Added README

Author: Josh Smith

README.md

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+# Streams Processing for Inventory Management
+
+Simple python example that demonstrates the power of stream processing for cases like inventory management. 
+
+Processor takes a tumbling window of 10 seconds, and aggregates the inventory changes by SKU and Location before making them into a 
+more coherent messages to send downstream. 
+
+Good example of how to group things to eliminate excessive noise to downstream systems. 
+
+
+## Setup
+
+- Python (3.12 is what I used)
+- Atlas Streams Processor
+
+
+###
+Create a file called `.env` and give it the following properties. 
+
+```commandline
+ATLAS_URL=<connection string here>
+DB_NAME=retail_demo
+COLLECTION_NAME=inventory
+
+```
+
+Then setup python 
+
+```commandline
+python3 -m venv venv
+pip install -r requirements.txt
+python3 data_loader.py
+```
+
+That will create an initial set of 10,000 records into the DB and Collection defined, and then start pushing changes
+to those inventory levels using `$inc`. 
+
+If you adjust the names of the DB or collection from those listed in the example then you will need to adjust 
+them in the `inventory_processor.js` file as well. 
+
+Once done, you create the stream processor instance using the instructions here [Atlas Stream Processing - Get Started](https://www.mongodb.com/docs/atlas/atlas-stream-processing/tutorial/)
+
+Current setup outputs the grouped results to a new collection, but you could change at that to `$emit` to a Kafka topic if 
+needed for the demo.
+
+
+
+
+
+