diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..f4f55d5
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,3 @@
+db.py
+__pycache__
+*.json
\ No newline at end of file
diff --git a/app.py b/app.py
index e293225..ad0ed51 100644
--- a/app.py
+++ b/app.py
@@ -1 +1,162 @@
 # Your DB Code Here
+
+from db import db
+from db import DB_PASSWORD, DB_USERNAME, URL_LINK
+import pymongo
+from bson.objectid import ObjectId
+import datetime
+
+URL = URL_LINK.format(DB_USERNAME, DB_PASSWORD)
+client = pymongo.MongoClient(URL)
+db = client["RHDEVS-BE-Mongo"]
+
+# 1. Number of entries of selling data grouped by isbn
+
+stage_1 = {
+    "$group":
+        {
+            "_id": "$isbn",
+            "order_count": {"$sum": 1},
+        }
+}
+
+aggregation_1 = db.books_selling_data.aggregate([stage_1])
+
+
+# print(list(aggregation_1))
+
+# 2. For books with more than 15000 total copies sold, return all the titles in a single array
+
+stage_2_1 = {
+    "$group":
+        {
+            "_id": "$isbn",
+            "total_copies": { "$sum": "$copies_sold" }
+            
+        }
+}
+
+stage_2_2 = {
+    "$match":
+        {
+            "total_copies_sold": { "$gt": 15000 }
+        }
+
+}
+
+stage_2_3 = {
+    "$lookup": {
+        "from": "books",
+        "localField": "_id",
+        "foreignField": "isbn",
+        "as": "book_info"
+    }
+}
+
+stage_2_4 = {
+    "$project": {
+        "_id": 0,
+        "total_copies_sold": 0,
+        "title": 1
+    }
+}
+
+
+aggregation_2 = db.books_selling_data.aggregate([stage_2_1, stage_2_2, stage_2_3, stage_2_4])
+
+# print(list(aggregation_2))
+
+# 3. Find the number of books by John Doe, sorted by isbn (but isbn is not returned)
+
+stage_3_1 = {
+    "$match": {
+        "author": "John Doe"
+    }
+}
+
+
+stage_3_2 = {
+    "$sort": {
+        "$isbn": 1
+    }
+}
+
+stage_3_3 = {
+    "$project": {
+        "isbn": 0, 
+        "title": 1, 
+        "author": 1
+    }
+}
+
+
+
+aggregation_3 = db.books.aggregate([stage_3_1, stage_3_2, stage_3_3])
+
+# print(len(list(aggregation_3)))
+
+# 4. Return the price per book for each order
+
+
+stage_4_1 = {
+    "$addFields": {
+        "price_per_book": {
+            "$round": [{"$divide": ["$total_price", "$copies_sold"]}, 2]
+            }
+    }
+}
+
+stage_4_2 = {
+    "$project": {
+        "_id": 0,
+        "order_id": 1,
+        "copies_sold": 0,
+        "total_price": 0,
+        "supplier": 0
+    }
+}
+
+
+aggregation_4 = db.books_selling_data.aggregate([stage_4_1, stage_4_2])
+
+# print(list(aggregation_4))
+
+# 5. Return the average price per book for each order supplied from titan (we want to sum up all the total copies sold and total price of all copies sold where titan is a supplier, but average.like weighted average for the number of bookd)
+
+stage_5_1 = {
+    "$unwind": "$supplier"
+}
+
+stage_5_2 = {
+    "$group": {
+        "_id": "$supplier",
+        "overall_sale": {"$sum": "$copies_sold"},
+        "overall_price": {"$sum": "total_price"}
+    }
+}
+
+stage_5_3 = {
+    "$match": {
+        "supplier": "titan"
+    }
+}
+
+
+
+stage_5_4 = {
+    "addFields": {
+            "average_price_per_book": {"round": [{"divide":["overall_price", "overall_sale"]}, 2]}
+        }
+}
+
+stage_5_5 = {
+    "$project": {
+        "$_id": 1,
+        "$average_price_per_book": 1
+    }
+}
+
+
+aggregation_5 = db.books_selling_data.aggregate([stage_5_1, stage_5_2, stage_5_3, stage_5_4, stage_5_5])
+
+# print(list(aggregation_5))
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