adding README

README.md

@@ -1,20 +1,37 @@
 # irr_calculator
-## Introduction
-Python solution that calculates irr for a set of entities.
+Python solution that calculates Internal Rate of Return (IRR) for a set of entities.
 
-## Execution
-On this section you will find how to run the code locally.
+## Internal Rate of Return (IRR)
 
-### Python environment
-To execute the solution with your machine you will need an environment with python 3.10.0 and the libraries listed in 
-requirements.txt. In case you do not have such environment, you can create it as follows with conda:
-
-```
-conda create -n [] python=3.10.0 pip
-pip install -r cloud_function/requirements.txt
-```
+Internal Rate of Return (IRR) is a financial metric that calculates the profitability of an investment by 
+determining the Discount Rate at which the net present value (NPV) of the investment becomes zero. 
+In other words, IRR represents the interest rate at which the present value of cash inflows equals the present 
+value of cash outflows. The primary purpose of IRR is to assess the attractiveness of an investment opportunity.
 
-### Testing
+The IRR is calculated using the following formula:
+
+$`\[ NPV = \sum_{t=0}^{T} \frac{CF_t}{(1 + r)^t} \]`$
+
+Where:
+- \( NPV \) is the net present value of cash inflows and outflows.
+- \( T \) is the total number of periods.
+- \( CF_t \) is the cash flow in period \( t \).
+- \( r \) is the discount rate (IRR).
+
+The IRR is found by solving the NPV equation for \( r \) when \( NPV = 0 \). 
+
+## Terraform code
+The provided Terraform code automates the deployment of the python solution to calculate IRR as a 
+Cloud Function on Google Cloud Platform (GCP). It begins by configuring the necessary GCP provider settings, 
+such as the project ID and region. The code then creates a service account for the Cloud Function, 
+assigning it specific roles for interacting with BigQuery. 
+It also establishes a Cloud Storage bucket to store the Cloud Function's source code, archives the source code, 
+and uploads it to the designated bucket. Additionally, the configuration sets up a Pub/Sub topic and a 
+Cloud Scheduler job, allowing the Cloud Function to be triggered periodically. 
+Finally, it defines the Cloud Function itself. This Terraform setup streamlines the deployment process and 
+ensures a consistent environment for the IRR calculator on GCP.
+
+## Testing
 
 To execute the Python tests use next command on the CLI:
 
@@ -32,4 +49,26 @@ DATASET=
 ```
 
 You will also need to provide a Service Account credentials or to use a user account with the right permissions to 
-interact with BigQuery.
+interact with BigQuery.
+
+### Python environment
+To execute these tests within your machine you will need an environment with python 3.10.0 and the libraries listed in 
+requirements.txt. In case you do not have such environment, you can create it as follows with conda:
+
+```
+conda create -n [] python=3.10.0 pip
+pip install -r cloud_function/requirements.txt
+```
+
+You also need to install pytest==7.4.3 & python-dotenv==0.14.0
+
+## GitHub Workflow
+GitHub workflow automates Python testing for the project, triggered on every push  or pull requests to the main branch. 
+Operating on the latest Ubuntu environment, it employs a matrix strategy to test against Python 3.10. 
+The workflow initializes Python, installs project dependencies, including Pytest and Python-dotenv, 
+and executes Pytest. 
+Key environment variables, such as project details and service account JSON, are securely managed using GitHub Secrets. 
+
+
+
+