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import pandas as pd
import requests
import io
from pymongo import MongoClient
def get_mongo_client():
client = MongoClient("mongodb+srv://groupA:[email protected]/?retryWrites=true&w=majority&appName=SentimentCluster")
db = client["sentiment_db"]
return db["tweets"]
def insert_data_if_empty():
collection = get_mongo_client()
if collection.count_documents({}) == 0:
print("🟢 No data found. Inserting dataset...")
csv_url = "https://huggingface.co/spaces/sharangrav24/SentimentAnalysis/resolve/main/sentiment140.csv"
try:
response = requests.get(csv_url)
response.raise_for_status()
df = pd.read_csv(io.StringIO(response.text), encoding="ISO-8859-1")
# Add default fields if not present.
if "user" not in df.columns:
df["user"] = "Unknown"
if "date" not in df.columns:
df["date"] = "Unknown"
collection.insert_many(df.to_dict("records"))
print("✅ Data Inserted into MongoDB!")
except Exception as e:
print(f"❌ Error loading dataset: {e}")
def get_dataset_summary():
collection = get_mongo_client()
pipeline = [
{"$group": {"_id": "$target", "count": {"$sum": 1}}}
]
results = list(collection.aggregate(pipeline))
mapping = {"0": "Negative", "2": "Neutral", "4": "Positive"}
summary_parts = []
total = 0
for doc in results:
target = str(doc["_id"])
count = doc["count"]
total += count
label = mapping.get(target, target)
summary_parts.append(f"{label}: {count}")
summary = f"Total tweets: {total}. " + ", ".join(summary_parts) + "."
return summary
def get_entry_by_index(index=0):
collection = get_mongo_client()
doc_cursor = collection.find({}, {"_id": 0}).skip(index).limit(1)
docs = list(doc_cursor)
if docs:
return docs[0]
return None
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