sovietscout · April 27, 2025 11:04 · Apr 27, 2025 · Apr 27, 2025
diff --git a/README.md b/README.md
@@ -1,4 +1,4 @@
-**CUET Score Checker**  
+## CUET Score Checker 
 
 **Requirements**:  
 - Python 3.8+  

diff --git a/README.md b/README.md
@@ -0,0 +1,19 @@
+**CUET Score Checker**  
+
+**Requirements**:  
+- Python 3.8+  
+- `pandas`, `lxml`, `requests` (install via `pip install -r pandas lxml requests`)  
+- `master.csv` (provisional answer key for the subject; must be in the same folder)  
+
+**Usage**:  
+1. Place your response sheet URL in `response_url` variable.  
+2. Run `python cuet-score-checker.py`.  
+3. Get a summary and a scorecard (`[student-name]-scorecard.csv`) with detailed results.  
+
+**Output**:  
+- Total score, correct/incorrect/unattempted counts  
+- Question-wise analysis (QID, chosen option, correct answer, marks)  
+
+**Note**:  
+- Replace `master.csv` with updated keys if needed.  
+- Response URLs follow the format: `https://cdn3.digialm.com/.../...07E1.html`
diff --git a/cuet-score-checker.py b/cuet-score-checker.py
@@ -0,0 +1,63 @@
+import requests
+import pandas as pd
+import numpy as np
+from lxml import etree
+from typing import Union
+
+
+def get_responses(url: str) -> Union[str, pd.DataFrame]:
+    r = requests.get(url)
+    r.raise_for_status()
+    tree = etree.HTML(r.content)
+
+    name_raw: str = tree.xpath('//div[@class="main-info-pnl"]//td[.="Candidate Name"]/following-sibling::td/text()')[0]
+    name = name_raw.split()[0].strip().lower()
+
+    questions = []
+    for panel in tree.xpath('//div[@class="question-pnl"]'):
+        qno_raw = panel.xpath('.//td[@class="bold" and starts-with(text(), "Q.")]/text()')[0].split()[-1]
+        qno = int(qno_raw.split(".")[1].strip())
+        menu_tbl = panel.xpath('.//table[@class="menu-tbl"]')[0]
+
+        qid = int(menu_tbl.xpath('.//td[.="Question ID :"]/following-sibling::td/text()')[0])
+        ono_raw = menu_tbl.xpath('.//td[.="Chosen Option :"]/following-sibling::td/text()')[0].strip()
+
+        if ono_raw == "--":
+            ono = None
+            oid = None
+        else:
+            ono = float(ono_raw)
+            oid = float(menu_tbl.xpath(f'.//td[.="Option {ono_raw} ID :"]/following-sibling::td/text()')[0].strip())
+
+        questions.append({
+            "QNO": qno,
+            "QID": qid,
+            "ONO": ono,
+            "OID": oid,
+        })
+
+    return name, pd.DataFrame(questions)
+
+
+def check_result(your_df: pd.DataFrame, master_df: pd.DataFrame) -> pd.DataFrame:
+    df = pd.merge(your_df, master_df, how='left', on='QID')
+
+    df['TOID'] = df['TOID'].astype(float)
+    df['Score'] = np.where(df['OID'].isna(), 0, np.where(df['OID'] == df['TOID'], 4, -1))
+
+    print(f'Score: {df["Score"].sum()}')
+    print(f'Correct: {len(df[df['Score'] == 4]['QNO'].tolist())}, Incorrect: {len(df[df['Score'] == -1]['QNO'].tolist())}, Unattempted: {len(df[df['Score'] == 0]['QNO'].tolist())}')
+
+    print(df[df['Score'] == -1]['QNO'].tolist())
+
+    return df
+
+
+if __name__ == '__main__':
+    response_url = '<your-response-sheet-url>'
+
+    master = pd.read_csv('master.csv')
+    stdn_name, stdn = get_responses(response_url)
+
+    stdn_df = check_result(stdn, master)
+    stdn_df.to_csv(f'{stdn_name}-scorecard.csv', index=False)
diff --git a/master.csv b/master.csv
@@ -0,0 +1,76 @@
+QID,TOID
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