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Small fixes for web rendering
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docs/src/client/stores.md

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docs/src/faq.md

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It is common to enter data during experiments using a graphical user interface.
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1. The [DataJoint Works](https://works.datajoint.com) platform is a web-based, fully
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managed service to host and execute data pipelines.
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1. The [DataJoint Works](https://works.datajoint.com) platform is a web-based,
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end-to-end platform to host and execute data pipelines.
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2. [DataJoint LabBook](https://github.com/datajoint/datajoint-labbook) is an open
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source project for data entry but is no longer actively maintained.

docs/src/quick-start.md

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# Quick Start Guide
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## Tutorials
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The easiest way to get started is through the [DataJoint
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Tutorials](https://github.com/datajoint/datajoint-tutorials). These tutorials are
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configured to run using [GitHub Codespaces](https://github.com/features/codespaces)
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where the full environment including the database is already set up.
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Advanced users can install DataJoint locally. Please see the installation instructions below.
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## Installation
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First, please [install Python](https://www.python.org/downloads/) version

docs/src/tutorials/dj-top.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Using the `dj.Top` restriction\n",
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"\n",
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"# Using the dj.Top restriction"
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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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"First you will need to [install](../../getting-started/#installation) and [connect](../../getting-started/#connection) to a DataJoint [data pipeline](https://datajoint.com/docs/core/glossary/#data-pipeline).\n",
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"\n",
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"Now let's start by importing the `datajoint` client."
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"schema = dj.Schema('university')"
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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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"# Table Definition"
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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": 2,
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" \"\"\""
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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": 59,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"[2024-12-26 12:03:01,311][INFO]: Table altered\n"
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]
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}
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],
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"source": [
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"StudentMajor.definition = \"\"\"\n",
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"-> Student\n",
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"---\n",
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"-> Department\n",
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"declare_date : date # when student declared her major\n",
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"\"\"\"\n",
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"StudentMajor.alter()"
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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": 60,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"-> Student\n",
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"---\n",
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"-> Department\n",
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"declare_date : date # when student declared her major\n",
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"\n"
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]
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}
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],
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"source": [
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"print(StudentMajor.describe())"
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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": 5,
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" \"\"\""
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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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"# Insert"
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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": 6,
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" for key, grade in zip(grade_keys, random.choices(grades, k=len(grade_keys))))"
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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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"# dj.Top Restriction"
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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": 29,

docs/src/tutorials/json.ipynb

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"id": "7fe24127-c0d0-4ff8-96b4-6ab0d9307e73",
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"metadata": {},
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"source": [
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"# Using the `json` type"
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"# Using the json type"
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]
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},
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{

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