Added the first custom crawler documentation files

custom-crawls/README.md

@@ -0,0 +1,42 @@
+# Tutorial: Custom Crawlers
+
+_Note: This tutorial is a work in progress. Please add your feedback to [datatogether/learning](https://github.com/datatogether/learning/issues)!_
+
+## Prerequisites
+
+* You would like to provide a custom representation of data on a website. This can include difficult-to-scrape dynamic content such database views, web application or search form results, but can also include "crawlable" content that may be useful in a different data representation (e.g. a csv version of an HTML table).
+
+## Learning Objectives
+
+After going through this tutorial you will know
+
+* What a custom crawler is and why some websites need one
+* What your custom crawler needs to extract from a webpage
+* How to write a custom crawler that works with Data Together
+
+## Key Concepts
+
+* Custom Crawler:  An automated way to download data and prepare it for upload into the Data Together network. This is usually a script file that is written specifically for a dataset.
+* [Morph.io](https://morph.io/): An online service that automates and saves user created scripts.
+* [Archivertools](https://github.com/datatogether/archivertools): An Python package to aid in accessing Morph.io and Data Together APIs using an Archiver class. This package also contains some common scraping functions. Currently written in Python 3.
+
+## Lessons
+
+1. What is custom crawling?
+   * Why do some websites need custom crawls?
+   * What should your custom crawler extract from the webpage?
+   * Examples of sites needing custom crawlers
+1. Introduction/tutorial for Morph
+   * What is Morph.io?
+   * How to setup a Morph.io account
+   * Getting a DataTogether API key, and making sure Morph can access it
+1. A tutorial for Archivertools package
+   * What does it do?
+   * Installing the package
+   * <https://github.com/datatogether/archivertools>
+   * Using the Archiver class
+1.	Some example custom crawls scripts and implementation
+
+## Next Steps
+
+Look at the other resources under Data Together for more background on DataTogether and storing datasets