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Create kite_tutorial.ipynb
Co-Authored-By: Ranuga <[email protected]>
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‎kite_tutorial.ipynb

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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"![Logo](https://kite.com/kite-public/kite-plus-jlab-scaled.png)\n",
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"\n",
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"### Welcome to Kite's JupyterLab extension tutorial\n",
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"\n",
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"Kite gives you **ML-powered autocompletions** and **rich documentation** inside JupyterLab. This guide will teach you everything you need to know about Kite in 5 minutes or less.\n",
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"\n",
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"> 💡 _**Tip:** You can open this file at any time with the command `Kite: Open Tutorial` in JupyterLab's command palette._\n",
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"\n",
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"#### Before we start...\n",
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"\n",
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"Make sure that the Kite icon at the bottom of the window reads `Kite: ready`.\n",
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"\n",
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"![Kite icon](https://kite.com/kite-public/kite-status.png)\n",
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"\n",
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"* If it says `Kite: not running`, please start the Kite Engine first.\n",
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"* If it says `Kite: not installed`, please [download and install Kite](https://kite.com/download) first."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Part 1: Autocompletions\n",
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"\n",
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"**Step 1a**<br/>\n",
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"Run the code cell below with all the necessary imports 👇"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Run me!\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"import pandas as pd"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Step 1b**<br/>\n",
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"Let's try typing out some code to plot a sine graph. As you type, Kite will automatically show you completions for what you're going to type next.\n",
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"\n",
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"![Autocompletions](https://www.kite.com/kite-public/kite-jlab-autocompletions.gif)\n",
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"\n",
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"> 💡 _**Tip:** You can turn completions docs on and off in JupyterLab's command palette with the command `Kite: Toggle Docs Panel`._\n",
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"\n",
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"> 💡 _**Tip:** The starred completions ★ are from Kite Pro. You can [start your free Kite Pro trial](https://www.kite.com/pro/trial/) anytime. Afterwards, if you choose not to upgrade, you can still use Kite 100% for free._\n",
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"\n",
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"Try typing out the code yourself to see Kite's autocompletions in action.<br/>\n",
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"\n",
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"```python\n",
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"x = np.linspace(-np.pi, np.pi, 50)\n",
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"y = np.sin(x)\n",
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"plt.plot(x, y)\n",
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"```\n",
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"\n",
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"Type this code in the cell below 👇"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Put code in me\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Part 2: Manual completions\n",
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"\n",
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"You can still use JupyterLab's builtin kernel completions. These are particularly useful when you need to access a `DataFrame`'s column names.\n",
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"\n",
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"**Step 2a**<br/>\n",
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"First, run the code cell below to get some sample data to store in a `DataFrame` 👇"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Run me!\n",
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"url = 'https://kite.com/kite-public/iris.csv'\n",
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"df = pd.read_csv(url)\n",
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"df.head()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Step 2b**<br/>\n",
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"Let's plot a scatter graph of sepal length vs. sepal width. When you are accessing a `DataFrame`'s columns, you'll still need to hit `tab` to request completions from the kernel.\n",
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"\n",
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"![Manual completions](https://www.kite.com/kite-public/kite-jlab-manual-completions.gif)\n",
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"\n",
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"Try requesting kernel completions yourself.\n",
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"\n",
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"```python\n",
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"plt.scatter(df['sepal_length'], df['sepal_width'])\n",
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"```\n",
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"\n",
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"Type this code in the cell below, making sure to hit `tab` when you are filling in the column names 👇"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Put code in me\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### Part 3: Copilot Documentation\n",
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"\n",
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"If you've enabled \"docs following cursor\" in the Copilot, the Copilot will automatically update with the documentation of the identifier underneath your cursor.\n",
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"\n",
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"![Autosearch](https://www.kite.com/kite-public/kite-jlab-autosearch.gif)\n",
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"\n",
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"**Step 3a**<br/>\n",
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"Try it yourself! Just click around in the code cells of this notebook and see the Copilot update automatically."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"#### The End\n",
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"\n",
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"Now you know everything you need to know about Kite's JupyterLab plugin. Kite is under active development and we expect to ship improvements and more features in the near future.\n",
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"\n",
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"In the meantime, if you experience bugs or have feature requests, feel free to open an issue in our [public GitHub repo](https://github.com/kiteco/issue-tracker).\n",
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"\n",
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"Happy coding!"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}

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