commit d3d0b1b3bfbf431066be0cb842e0f62290ba3253 Author: Black Box Date: Sun Mar 29 10:58:13 2026 +0530 Initial commit for SSCTopper platform diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..9c77834 --- /dev/null +++ b/.gitignore @@ -0,0 +1,29 @@ +# dependencies +/node_modules +/.pnp +.pnp.js + +# testing +/coverage + +# next.js +/.next/ +/out/ + +# production +/build + +# misc +.DS_Store +*.pem + +# debug +npm-debug.log* +yarn-debug.log* +yarn-error.log* + +# local env files +.env*.local + +# database +*.db diff --git a/db/__pycache__/init.cpython-314.pyc b/db/__pycache__/init.cpython-314.pyc new file mode 100644 index 0000000..3aa1f26 Binary files /dev/null and b/db/__pycache__/init.cpython-314.pyc differ diff --git a/db/init.py b/db/init.py new file mode 100644 index 0000000..cc6ad41 --- /dev/null +++ b/db/init.py @@ -0,0 +1,145 @@ +#!/usr/bin/env python3 +""" +Database initialization script for SSCTopper. +Creates the database at /tmp/ssctopper.db, applies schema, and seeds the syllabus structure. +""" +import sqlite3 +import json +import os +import sys + +DB_DIR = os.path.dirname(os.path.abspath(__file__)) +DB_PATH = os.environ.get('SSCTOPPER_DB', '/tmp/ssctopper.db') +SCHEMA_PATH = os.path.join(DB_DIR, 'schema.sql') +SYLLABUS_PATH = os.path.join(DB_DIR, 'syllabus.json') + + +def get_db(): + """Get database connection.""" + conn = sqlite3.connect(DB_PATH) + conn.execute("PRAGMA journal_mode=WAL") + conn.execute("PRAGMA foreign_keys=ON") + conn.row_factory = sqlite3.Row + return conn + + +def init_db(force=False): + """Initialize database with schema and syllabus data.""" + if os.path.exists(DB_PATH): + if force: + os.remove(DB_PATH) + print(f"Removed existing database at {DB_PATH}") + else: + print(f"Database already exists at {DB_PATH}. Use --force to recreate.") + return + + conn = sqlite3.connect(DB_PATH) + conn.execute("PRAGMA journal_mode=WAL") + conn.execute("PRAGMA foreign_keys=ON") + cursor = conn.cursor() + + # Apply schema + with open(SCHEMA_PATH, 'r') as f: + cursor.executescript(f.read()) + print("Schema applied successfully.") + + # Load syllabus + with open(SYLLABUS_PATH, 'r') as f: + syllabus = json.load(f) + + # Seed syllabus data + stats = {'subjects': 0, 'subtopics': 0, 'topics': 0, 'qtypes': 0} + + for subject in syllabus['subjects']: + cursor.execute( + "INSERT INTO subjects (name, tier, description, target_questions) VALUES (?, ?, ?, ?)", + (subject['name'], subject['tier'], subject['description'], subject.get('target_questions', 0)) + ) + subject_id = cursor.lastrowid + stats['subjects'] += 1 + + for subtopic in subject.get('subtopics', []): + cursor.execute( + "INSERT INTO subtopics (subject_id, name, description) VALUES (?, ?, ?)", + (subject_id, subtopic['name'], subtopic.get('description', '')) + ) + subtopic_id = cursor.lastrowid + stats['subtopics'] += 1 + + for topic in subtopic.get('topics', []): + cursor.execute( + "INSERT INTO topics (subtopic_id, name, description) VALUES (?, ?, ?)", + (subtopic_id, topic['name'], topic.get('description', '')) + ) + topic_id = cursor.lastrowid + stats['topics'] += 1 + + for qtype in topic.get('question_types', []): + cursor.execute( + "INSERT INTO question_types (topic_id, name) VALUES (?, ?)", + (topic_id, qtype) + ) + stats['qtypes'] += 1 + + conn.commit() + conn.close() + + print(f"\n{'='*50}") + print(f"Database initialized at: {DB_PATH}") + print(f"{'='*50}") + print(f" Subjects: {stats['subjects']}") + print(f" Sub-topics: {stats['subtopics']}") + print(f" Topics: {stats['topics']}") + print(f" Question Types: {stats['qtypes']}") + print(f"\nReady for question generation!") + return stats + + +def get_question_type_id(conn, subject_name, subtopic_name, topic_name, qtype_name): + """Look up a question_type_id by hierarchical names.""" + row = conn.execute(""" + SELECT qt.id FROM question_types qt + JOIN topics t ON qt.topic_id = t.id + JOIN subtopics st ON t.subtopic_id = st.id + JOIN subjects s ON st.subject_id = s.id + WHERE s.name = ? AND st.name = ? AND t.name = ? AND qt.name = ? + """, (subject_name, subtopic_name, topic_name, qtype_name)).fetchone() + return row[0] if row else None + + +def insert_questions_batch(conn, questions): + """Insert a batch of questions. Each question is a dict with keys: + question_type_id, question_text, option_a, option_b, option_c, option_d, + correct_option, explanation, difficulty + """ + conn.executemany(""" + INSERT INTO questions (question_type_id, question_text, option_a, option_b, option_c, option_d, + correct_option, explanation, difficulty) + VALUES (:question_type_id, :question_text, :option_a, :option_b, :option_c, :option_d, + :correct_option, :explanation, :difficulty) + """, questions) + conn.commit() + + +def get_stats(conn): + """Get current question statistics.""" + stats = {} + rows = conn.execute(""" + SELECT s.name, COUNT(q.id) as count + FROM subjects s + LEFT JOIN subtopics st ON st.subject_id = s.id + LEFT JOIN topics t ON t.subtopic_id = st.id + LEFT JOIN question_types qt ON qt.topic_id = t.id + LEFT JOIN questions q ON q.question_type_id = qt.id + GROUP BY s.id + """).fetchall() + for row in rows: + stats[row[0]] = row[1] + total = conn.execute("SELECT COUNT(*) FROM questions").fetchone()[0] + stats['TOTAL'] = total + return stats + + +if __name__ == '__main__': + force = '--force' in sys.argv + init_db(force=force) diff --git a/db/schema.sql b/db/schema.sql new file mode 100644 index 0000000..0b917e7 --- /dev/null +++ b/db/schema.sql @@ -0,0 +1,83 @@ +-- SSCTopper Database Schema +-- Complete SSC CGL Question Bank + +CREATE TABLE IF NOT EXISTS subjects ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + name TEXT NOT NULL UNIQUE, + tier TEXT NOT NULL, + description TEXT, + target_questions INTEGER DEFAULT 0 +); + +CREATE TABLE IF NOT EXISTS subtopics ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + subject_id INTEGER NOT NULL, + name TEXT NOT NULL, + description TEXT, + FOREIGN KEY (subject_id) REFERENCES subjects(id), + UNIQUE(subject_id, name) +); + +CREATE TABLE IF NOT EXISTS topics ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + subtopic_id INTEGER NOT NULL, + name TEXT NOT NULL, + description TEXT, + FOREIGN KEY (subtopic_id) REFERENCES subtopics(id), + UNIQUE(subtopic_id, name) +); + +CREATE TABLE IF NOT EXISTS question_types ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + topic_id INTEGER NOT NULL, + name TEXT NOT NULL, + FOREIGN KEY (topic_id) REFERENCES topics(id), + UNIQUE(topic_id, name) +); + +CREATE TABLE IF NOT EXISTS questions ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + question_type_id INTEGER NOT NULL, + question_text TEXT NOT NULL, + option_a TEXT NOT NULL, + option_b TEXT NOT NULL, + option_c TEXT NOT NULL, + option_d TEXT NOT NULL, + correct_option TEXT NOT NULL CHECK(correct_option IN ('A','B','C','D')), + explanation TEXT, + difficulty INTEGER DEFAULT 1 CHECK(difficulty BETWEEN 1 AND 3), + year_appeared TEXT, + created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + FOREIGN KEY (question_type_id) REFERENCES question_types(id) +); + +-- Performance indexes +CREATE INDEX IF NOT EXISTS idx_questions_type ON questions(question_type_id); +CREATE INDEX IF NOT EXISTS idx_questions_difficulty ON questions(difficulty); +CREATE INDEX IF NOT EXISTS idx_topics_subtopic ON topics(subtopic_id); +CREATE INDEX IF NOT EXISTS idx_subtopics_subject ON subtopics(subject_id); +CREATE INDEX IF NOT EXISTS idx_qtypes_topic ON question_types(topic_id); + +-- User Management +CREATE TABLE IF NOT EXISTS users ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + username TEXT NOT NULL UNIQUE, + email TEXT NOT NULL UNIQUE, + password_hash TEXT NOT NULL, + created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP +); + +-- Progress Tracking (Question level) +CREATE TABLE IF NOT EXISTS user_answers ( + id INTEGER PRIMARY KEY AUTOINCREMENT, + user_id INTEGER NOT NULL, + question_id INTEGER NOT NULL, + is_correct BOOLEAN NOT NULL, + time_taken REAL DEFAULT 0.0, + answered_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP, + FOREIGN KEY (user_id) REFERENCES users(id), + FOREIGN KEY (question_id) REFERENCES questions(id) +); + +CREATE INDEX IF NOT EXISTS idx_user_answers_user ON user_answers(user_id); +CREATE INDEX IF NOT EXISTS idx_user_answers_question ON user_answers(question_id); diff --git a/db/syllabus.json b/db/syllabus.json new file mode 100644 index 0000000..2938d7f --- /dev/null +++ b/db/syllabus.json @@ -0,0 +1,826 @@ +{ + "subjects": [ + { + "name": "Quantitative Aptitude", + "tier": "1,2", + "description": "Mathematical skills including arithmetic, algebra, geometry, mensuration, trigonometry, and data interpretation", + "target_questions": 30000, + "subtopics": [ + { + "name": "Arithmetic", + "description": "Basic arithmetic operations and number concepts", + "topics": [ + { + "name": "Number System", + "description": "Natural numbers, whole numbers, integers, rational & irrational numbers, divisibility, remainders", + "question_types": ["Find the value", "Divisibility test", "Remainder problems", "Unit digit", "LCM/HCF word problems"] + }, + { + "name": "HCF and LCM", + "description": "Highest Common Factor and Lowest Common Multiple", + "question_types": ["Find HCF", "Find LCM", "Word problems on HCF/LCM", "Product of two numbers"] + }, + { + "name": "Simplification", + "description": "BODMAS, fractions, decimals, surds", + "question_types": ["Simplify expression", "Compare values", "Find missing number"] + }, + { + "name": "Decimals and Fractions", + "description": "Conversion, operations on decimals and fractions", + "question_types": ["Convert fraction to decimal", "Operations on fractions", "Recurring decimals", "Ordering fractions"] + } + ] + }, + { + "name": "Percentage", + "description": "Percentage calculations and applications", + "topics": [ + { + "name": "Basic Percentage", + "description": "Finding percentage of a number, expressing as percentage", + "question_types": ["Find X% of Y", "What percent is X of Y", "Percentage change", "Find original value"] + }, + { + "name": "Successive Percentage", + "description": "Multiple percentage changes applied successively", + "question_types": ["Net percentage change", "Two successive increases/decreases", "Mixed increase and decrease"] + }, + { + "name": "Population and Depreciation", + "description": "Population growth and depreciation of value over time", + "question_types": ["Population after N years", "Depreciation value", "Find rate of growth"] + } + ] + }, + { + "name": "Profit and Loss", + "description": "Cost price, selling price, profit, loss, discount and marked price", + "topics": [ + { + "name": "Basic Profit and Loss", + "description": "Finding profit, loss, cost price, selling price", + "question_types": ["Find profit/loss", "Find profit/loss percentage", "Find CP given SP and profit%", "Find SP given CP and loss%"] + }, + { + "name": "Discount and Marked Price", + "description": "Marked price, discount percentage, successive discounts", + "question_types": ["Find selling price after discount", "Find marked price", "Successive discounts", "Find single equivalent discount"] + }, + { + "name": "Dishonest Dealings", + "description": "False weights, mixing to gain profit", + "question_types": ["Profit with false weight", "Overall gain/loss in mixing"] + } + ] + }, + { + "name": "Ratio and Proportion", + "description": "Ratios, proportions, and their applications", + "topics": [ + { + "name": "Basic Ratio", + "description": "Simplifying ratios, comparing ratios, dividing in ratio", + "question_types": ["Simplify ratio", "Divide in given ratio", "Find quantity from ratio", "Compare ratios"] + }, + { + "name": "Proportion", + "description": "Direct proportion, inverse proportion, mean proportional", + "question_types": ["Find fourth proportional", "Find mean proportional", "Third proportional"] + }, + { + "name": "Partnership", + "description": "Profit sharing among partners based on investment and time", + "question_types": ["Divide profit among partners", "Find investment amount", "Find time of investment"] + }, + { + "name": "Mixture and Alligation", + "description": "Mixing two or more quantities", + "question_types": ["Find ratio of mixing", "Mean price of mixture", "Replacement problems"] + } + ] + }, + { + "name": "Average", + "description": "Mean, weighted average and related problems", + "topics": [ + { + "name": "Simple Average", + "description": "Average of numbers, runs, marks", + "question_types": ["Find average", "Find sum from average", "Find missing value", "Average after adding/removing"] + }, + { + "name": "Weighted Average", + "description": "Average with