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Updated the link to our Attachments documentation for the data rows tutorial.
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examples/basics/data_rows.ipynb

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"cells": [
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{
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"cell_type": "markdown",
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"id": "premier-olympus",
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"metadata": {},
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"source": [
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"# Data rows"
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]
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},
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{
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"cell_type": "markdown",
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"id": "affecting-former",
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"metadata": {},
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"source": [
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"* Data rows are the items that are actually being labeled. We currently support the following:\n",
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "posted-nation",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "beautiful-ready",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "vertical-stockholm",
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "markdown",
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"id": "legendary-harvard",
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"metadata": {},
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"source": [
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"* Set the following cell with your data to run this notebook"
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{
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"cell_type": "code",
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"execution_count": 3,
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"id": "rural-fellow",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "proof-detective",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "selective-reconstruction",
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"metadata": {},
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"outputs": [],
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"source": [
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},
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{
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"cell_type": "markdown",
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"id": "registered-cause",
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"metadata": {},
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"source": [
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"### Read"
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{
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"cell_type": "code",
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"execution_count": 6,
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"id": "extra-paris",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "packed-going",
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"metadata": {},
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"outputs": [
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{
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{
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"cell_type": "code",
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"execution_count": 8,
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"id": "above-vocabulary",
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"metadata": {},
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"outputs": [
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{
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},
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{
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"cell_type": "markdown",
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"id": "successful-patch",
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"metadata": {},
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"source": [
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"### Create\n",
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{
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"cell_type": "code",
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"execution_count": 9,
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"id": "medical-portuguese",
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"metadata": {},
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"outputs": [
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{
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},
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{
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"cell_type": "markdown",
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"id": "helpful-lingerie",
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"metadata": {},
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"source": [
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"* Bulk create data rows (This is much faster than creating individual data rows)"
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{
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"cell_type": "code",
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"execution_count": 10,
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"id": "round-perfume",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "breeding-brother",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 12,
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"id": "thrown-designation",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 13,
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"id": "japanese-jefferson",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 14,
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"id": "accessible-effort",
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"metadata": {},
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"outputs": [
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{
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},
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{
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"cell_type": "markdown",
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"id": "interested-proxy",
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"metadata": {},
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"source": [
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"### Update"
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{
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"cell_type": "code",
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"execution_count": 15,
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"id": "floral-elimination",
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"metadata": {},
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"outputs": [
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{
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{
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"cell_type": "code",
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"execution_count": 16,
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"id": "collect-cosmetic",
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"metadata": {},
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"outputs": [
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{
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"# Attachments are visible for all projects connected to the data_row \n",
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"data_row.create_attachment(attachment_type=\"TEXT\", attachment_value=\"LABELERS WILL SEE THIS \")\n",
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"# See more information here:\n",
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"# https://docs.labelbox.com/data-model/en/index-en#attachments\n",
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"# https://docs.labelbox.com/reference/type-image\n",
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"# Note that attachment_value must always be a string (url to a video/image or a text value to display)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "explicit-morrison",
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"metadata": {},
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"source": [
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"### Delete"
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{
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"cell_type": "code",
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"execution_count": 17,
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"id": "dental-banana",
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"metadata": {},
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"outputs": [],
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"source": [
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "binary-organic",
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"metadata": {},
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"outputs": [],
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"source": [
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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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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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.2"
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"version": "3.8.5"
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}
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},
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"nbformat": 4,

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