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Merge pull request #113 from oceanprotocol/link-to-datascience-oceanprotocol-com
Add link & explanation of Jupyter notebook tuts
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@ -3,20 +3,18 @@ title: Tools & Examples
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description: Tools and examples for developing with Ocean Protocol.
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---
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The Setup & Tutorials sections have some examples to get you started.
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- [Setup: Quick Start](/setup/quickstart/)
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- [Tutorials: Introduction](/tutorials/introduction/)
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## Tools
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Coming soon!
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## Examples
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The [Tutorials](/tutorials/introduction/) include many examples.
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Examples of using the [🦑 squid-py](https://github.com/oceanprotocol/squid-js) Python library:
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<repo name="mantaray"></repo>
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<repo name="tuna"></repo>
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Examples of using the [🦑 squid-js](https://github.com/oceanprotocol/squid-js) JavaScript library:
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@ -3,14 +3,9 @@ title: Overview of the Tutorials
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description: What you can expect to find in these Ocean Protocol tutorials.
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---
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These tutorials give examples of how to use squid-js (JavaScript) and squid-py (Python) to:
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The idea of these tutorials is to show you how to use squid-js (JavaScript) and squid-py (Python) to:
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- publish a data set
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- publish a compute service
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- get and use a data set
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- publish a compute service
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- get and use a compute service
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The Python tutorials use [Jupyter notebooks](http://jupyter.org/).
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For now, check out [the Mantaray repository](https://github.com/oceanprotocol/mantaray). In the future, we hope to have live online Jupyter notebooks.
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<repo name="mantaray"></repo>
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17
content/tutorials/jupyter-notebooks.md
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17
content/tutorials/jupyter-notebooks.md
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@ -0,0 +1,17 @@
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---
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title: Jupyter Notebooks
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description: Try some online interactive squid-py tutorials.
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---
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You can go through interactive squid-py tutorials at [datascience.oceanprotocol.com](https://datascience.oceanprotocol.com/).
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They're [Jupyter Notebooks](http://jupyter.org/) running on your own [JupyterLab](https://github.com/jupyterlab/jupyterlab) instance.
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It's quite easy to figure out, but if you get stuck, here are some initial steps:
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- Visit [datascience.oceanprotocol.com](https://datascience.oceanprotocol.com/).
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- Click the **JupyterLab Instance** button.
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- Login with your GitHub account.
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- Once you're in the JupyterLab console, double-click on **mantaray_jupyter**.
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- Double-click on **introdution.txt** and read it.
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- Double-click on one of the **.ipynb** files. They're labelled to appear in a logical order.
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- When asked to select a kernel, select Python 3.
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- To make stuff happen (e.g. to run code cells), use the menus at the top of the JupyterLab console, or at the top of your current Jupyter notebook.
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@ -7,7 +7,7 @@
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- title: Set Up Azure Storage
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link: /tutorials/azure-for-brizo/
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- group: React App Tutorial
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- group: React App Tutorial (squid-js)
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items:
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- title: Setup
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link: /tutorials/react-setup/
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@ -15,3 +15,8 @@
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link: /tutorials/react-publish-data-set/
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- title: Get & Use a Data Set
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link: /tutorials/react-get-use-data-set/
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- group: squid-py Tutorials
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items:
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- title: Jupyter Notebooks
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link: /tutorials/jupyter-notebooks/
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