different weights", + "question_types": ["Weighted mean", "Combined average of groups", "Average speed"] + }, + { + "name": "Age Problems", + "description": "Average age related problems", + "question_types": ["Average age of family", "Age ratio problems", "Present/future/past average age"] + } + ] + }, + { + "name": "Time and Work", + "description": "Work efficiency, combined work, pipes and cisterns", + "topics": [ + { + "name": "Basic Time and Work", + "description": "Individual and combined work efficiency", + "question_types": ["Find time to complete work", "Find combined time", "Work done in given days", "Alternate working"] + }, + { + "name": "Pipes and Cisterns", + "description": "Filling and emptying tanks through pipes", + "question_types": ["Time to fill tank", "Net filling rate", "Leak problems", "Multiple pipes"] + }, + { + "name": "Work and Wages", + "description": "Wages proportional to work done", + "question_types": ["Divide wages", "Find individual wage", "Efficiency-based wages"] + } + ] + }, + { + "name": "Time, Speed and Distance", + "description": "Speed, distance, time relationships and applications", + "topics": [ + { + "name": "Basic Speed and Distance", + "description": "Finding speed, distance, time", + "question_types": ["Find speed", "Find distance", "Find time", "Average speed", "Relative speed"] + }, + { + "name": "Trains", + "description": "Problems involving trains passing objects or each other", + "question_types": ["Train passing pole", "Train passing platform", "Two trains passing each other", "Find length of train"] + }, + { + "name": "Boats and Streams", + "description": "Upstream and downstream problems", + "question_types": ["Find speed in still water", "Find stream speed", "Time for upstream/downstream journey", "Round trip time"] + }, + { + "name": "Races", + "description": "Head start, dead heat, circular track", + "question_types": ["Head start distance", "Dead heat problems", "Meeting point on circular track"] + } + ] + }, + { + "name": "Interest", + "description": "Simple and compound interest calculations", + "topics": [ + { + "name": "Simple Interest", + "description": "SI = PRT/100", + "question_types": ["Find SI", "Find principal", "Find rate", "Find time", "Amount after time"] + }, + { + "name": "Compound Interest", + "description": "Interest compounded annually, half-yearly, quarterly", + "question_types": ["Find CI", "Find amount", "Difference between CI and SI", "Half-yearly/quarterly compounding"] + } + ] + }, + { + "name": "Algebra", + "description": "Algebraic expressions, equations and identities", + "topics": [ + { + "name": "Linear Equations", + "description": "One variable and two variable linear equations", + "question_types": ["Solve for x", "Word problems", "System of equations", "Find value of expression"] + }, + { + "name": "Quadratic Equations", + "description": "Solving quadratic equations, nature of roots", + "question_types": ["Find roots", "Sum and product of roots", "Nature of roots", "Form equation from roots"] + }, + { + "name": "Algebraic Identities", + "description": "Standard identities and their applications", + "question_types": ["Simplify using identity", "Find value of expression", "Factorize"] + }, + { + "name": "Surds and Indices", + "description": "Laws of exponents, simplification of surds", + "question_types": ["Simplify expression", "Rationalize denominator", "Compare surds", "Find value"] + } + ] + }, + { + "name": "Geometry", + "description": "Lines, angles, triangles, circles, quadrilaterals", + "topics": [ + { + "name": "Lines and Angles", + "description": "Parallel lines, transversals, angle relationships", + "question_types": ["Find angle value", "Identify angle type", "Parallel line properties"] + }, + { + "name": "Triangles", + "description": "Properties, congruence, similarity, centers of triangle", + "question_types": ["Find angle in triangle", "Congruence condition", "Similar triangle ratio", "Centroid/Incenter/Circumcenter problems"] + }, + { + "name": "Circles", + "description": "Chord, tangent, arc, sector properties", + "question_types": ["Find angle in circle", "Chord length", "Tangent properties", "Arc/sector angle"] + }, + { + "name": "Quadrilaterals and Polygons", + "description": "Properties of parallelogram, rhombus, rectangle, regular polygons", + "question_types": ["Find angle", "Find diagonal", "Properties identification", "Interior/exterior angle sum"] + }, + { + "name": "Coordinate Geometry", + "description": "Distance, section formula, area of triangle, equation of line", + "question_types": ["Find distance between points", "Find midpoint", "Area of triangle", "Slope of line"] + } + ] + }, + { + "name": "Mensuration", + "description": "Area, perimeter, volume, surface area of 2D and 3D shapes", + "topics": [ + { + "name": "2D Figures", + "description": "Area and perimeter of plane figures", + "question_types": ["Find area", "Find perimeter", "Find diagonal", "Combined figure area"] + }, + { + "name": "3D Figures", + "description": "Volume and surface area of solids", + "question_types": ["Find volume", "Find surface area", "Find curved surface area", "Conversion between shapes"] + } + ] + }, + { + "name": "Trigonometry", + "description": "Trigonometric ratios, identities, heights and distances", + "topics": [ + { + "name": "Trigonometric Ratios", + "description": "sin, cos, tan and their values for standard angles", + "question_types": ["Find value of expression", "Simplify trig expression", "Find angle"] + }, + { + "name": "Trigonometric Identities", + "description": "Standard identities and their proofs", + "question_types": ["Prove identity", "Simplify using identity", "Find value given condition"] + }, + { + "name": "Heights and Distances", + "description": "Application of trigonometry to find heights and distances", + "question_types": ["Find height of tower", "Find distance", "Angle of elevation/depression", "Two-observer problems"] + } + ] + }, + { + "name": "Data Interpretation", + "description": "Reading and analyzing data from charts and tables", + "topics": [ + { + "name": "Bar Graph", + "description": "Interpreting bar charts", + "question_types": ["Find value", "Calculate ratio", "Find percentage change", "Compare data"] + }, + { + "name": "Pie Chart", + "description": "Interpreting pie charts", + "question_types": ["Find degree/value", "Calculate percentage", "Compare sectors"] + }, + { + "name": "Line Graph", + "description": "Interpreting line graphs", + "question_types": ["Find trend", "Calculate change", "Average over period"] + }, + { + "name": "Table", + "description": "Interpreting tabular data", + "question_types": ["Calculate from table", "Find ratio", "Percentage calculation"] + } + ] + }, + { + "name": "Statistics", + "description": "Measures of central tendency and dispersion", + "topics": [ + { + "name": "Mean, Median and Mode", + "description": "Central tendency measures for grouped and ungrouped data", + "question_types": ["Find mean", "Find median", "Find mode", "Combined mean"] + }, + { + "name": "Range and Standard Deviation", + "description": "Measures of spread", + "question_types": ["Find range", "Find standard deviation", "Find variance"] + } + ] + } + ] + }, + { + "name": "General Intelligence and Reasoning", + "tier": "1,2", + "description": "Logical and analytical reasoning covering verbal, non-verbal, and critical thinking", + "target_questions": 25000, + "subtopics": [ + { + "name": "Verbal Reasoning", + "description": "Reasoning with words, letters, and numbers", + "topics": [ + { + "name": "Analogy", + "description": "Finding relationships between pairs of words/numbers/letters", + "question_types": ["Word analogy", "Number analogy", "Letter analogy", "Mixed analogy"] + }, + { + "name": "Classification", + "description": "Finding the odd one out from a group", + "question_types": ["Word classification", "Number classification", "Letter classification", "Mixed classification"] + }, + { + "name": "Number Series", + "description": "Finding patterns in number sequences", + "question_types": ["Find next number", "Find missing number", "Find wrong number"] + }, + { + "name": "Letter Series", + "description": "Finding patterns in letter sequences", + "question_types": ["Find next letters", "Find missing letters", "Pattern identification"] + }, + { + "name": "Alpha-Numeric Series", + "description": "Combined letter-number patterns", + "question_types": ["Find next term", "Find missing term", "Pattern rule"] + }, + { + "name": "Coding-Decoding", + "description": "Encoding and decoding messages using rules", + "question_types": ["Letter coding", "Number coding", "Mixed coding", "Conditional coding"] + } + ] + }, + { + "name": "Logical Reasoning", + "description": "Logical deduction and analytical problems", + "topics": [ + { + "name": "Blood Relations", + "description": "Family relationship problems", + "question_types": ["Direct relation", "Coded relation", "Family tree", "Generation problems"] + }, + { + "name": "Direction and Distance", + "description": "Navigation and displacement problems", + "question_types": ["Find final direction", "Find distance from start", "Shortest distance", "Shadow-based direction"] + }, + { + "name": "Order and Ranking", + "description": "Position-based problems", + "question_types": ["Find rank from top/bottom", "Total number of persons", "Interchange positions", "Between positions"] + }, + { + "name": "Syllogism", + "description": "Logical conclusions from given statements", + "question_types": ["All/Some/No conclusions", "Either-or conclusions", "Possibility-based"] + }, + { + "name": "Seating Arrangement", + "description": "Linear and circular arrangement puzzles", + "question_types": ["Linear row arrangement", "Circular arrangement", "Two-row arrangement", "Complex multi-variable"] + }, + { + "name": "Puzzle", + "description": "Floor, scheduling, and distribution puzzles", + "question_types": ["Floor-based puzzle", "Day/month scheduling", "Distribution puzzle", "Comparison-based ordering"] + } + ] + }, + { + "name": "Non-Verbal Reasoning", + "description": "Reasoning with figures, patterns and spatial concepts", + "topics": [ + { + "name": "Figure Series", + "description": "Finding next figure in a sequence", + "question_types": ["Find next figure", "Find missing figure", "Pattern completion"] + }, + { + "name": "Mirror and Water Image", + "description": "Reflection of figures and text", + "question_types": ["Mirror image of figure", "Water image of figure", "Mirror image of text/numbers"] + }, + { + "name": "Paper Folding and Cutting", + "description": "Predicting result of folding and cutting paper", + "question_types": ["Find pattern after unfolding", "Number of pieces after cutting"] + }, + { + "name": "Embedded Figures", + "description": "Finding figures hidden within complex figures", + "question_types": ["Find embedded figure", "Count embedded shapes"] + }, + { + "name": "Dice and Cube", + "description": "Problems on dice faces and cube painting", + "question_types": ["Opposite face of dice", "Adjacent faces", "Painted cube counting"] + } + ] + }, + { + "name": "Mathematical Reasoning", + "description": "Reasoning using mathematical operations", + "topics": [ + { + "name": "Mathematical Operations", + "description": "Substituted operations and symbols", + "question_types": ["Symbol substitution", "Find correct equation", "Balancing equations"] + }, + { + "name": "Number Puzzles", + "description": "Missing numbers in grids and figures", + "question_types": ["Find missing number in grid", "Find missing in triangle/circle", "Pattern in figures"] + }, + { + "name": "Venn Diagram", + "description": "Representing relationships using Venn diagrams", + "question_types": ["Identify correct Venn diagram", "Count elements in region", "Minimum/maximum in region"] + } + ] + }, + { + "name": "Critical Thinking", + "description": "Evaluating statements, assumptions and conclusions", + "topics": [ + { + "name": "Statement and Conclusion", + "description": "Drawing valid conclusions from statements", + "question_types": ["Which conclusion follows", "Both/neither/either follows"] + }, + { + "name": "Statement and Assumption", + "description": "Identifying implicit assumptions", + "question_types": ["Which assumption is implicit", "Both/neither implicit"] + }, + { + "name": "Cause and Effect", + "description": "Identifying cause-effect relationships", + "question_types": ["Identify cause", "Identify effect", "Independent/dependent events"] + }, + { + "name": "Course of Action", + "description": "Deciding appropriate actions from given situations", + "question_types": ["Which