Merge pull request #60 from amosproj/dev

Merge result of sprint 4 into main

.env.docker.example

@@ -0,0 +1,6 @@
+#Copy and rename this file to .env.docker
+DATABASE_HOST="host.docker.internal"
+DATABASE_PORT=5433
+DATABASE_USER="postgres"
+DATABASE_PASSWORD="postgres"
+DATABASE_DATABASE="postgres"

.gitignore

@@ -18,6 +18,7 @@ pids
 # Python
 *.pyc
 __pycache__/
+.venv/
 
 # vscode
 .vscode/
@@ -37,8 +38,11 @@ bin/
 
 # Local env files
 apps/*/.env
+.env.docker
 
 .nx/cache
 .nx/workspace-data
 **/vite.config.{js,ts,mjs,mts,cjs,cts}.timestamp*
 .angular
+
+.cache/*

Dockerfile

@@ -0,0 +1,9 @@
+# Container for the shared node module
+FROM node:18-alpine
+
+WORKDIR /app
+
+COPY . .
+
+RUN npm i -g [email protected]
+RUN npm install

Documentation/README.md

@@ -1,22 +1,47 @@
-Build, user, and technical documentation
+# Build, user, and technical documentation
+
 Software architecture description
 
-basic setup:
+## Basic setup:
+
+```bash
+npm ci
+cd ./apps/analyzer/metadata_analyzer ; poetry install
+```
 
 - `npm ci`: dependency install
-- copy `.env.example` file and rename to `.env` (adjust database properties according to database setup if necessary)
+
+- copy `.env.example` file in backend and rename to `.env` (adjust database properties according to database setup if necessary)
+- copy `.env.example` file in analyzer and rename to `.env` (adjust port properties according to backend setup if necessary)
 - To insert dummy data into table backupData you can use the SQL script `dummyData.sql` in `apps/backend/src/app/utils`
 
-running the code locally:
+### Running the code locally:
 
 - `npm run be`: run backend individually
 - `npm run fe`: run frontend individually
-- `npm run both`: run backend and frontend
+- `npm run py` : run python app
+- `npm run all`: run backend, frontend and python module
 
-generating database migrations:
+### Generating database migrations:
 
 - the entity files need to be annotated with `@Entity(<table-name>)`
 - append the entity file to the `entities` array in `db-config.service.ts`
 - run the following command to generate a migration file:
-    - `nx run metadata-analyzer-backend:migrations:generate --name <migration-name>`
-- append the generated file to the `migrations` array in `db-config.service.ts`
+  - `nx run metadata-analyzer-backend:migrations:generate --name <migration-name>`
+- append the generated file to the `migrations` array in `db-config.service.ts`
+
+
+
+## Installing new dependencies
+
+### in python app
+
+When working with python dependencies, first cd into the `analyzer` folder.
+
+#### Install a new dependency
+
+`poetry add <dependency-name>`
+
+#### Remove a dependency
+
+`poetry remove <dependency-name>`

