refactor: move db dir into server

server/db/database.py

@@ -0,0 +1,138 @@
+import os
+import psycopg2
+import pandas as pd
+from psycopg2.extras import RealDictCursor
+from psycopg2.extras import execute_batch, Json
+
+
+class PostgresConnector:
+    """
+    Simple PostgreSQL connector (single connection).
+    """
+
+    def __init__(self):
+        self.connection = psycopg2.connect(
+            host=os.getenv("POSTGRES_HOST", "localhost"),
+            port=os.getenv("POSTGRES_PORT", 5432),
+            user=os.getenv("POSTGRES_USER", "postgres"),
+            password=os.getenv("POSTGRES_PASSWORD", "postgres"),
+            database=os.getenv("POSTGRES_DB", "postgres"),
+        )
+        self.connection.autocommit = False
+
+    def execute(self, query, params=None, fetch=False) -> list:
+        with self.connection.cursor(cursor_factory=RealDictCursor) as cursor:
+            cursor.execute(query, params)
+            if fetch:
+                return cursor.fetchall()
+            self.connection.commit()
+
+    def executemany(self, query, param_list) -> list:
+        with self.connection.cursor(cursor_factory=RealDictCursor) as cursor:
+            cursor.executemany(query, param_list)
+            self.connection.commit()
+
+    ## User Management Methods
+    def save_user(self, username, email, password_hash):
+        query = """
+            INSERT INTO users (username, email, password_hash)
+            VALUES (%s, %s, %s)
+        """
+        self.execute(query, (username, email, password_hash))
+
+    def get_user_by_username(self, username) -> dict:
+        query = "SELECT id, username, email, password_hash FROM users WHERE username = %s"
+        result = self.execute(query, (username,), fetch=True)
+        return result[0] if result else None
+    
+    def get_user_by_email(self, email) -> dict:
+        query = "SELECT id, username, email, password_hash FROM users WHERE email = %s"
+        result = self.execute(query, (email,), fetch=True)
+        return result[0] if result else None
+    
+    # Dataset Management Methods
+    def save_dataset_info(self, user_id: int, dataset_name: str, topics: dict) -> int:
+        query = """
+            INSERT INTO datasets (user_id, name, topics)
+            VALUES (%s, %s, %s)
+            RETURNING id
+        """
+        result = self.execute(query, (user_id, dataset_name, Json(topics)), fetch=True)
+        return result[0]["id"] if result else None
+
+    def save_dataset_content(self, dataset_id: int, event_data: pd.DataFrame):
+        query = """
+            INSERT INTO events (
+                dataset_id,
+                type,
+                parent_id,
+                author,
+                content,
+                timestamp,
+                date,
+                dt,
+                hour,
+                weekday,
+                reply_to,
+                source,
+                topic,
+                topic_confidence,
+                ner_entities,
+                emotion_anger,
+                emotion_disgust,
+                emotion_fear,
+                emotion_joy,
+                emotion_sadness
+            )
+            VALUES (
+                %s, %s, %s, %s, %s,
+                %s, %s, %s, %s, %s,
+                %s, %s, %s, %s, %s,
+                %s, %s, %s, %s, %s
+            )
+        """
+
+        values = []
+
+        for _, row in event_data.iterrows():
+            values.append((
+                dataset_id,
+                row["type"],
+                row["parent_id"],
+                row["author"],
+                row["content"],
+                row["timestamp"],
+                row["date"],
+                row["dt"],
+                row["hour"],
+                row["weekday"],
+                row.get("reply_to"),
+                row["source"],
+                row.get("topic"),
+                row.get("topic_confidence"),
+                Json(row["ner_entities"]) if row.get("ner_entities") else None,
+                row.get("emotion_anger"),
+                row.get("emotion_disgust"),
+                row.get("emotion_fear"),
+                row.get("emotion_joy"),
+                row.get("emotion_sadness"),
+            ))
+
+        
+        with self.connection.cursor(cursor_factory=RealDictCursor) as cursor:
+            execute_batch(cursor, query, values)
+            self.connection.commit()
+
+    def get_dataset_content(self, dataset_id: int) -> pd.DataFrame:
+        query = "SELECT * FROM events WHERE dataset_id = %s"
+        result = self.execute(query, (dataset_id,), fetch=True)
+        return pd.DataFrame(result)
+    
+    def get_dataset_info(self, dataset_id: int) -> dict:
+        query = "SELECT * FROM datasets WHERE id = %s"
+        result = self.execute(query, (dataset_id,), fetch=True)
+        return result[0] if result else None
+
+    def close(self):
+        if self.connection:
+            self.connection.close()

server/db/schema.sql

@@ -0,0 +1,51 @@
+CREATE TABLE users (
+    id SERIAL PRIMARY KEY,
+    username VARCHAR(255) NOT NULL UNIQUE,
+    email VARCHAR(255) NOT NULL UNIQUE,
+    password_hash VARCHAR(255) NOT NULL,
+    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
+);
+
+CREATE TABLE datasets (
+    id SERIAL PRIMARY KEY,
+    user_id INTEGER NOT NULL,
+    name VARCHAR(255) NOT NULL,
+    description TEXT,
+    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+    topics JSONB,
+    FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE
+);
+
+CREATE TABLE events (
+    /* Required Fields */
+    id SERIAL PRIMARY KEY,
+    dataset_id INTEGER NOT NULL,
+    type VARCHAR(255) NOT NULL,
+
+    author VARCHAR(255) NOT NULL,
+    content TEXT NOT NULL,
+    timestamp BIGINT NOT NULL,
+    date DATE NOT NULL,
+    dt TIMESTAMP NOT NULL,
+    hour INTEGER NOT NULL,
+    weekday VARCHAR(255) NOT NULL,
+
+    /* Comments and Replies */
+    parent_id VARCHAR(255),
+    reply_to VARCHAR(255),
+    source VARCHAR(255) NOT NULL,
+
+    /* NLP Fields */
+    topic VARCHAR(255),
+    topic_confidence FLOAT,
+
+    ner_entities JSONB,
+
+    emotion_anger FLOAT,
+    emotion_disgust FLOAT,
+    emotion_fear FLOAT,
+    emotion_joy FLOAT,
+    emotion_sadness FLOAT,
+
+    FOREIGN KEY (dataset_id) REFERENCES datasets(id) ON DELETE CASCADE
+);