action follows", "Appropriate/inappropriate action"] + } + ] + } + ] + }, + { + "name": "English Language and Comprehension", + "tier": "1,2", + "description": "English vocabulary, grammar, sentence structure, and reading comprehension", + "target_questions": 25000, + "subtopics": [ + { + "name": "Vocabulary", + "description": "Word meanings, usage, and recognition", + "topics": [ + { + "name": "Synonyms", + "description": "Words with similar meanings", + "question_types": ["Choose synonym", "Most similar meaning in context", "Replace with synonym"] + }, + { + "name": "Antonyms", + "description": "Words with opposite meanings", + "question_types": ["Choose antonym", "Most opposite meaning", "Replace with antonym"] + }, + { + "name": "One Word Substitution", + "description": "Single word for a group of words or phrase", + "question_types": ["Find one word for phrase", "Identify correct substitution"] + }, + { + "name": "Idioms and Phrases", + "description": "Common English idioms and their meanings", + "question_types": ["Meaning of idiom", "Use idiom in context", "Choose correct idiom"] + }, + { + "name": "Spelling Correction", + "description": "Identifying correctly/incorrectly spelled words", + "question_types": ["Find misspelled word", "Choose correct spelling", "Correct the spelling"] + }, + { + "name": "Foreign Words", + "description": "Commonly used foreign words and phrases in English", + "question_types": ["Meaning of foreign phrase", "Use in context"] + } + ] + }, + { + "name": "Grammar", + "description": "Rules of English grammar", + "topics": [ + { + "name": "Tenses", + "description": "Past, present, future tenses and their forms", + "question_types": ["Fill in correct tense", "Identify tense", "Correct the tense error"] + }, + { + "name": "Articles", + "description": "Use of a, an, the", + "question_types": ["Fill in correct article", "Identify article error", "No article needed"] + }, + { + "name": "Prepositions", + "description": "Correct use of prepositions", + "question_types": ["Fill in preposition", "Correct preposition error", "Choose appropriate preposition"] + }, + { + "name": "Subject-Verb Agreement", + "description": "Matching subjects with correct verb forms", + "question_types": ["Choose correct verb", "Find agreement error", "Correct the sentence"] + }, + { + "name": "Modals", + "description": "Can, could, may, might, should, would, etc.", + "question_types": ["Choose correct modal", "Modal usage in context"] + }, + { + "name": "Conjunctions", + "description": "Coordinating, subordinating, correlative conjunctions", + "question_types": ["Fill in conjunction", "Choose correct connector"] + } + ] + }, + { + "name": "Sentence Structure", + "description": "Sentence formation, transformation, and improvement", + "topics": [ + { + "name": "Active and Passive Voice", + "description": "Converting between active and passive voice", + "question_types": ["Convert to passive", "Convert to active", "Identify voice"] + }, + { + "name": "Direct and Indirect Speech", + "description": "Converting between direct and indirect narration", + "question_types": ["Convert to indirect speech", "Convert to direct speech", "Identify correct conversion"] + }, + { + "name": "Sentence Improvement", + "description": "Improving parts of sentences for correctness/style", + "question_types": ["Replace underlined part", "Choose best improvement", "No improvement needed"] + }, + { + "name": "Sentence Rearrangement", + "description": "Arranging jumbled sentences or parts in correct order", + "question_types": ["Arrange sentence parts", "Arrange sentences in paragraph", "Find first/last sentence"] + }, + { + "name": "Sentence Completion", + "description": "Completing sentences with appropriate words/phrases", + "question_types": ["Fill in the blank (single)", "Fill in the blank (double)", "Choose correct phrase"] + } + ] + }, + { + "name": "Error Detection", + "description": "Identifying grammatical and usage errors", + "topics": [ + { + "name": "Spot the Error", + "description": "Finding errors in given sentences", + "question_types": ["Identify erroneous part", "No error option", "Multiple error identification"] + }, + { + "name": "Sentence Correction", + "description": "Correcting given erroneous sentences", + "question_types": ["Choose correct version", "Identify and correct error"] + } + ] + }, + { + "name": "Comprehension", + "description": "Understanding and analyzing written passages", + "topics": [ + { + "name": "Reading Comprehension", + "description": "Answering questions based on passages", + "question_types": ["Main idea", "Inference", "Vocabulary in context", "Detail-based", "Tone/attitude"] + }, + { + "name": "Cloze Test", + "description": "Filling blanks in a passage", + "question_types": ["Fill appropriate word", "Grammar-based blank", "Vocabulary-based blank"] + }, + { + "name": "Para Jumbles", + "description": "Arranging sentences to form coherent paragraph", + "question_types": ["Arrange in order", "Find opening sentence", "Find closing sentence"] + } + ] + } + ] + }, + { + "name": "General Awareness", + "tier": "1,2", + "description": "General knowledge covering history, geography, polity, economics, science, and current affairs", + "target_questions": 20000, + "subtopics": [ + { + "name": "History", + "description": "Indian and world history from ancient to modern times", + "topics": [ + { + "name": "Ancient India", + "description": "Indus Valley, Vedic period, Mauryas, Guptas, post-Gupta", + "question_types": ["Who/What/When", "Match the following", "Chronological order", "Identify dynasty/ruler"] + }, + { + "name": "Medieval India", + "description": "Delhi Sultanate, Mughal Empire, Vijayanagara, Bhakti/Sufi", + "question_types": ["Who/What/When", "Match ruler with achievement", "Battle identification"] + }, + { + "name": "Modern India", + "description": "British rule, freedom movement, post-independence", + "question_types": ["Freedom fighter identification", "Movement/event in order", "Governor General/Viceroy"] + }, + { + "name": "World History", + "description": "World wars, revolutions, important treaties", + "question_types": ["Event identification", "Treaty/agreement", "Revolution causes"] + }, + { + "name": "Art and Culture", + "description": "Indian art forms, dance, music, architecture, literature", + "question_types": ["Identify art form", "Match dance with state", "Architecture identification"] + } + ] + }, + { + "name": "Geography", + "description": "Physical, Indian, and world geography", + "topics": [ + { + "name": "Physical Geography", + "description": "Earth, atmosphere, lithosphere, hydrosphere", + "question_types": ["Concept identification", "Layer/zone properties", "Natural phenomena"] + }, + { + "name": "Indian Geography", + "description": "Rivers, mountains, climate, soil, vegetation, states", + "question_types": ["River system", "Mountain pass/peak", "State capital/boundary", "Climate zone"] + }, + { + "name": "World Geography", + "description": "Continents, oceans, countries, capitals", + "question_types": ["Country-capital", "Largest/smallest/longest", "Geographic features"] + }, + { + "name": "Climate and Weather", + "description": "Monsoons, cyclones, climate change, seasons", + "question_types": ["Monsoon mechanism", "Climate type", "Weather phenomena"] + }, + { + "name": "Resources and Agriculture", + "description": "Natural resources, crops, minerals, industries", + "question_types": ["Crop-region", "Mineral-state", "Industry location", "Resource type"] + } + ] + }, + { + "name": "Indian Polity", + "description": "Constitution, governance, judiciary, and political system", + "topics": [ + { + "name": "Indian Constitution", + "description": "Preamble, fundamental rights, DPSP, duties, amendments", + "question_types": ["Article identification", "Amendment detail", "Right classification", "Feature borrowed from"] + }, + { + "name": "Parliament and State Legislature", + "description": "Lok Sabha, Rajya Sabha, state assemblies, bills", + "question_types": ["Functions", "Composition", "Bill passage process", "Speaker/Chairman powers"] + }, + { + "name": "Judiciary", + "description": "Supreme Court, High Courts, lower courts, judicial review", + "question_types": ["Jurisdiction", "Appointment process", "Writ identification", "Landmark judgement"] + }, + { + "name": "Governance", + "description": "President, PM, Council of Ministers, Governor, CAG", + "question_types": ["Powers and functions", "Appointment", "Removal process", "Emergency provisions"] + }, + { + "name": "Panchayati Raj and Local Governance", + "description": "73rd and 74th amendments, three-tier system", + "question_types": ["Structure", "Functions", "Elections", "Constitutional provisions"] + } + ] + }, + { + "name": "Economics", + "description": "Indian economy, banking, fiscal policy, international trade", + "topics": [ + { + "name": "Indian Economy Basics", + "description": "GDP, GNP, NI, sectors of economy, planning", + "question_types": ["Define term", "Sector identification", "Economic indicator", "Five Year Plan"] + }, + { + "name": "Banking and Finance", + "description": "RBI, commercial banks, monetary policy, financial markets", + "question_types": ["RBI functions", "Bank rate/repo rate", "Financial term", "Banking instrument"] + }, + { + "name": "Budget and Fiscal Policy", + "description": "Union budget, taxes, fiscal deficit, public debt", + "question_types": ["Tax type", "Budget component", "Deficit type", "Revenue/capital"] + }, + { + "name": "International Organizations", + "description": "IMF, World Bank, WTO, ASEAN, BRICS, G20", + "question_types": ["Organization HQ", "Member countries", "Functions", "Formation year"] + }, + { + "name": "Government Schemes", + "description": "Major government welfare and development schemes", + "question_types": ["Scheme objective", "Launch year", "Ministry responsible", "Beneficiary"] + } + ] + }, + { + "name": "Science", + "description": "Physics, chemistry, biology, and technology", + "topics": [ + { + "name": "Physics", + "description": "Mechanics, heat, light, sound, electricity, magnetism", + "question_types": ["Law/principle identification", "Unit/dimension", "Application of concept", "Inventor/discovery"] + }, + { + "name": "Chemistry", + "description": "Elements, compounds, reactions, acids and bases, everyday chemistry", + "question_types": ["Chemical formula", "Reaction type", "Element property", "Everyday chemistry application"] + }, + { + "name": "Biology", + "description": "Cell biology, human body, diseases, nutrition, ecology", + "question_types": ["Organ/system function", "Disease-cause", "Vitamin-deficiency", "Ecology concept"] + }, + { + "name": "Space and Technology", + "description": "ISRO missions, satellites, recent tech developments", + "question_types": ["Mission identification", "Satellite purpose", "Technology application", "First achievements"] + }, + { + "name": "Computer Awareness", + "description": "Computer fundamentals, MS Office, Internet, networking, cybersecurity", + "question_types": ["Term definition", "Shortcut key", "Component function", "Software feature"] + } + ] + }, + { + "name": "Static GK", + "description": "Fixed factual knowledge that doesn't change frequently", + "topics": [ + { + "name": "Books and Authors", + "description": "Famous books and their authors", + "question_types": ["Match book-author", "Identify author", "Award-winning book"] + }, + { + "name": "Important Days and Dates", + "description": "National and international important days", + "question_types": ["Date identification", "Theme of the year", "Organizing body"] + }, + { + "name": "Awards and Honours", + "description": "Bharat Ratna, Padma awards, Nobel Prize, national awards", + "question_types": ["Award-winner", "Award category", "First recipient", "Recent winner"] + }, + { + "name": "Sports", + "description": "Major sports events, trophies, records, personalities", + "question_types": ["Trophy-sport", "Record holder", "Venue/host country", "Player-team"] + }, + { + "name": "National Symbols and Firsts", + "description": "National symbols, firsts in India and world", + "question_types": ["Identify symbol", "First person/event", "National identifier"] + } + ] + } + ] + } + ] +} diff --git a/generators/__init__.py b/generators/__init__.py new file mode 100644 index 0000000..6cec990 --- /dev/null +++ b/generators/__init__.py @@ -0,0 +1 @@ +# SSCTopper Question Generators diff --git a/generators/__pycache__/__init__.cpython-314.pyc b/generators/__pycache__/__init__.cpython-314.pyc new file mode 100644 index 0000000..536e82b Binary files /dev/null and b/generators/__pycache__/__init__.cpython-314.pyc differ diff --git a/generators/__pycache__/base.cpython-314.pyc b/generators/__pycache__/base.cpython-314.pyc new file mode 100644 index 0000000..c3b6630 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mode 100644 index 0000000..8a11129 Binary files /dev/null and b/generators/__pycache__/reasoning_generator.cpython-314.pyc differ diff --git a/generators/base.py b/generators/base.py new file mode 100644 index 0000000..1a8f54f --- /dev/null +++ b/generators/base.py @@ -0,0 +1,89 @@ + + +#!