Improve getting started documentation (kensho-technologies#323)

* Improving schema autogeneration documentation

* Fix README.md example

* Nits

* Fix typo

* Fix step number

* Revert testing config changes

* Fix end-to-end example

* Shorten README.md

* Nit

* Remove boilerplate database startup code

* Fix typo

* Communicate assumptions through code

* Nits

* Remove getting started section

Author: pmantica1

README.md

@@ -23,7 +23,7 @@ query languages.
 
 Furthermore, the GraphQL compiler validates queries through the use of a GraphQL schema 
 that specifies the underlying schema of the database. We can currently autogenerate a 
-GraphQL schema by introspecting an OrientDB database, (see [Querying OrientDB with GraphQL](#querying-orientdb-with-graphql)). 
+GraphQL schema by introspecting an OrientDB database, (see [End to End Example](#end-to-end-example)). 
 
 In the near future, we plan to add schema autogeneration from SQLAlchemy metadata as well. 
 
@@ -32,7 +32,7 @@ For a more detailed overview and getting started guide, please see
 
 ## Table of contents
   * [Features](#features)
-  * [Querying OrientDB with GraphQL](#querying-orientdb-with-graphql)
+  * [End to End Example](#end-to-end-example)
   * [Definitions](#definitions)
   * [Directives](#directives)
      * [@optional](#optional)
@@ -77,27 +77,56 @@ For a more detailed overview and getting started guide, please see
    these databases. See the [SQL](#sql) section for more details.
 * **GraphQL Language Features:**  We prioritized and implemented a subset of all functionality supported by the GraphQL language. We hope to add more functionality over time.
 
-## Querying OrientDB with GraphQL
-```python3
+## End-to-End Example
+Even though this example specifically targets an OrientDB database, it is meant as a generic 
+end-to-end example of how to use the GraphQL compiler.
+
+```python
+from graphql.utils.schema_printer import print_schema
 from graphql_compiler import (
     get_graphql_schema_from_orientdb_schema_data, graphql_to_match
 )
 from graphql_compiler.schema_generation.orientdb.utils import ORIENTDB_SCHEMA_RECORDS_QUERY
-from graphql_compiler.tests.conftest import init_integration_graph_client
-
-# The following code is meant to serve as a mock example and will not run
-# unless you are in the development environment outlined by CONTRIBUTING.md.
-
-# Step 1: Initialize dummy OrientDB database and get pyorient OrientDB client
-client = init_integration_graph_client()
 
-# Step 2: Generate GraphQL schema from queried OrientDB schema records
+# Step 1: Get schema metadata from hypothetical Animals database.
+client = your_function_that_returns_an_orientdb_client()
 schema_records = client.command(ORIENTDB_SCHEMA_RECORDS_QUERY)
-schema_data = [x.oRecordData for x in schema_records]
+schema_data = [record.oRecordData for record in schema_records]
+
+# Step 2: Generate GraphQL schema from metadata.
 schema, type_equivalence_hints = get_graphql_schema_from_orientdb_schema_data(schema_data)
 
-# Step 3: Write GraphQL query to get the names of all animals with a particular net worth
-# Note that we prefix net_worth with '$' and surround it with quotes to indicate it's a parameter
+print(print_schema(schema))
+# schema {
+#    query: RootSchemaQuery
+# }
+#
+# directive @filter(op_name: String!, value: [String!]!) on FIELD | INLINE_FRAGMENT
+#
+# directive @tag(tag_name: String!) on FIELD
+#
+# directive @output(out_name: String!) on FIELD
+#
+# directive @output_source on FIELD
+#
+# directive @optional on FIELD
+#
+# directive @recurse(depth: Int!) on FIELD
+#
+# directive @fold on FIELD
+#
+# type Animal {
+#     name: String
+#     net_worth: Int
+#     limbs: Int
+# }
+#
+# type RootSchemaQuery{
+#     Animal: [Animal]
+# }
+    
+# Step 3: Write GraphQL query that returns the names of all animals with a certain net worth.
+# Note that we prefix net_worth with '$' and surround it with quotes to indicate it's a parameter.
 graphql_query = '''
 {
     Animal {
@@ -110,24 +139,14 @@ parameters = {
     'net_worth': '100',
 }
 
-# Step 4: Use autogenerated GraphQL schema to compile query into Match, an OrientDB query language
+# Step 4: Use autogenerated GraphQL schema to compile query into the target database language.
 compilation_result = graphql_to_match(schema, graphql_query, parameters, type_equivalence_hints)
-
-# Step 5: Run query in OrientDB
-query = compilation_result.query
-results = [row.oRecordData for row in client.command(query)]
-assert results == [{'animal_name': 'Animal 1'}]
+print(compilation_result.query)
+# SELECT Animal___1.name AS `animal_name` 
+# FROM  ( MATCH  { class: Animal, where: ((net_worth = decimal("100"))), as: Animal___1 } 
+# RETURN $matches)
 ```
 ## Definitions
-- **GraphQLSchema object**- To be able to compile GraphQL, the first thing you will need is a GraphQLSchema object describing 
-the underlying database. To build it you can use `get_graphql_schema_from_orientdb_schema_data` as 
-demonstrated in the code example below. 
-```python
-# Generate GraphQL schema from queried OrientDB schema records
-schema_records = client.command(ORIENTDB_SCHEMA_RECORDS_QUERY)
-schema_data = [x.oRecordData for x in schema_records]
-schema, type_equivalence_hints = get_graphql_schema_from_orientdb_schema_data(schema_data)
-```
 - **Vertex field**: A field corresponding to a vertex in the graph. In the below example, `Animal`
   and `out_Entity_Related` are vertex fields. The `Animal` field is the field at which querying
   starts, and is therefore the **root vertex field**. In any scope, fields with the prefix `out_`