From 1621b4eb5bb6bfd133ffbc15016c3f1ec40c4884 Mon Sep 17 00:00:00 2001
From: Thomas Geromichalos <thomas@MacBook-Pro-3.local>
Date: Wed, 29 Oct 2025 19:15:30 -0700
Subject: [PATCH] add main2.py

---
 main2.py | 86 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 86 insertions(+)
 create mode 100644 main2.py

diff --git a/main2.py b/main2.py
new file mode 100644
index 0000000..88d9c7f
--- /dev/null
+++ b/main2.py
@@ -0,0 +1,86 @@
+import pymongo
+import json
+client=pymongo.MongoClient("localhost", 27017)
+db = client["timdb"]
+collection = db["tim"]
+
+# first check that the collection exists, if not, load the data from the file
+#step 1: import json data and turn into python list of dictionaries insert into tim collection
+if "tim" not in db.list_collection_names() or collection.count_documents({}) == 0:
+    #step 2: Turn it into average team data
+    #step 3: insert into team collection
+    with open('example_tim_data.json', 'r') as f:
+        data = json.load(f)
+
+    # write data into the database
+    collection.insert_many(data)
+
+# read the data from the database, not the file
+data = list(collection.find())
+teams = []
+   
+#Helps figure out the number of teams in the data as well as their unique numbers
+for item in data:
+    if item["team_num"] not in teams:
+        
+
+        teams.append(item["team_num"])     
+
+# Creates a function where max score is calculated by adding difference of the number and the previous math score if the new number is greater than the old max
+def maximumscore(list_of_team_data):
+    max_score=0
+    for item in list_of_team_data:
+        if item["num_balls"]>=max_score:
+            max_score+=(item["num_balls"]-max_score)
+    return(max_score)
+
+
+# finds the minimum score by a similar method to the previous function.
+def minimumscore(list_of_team_data):
+    min_score=1000
+    for  item in list_of_team_data:
+        if item["num_balls"]<=min_score:
+            min_score-=(min_score-item["num_balls"])
+    return(min_score)
+
+
+# finds the number of matches played by reading the data and adding one every time the team shows up.
+def matches(list_of_team_data):
+    x=0
+    for item in list_of_team_data:
+        if item["team_num"]==item["team_num"]:
+            x+=1
+    return(x)
+
+# creates the average by finding the total balls scored divided by the total matches played
+def average(list_of_team_data):
+    total=0
+    a=0
+    for item in list_of_team_data:
+        if item["team_num"]==item["team_num"]:
+            total+=item["num_balls"]
+            a+=1
+    return(total/a)
+
+# 1 is added to c every time the team has climbed and the percentage is found by c/total matches played
+def succsess(list_of_team_data):
+    c=0
+    d=0
+    for item in list_of_team_data:
+        if item["team_num"]==item["team_num"]:
+            d+=1
+            if item["climbed"]==True:
+                c+=1
+    return(c/d)
+
+for team in teams:
+    team_list=[]
+    for item in data:
+        if item["team_num"]==team:
+            team_list.append(item)
+    result=maximumscore(team_list)
+    result2=minimumscore(team_list)
+    result3=matches(team_list)
+    result4=average(team_list)
+    result5=succsess(team_list)
+    print(f"team num: {team}.  max balls scored: {result}.  Min balls scored: {result2}.  Matches played: {result3}.  Average balls scored: {result4}. Climb succsess rate: {result5}")