/usr/bin/env python3 +"""Base utilities for question generation.""" +import random +import sys +import os + +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) +from db.init import get_db, get_question_type_id, insert_questions_batch + + +def shuffle_options(correct, wrongs, explanation=""): + """Create options with correct answer randomly placed.""" + options = [correct] + wrongs[:3] + # Map original correct to its letter + indices = list(range(4)) + random.shuffle(indices) + shuffled = [options[i] for i in indices] + correct_letter = chr(65 + indices.index(0)) # A, B, C, D + return { + 'option_a': str(shuffled[0]), + 'option_b': str(shuffled[1]), + 'option_c': str(shuffled[2]), + 'option_d': str(shuffled[3]), + 'correct_option': correct_letter, + 'explanation': explanation + } + + +def make_question(qtype_id, text, correct, wrongs, explanation="", difficulty=1): + """Build a question dict ready for DB insertion.""" + q = shuffle_options(correct, wrongs, explanation) + q['question_type_id'] = qtype_id + q['question_text'] = text + q['difficulty'] = difficulty + return q + + +def get_qtid(conn, subject, subtopic, topic, qtype): + """Shorthand for get_question_type_id.""" + return get_question_type_id(conn, subject, subtopic, topic, qtype) + + +def nearby_wrong(val, spread=None): + """Generate plausible wrong answers near the correct value.""" + if spread is None: + spread = max(1, abs(val) // 5) if val != 0 else 5 + wrongs = set() + attempts = 0 + while len(wrongs) < 3 and attempts < 50: + offset = random.randint(1, max(1, spread)) + sign = random.choice([-1, 1]) + w = val + sign * offset + if w != val and w not in wrongs: + wrongs.add(w) + attempts += 1 + # Fallback + while len(wrongs) < 3: + wrongs.add(val + len(wrongs) + 1) + return [str(w) for w in wrongs] + + +def nearby_wrong_float(val, spread=None, decimals=2): + """Generate plausible wrong answers for float values.""" + if spread is None: + spread = max(0.5, abs(val) * 0.2) + wrongs = set() + attempts = 0 + while len(wrongs) < 3 and attempts < 50: + offset = round(random.uniform(0.1, spread), decimals) + sign = random.choice([-1, 1]) + w = round(val + sign * offset, decimals) + if w != round(val, decimals) and w not in wrongs and w > 0: + wrongs.add(w) + attempts += 1 + while len(wrongs) < 3: + wrongs.add(round(val + (len(wrongs) + 1) * 0.5, decimals)) + return [str(w) for w in wrongs] + + +def frac_str(num, den): + """Format a fraction as string.""" + from math import gcd + g = gcd(abs(num), abs(den)) + n, d = num // g, den // g + if d == 1: + return str(n) + return f"{n}/{d}" diff --git a/generators/english_generator.py b/generators/english_generator.py new file mode 100644 index 0000000..d363a2b --- /dev/null +++ b/generators/english_generator.py @@ -0,0 +1,545 @@ +#!/usr/bin/env python3 +""" +English Language & Comprehension Question Generator for SSC CGL. +Generates ~25,000 questions covering vocabulary, grammar, sentence structure, error detection. +""" +import random +import sys +import os + +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) +from generators.base import make_question, get_qtid, get_db, insert_questions_batch + +SUBJECT = "English Language and Comprehension" + +# ============ WORD BANKS ============ + +SYNONYMS = [ + ("Abundant", "Plentiful", ["Scarce", "Meager", "Rare"]), + ("Accurate", "Precise", ["Wrong", "Vague", "Incorrect"]), + ("Admire", "Respect", ["Despise", "Hate", "Ignore"]), + ("Affluent", "Wealthy", ["Poor", "Needy", "Destitute"]), + ("Agile", "Nimble", ["Clumsy", "Slow", "Stiff"]), + ("Amiable", "Friendly", ["Hostile", "Rude", "Cold"]), + ("Ancient", "Old", ["Modern", "New", "Recent"]), + ("Arduous", "Difficult", ["Easy", "Simple", "Effortless"]), + ("Audacious", "Bold", ["Timid", "Meek", "Cowardly"]), + ("Authentic", "Genuine", ["Fake", "False", "Counterfeit"]), + ("Benevolent", "Kind", ["Cruel", "Malicious", "Harsh"]), + ("Bizarre", "Strange", ["Normal", "Usual", "Ordinary"]), + ("Candid", "Frank", ["Deceptive", "Dishonest", "Sly"]), + ("Cautious", "Careful", ["Reckless", "Careless", "Rash"]), + ("Comprehend", "Understand", ["Misunderstand", "Confuse", "Ignore"]), + ("Conceal", "Hide", ["Reveal", "Expose", "Display"]), + ("Contempt", "Scorn", ["Respect", "Admiration", "Regard"]), + ("Courage", "Bravery", ["Cowardice", "Fear", "Timidity"]), + ("Delight", "Joy", ["Sorrow", "Grief", "Misery"]), + ("Diligent", "Hardworking", ["Lazy", "Idle", "Indolent"]), + ("Diminish", "Reduce", ["Increase", "Enlarge", "Expand"]), + ("Eloquent", "Expressive", ["Inarticulate", "Stammering", "Dull"]), + ("Enormous", "Huge", ["Tiny", "Small", "Minute"]), + ("Eternal", "Everlasting", ["Temporary", "Brief", "Fleeting"]), + ("Exquisite", "Beautiful", ["Ugly", "Plain", "Crude"]), + ("Feeble", "Weak", ["Strong", "Powerful", "Mighty"]), + ("Ferocious", "Fierce", ["Gentle", "Mild", "Tame"]), + ("Frigid", "Cold", ["Hot", "Warm", "Tropical"]), + ("Generous", "Liberal", ["Stingy", "Miserly", "Tight"]), + ("Gratitude", "Thankfulness", ["Ingratitude", "Ungratefulness", "Resentment"]), + ("Halt", "Stop", ["Continue", "Proceed", "Advance"]), + ("Hazardous", "Dangerous", ["Safe", "Secure", "Harmless"]), + ("Hostile", "Unfriendly", ["Friendly", "Warm", "Kind"]), + ("Immense", "Vast", ["Tiny", "Small", "Little"]), + ("Impeccable", "Flawless", ["Faulty", "Defective", "Imperfect"]), + ("Jubilant", "Joyful", ["Sad", "Gloomy", "Depressed"]), + ("Keen", "Eager", ["Reluctant", "Unwilling", "Indifferent"]), + ("Laudable", "Praiseworthy", ["Blameworthy", "Shameful", "Disgraceful"]), + ("Lucid", "Clear", ["Confusing", "Vague", "Obscure"]), + ("Magnificent", "Splendid", ["Ordinary", "Plain", "Dull"]), + ("Meticulous", "Careful", ["Careless", "Sloppy", "Negligent"]), + ("Mundane", "Ordinary", ["Extraordinary", "Unusual", "Special"]), + ("Novice", "Beginner", ["Expert", "Veteran", "Professional"]), + ("Obstinate", "Stubborn", ["Flexible", "Yielding", "Compliant"]), + ("Opulent", "Luxurious", ["Poor", "Shabby", "Modest"]), + ("Pacify", "Calm", ["Agitate", "Provoke", "Irritate"]), + ("Prudent", "Wise", ["Foolish", "Reckless", "Imprudent"]), + ("Replenish", "Refill", ["Drain", "Empty", "Deplete"]), + ("Serene", "Calm", ["Turbulent", "Agitated", "Noisy"]), + ("Tedious", "Boring", ["Interesting", "Exciting", "Engaging"]), + ("Trivial", "Insignificant", ["Important", "Significant", "Vital"]), + ("Ubiquitous", "Everywhere", ["Rare", "Scarce", "Uncommon"]), + ("Valiant", "Brave", ["Cowardly", "Timid", "Fearful"]), + ("Verbose", "Wordy", ["Concise", "Brief", "Terse"]), + ("Wrath", "Anger", ["Calm", "Peace", "Happiness"]), + ("Zealous", "Enthusiastic", ["Apathetic", "Indifferent", "Passive"]), +] + +ANTONYMS = [ + ("Accept", "Reject"), ("Advance", "Retreat"), ("Ancient", "Modern"), + ("Arrival", "Departure"), ("Ascend", "Descend"), ("Bold", "Timid"), + ("Brave", "Cowardly"), ("Bright", "Dim"), ("Calm", "Agitated"), + ("Create", "Destroy"), ("Dawn", "Dusk"), ("Defend", "Attack"), + ("Expand", "Contract"), ("Forget", "Remember"), ("Generous", "Miserly"), + ("Guilty", "Innocent"), ("Humble", "Proud"), ("Import", "Export"), + ("Joy", "Sorrow"), ("Knowledge", "Ignorance"), ("Liberty", "Captivity"), + ("Major", "Minor"), ("Natural", "Artificial"), ("Optimist", "Pessimist"), + ("Peace", "War"), ("Rapid", "Slow"), ("Rigid", "Flexible"), + ("Simple", "Complex"), ("Temporary", "Permanent"), ("Victory", "Defeat"), + ("Wisdom", "Folly"), ("Zenith", "Nadir"), ("Transparent", "Opaque"), + ("Voluntary", "Compulsory"), ("Shallow", "Deep"), ("Fertile", "Barren"), + ("Concord", "Discord"), ("Benign", "Malignant"), ("Prolific", "Barren"), + ("Affluent", "Destitute"), +] + +ONE_WORD_SUBS = [ + ("A person who loves books", "Bibliophile", ["Bibliographer", "Librarian", "Bookworm"]), + ("Government by the people", "Democracy", ["Monarchy", "Autocracy", "Oligarchy"]), + ("One who hates mankind", "Misanthrope", ["Philanthropist", "Misogynist", "Anthropologist"]), + ("A person who speaks two languages", "Bilingual", ["Polyglot", "Monoglot", "Linguist"]), + ("A person who walks in sleep", "Somnambulist", ["Insomniac", "Sleepwalker", "Narcoleptic"]), + ("Fear of water", "Hydrophobia", ["Aquaphobia", "Claustrophobia", "Acrophobia"]), + ("Fear of heights", "Acrophobia", ["Hydrophobia", "Claustrophobia", "Agoraphobia"]), + ("One who eats human flesh", "Cannibal", ["Carnivore", "Omnivore", "Herbivore"]), + ("A word that is opposite in meaning", "Antonym", ["Synonym", "Homonym", "Acronym"]), + ("Killing of a king", "Regicide", ["Homicide", "Genocide", "Fratricide"]), + ("A place for keeping bees", "Apiary", ["Aviary", "Aquarium", "Nursery"]), + ("One who knows everything", "Omniscient", ["Omnipresent", "Omnipotent", "Omnivore"]), + ("Medicine that kills germs", "Antiseptic", ["Antibiotic", "Antidote", "Analgesic"]), + ("A person who is 100 years old", "Centenarian", ["Octogenarian", "Nonagenarian", "Septuagenarian"]), + ("Study of stars", "Astronomy", ["Astrology", "Cosmology", "Astrophysics"]), + ("Government by a single person", "Autocracy", ["Democracy", "Monarchy", "Theocracy"]), + ("One who does not believe in God", "Atheist", ["Theist", "Agnostic", "Pagan"]), + ("A speech delivered without preparation", "Extempore", ["Impromptu", "Rehearsed", "Deliberate"]), + ("One who lives on vegetables", "Vegetarian", ["Vegan", "Carnivore", "Omnivore"]), + ("A place for keeping dead bodies", "Mortuary", ["Cemetery", "Crematorium", "Mausoleum"]), + ("That which cannot be read", "Illegible", ["Eligible", "Legible", "Indelible"]), + ("A person who cannot be corrected", "Incorrigible", ["Incurable", "Invincible", "Inevitable"]), + ("One who is present everywhere", "Omnipresent", ["Omniscient", "Omnipotent", "Omnivore"]), + ("One who looks on the bright side", "Optimist", ["Pessimist", "Realist", "Fatalist"]), + ("Study of ancient things", "Archaeology", ["Anthropology", "Paleontology", "Geology"]), +] + +IDIOMS = [ + ("Break the ice", "To initiate conversation in a social setting", ["To break something", "To melt ice", "To cool down"]), + ("Burn the midnight oil", "To work or study late into the night", ["To waste oil", "To start a fire", "To cook at night"]), + ("Cry over spilt milk", "To regret something that cannot be undone", ["To cry while drinking milk", "To waste milk", "To be sad about dairy"]), + ("Hit the nail on the head", "To be exactly right", ["To do carpentry", "To hurt oneself", "To break something"]), + ("A piece of cake", "Something very easy", ["A type of dessert", "A small portion", "A bakery item"]), + ("Bite the bullet", "To face a difficult situation bravely", ["To eat ammunition", "To hurt teeth", "To be violent"]), + ("Cost an arm and a leg", "Very expensive", ["Physical injury", "Amputation", "Medical procedure"]), + ("Let the cat out of the bag", "To reveal a secret", ["To free an animal", "To open a bag", "To go shopping"]), + ("Once in a blue moon", "Very rarely", ["During full moon", "Monthly", "Nightly"]), + ("Raining cats and dogs", "Raining very heavily", ["Animals falling", "Pet show", "Zoo visit"]), + ("Spill the beans", "To reveal secret information", ["To cook", "To waste food", "To plant seeds"]), + ("The ball is in your court", "It is your turn to take action", ["Playing tennis", "Court hearing", "Ball game"]), + ("Under the weather", "Feeling unwell", ["In rain", "Below clouds", "Bad climate"]), + ("Actions speak louder than words", "What you do matters more than what you say", ["Being noisy", "Shouting", "Speaking loudly"]), + ("Beat around the bush", "To avoid the main topic", ["Gardening", "Playing in bush", "Walking in forest"]), + ("Burning bridges", "Destroying relationships", ["Arson", "Building fire", "Demolition"]), + ("Every cloud has a silver lining", "Good things come after bad", ["Weather forecast", "Cloud watching", "Silver mining"]), + ("Keep your chin up", "Stay positive", ["Posture advice", "Exercise tip", "Looking upward"]), + ("Back to the drawing board", "Start over", ["Art class", "Going backwards", "Drawing pictures"]), + ("Barking up the wrong tree", "Making a wrong assumption", ["Disturbing a dog", "Climbing trees", "Forest activity"]), +] + +# ============ GENERATORS ============ + +def gen_synonyms(conn, count=2500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Vocabulary", "Synonyms", "Choose synonym") + if not qtid: return questions + for _ in range(count): + word, syn, wrongs = random.choice(SYNONYMS) + questions.append(make_question(qtid, + f"Choose the synonym of '{word}':", + syn, wrongs, f"'{word}' means '{syn}'", 1)) + return questions + + +def gen_antonyms(conn, count=2500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Vocabulary", "Antonyms", "Choose antonym") + if not qtid: return questions + for _ in range(count): + word, ant = random.choice(ANTONYMS) + other_ants = [a[1] for a in random.sample(ANTONYMS, 3) if a[0] != word][:3] + if len(other_ants) < 3: + other_ants = ["None", "All", "Some"][:3] + questions.append(make_question(qtid, + f"Choose the antonym of '{word}':", + ant, other_ants, f"Opposite of '{word}' is '{ant}'", 1)) + return questions + + +def gen_one_word(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Vocabulary", "One Word Substitution", "Find one word for phrase") + if not qtid: return questions + for _ in range(count): + phrase, word, wrongs = random.choice(ONE_WORD_SUBS) + questions.append(make_question(qtid, + f"One word for: '{phrase}'", + word, wrongs, f"'{phrase}' = {word}", 1)) + return questions + + +def gen_idioms(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Vocabulary", "Idioms and Phrases", "Meaning of idiom") + if not qtid: return questions + for _ in range(count): + idiom, meaning, wrongs = random.choice(IDIOMS) + questions.append(make_question(qtid, + f"What does the idiom '{idiom}' mean?", + meaning, wrongs, f"'{idiom}' = {meaning}", 1)) + return questions + + +def gen_spelling(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Vocabulary", "Spelling Correction", "Choose correct spelling") + if not qtid: return questions + words = ["Accommodation", "Achievement", "Acknowledge", "Acquaintance", "Aggressive", + "Apparently", "Argument", "Assassination", "Beautiful", "Beginning", + "Believe", "Bureaucracy", "Calendar", "Changeable", "Committed", + "Conscience", "Conscious", "Definitely", "Dilemma", "Disappear", + "Disappoint", "Discipline", "Embarrass", "Environment", "Exaggerate", + "Existence", "Experience", "Fascinate", "February", "Fluorescent", + "Foreign", "Forty", "Government", "Guarantee", "Harass", + "Hierarchy", "Humorous", "Hygiene", "Immediately", "Independent", + "Intelligence", "Jewellery", "Judgement", "Knowledge", "Leisure", + "License", "Maintenance", "Mediterranean", "Millennium", "Necessary", + "Noticeable", "Occasion", "Occurrence", "Parliament", "Perseverance", + "Pneumonia", "Possession", "Privilege", "Pronunciation", "Psychology", + "Questionnaire", "Receive", "Recommend", "Rhythm", "Schedule", + "Separate", "Successful", "Supersede", "Surprise", "Threshold", + "Tomorrow", "Tyranny", "Unnecessary", "Vacuum", "Vegetable", + "Wednesday", "Weird"] + for _ in range(count): + w = random.choice(words) + # Create misspellings + misspells = [] + for _ in range(3): + idx = random.randint(1, len(w) - 2) + chars = list(w) + chars[idx] = random.choice('aeiou') if chars[idx] not in 'aeiou' else random.choice('bcdfg') + m = "".join(chars) + if m != w: + misspells.append(m) + while len(misspells) < 3: + misspells.append(w[:-1] + random.choice('aeioust')) + questions.append(make_question(qtid, + f"Choose the correctly spelled word:", + w, misspells[:3], f"Correct spelling: {w}", 1)) + return questions + + +def gen_tenses(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Grammar", "Tenses", "Fill in correct tense") + if not qtid: return questions + templates = [ + ("She ___ to school every day.", "goes", ["go", "went", "going"], "Simple Present"), + ("They ___ playing football yesterday.", "were", ["was", "are", "is"], "Past Continuous"), + ("He ___ the work by tomorrow.", "will finish", ["finished", "finishes", "finishing"], "Simple Future"), + ("I ___ this book already.", "have read", ["had read", "read", "reading"], "Present Perfect"), + ("She ___ dinner when I arrived.", "was cooking", ["cooked", "cooks", "cooking"], "Past Continuous"), + ("We ___ here since morning.", "have been", ["are", "were", "was"], "Present Perfect Continuous"), + ("The train ___ before we reached.", "had left", ["left", "leaves", "leaving"], "Past Perfect"), + ("By next year, I ___ my degree.", "will have completed", ["complete", "completed", "completing"], "Future Perfect"), + ("He ___ a letter now.", "is writing", ["writes", "wrote", "written"], "Present Continuous"), + ("They ___ the match last week.", "won", ["win", "wins", "winning"], "Simple Past"), + ("She ___ the piano since childhood.", "has been playing", ["plays", "played", "play"], "Present Perfect Continuous"), + ("I ___ you tomorrow.", "will call", ["called", "call", "calling"], "Simple Future"), + ] + for _ in range(count): + q_text, correct, wrongs, tense = random.choice(templates) + questions.append(make_question(qtid, f"Fill in the blank: {q_text}", + correct, wrongs, f"Tense: {tense}", 1)) + return questions + + +def gen_articles(conn, count=1000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Grammar", "Articles", "Fill in correct article") + if not qtid: return questions + templates = [ + ("___ apple a day keeps the doctor away.", "An", ["A", "The", "No article"]), + ("He is ___ honest man.", "an", ["a", "the", "no article"]), + ("___ sun rises in the east.", "The", ["A", "An", "No article"]), + ("She is ___ doctor.", "a", ["an", "the", "no article"]), + ("I saw ___ elephant in the zoo.", "an", ["a", "the", "no article"]), + ("___ Ganges is a holy river.", "The", ["A", "An", "No article"]), + ("He gave me ___ useful tip.", "a", ["an", "the", "no article"]), + ("___ gold is a precious metal.", "No article", ["A", "An", "The"]), + ("She is ___ European.", "a", ["an", "the", "no article"]), + ("I need ___ umbrella.", "an", ["a", "the", "no article"]), + ] + for _ in range(count): + q_text, correct, wrongs = random.choice(templates) + questions.append(make_question(qtid, f"Fill in the correct article: {q_text}", + correct, wrongs, f"Article rule applied", 1)) + return questions + + +def gen_prepositions(conn, count=1000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Grammar", "Prepositions", "Fill in preposition") + if not qtid: return questions + templates = [ + ("The book is ___ the table.", "on", ["in", "at", "by"]), + ("She arrived ___ Monday.", "on", ["in", "at", "by"]), + ("He lives ___ Mumbai.", "in", ["on", "at", "by"]), + ("The meeting is ___ 3 PM.", "at", ["in", "on", "by"]), + ("I have been waiting ___ morning.", "since", ["for", "from", "by"]), + ("She is good ___ mathematics.", "at", ["in", "on", "with"]), + ("He is fond ___ music.", "of", ["with", "in", "at"]), + ("The cat jumped ___ the wall.", "over", ["on", "in", "at"]), + ("She is interested ___ painting.", "in", ["on", "at", "by"]), + ("He walked ___ the park.", "through", ["in", "on", "at"]), + ("They traveled ___ train.", "by", ["in", "on", "with"]), + ("The match starts ___ 5 o'clock.", "at", ["in", "on", "by"]), + ] + for _ in range(count): + q_text, correct, wrongs = random.choice(templates) + questions.append(make_question(qtid, f"Fill in the correct preposition: {q_text}", + correct, wrongs, f"Preposition: {correct}", 1)) + return questions + + +def gen_voice(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Sentence Structure", "Active and Passive Voice", "Convert to passive") + if not qtid: return questions + templates = [ + ("She writes a letter.", "A letter is written by her.", ["A letter was written by her.", "A letter were written by her.", "A letter has written by her."]), + ("He plays cricket.", "Cricket is played by him.", ["Cricket was played by him.", "Cricket were played by him.", "Cricket has played by him."]), + ("They are building a house.", "A house is being built by them.", ["A house was being built by them.", "A house has been built by them.", "A house is built by them."]), + ("She cooked food.", "Food was cooked by her.", ["Food is cooked by her.", "Food has been cooked by her.", "Food was being cooked by her."]), + ("I have finished the work.", "The work has been finished by me.", ["The work was finished by me.", "The work is finished by me.", "The work had been finished by me."]), + ("The teacher teaches the students.", "The students are taught by the teacher.", ["The students were taught by the teacher.", "The students has been taught by the teacher.", "The students is taught by the teacher."]), + ("He will write a book.", "A book will be written by him.", ["A book would be written by him.", "A book shall be written by him.", "A book is written by him."]), + ("Ram killed Ravana.", "Ravana was killed by Ram.", ["Ravana is killed by Ram.", "Ravana has been killed by Ram.", "Ravana were killed by Ram."]), + ] + for _ in range(count): + active, passive, wrongs = random.choice(templates) + questions.append(make_question(qtid, + f"Convert to passive voice: '{active}'", + passive, wrongs, f"Passive: {passive}", 1)) + return questions + + +def gen_direct_indirect(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Sentence Structure", "Direct and Indirect Speech", "Convert to indirect speech") + if not qtid: return questions + templates = [ + ('He said, "I am happy."', 'He said that he was happy.', + ['He said that he is happy.', 'He said that I am happy.', 'He told that he was happy.']), + ('She said, "I will come tomorrow."', 'She said that she would come the next day.', + ['She said that she will come tomorrow.', 'She told she would come next day.', 'She said she will come.']), + ('He asked, "Where do you live?"', 'He asked where I lived.', + ['He asked where do I live.', 'He asked that where I lived.', 'He asked me where I live.']), + ('She said, "I have finished my work."', 'She said that she had finished her work.', + ['She said that she has finished her work.', 'She told she had finished work.', 'She said she finished her work.']), + ('The teacher said, "The Earth revolves around the Sun."', 'The teacher said that the Earth revolves around the Sun.', + ['The teacher said the Earth revolved around the Sun.', 'The teacher told the Earth revolves around Sun.', 'The teacher said Earth revolving around Sun.']), + ] + for _ in range(count): + direct, indirect, wrongs = random.choice(templates) + questions.append(make_question(qtid, + f"Convert to indirect speech: {direct}", + indirect, wrongs, f"Indirect: {indirect}", 1)) + return questions + + +def gen_sentence_improvement(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Sentence Structure", "Sentence Improvement", "Replace underlined part") + if not qtid: return questions + templates = [ + ("He don't know the answer.", "doesn't know", ["don't knows", "didn't knew", "not know"]), + ("She is more taller than her sister.", "taller", ["most taller", "more tall", "tallest"]), + ("I am going to market.", "to the market", ["in market", "for market", "at market"]), + ("He told to me a story.", "told me", ["said to me", "tell me", "telling me"]), + ("Each of the boys have done their work.", "has done his", ["have done his", "has did their", "have done their"]), + ("One should do his duty.", "one's duty", ["their duty", "your duty", "our duty"]), + ("She is knowing the answer.", "knows", ["is know", "was knowing", "has knowing"]), + ("I am having a car.", "have", ["is having", "has", "having"]), + ("He prevented me to go.", "from going", ["for going", "about going", "of going"]), + ("She is elder than me.", "older than I", ["elder than I", "more elder than me", "oldest than me"]), + ] + for _ in range(count): + sentence, correct, wrongs = random.choice(templates) + questions.append(make_question(qtid, + f"Improve the sentence: '{sentence}'", + correct, wrongs, f"Correct: {correct}", 2)) + return questions + + +def gen_error_detection(conn, count=2500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Error Detection", "Spot the Error", "Identify erroneous part") + if not qtid: return questions + templates = [ + ("He go to school daily.", "Part A: 'go' should be 'goes'", ["Part B: 'to' is wrong", "Part C: 'daily' is wrong", "No error"]), + ("She don't like ice cream.", "Part A: 'don't' should be 'doesn't'", ["Part B: 'like' is wrong", "Part C is wrong", "No error"]), + ("The news are good.", "Part A: 'are' should be 'is'", ["Part B: 'good' is wrong", "Part C is wrong", "No error"]), + ("Mathematics are my favourite subject.", "Part A: 'are' should be 'is'", ["Part B is wrong", "Part C is wrong", "No error"]), + ("Each of the students have passed.", "Part B: 'have' should be 'has'", ["Part A is wrong", "Part C is wrong", "No