README.md

@@ -1,2 +1,31 @@
-# Backup Metadata Analyzer (AMOS WS 2024/25)
-Something something something
+# AMOS Backup Metadata Analyzer
+
+
+## Prerequisites
+Make sure the following are installed on your machine:
+- **Node 20**
+- **Docker**
+- **Docker Compose**
+
+## Setup Instructions
+
+1. **Clone the repository**:
+   ```bash
+   git clone https://github.com/amosproj/amos2024ws02-backup-metadata-analyzer.git
+
+2. **Change directory**:
+   ```bash
+cd ./amos2024ws02-backup-metadata-analyzer/
+
+3. **Setup .env files**:
+   ```bash
+cp .env.docker.example .env.docker
+cp apps/backend/.env.example apps/backend/.env
+
+4. **Docker compose up**:
+   ```bash
+docker-compose --env-file .env.docker up --build
+
+5. **Docker compose down**:
+   ```bash
+docker-compose --env-file .env.docker down

apps/analyzer/.env.example

@@ -0,0 +1,2 @@
+FLASK_RUN_HOST="localhost"
+FLASK_RUN_PORT="8000"

apps/analyzer/.flake8

@@ -0,0 +1,11 @@
+[flake8]
+exclude =
+	.git,
+	__pycache__,
+	build,
+	dist,
+	.tox,
+	venv,
+	.venv,
+	.pytest_cache
+max-line-length = 120

apps/analyzer/.python-version

@@ -0,0 +1 @@
+3.11.2

apps/analyzer/README.md

@@ -0,0 +1,9 @@
+# metadata-analyzer
+
+Rename .env.example to .env, adjust necessary values
+
+if flask imports are not recognized, potential vscode problem:
+strg + shift + p
+-> Select Interpreter
+-> Enter Interpreter Path
+(select python that lies in .venv directory)

apps/analyzer/main.py

@@ -0,0 +1,4 @@
+from metadata_analyzer.main import main
+
+if __name__ == "__main__":
+    main()

apps/analyzer/metadata_analyzer/__init__.py

@@ -0,0 +1 @@
+"""Automatically generated by Nx."""

apps/analyzer/metadata_analyzer/database.py

@@ -0,0 +1,20 @@
+import pg8000.dbapi
+from sqlalchemy import create_engine, select
+from sqlalchemy.orm import Session
+from metadata_analyzer.models import BackupData
+import os
+
+
+class Database:
+    def __init__(self):
+        self.engine = create_engine("postgresql+pg8000://postgres:postgres@localhost:5432/postgres")
+
+
+def get_data(self):
+    session = Session(self.engine)
+    stmt = select(BackupData)
+
+    result = session.scalars(stmt)
+    return result
+
+

apps/analyzer/metadata_analyzer/main.py

@@ -0,0 +1,44 @@
+from flask import Flask, request, jsonify
+from dotenv import load_dotenv
+from metadata_analyzer.database import Database, get_data
+from metadata_analyzer.simple_analyzer import SimpleAnalyzer
+import os
+
+app = Flask(__name__)
+
+@app.route("/")
+def hello_world():
+    return "Hello, world!"
+
+
+@app.route("/echo", methods=["POST"])
+def echo():
+    if request.method == "POST":
+        data = request.get_json()
+        obj = data["body"]
+        strData = obj["text"]
+        newData = ""
+
+        for i in range(len(strData) - 1, -1, -1):
+            newData = newData + strData[i]
+
+        newBody = '{ "output": "' + newData + '" }'
+        return newBody
+
+@app.route("/analyze", methods=["GET"])
+def analyze():
+    data = list(get_data(database))
+    result = simple_analyzer.analyze(data)
+
+    return jsonify(result)
+
+def main():
+    global database
+    global simple_analyzer
+    database = Database()
+    simple_analyzer = SimpleAnalyzer()
+
+    new_port = os.getenv("FLASK_RUN_PORT")
+    int_port = int(new_port or 5000)
+    print("int_port: " + str(int_port))
+    app.run(host="localhost", port=int_port, debug=False)

apps/analyzer/metadata_analyzer/models.py

@@ -0,0 +1,19 @@
+from sqlalchemy.orm import mapped_column, Mapped
+from sqlalchemy.ext.declarative import declarative_base
+from datetime import datetime
+
+Base = declarative_base()
+
+class BackupData(Base):
+    __tablename__ = "BackupData"
+
+    id: Mapped[str] = mapped_column(primary_key=True)
+    sizeMB: Mapped[int]
+    creationDate: Mapped[datetime]
+    bio: Mapped[str]
+
+    def __repr__(self):
+        return f"""BackupData(id={self.id}, sizeMB={self.sizeMB}, creationDate={self.creationDate}, bio={self.bio!r})"""
+
+    def __str__(self):
+        return repr(self)

apps/analyzer/metadata_analyzer/simple_analyzer.py

@@ -0,0 +1,15 @@
+class SimpleAnalyzer:
+    def __init__(self):
+        pass
+
+    def analyze(self, data):
+        count = len(data)
+        dates = list(map(lambda backup_data: backup_data.creationDate, data))
+        sizes = list(map(lambda backup_data: backup_data.sizeMB, data))
+        return {
+            "count": count,
+            "firstBackup": min(dates),
+            "lastBackup": max(dates),
+            "minSize": min(sizes),
+            "maxSize": max(sizes),
+        }