All the (read-only) methods that work on Python dictionaries work on Containers. We can lookup a specific value by its key."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "79f0pNXpz1vx",
+        "outputId": "4bb64947-8608-4f95-c37d-73361d790d2e"
+      },
+      "outputs": [],
+      "source": [
+        "client"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "qLkXvf79_gY9"
+      },
+      "source": [
+        "list all the keys."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "0A5p_E2Stj6Y",
+        "outputId": "d809d623-82e1-4306-f16f-7e8ca53319a0"
+      },
+      "outputs": [],
+      "source": [
+        "list(client)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "ZlfARXNHsAsm",
+        "outputId": "d6482c04-1f61-4b1a-f4f9-190dffbb05f3"
+      },
+      "outputs": [],
+      "source": [
+        "client['newville']"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "jnH6teuwsCuz",
+        "outputId": "299b3ce3-13b9-45c8-83b4-c1d8019ae4d2"
+      },
+      "outputs": [],
+      "source": [
+        "client['newville']['2DKJLMZPi8s']"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "9KIsSXwGNnyu"
+      },
+      "source": [
+        "To read data"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 424
+        },
+        "id": "7INhruoMvVJX",
+        "outputId": "c7293d8b-6b0c-4c2a-ed6b-ab5e2d292d48"
+      },
+      "outputs": [],
+      "source": [
+        "client['newville']['2DKJLMZPi8s'].read()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "tj_plDvVNvTs"
+      },
+      "source": [
+        "To read slices of data"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 424
+        },
+        "id": "LD0ycDlcNu0-",
+        "outputId": "aef08994-7751-4274-eb48-3a40d8b99197"
+      },
+      "outputs": [],
+      "source": [
+        "client['newville']['2DKJLMZPi8s'].read(['energy', 'i0'])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "SbitOnXkOYds"
+      },
+      "source": [
+        "The Tiled server can encode its structures in various formats for exporting data. These are just a couple of the supported formats:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "sCnQ-wLpOG6w"
+      },
+      "outputs": [],
+      "source": [
+        "# Table\n",
+        "client['newville']['2DKJLMZPi8s'].export(\"table.xlsx\")  # Excel\n",
+        "client['newville']['2DKJLMZPi8s'].export(\"table.csv\")  # CSV\n",
+        "\n",
+        "# Array\n",
+        "client['newville']['2DKJLMZPi8s'].export(\"numbers.csv\")  # CSV\n",
+        "# client['newville']['2DKJLMZPi8s'].export(\"image.png\")  # PNG image\n",
+        "# client['newville']['2DKJLMZPi8s'].export(\"image.tiff\")  # TIFF image"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "xSxpVbrAO6Ph"
+      },
+      "source": [
+        "If running this notebook on Google Colab, click the folder sign on the left panel and you will see the exported files, right click to download to your local machine."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "165CoOVROG8n"
+      },
+      "outputs": [],
+      "source": [
+        "# Export just some of the columns...\n",
+        "# client['newville']['2DKJLMZPi8s'].export(\"table.csv\", columns=[\"energy\", \"i0\"])"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "1QgVv9u6Q5Wb"
+      },
+      "source": [
+        "### <a id='section-23'>2.3 - Visualization and data analysis</a>"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "Nt_cqdqFwcZu",
+        "outputId": "592e2718-e627-4a88-fc85-7ff67fee9738"
+      },
+      "outputs": [],
+      "source": [
+        "import matplotlib.pyplot as plt\n",
+        "\n",
+        "energy_data = client['newville']['2DKJLMZPi8s'].read(['energy'])\n",
+        "i0_data = client['newville']['2DKJLMZPi8s'].read(['i0'])\n",
+        "\n",
+        "plt.plot(energy_data, i0_data)\n",
+        "plt.xlabel('Energy')\n",
+        "plt.ylabel('i0')\n",
+        "plt.title('Energy vs i0 Plot')\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 472
+        },
+        "id": "RgiE5P5vRQ_h",
+        "outputId": "ee93822c-4d32-4f67-ce4e-a08b1e1ed15b"
+      },
+      "outputs": [],
+      "source": [
+        "plt.hist(energy_data, bins=50, color='blue', alpha=0.7)\n",
+        "plt.title('Energy Histogram')\n",
+        "plt.xlabel('Values')\n",
+        "plt.ylabel('Frequency')\n",
+        "plt.grid(True)\n",
+        "plt.show()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "CuIak7-zRvzZ"
+      },
+      "source": [
+        "<a id='section-24'></a>\n",
+        "## 2.4 Log into an Authenticated Tiled Server\n",
+        "So that you can access private dataset"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "qk7sUInyto1u",
+        "outputId": "7cb97f0a-c459-44b4-e2b7-c6a89dd60855"
+      },
+      "outputs": [],
+      "source": [
+        "client.login()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "NrQCq4uLuC6e",
+        "outputId": "6c5827c9-8a78-40fc-9fa8-eefa5228a5b5"
+      },
+      "outputs": [],
+      "source": [
+        "client"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/"
+        },
+        "id": "rOwzNdh9uNRj",
+        "outputId": "8a619ebc-322f-4f46-f46d-ed24e1099b75"
+      },
+      "outputs": [],
+      "source": [
+        "list(client)"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "tjdHaFS8uRG5"
+      },
+      "outputs": [],
+      "source": [
+        "wanli_dataset = client['aimm_core']"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "colab": {
+          "base_uri": "https://localhost:8080/",
+          "height": 424
+        },
+        "id": "BlEIzj8IuV1o",
+        "outputId": "4180f230-4aef-48df-a578-631cb876de76"
+      },
+      "outputs": [],
+      "source": [
+        "wanli_dataset['4yk5nB7RvRN'].read()"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {
+        "id": "qd6XJtkSSbQ4"
+      },
+      "source": [
+        "Now log out via:"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "1PX79QRNul_s"
+      },
+      "outputs": [],
+      "source": [
+        "client.logout()"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "plULB7QOScjJ"
+      },
+      "outputs": [],
+      "source": []
+    }
+  ],
+  "metadata": {
+    "colab": {
+      "provenance": []
+    },
+    "kernelspec": {
+      "display_name": "Python 3",
+      "name": "python3"
+    },
+    "language_info": {
+      "name": "python"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 0
+}