error"]), + ("He is more stronger than me.", "Part A: 'more stronger' should be 'stronger'", ["Part B is wrong", "Part C is wrong", "No error"]), + ("I am agree with you.", "Part A: 'am agree' should be 'agree'", ["Part B is wrong", "Part C is wrong", "No error"]), + ("The furniture are expensive.", "Part A: 'are' should be 'is'", ["Part B is wrong", "Part C is wrong", "No error"]), + ("He gave me a advise.", "Part B: 'advise' should be 'advice'", ["Part A is wrong", "Part C is wrong", "No error"]), + ("She discuss about the matter.", "Part A: 'discuss about' should be 'discussed'", ["Part B is wrong", "Part C is wrong", "No error"]), + ] + for _ in range(count): + sentence, error, wrongs = random.choice(templates) + questions.append(make_question(qtid, + f"Find the error in: '{sentence}'", + error, wrongs, f"Error: {error}", 2)) + return questions + + +def gen_fill_blanks(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Sentence Structure", "Sentence Completion", "Fill in the blank (single)") + if not qtid: return questions + templates = [ + ("Hard work is the key to ___.", "success", ["failure", "defeat", "loss"]), + ("The weather is ___ today.", "pleasant", ["unpleasant", "horrible", "terrible"]), + ("She showed great ___ in the face of danger.", "courage", ["cowardice", "fear", "hesitation"]), + ("The doctor ___ the patient carefully.", "examined", ["ignored", "neglected", "avoided"]), + ("He has a strong ___ for justice.", "passion", ["hatred", "dislike", "disregard"]), + ("The students were ___ to learn the new topic.", "eager", ["reluctant", "unwilling", "indifferent"]), + ("Her ___ attitude made everyone uncomfortable.", "arrogant", ["humble", "polite", "modest"]), + ("The company achieved remarkable ___ this year.", "growth", ["decline", "loss", "failure"]), + ("He is ___ of solving complex problems.", "capable", ["incapable", "unable", "unfit"]), + ("The ___ of the river was very strong after the rain.", "current", ["calm", "stillness", "silence"]), + ("She has an ___ personality that attracts people.", "amiable", ["hostile", "rude", "cold"]), + ("The government ___ new policies for education.", "introduced", ["removed", "cancelled", "deleted"]), + ] + for _ in range(count): + sentence, correct, wrongs = random.choice(templates) + questions.append(make_question(qtid, + f"Fill in the blank: {sentence}", + correct, wrongs, f"Answer: {correct}", 1)) + return questions + + +def gen_sentence_rearrangement(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Sentence Structure", "Sentence Rearrangement", "Arrange sentence parts") + if not qtid: return questions + templates = [ + (["The early bird", "catches", "the worm"], "The early bird catches the worm", + ["catches the worm the early bird", "the worm catches the early bird", "the worm the early bird catches"]), + (["Knowledge is", "better than", "wealth"], "Knowledge is better than wealth", + ["better than wealth knowledge is", "wealth is better than knowledge", "is knowledge better than wealth"]), + (["Honesty", "is the", "best policy"], "Honesty is the best policy", + ["is the best policy honesty", "the best policy is honesty", "policy best is the honesty"]), + (["United we stand", "divided", "we fall"], "United we stand divided we fall", + ["divided we fall united we stand", "we fall divided united we stand", "stand united we divided fall we"]), + (["Practice makes", "a man", "perfect"], "Practice makes a man perfect", + ["a man perfect practice makes", "makes practice a man perfect", "perfect a man makes practice"]), + ] + for _ in range(count): + parts, correct, wrongs = random.choice(templates) + random.shuffle(parts) + questions.append(make_question(qtid, + f"Arrange in correct order: {' / '.join(parts)}", + correct, wrongs, f"Correct order: {correct}", 2)) + return questions + + +def gen_cloze_test(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Comprehension", "Cloze Test", "Fill appropriate word") + if not qtid: return questions + templates = [ + ("Education is the most powerful ___ to change the world.", "weapon", ["weakness", "problem", "barrier"]), + ("The ___ of success is hard work and dedication.", "foundation", ["destruction", "failure", "absence"]), + ("A healthy mind lives in a healthy ___.", "body", ["house", "room", "place"]), + ("Books are the ___ teachers of all time.", "best", ["worst", "slowest", "latest"]), + ("Time and ___ wait for none.", "tide", ["money", "people", "luck"]), + ("Prevention is better than ___.", "cure", ["disease", "medicine", "treatment"]), + ("All that ___ is not gold.", "glitters", ["shines", "sparkles", "reflects"]), + ("A rolling stone gathers no ___.", "moss", ["grass", "dust", "speed"]), + ("Where there is a will, there is a ___.", "way", ["wall", "path", "road"]), + ("Rome was not built in a ___.", "day", ["week", "month", "hour"]), + ] + for _ in range(count): + sentence, correct, wrongs = random.choice(templates) + if isinstance(wrongs, str): # Fix the Rome template + wrongs = [wrongs, "year", "hour"] + questions.append(make_question(qtid, + f"Fill in the blank: {sentence}", + correct, wrongs, f"Answer: {correct}", 1)) + return questions + + +def gen_subject_verb(conn, count=1000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Grammar", "Subject-Verb Agreement", "Choose correct verb") + if not qtid: return questions + templates = [ + ("The team ___ playing well this season.", "is", ["are", "were", "have been"]), + ("Neither the teacher nor the students ___ present.", "were", ["was", "is", "has been"]), + ("Each of the boys ___ given a prize.", "was", ["were", "are", "have been"]), + ("Either you or I ___ going to attend.", "am", ["are", "is", "were"]), + ("The quality of these apples ___ good.", "is", ["are", "were", "have been"]), + ("Bread and butter ___ my favourite breakfast.", "is", ["are", "were", "have been"]), + ("One of my friends ___ from Delhi.", "is", ["are", "were", "have been"]), + ("The news ___ very surprising.", "was", ["were", "are", "have been"]), + ("No news ___ good news.", "is", ["are", "were", "have been"]), + ("Mathematics ___ my favourite subject.", "is", ["are", "were", "have been"]), + ] + for _ in range(count): + sentence, correct, wrongs = random.choice(templates) + questions.append(make_question(qtid, + f"Choose the correct verb: {sentence}", + correct, wrongs, f"Correct: {correct}", 2)) + return questions + + +def generate_all(conn): + """Generate all English Language questions.""" + generators = [ + ("Synonyms", gen_synonyms, 2500), + ("Antonyms", gen_antonyms, 2500), + ("One Word Substitution", gen_one_word, 2000), + ("Idioms & Phrases", gen_idioms, 2000), + ("Spelling", gen_spelling, 1500), + ("Tenses", gen_tenses, 1500), + ("Articles", gen_articles, 1000), + ("Prepositions", gen_prepositions, 1000), + ("Subject-Verb Agreement", gen_subject_verb, 1000), + ("Active/Passive Voice", gen_voice, 1500), + ("Direct/Indirect Speech", gen_direct_indirect, 1500), + ("Sentence Improvement", gen_sentence_improvement, 2000), + ("Error Detection", gen_error_detection, 2500), + ("Fill in Blanks", gen_fill_blanks, 2000), + ("Sentence Rearrangement", gen_sentence_rearrangement, 1500), + ("Cloze Test", gen_cloze_test, 1500), + ] + + total = 0 + all_questions = [] + for name, gen_func, count in generators: + questions = gen_func(conn, count) + all_questions.extend(questions) + print(f" {name}: {len(questions)} questions") + total += len(questions) + + batch_size = 5000 + for i in range(0, len(all_questions), batch_size): + insert_questions_batch(conn, all_questions[i:i+batch_size]) + + print(f" TOTAL English: {total}") + return total + + +if __name__ == '__main__': + conn = get_db() + print("Generating English Language questions...") + generate_all(conn) + conn.close() diff --git a/generators/gk_generator.py b/generators/gk_generator.py new file mode 100644 index 0000000..b8ba7a6 --- /dev/null +++ b/generators/gk_generator.py @@ -0,0 +1,354 @@ +#!/usr/bin/env python3 +""" +General Awareness Question Generator for SSC CGL. +Generates ~20,000+ questions from curated fact banks covering History, Geography, +Polity, Economics, Science, and Static GK. +""" +import random +import sys +import os + +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) +from generators.base import make_question, get_qtid, get_db, insert_questions_batch + +SUBJECT = "General Awareness" + +# ============ FACT BANKS ============ + +ANCIENT_INDIA = [ + ("The Indus Valley Civilization was discovered in", "1921", ["1911", "1931", "1901"]), + ("Harappa was discovered by", "Daya Ram Sahni", ["R.D. Banerji", "John Marshall", "Mortimer Wheeler"]), + ("Mohenjo-daro was discovered by", "R.D. Banerji", ["Daya Ram Sahni", "John Marshall", "Alexander Cunningham"]), + ("The Great Bath was found at", "Mohenjo-daro", ["Harappa", "Lothal", "Kalibangan"]), + ("The founder of the Maurya dynasty was", "Chandragupta Maurya", ["Ashoka", "Bindusara", "Bimbisara"]), + ("Ashoka embraced Buddhism after the battle of", "Kalinga", ["Hydaspes", "Plassey", "Panipat"]), + ("The author of Arthashastra was", "Kautilya", ["Kalidasa", "Banabhatta", "Vishakhadatta"]), + ("Who was the court poet of Chandragupta Vikramaditya?", "Kalidasa", ["Banabhatta", "Harisena", "Amarsimha"]), + ("The capital of the Chola dynasty was", "Thanjavur", ["Madurai", "Kanchipuram", "Hampi"]), + ("The Iron Pillar at Delhi was erected by", "Chandragupta II", ["Ashoka", "Kanishka", "Samudragupta"]), + ("Nalanda University was founded by", "Kumaragupta I", ["Ashoka", "Harsha", "Chandragupta II"]), + ("The Gupta period is known as the", "Golden Age of India", ["Silver Age", "Bronze Age", "Iron Age"]), + ("Sangam literature belongs to", "Tamil Nadu", ["Kerala", "Karnataka", "Andhra Pradesh"]), + ("The first Jain council was held at", "Pataliputra", ["Vaishali", "Rajgir", "Vallabhi"]), + ("Gautama Buddha attained enlightenment at", "Bodh Gaya", ["Sarnath", "Kushinagar", "Lumbini"]), + ("The Ajanta caves are famous for", "Paintings", ["Sculptures", "Architecture", "Inscriptions"]), + ("Who built the Sanchi Stupa?", "Ashoka", ["Kanishka", "Harsha", "Chandragupta"]), + ("The Vedic period is divided into how many parts?", "Two (Early and Later)", ["Three", "Four", "Five"]), + ("The oldest Veda is", "Rigveda", ["Samaveda", "Yajurveda", "Atharvaveda"]), + ("Alexander invaded India in", "326 BC", ["321 BC", "331 BC", "316 BC"]), +] + +MEDIEVAL_INDIA = [ + ("The Delhi Sultanate was established in", "1206", ["1192", "1210", "1290"]), + ("Who founded the Mughal Empire in India?", "Babur", ["Akbar", "Humayun", "Shah Jahan"]), + ("The Battle of Panipat (1526) was fought between", "Babur and Ibrahim Lodi", ["Akbar and Hemu", "Babur and Rana Sanga", "Humayun and Sher Shah"]), + ("Taj Mahal was built by", "Shah Jahan", ["Akbar", "Jahangir", "Aurangzeb"]), + ("Akbar founded the religion", "Din-i-Ilahi", ["Islam", "Sikhism", "Jainism"]), + ("The court language of the Mughals was", "Persian", ["Urdu", "Arabic", "Hindi"]), + ("Who built the Red Fort in Delhi?", "Shah Jahan", ["Akbar", "Aurangzeb", "Babur"]), + ("The last Mughal emperor was", "Bahadur Shah Zafar", ["Aurangzeb", "Shah Alam II", "Muhammad Shah"]), + ("Sher Shah Suri introduced", "Rupee coin", ["Gold coin", "Copper coin", "Silver coin"]), + ("Who built Qutub Minar?", "Qutb-ud-din Aibak", ["Iltutmish", "Alauddin Khilji", "Muhammad Tughlaq"]), + ("The Bhakti movement was started by", "Ramanuja", ["Kabir", "Nanak", "Tulsidas"]), + ("Vijayanagara Empire was founded by", "Harihara and Bukka", ["Krishna Deva Raya", "Rama Raya", "Sangama"]), + ("The capital of Vijayanagara was", "Hampi", ["Thanjavur", "Madurai", "Warangal"]), + ("Who introduced the Mansabdari system?", "Akbar", ["Babur", "Shah Jahan", "Aurangzeb"]), + ("The famous poet Amir Khusrau was associated with", "Alauddin Khilji", ["Akbar", "Babur", "Iltutmish"]), +] + +MODERN_INDIA = [ + ("Who is known as the Father of the Nation?", "Mahatma Gandhi", ["Jawaharlal Nehru", "Subhas Chandra Bose", "B.R. Ambedkar"]), + ("The first war of Indian Independence was in", "1857", ["1847", "1867", "1877"]), + ("Who gave the slogan 'Do or Die'?", "Mahatma Gandhi", ["Subhas Chandra Bose", "Bal Gangadhar Tilak", "Bhagat Singh"]), + ("The Indian National Congress was founded in", "1885", ["1875", "1895", "1905"]), + ("Who founded the Indian National Congress?", "A.O. Hume", ["Dadabhai Naoroji", "Surendranath Banerjee", "W.C. Bonnerjee"]), + ("The Jallianwala Bagh massacre occurred in", "1919", ["1920", "1918", "1921"]), + ("The Salt March took place in", "1930", ["1929", "1931", "1932"]), + ("India gained independence on", "15 August 1947", ["26 January 1947", "15 August 1946", "26 January 1950"]), + ("Who