Update README.md

Author: JohnMachado11

README.md

@@ -1,34 +1,38 @@
 ## Cloud-Python-to-Cpp
 
-This project was designed to leverage **several** `Google Cloud Platform` cloud services to create a robust and automated system which can be interacted with via `C++` code. Why `C++`? The use case of that programming language specifically in the context of this project would be for example, having a `C++` based physical device pull from the cloud the latest `firmware` it needs, or just any kind of data from the cloud really.
+This project was designed to leverage **several** `Google Cloud Platform` cloud services to create a robust and automated system which can be interacted with via `C++` code. 
 
-Ultimately in the end, a secure API to pull data from a `BigQuery` database table was designed and it can actually be called by **any** programming language as long as the correct credentials get sent in `json` format. 
+Why `C++`? The use case of that programming language specifically in the context of this project would be for example, having a `C++` based physical device pull from the cloud the latest `firmware` it needs, or just any kind of data from the cloud really.
+
+Ultimately in the end, a secure API to pull data from a `BigQuery` database table was designed and it can actually be called by **any** programming language as long as the correct credentials get sent in `json` format to the `Auth_Func`. 
 
 The programming language `Python` is utilized to create the entire backend component on `Google Cloud Platform`. 
 
 `Firebase` is also utilized as part of the authentication system. 
 
 ------
 
-**`Google Cloud Platform` technologies:**
+`Google Cloud Platform` technologies:
+
+- `Artifact Registry` - Stores the latest Docker image builds for `Cloud Run`
 
-1. `Artifact Registry` - Stores the latest Docker image builds for the Cloud Functions / Cloud Run
+- `BigQuery` - Data warehouse which stores the table of data we interact with
 
-2. `BigQuery` - Data warehouse which stores the table of data we interact with
+- `Cloud Build` - Monitors GitHub repo and automates the process of deploying new code into the cloud
 
-3. `Cloud Build` - Monitors GitHub repo and automates the process of deploying new code into the cloud
+- `Cloud Functions (Gen 2)` - The backend for the project. Within each Cloud Function is the `Python` code. 
 
-4. `Cloud Functions (Gen 2)` - The backend for the project. Within each Cloud Function is the `Python` code. 
+- `Cloud Run` - Generation 2 of `Cloud Functions` is actually `Cloud Run` behind the scenes. Therefore `Python` code executes here. 
 
-5. `Cloud Run` - Generation 2 of `Cloud Functions` is actually `Cloud Run` behind the scenes. Therefore `Python` code executes here. 
+- `Cloud Scheduler` - Cron job scheduler for any job in the cloud
 
-6. `Cloud Scheduler` - Cron job scheduler for any job in the cloud
+- `Cloud Storage` - Stores the latest `Python` code for the `Cloud Functions`
 
-7. `Secret Manager` - Secure storage system for sensitive data
+- `Secret Manager` - Secure storage system for sensitive data
 
-**`Firebase` technologies:**
+`Firebase` technologies:
 
-1. `Authentication` - Stores the user account data
+- `Authentication` - Stores the user account data
 
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@@ -41,24 +45,34 @@ Values of the 5 most recent records from the BigQuery table get returned to the
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 ### Cloud Functions
 
-1. `Auth_Func` - Publically Accessible
+1. `Auth_Func` - Publically Accessible (could be private as well)
 2. `Compute_Func` - Private
 3. `Insert_Int_Func` - Private
 
 Let's talk about each:
 
-`Auth_Func` The authentication system. 
+1. `Auth_Func` The authentication system. 
 
-Everything starts here. Way before any data can be extracted from the `BigQuery` database table, a `request` from the user has to pass multiple tests before the code can proceeed. 
+- Everything starts here. Way before any data can be extracted from the `BigQuery` database table, a `request` from the user has to pass multiple tests before the code can proceeed. 
 
-1. The `request` cannot be empty and the `json` must have the correct keys, `email` and `password`.
-2. The value of the `email` key of the `json` must be a string.
-3. The format of the value of the `email` key of the `json` must be in the correct format e.g. `"name@domain.com"`.
-4. The value of the `password` key of the `json` must be a string.
-5. The `email` and `password` must correlate to an existing user within `Firebase Authentication`.
+- 1. The `request` cannot be empty and the `json` must have the correct keys, `email` and `password`.
+- 2. The value of the `email` key of the `json` must be a string.
+- 3. The format of the value of the `email` key of the `json` must be in the correct format e.g. `"name@domain.com"`.
+- 4. The value of the `password` key of the `json` must be a string.
+- 5. The `email` and `password` must correlate to an existing user within `Firebase Authentication`.
 
-If everything checks out, then the `Compute_Func` `Cloud Function` gets called directly from the `Auth_Func`.
+- If everything checks out, then the `Compute_Func` `Cloud Function` gets called directly from the `Auth_Func`.
+
+2. `Compute_Func` The computation system. Computation in the sense of enumerating, listing out. 
+
+- The job of the `Compute_Func` is to simply extract the values of the 5 most recent records from a `BigQuery` table. 
+- Those values are then placed into a list. 
+- That list is converted to a string and then the string is returned to the `Auth_Func`. 
 
+3. `Insert_Int_Func` The data insertion system. 
 
+- The `Insert_Int_Func` operates independently from the `Auth_Func` and `Compute_Func`. 
+- `Insert_Int_Func` is triggered every **6 hours** by `Cloud Scheduler`
+- A randomized integer between the ranges of 0-75 is inserted into a `BigQuery` table