Update README.md, verify correct deployment

Author: Timotej979

Project/README.md

@@ -0,0 +1,63 @@
+# Pattern recognition WEB and API
+
+This is a full-stack project for the subject of pattern recognition. The project is split into 3 parts:
+- **backend** - API and DB for feature set creation/deletion and execution of exploratory data analysis using PCA and hierarchical clustering
+- **frontend** - Interface for hosting a SPA and a wrapper for various web requests done from the frontend 
+- **nginx** - Reverse proxy and load balancer for the backend and frontend and serving static files (CSS/JS)
+
+For each part, there is a separate README file with more detailed information in the respective folder.
+
+
+## Running the code
+
+You can run the project by running the following command in the root of the project:
+```
+docker compose build
+docker compose up -d
+```
+To stop the project, run the following command in the root of the project:
+```
+docker compose down
+```
+
+The dashboard can be accessed on the following URL: [http://localhost:5000/recognition-web/v1/dashboard](http://localhost:5000/recognition-web/v1/dashboard)
+
+
+## Basic project architecture
+
+The project uses a microservices architecture with docker compose to run the services. It creates **4 containers** that are interconnected with **2 networks**. The containers are:
+- **db** - Postgres database for storing the feature sets (Network: __db-api__)
+- **recognition-api** - API for creating/deleting feature sets and running exploratory data analysis (Network: __db-api__, __api-nginx__)
+- **recognition-web** - SPA for the dashboard and a wrapper for the API requests (Network: __web-nginx__)
+- **recognition-nginx** - Reverse proxy and load balancer for the backend and frontend and serving static files (CSS/JS) (Network: __web-nginx__, __api-nginx__)
+
+## Dependencies used
+
+Bellow is a list of dependencies used in the project by each part of the project:
+- **Backend** (API and DB)
+    - API (Docker image: python:3.11-alpine)
+        - __Python__ (Version: >=3.9, <3.12)
+        - __asyncio__ (Version: ^3.4.3)
+        - __aiohttp__ (Version: ^3.8.1)
+        - __asyncpg__ (Version: ^0.26.0)
+        - __aiohttp-sqlalchemy__ (Version: ^0.34.0)
+        - __SQLAlchemy__ (Version: ^1.4.39)
+        - __numpy__ (Version: ^1.17.3)
+        - __scikit-learn__ (Version: ^1.2.0)
+        - __pytest__ (Version: ^6.2.5)
+        - __pytest-asyncio__ (Version: ^0.16.0)
+        - __testcontainers__ (Version: ^3.0.0)
+    - DB (Docker image: postgres:15.1)
+        - __Postgres__ (Version: 15.1)
+
+- **Frontend** (Docker image: python:3.11-alpine)
+    - __Python__ (Version: >=3.9, <3.12)
+    - __asyncio__ (Version: ^3.4.3)
+    - __aiohttp__ (Version: ^3.8.1)
+
+- **Nginx**
+    - __Nginx__ (Version: 1.23)
+
+## References
+
+[1] Markelle Kelly, Rachel Longjohn, Kolby Nottingham, The UCI Machine Learning Repository, https://archive.ics.uci.edu

Project/backend/api/Dockerfile

@@ -68,4 +68,6 @@ USER apprunner
 RUN ./.venv/bin/pip install *.whl
 #This will initialize the python's virtual env (so we don't need to call source .venv/bin/activate)
 ENV PATH="/app/.venv/bin:${PATH}"
-ENV VIRTUAL_ENV="/app/.venv"
+ENV VIRTUAL_ENV="/app/.venv"
+# Invoke the application
+CMD ["python", "/app/.venv/lib/python3.11/site-packages/recognition_api/main.py"]

Project/docker-compose.yml

@@ -39,8 +39,8 @@ services:
       - POSTGRES_USER=${APP_DB_USERNAME}
       - POSTGRES_DB=${APP_DB_DBNAME} 
     # Comment out ports here if you do not want outside DB access
-    ports:
-      - ${APP_DB_OUT_PORT}:5432
+    #ports:
+    #  - ${APP_DB_OUT_PORT}:5432
     volumes:
       - ./backend/postgres-docker/data:/var/lib/postgresql/data/
     healthcheck:
@@ -63,7 +63,7 @@ services:
       api:
         condition: service_healthy
     networks:
-      - frontend-nginx
+      - web-nginx
     environment:
       - API_WEB_CONNECTION_STRING=http://nginx:8000/recognition-api/v1
       - APP_CONFIG
@@ -77,13 +77,13 @@ services:
       retries: 5
 
   nginx:
-    image: "recognition-api:nginx"
+    image: "recognition-nginx:v1"
     restart: unless-stopped
     build: 
       context: ./nginx
     networks:
       - api-nginx
-      - frontend-nginx
+      - web-nginx
     ports:
       - ${NGINX_OUT_PORT}:8000
     depends_on:
@@ -104,4 +104,4 @@ services:
 networks:
   db-api:
   api-nginx:
-  frontend-nginx:
+  web-nginx:

README.md

@@ -49,20 +49,20 @@ python3 exercise2.py
 
 ## Project
 
-The final project is a pattern recognition API. It uses aiohttp server in combination with Postgres DB and NGINX reverse proxy. Deployment is done via docker compose. 
-
-Curently implemented features are as follows:
-- Basic API and DB for feature upload and chunked upload webpage
-- All possible web requests are available in "test_requests.txt" file in Backend folder
-- Uploaded dataset should be in the following format: 
-
-```
-numeric, numeric, numeric, ... , numeric, label
-```
-
-Still work in progress.
-
-
-### References
-
-[1] Markelle Kelly, Rachel Longjohn, Kolby Nottingham, The UCI Machine Learning Repository, https://archive.ics.uci.edu
+The final project is a pattern recognition API for exploratory data analysis. More information can be found in the respective README file in the Project folder.
+
+The project is still in development and is not yet finished...
+
+Curent roadmap:
+- [x] Create a basic API for feature set creation/deletion
+- [x] Create a basic API for exploratory data analysis using PCA and hierarchical clustering
+- [x] Create a basic nginx reverse proxy for the frontend and backend
+- [x] Create a basic wrapper for various web requests done from the frontend
+- [x] Deploy the project using docker compose
+- [ ] Create a basic frontend for the API
+- [ ] Add more features to the API
+- [ ] Add more features to the frontend
+- [ ] Deploy the project using Kubernetes
+    - [ ] Add a DB k8s deployment
+    - [ ] Add a API k8s deployment
+    - [ ] Add a frontend k8s deployment