was the first President of India?", "Dr. Rajendra Prasad", ["Dr. S. Radhakrishnan", "Jawaharlal Nehru", "B.R. Ambedkar"]), + ("Who was the first Prime Minister of India?", "Jawaharlal Nehru", ["Sardar Patel", "Dr. Rajendra Prasad", "Mahatma Gandhi"]), + ("The Quit India Movement was launched in", "1942", ["1940", "1943", "1945"]), + ("Who gave the slogan 'Jai Hind'?", "Subhas Chandra Bose", ["Mahatma Gandhi", "Jawaharlal Nehru", "Bhagat Singh"]), + ("The Rowlatt Act was passed in", "1919", ["1918", "1920", "1921"]), + ("The Non-Cooperation Movement was launched in", "1920", ["1919", "1921", "1922"]), + ("Who was known as the Iron Man of India?", "Sardar Vallabhbhai Patel", ["Subhas Chandra Bose", "Bhagat Singh", "Lal Bahadur Shastri"]), + ("The Partition of Bengal took place in", "1905", ["1903", "1907", "1909"]), + ("Who founded the Arya Samaj?", "Swami Dayanand Saraswati", ["Swami Vivekananda", "Raja Ram Mohan Roy", "Ramakrishna"]), + ("The Lucknow Pact was signed in", "1916", ["1915", "1917", "1918"]), + ("Who wrote 'Vande Mataram'?", "Bankim Chandra Chattopadhyay", ["Rabindranath Tagore", "Kazi Nazrul Islam", "Sarojini Naidu"]), + ("Who composed the National Anthem of India?", "Rabindranath Tagore", ["Bankim Chandra", "Sarojini Naidu", "Muhammad Iqbal"]), +] + +GEOGRAPHY_FACTS = [ + ("The largest continent by area is", "Asia", ["Africa", "North America", "Europe"]), + ("The longest river in the world is", "Nile", ["Amazon", "Yangtze", "Mississippi"]), + ("The highest peak in the world is", "Mount Everest", ["K2", "Kangchenjunga", "Lhotse"]), + ("The largest ocean is", "Pacific Ocean", ["Atlantic Ocean", "Indian Ocean", "Arctic Ocean"]), + ("The largest desert in the world is", "Sahara", ["Arabian", "Gobi", "Kalahari"]), + ("The longest river in India is", "Ganga", ["Godavari", "Krishna", "Brahmaputra"]), + ("The highest peak in India is", "Kangchenjunga", ["Nanda Devi", "K2", "Annapurna"]), + ("Which state in India has the longest coastline?", "Gujarat", ["Maharashtra", "Tamil Nadu", "Andhra Pradesh"]), + ("The Tropic of Cancer passes through how many Indian states?", "8", ["6", "7", "9"]), + ("The largest freshwater lake in India is", "Wular Lake", ["Dal Lake", "Chilika Lake", "Loktak Lake"]), + ("Which Indian state is known as the 'Spice Garden of India'?", "Kerala", ["Karnataka", "Tamil Nadu", "Goa"]), + ("The Western Ghats are also known as", "Sahyadri", ["Vindhya", "Aravalli", "Nilgiri"]), + ("The northernmost point of India is", "Indira Col", ["Kanyakumari", "Rann of Kutch", "Indira Point"]), + ("Which river is known as the 'Sorrow of Bengal'?", "Damodar", ["Hooghly", "Teesta", "Mahanadi"]), + ("The largest state in India by area is", "Rajasthan", ["Madhya Pradesh", "Maharashtra", "Uttar Pradesh"]), + ("The Thar Desert is located in", "Rajasthan", ["Gujarat", "Haryana", "Punjab"]), + ("The capital of Arunachal Pradesh is", "Itanagar", ["Shillong", "Imphal", "Kohima"]), + ("Chilika Lake is located in", "Odisha", ["Andhra Pradesh", "Tamil Nadu", "Kerala"]), + ("The Deccan Plateau lies in", "Southern India", ["Northern India", "Eastern India", "Western India"]), + ("The soil best suited for cotton cultivation is", "Black soil", ["Red soil", "Alluvial soil", "Laterite soil"]), +] + +POLITY_FACTS = [ + ("The Constitution of India came into effect on", "26 January 1950", ["15 August 1947", "26 November 1949", "15 August 1950"]), + ("How many Fundamental Rights are there?", "6", ["5", "7", "8"]), + ("Right to Education was added by which amendment?", "86th Amendment", ["42nd Amendment", "44th Amendment", "91st Amendment"]), + ("The Preamble declares India as a", "Sovereign Socialist Secular Democratic Republic", ["Federal Republic", "Parliamentary Republic", "Constitutional Monarchy"]), + ("Who is known as the Father of Indian Constitution?", "Dr. B.R. Ambedkar", ["Jawaharlal Nehru", "Mahatma Gandhi", "Rajendra Prasad"]), + ("The total number of members in Lok Sabha is", "545", ["250", "500", "552"]), + ("Rajya Sabha members are elected for", "6 years", ["5 years", "4 years", "3 years"]), + ("The minimum age to become President of India is", "35 years", ["25 years", "30 years", "40 years"]), + ("The Chief Justice of India is appointed by", "The President", ["The Prime Minister", "The Parliament", "The Law Minister"]), + ("Which Article deals with the Right to Equality?", "Article 14", ["Article 19", "Article 21", "Article 32"]), + ("Article 21 deals with", "Right to Life and Personal Liberty", ["Right to Freedom", "Right to Equality", "Right against Exploitation"]), + ("The Directive Principles are in which Part of the Constitution?", "Part IV", ["Part III", "Part V", "Part VI"]), + ("How many schedules are there in the Indian Constitution?", "12", ["8", "10", "14"]), + ("The Vice President is the ex-officio Chairman of", "Rajya Sabha", ["Lok Sabha", "Parliament", "NITI Aayog"]), + ("Emergency provisions are in which Article?", "Article 352", ["Article 356", "Article 360", "Article 370"]), + ("The 73rd Amendment is related to", "Panchayati Raj", ["Municipal Corporation", "Fundamental Rights", "DPSP"]), + ("Who appoints the Governor of a state?", "The President", ["The Prime Minister", "The Chief Minister", "The Parliament"]), + ("The Finance Commission is appointed every", "5 years", ["3 years", "4 years", "6 years"]), + ("Judicial review is the power of", "Supreme Court", ["Parliament", "President", "Prime Minister"]), + ("The CAG is appointed by", "The President", ["The Prime Minister", "The Parliament", "The Finance Minister"]), +] + +ECONOMICS_FACTS = [ + ("The Reserve Bank of India was established in", "1935", ["1947", "1950", "1921"]), + ("The current GST council is chaired by", "Union Finance Minister", ["Prime Minister", "RBI Governor", "Revenue Secretary"]), + ("Which Five Year Plan focused on rapid industrialization?", "Second Five Year Plan", ["First Plan", "Third Plan", "Fourth Plan"]), + ("NITI Aayog was established in", "2015", ["2014", "2016", "2017"]), + ("NITI Aayog replaced", "Planning Commission", ["Finance Commission", "UGC", "UPSC"]), + ("GDP stands for", "Gross Domestic Product", ["Grand Domestic Product", "General Domestic Product", "Gross Development Product"]), + ("The fiscal year in India starts from", "April 1", ["January 1", "March 1", "July 1"]), + ("WTO was established in", "1995", ["1947", "1991", "2000"]), + ("IMF headquarters is in", "Washington D.C.", ["New York", "Geneva", "London"]), + ("World Bank headquarters is in", "Washington D.C.", ["New York", "Geneva", "Paris"]), + ("BRICS includes India, Brazil, Russia, China and", "South Africa", ["Sri Lanka", "Singapore", "Saudi Arabia"]), + ("National income is calculated by", "Central Statistics Office", ["RBI", "NITI Aayog", "Finance Ministry"]), + ("The first bank in India was", "Bank of Hindustan", ["State Bank of India", "Bank of Bombay", "RBI"]), + ("SBI was formed from", "Imperial Bank of India", ["Bank of Bengal", "Bank of Bombay", "Bank of Madras"]), + ("Repo rate is the rate at which", "RBI lends to commercial banks", ["Banks lend to public", "Government borrows", "FDI flows"]), + ("CRR stands for", "Cash Reserve Ratio", ["Central Reserve Ratio", "Cash Recovery Rate", "Credit Reserve Ratio"]), + ("The currency of Japan is", "Yen", ["Yuan", "Won", "Baht"]), + ("Which organization gives the 'Ease of Doing Business' ranking?", "World Bank", ["IMF", "WTO", "UN"]), + ("Make in India was launched in", "2014", ["2015", "2016", "2013"]), + ("Digital India was launched in", "2015", ["2014", "2016", "2017"]), +] + +SCIENCE_FACTS = [ + ("The SI unit of force is", "Newton", ["Joule", "Watt", "Pascal"]), + ("The speed of light is approximately", "3 Ɨ 10āø m/s", ["3 Ɨ 10ā¶ m/s", "3 Ɨ 10Ā¹ā° m/s", "3 Ɨ 10āµ m/s"]), + ("The chemical formula of water is", "Hā‚‚O", ["Hā‚‚Oā‚‚", "HOā‚‚", "Hā‚ƒO"]), + ("Photosynthesis occurs in", "Chloroplast", ["Mitochondria", "Ribosome", "Nucleus"]), + ("The powerhouse of the cell is", "Mitochondria", ["Nucleus", "Ribosome", "Chloroplast"]), + ("The hardest natural substance is", "Diamond", ["Quartz", "Topaz", "Ruby"]), + ("The chemical symbol for gold is", "Au", ["Ag", "Fe", "Go"]), + ("Blood is purified in", "Kidneys", ["Liver", "Heart", "Lungs"]), + ("The largest organ of the human body is", "Skin", ["Liver", "Brain", "Heart"]), + ("The total number of bones in an adult human body is", "206", ["208", "204", "210"]), + ("Vitamin C deficiency causes", "Scurvy", ["Rickets", "Beriberi", "Night blindness"]), + ("Vitamin D deficiency causes", "Rickets", ["Scurvy", "Beriberi", "Pellagra"]), + ("The gas responsible for global warming is", "Carbon dioxide", ["Oxygen", "Nitrogen", "Hydrogen"]), + ("Sound travels fastest in", "Solids", ["Liquids", "Gases", "Vacuum"]), + ("The pH of pure water is", "7", ["5", "8", "6"]), + ("Newton's first law is also known as", "Law of Inertia", ["Law of Acceleration", "Law of Action-Reaction", "Law of Gravity"]), + ("The center of an atom is called", "Nucleus", ["Electron", "Proton", "Neutron"]), + ("Insulin is produced by", "Pancreas", ["Liver", "Kidney", "Thyroid"]), + ("The boiling point of water is", "100Ā°C", ["90Ā°C", "110Ā°C", "120Ā°C"]), + ("The chemical formula of common salt is", "NaCl", ["KCl", "NaOH", "HCl"]), + ("The study of fungi is called", "Mycology", ["Zoology", "Botany", "Virology"]), + ("The gas used in fire extinguishers is", "COā‚‚", ["Oā‚‚", "Nā‚‚", "Hā‚‚"]), + ("The lightest gas is", "Hydrogen", ["Helium", "Oxygen", "Nitrogen"]), + ("The element with atomic number 1 is", "Hydrogen", ["Helium", "Lithium", "Carbon"]), + ("Malaria is caused by", "Plasmodium", ["Bacteria", "Virus", "Fungus"]), + ("The human heart has how many chambers?", "4", ["2", "3", "5"]), + ("The instrument used to measure atmospheric pressure is", "Barometer", ["Thermometer", "Hygrometer", "Anemometer"]), + ("Who discovered Penicillin?", "Alexander Fleming", ["Louis Pasteur", "Edward Jenner", "Robert Koch"]), + ("The study of earthquake is called", "Seismology", ["Geology", "Volcanology", "Meteorology"]), + ("DNA stands for", "Deoxyribonucleic Acid", ["Deoxyribose Nucleic Acid", "Dinucleic Acid", "Deoxyribo Amino Acid"]), +] + +COMPUTER_FACTS = [ + ("The full form of CPU is", "Central Processing Unit", ["Central Program Unit", "Computer Processing Unit", "Central Process Utility"]), + ("RAM stands for", "Random Access Memory", ["Read Access Memory", "Random Alloc Memory", "Read All Memory"]), + ("The father of computers is", "Charles Babbage", ["Alan Turing", "John von Neumann", "Tim Berners-Lee"]), + ("HTML stands for", "HyperText Markup Language", ["HyperText Machine Language", "High Text Markup Language", "Hyper Transfer Markup Language"]), + ("Which shortcut key is used to copy?", "Ctrl + C", ["Ctrl + V", "Ctrl + X", "Ctrl + Z"]), + ("Which shortcut key is used to undo?", "Ctrl + Z", ["Ctrl + Y", "Ctrl + X", "Ctrl + C"]), + ("The brain of the computer is", "CPU", ["RAM", "Hard Disk", "Monitor"]), + ("1 KB equals", "1024 bytes", ["1000 bytes", "512 bytes", "2048 bytes"]), + ("An IP address is used to", "Identify a device on a network", ["Store data", "Display web pages", "Send emails"]), + ("HTTP stands for", "HyperText Transfer Protocol", ["High Text Transfer Protocol", "Hyper Transfer Text Protocol", "HyperText Transport Protocol"]), + ("The extension of a Word document is", ".docx", [".xlsx", ".pptx", ".pdf"]), + ("Which software is used for spreadsheets?", "MS Excel", ["MS Word", "MS PowerPoint", "MS Access"]), + ("A computer virus is a", "Malicious software program", ["Hardware defect", "Network issue", "Browser plugin"]), + ("Wi-Fi stands for", "Wireless Fidelity", ["Wireless Finder", "Wide Fidelity", "Wired Fidelity"]), + ("The first search engine on the internet was", "Archie", ["Google", "Yahoo", "Bing"]), + ("URL stands for", "Uniform Resource Locator", ["Universal Resource Link", "Uniform Retrieval Locator", "Universal Resource Locator"]), + ("LAN stands for", "Local Area Network", ["Large Area Network", "Long Access Network", "Local Access Network"]), + ("Which key is used to refresh a web page?", "F5", ["F1", "F2", "F12"]), + ("The default file extension for Excel is", ".xlsx", [".docx", ".pptx", ".csv"]), + ("Phishing is a type of", "Cyber fraud", ["Computer virus", "Software update", "Network protocol"]), +] + +STATIC_GK = [ + ("The national bird of India is", "Peacock", ["Sparrow", "Parrot", "Eagle"]), + ("The national animal of India is", "Tiger", ["Lion", "Elephant", "Leopard"]), + ("The national flower of India is", "Lotus", ["Rose", "Jasmine", "Sunflower"]), + ("The national game of India is", "Hockey", ["Cricket", "Football", "Badminton"]), + ("The national fruit of India is", "Mango", ["Apple", "Banana", "Guava"]), + ("The national river of India is", "Ganga", ["Yamuna", "Godavari", "Brahmaputra"]), + ("India's national currency is", "Indian Rupee", ["Dollar", "Pound", "Euro"]), + ("World Environment Day is celebrated on", "June 5", ["March 22", "April 22", "October 16"]), + ("International Women's Day is observed on", "March 8", ["February 14", "May 1", "June 21"]), + ("World Health Day is celebrated on", "April 7", ["March 7", "May 7", "June 7"]), + ("Teachers' Day in India is celebrated on", "September 5", ["November 14", "October 2", "January 26"]), + ("Children's Day in India is celebrated on", "November 14", ["September 5", "October 2", "January 26"]), + ("Republic Day is celebrated on", "January 26", ["August 15", "October 2", "November 14"]), + ("Who wrote the book 'Wings of Fire'?", "A.P.J. Abdul Kalam", ["Jawaharlal Nehru", "Mahatma Gandhi", "R.K. Narayan"]), + ("Who wrote 'Discovery of India'?", "Jawaharlal Nehru", ["Mahatma Gandhi", "Rabindranath Tagore", "S. Radhakrishnan"]), + ("The Nobel Prize for Literature was won by Rabindranath Tagore in", "1913", ["1910", "1920", "1930"]), + ("The Olympic Games are held every", "4 years", ["2 years", "3 years", "5 years"]), + ("The headquarters of UN is in", "New York", ["Geneva", "London", "Washington D.C."]), + ("Who was the first Indian woman to win an Olympic medal?", "Karnam Malleswari", ["P.T. Usha", "Saina Nehwal", "Mary Kom"]), + ("The Booker Prize is associated with", "Literature", ["Science", "Peace", "Economics"]), + ("The Grammy Award is associated with", "Music", ["Films", "Literature", "Sports"]), + ("The first Indian satellite was", "Aryabhata", ["Bhaskara", "INSAT-1A", "Rohini"]), + ("ISRO headquarters is in", "Bengaluru", ["Chennai", "Hyderabad", "New Delhi"]), + ("Who was the first Indian in space?", "Rakesh Sharma", ["Kalpana Chawla", "Sunita Williams", "Ravish Malhotra"]), + ("The Bharat Ratna is the highest", "Civilian award", ["Military award", "Sports award", "Literary award"]), +] + +GOVT_SCHEMES = [ + ("Swachh Bharat Mission was launched in", "2014", ["2015", "2016", "2013"]), + ("Pradhan Mantri Jan Dhan Yojana provides", "Bank accounts for all", ["Free healthcare", "Education scholarship", "Housing"]), + ("Ayushman Bharat scheme provides", "Health insurance coverage", ["Bank accounts", "Education", "Housing"]), + ("PM Kisan scheme provides", "ā‚¹6000 per year to farmers", ["Free seeds", "Loan waiver", "Insurance"]), + ("Beti Bachao Beti Padhao focuses on", "Girl child welfare and education", ["Boy child education", "Senior citizens", "Farmers"]), + ("Start-up India was launched in", "2016", ["2015", "2017", "2014"]), + ("Skill India Mission aims at", "Training youth in skills", ["Providing jobs", "Building schools", "Health camps"]), + ("MUDRA scheme provides", "Loans for small businesses", ["Education loans", "Home loans", "Car loans"]), + ("Ujjwala Yojana provides", "Free LPG connections", ["Free electricity", "Free water", "Free internet"]), + ("Atal Pension Yojana is for", "Retirement pension for unorganized sector", ["Health insurance", "Education", "Housing"]), +] + +SPORTS_FACTS = [ + ("The Cricket World Cup 2023 was held in", "India", ["England", "Australia", "South Africa"]), + ("The FIFA World Cup 2022 was held in", "Qatar", ["Russia", "Brazil", "Japan"]), + ("The Ranji Trophy is associated with", "Cricket", ["Football", "Hockey", "Tennis"]), + ("The Davis Cup is associated with", "Tennis", ["Cricket", "Football", "Badminton"]), + ("The Thomas Cup is associated with", "Badminton", ["Tennis", "Table Tennis", "Cricket"]), + ("The Durand Cup is the oldest football tournament in", "Asia", ["Europe", "Africa", "South America"]), + ("Wimbledon is played on", "Grass court", ["Clay court", "Hard court", "Carpet court"]), + ("A marathon race covers a distance of", "42.195 km", ["40 km", "45 km", "50 km"]), + ("The term 'Grand Slam' is used in", "Tennis", ["Cricket", "Football", "Hockey"]), + ("How many players are there in a cricket team?", "11", ["9", "13", "15"]), + ("How many players are there in a football team?", "11", ["9", "13", "15"]), + ("The term 'Checkmate' is used in", "Chess", ["Cricket", "Football", "Hockey"]), + ("The Summer Olympics 2024 was held in", "Paris", ["Tokyo", "Los Angeles", "London"]), + ("Who holds the record for most centuries in international cricket?", "Sachin Tendulkar", ["Virat Kohli", "Ricky Ponting", "Kumar Sangakkara"]), + ("The Dronacharya Award is given to", "Sports coaches", ["Players", "Scientists", "Teachers"]), +] + + +def _generate_from_facts(conn, facts, subtopic, topic, qtype_name, multiplier=3): + """Generate questions from a fact bank with variations.""" + questions = [] + qtid = get_qtid(conn, SUBJECT, subtopic, topic, qtype_name) + if not qtid: + return questions + for _ in range(len(facts) * multiplier): + q_text, correct, wrongs = random.choice(facts) + difficulty = random.choice([1, 1, 2]) + questions.append(make_question(qtid, q_text, correct, wrongs, f"Answer: {correct}", difficulty)) + return questions + + +def gen_history(conn, count_per=600): + q = [] + q.extend(_generate_from_facts(conn, ANCIENT_INDIA, "History", "Ancient India", "Who/What/When", 50)) + q.extend(_generate_from_facts(conn, MEDIEVAL_INDIA, "History", "Medieval India", "Who/What/When", 50)) + q.extend(_generate_from_facts(conn, MODERN_INDIA, "History", "Modern India", "Freedom fighter identification", 50)) + return q + + +def gen_geography(conn, count=2000): + return _generate_from_facts(conn, GEOGRAPHY_FACTS, "Geography", "Indian Geography", "River system", 130) + + +def gen_polity(conn, count=2000): + return _generate_from_facts(conn, POLITY_FACTS, "Indian Polity", "Indian Constitution", "Article identification", 130) + + +def gen_economics(conn, count=2000): + return _generate_from_facts(conn, ECONOMICS_FACTS, "Economics", "Indian Economy Basics", "Economic indicator", 130) + + +def gen_science(conn, count=3000): + return _generate_from_facts(conn, SCIENCE_FACTS, "Science", "Physics", "Law/principle identification", 135) + + +def gen_computer(conn, count=2000): + return _generate_from_facts(conn, COMPUTER_FACTS, "Science", "Computer Awareness", "Term definition", 100) + + +def gen_static_gk(conn, count=2000): + return _generate_from_facts(conn, STATIC_GK, "Static GK", "National Symbols and Firsts", "Identify symbol", 80) + + +def gen_schemes(conn, count=1000): + return _generate_from_facts(conn, GOVT_SCHEMES, "Economics", "Government Schemes", "Scheme objective", 100) + + +def gen_sports(conn, count=1000): + return _generate_from_facts(conn, SPORTS_FACTS, "Static GK", "Sports", "Trophy-sport", 70) + + +def generate_all(conn): + """Generate all General Awareness questions.""" + generators = [ + ("History", gen_history), + ("Geography", gen_geography), + ("Polity", gen_polity), + ("Economics", gen_economics), + ("Science", gen_science), + ("Computer Awareness", gen_computer), + ("Static GK", gen_static_gk), + ("Govt Schemes", gen_schemes), + ("Sports", gen_sports), + ] + + total = 0 + all_questions = [] + for name, gen_func in generators: + questions = gen_func(conn) + all_questions.extend(questions) + print(f" {name}: {len(questions)} questions") + total += len(questions) + + batch_size = 5000 + for i in range(0, len(all_questions), batch_size): + insert_questions_batch(conn, all_questions[i:i+batch_size]) + + print(f" TOTAL General Awareness: {total}") + return total + + +if __name__ == '__main__': + conn = get_db() + print("Generating General Awareness questions...") + generate_all(conn) + conn.close() diff --git a/generators/quant_generator.py b/generators/quant_generator.py new file mode 100644 index 0000000..a598552 --- /dev/null +++ b/generators/quant_generator.py @@ -0,0 +1,721 @@ +#!/usr/bin/env python3 +""" +Quantitative Aptitude Question Generator for SSC CGL. +Generates ~30,000 template-based math questions across all topics. +""" +import random +import math +import sys +import os + +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) +from generators.base import make_question, get_qtid, nearby_wrong, nearby_wrong_float, get_db, insert_questions_batch + +SUBJECT = "Quantitative Aptitude" + + +def gen_number_system(conn, count=800): + questions = [] + # Unit digit questions + qtid = get_qtid(conn, SUBJECT, "Arithmetic", "Number System", "Unit digit") + if qtid: + for _ in range(count // 4): + base = random.randint(2, 99) + exp = random.randint(10, 200) + unit = pow(base, exp, 10) + q = make_question(qtid, + f"What is the unit digit of {base}^{exp}?", + str(unit), nearby_wrong(unit, 4), + f"Unit digit of {base}^{exp} = {unit}", random.choice([1,1,2])) + questions.append(q) + + # Divisibility + qtid = get_qtid(conn, SUBJECT, "Arithmetic", "Number System", "Divisibility test") + if qtid: + divs = [2, 3, 4, 5, 6, 7, 8, 9, 11] + for _ in range(count // 4): + d = random.choice(divs) + num = random.randint(100, 9999) * d + q = make_question(qtid, + f"Which of the following numbers is divisible by {d}?", + str(num), [str(num + random.randint(1, d-1)) for _ in range(3)], + f"{num} Ć· {d} = {num//d}", 1) + questions.append(q) + + # Remainder + qtid = get_qtid(conn, SUBJECT, "Arithmetic", "Number System", "Remainder problems") + if qtid: + for _ in range(count // 4): + divisor = random.randint(3, 20) + quotient = random.randint(10, 200) + remainder = random.randint(0, divisor - 1) + num = divisor * quotient + remainder + q = make_question(qtid, + f"What is the remainder when {num} is divided by {divisor}?", + str(remainder), nearby_wrong(remainder, max(3, divisor)), + f"{num} = {divisor} Ɨ {quotient} + {remainder}", 1) + questions.append(q) + + # Find the value + qtid = get_qtid(conn, SUBJECT, "Arithmetic", "Number System", "Find the value") + if qtid: + for _ in range(count // 4): + a, b = random.randint(10, 99), random.randint(10, 99) + ops = [(f"{a} Ɨ {b}", a*b), (f"{a}Ā² - {b}Ā²", a*a - b*b), + (f"{a}Ā² + {b}Ā²", a*a + b*b)] + expr, ans = random.choice(ops) + q = make_question(qtid, f"Find the value of {expr}.", + str(ans), nearby_wrong(ans), + f"{expr} = {ans}", random.choice([1,2])) + questions.append(q) + return questions + + +def gen_hcf_lcm(conn, count=500): + questions = [] + qtid_hcf = get_qtid(conn, SUBJECT, "Arithmetic", "HCF and LCM", "Find HCF") + qtid_lcm = get_qtid(conn, SUBJECT, "Arithmetic", "HCF and LCM", "Find LCM") + qtid_word = get_qtid(conn, SUBJECT, "Arithmetic", "HCF and LCM", "Word problems on HCF/LCM") + + for _ in range(count // 3): + a, b = random.randint(10, 200), random.randint(10, 200) + h = math.gcd(a, b) + l = (a * b) // h + if qtid_hcf: + questions.append(make_question(qtid_hcf, + f"Find the HCF of {a} and {b}.", str(h), nearby_wrong(h), + f"HCF({a}, {b}) = {h}", 1)) + if qtid_lcm: + questions.append(make_question(qtid_lcm, + f"Find the LCM of {a} and {b}.", str(l), nearby_wrong(l), + f"LCM({a}, {b}) = {l}", 1)) + if qtid_word: + for _ in range(count // 3): + h = random.randint(5, 30) + m1, m2 = random.randint(2, 6), random.randint(2, 6) + a, b = h * m1, h * m2 + questions.append(make_question(qtid_word, + f"Two ropes of lengths {a} cm and {b} cm are to be cut into pieces of equal length. What is the maximum length of each piece?", + str(h) + " cm", [str(h+i) + " cm" for i in [1, 2, -1]], + f"HCF({a}, {b}) = {h} cm", 1)) + return questions + + +def gen_simplification(conn, count=600): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Arithmetic", "Simplification", "Simplify expression") + if not qtid: + return questions + for _ in range(count): + a, b, c = random.randint(2, 50), random.randint(2, 50), random.randint(1, 30) + templates = [ + (f"{a} + {b} Ɨ {c}", a + b * c), + (f"{a} Ɨ {b} - {c}", a * b - c), + (f"({a} + {b}) Ɨ {c}", (a + b) * c), + (f"{a}Ā² - {b} Ɨ {c}", a*a - b * c), + (f"{a} + {b}Ā² - {c}", a + b*b - c), + ] + expr, ans = random.choice(templates) + questions.append(make_question(qtid, f"Simplify: {expr}", + str(ans), nearby_wrong(ans), f"{expr} = {ans}", random.choice([1,1,2]))) + return questions + + +def gen_percentage(conn, count=2000): + questions = [] + # Basic percentage + qtid = get_qtid(conn, SUBJECT, "Percentage", "Basic Percentage", "Find X% of Y") + if qtid: + for _ in range(count // 4): + pct = random.choice([5, 10, 12, 15, 16, 20, 25, 30, 33, 40, 50, 60, 75]) + val = random.randint(50, 5000) + ans = val * pct / 100 + if ans == int(ans): + ans = int(ans) + questions.append(make_question(qtid, + f"What is {pct}% of {val}?", str(ans), nearby_wrong(ans), + f"{pct}% of {val} = {val} Ɨ {pct}/100 = {ans}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Percentage", "Basic Percentage", "What percent is X of Y") + if qtid: + for _ in range(count // 4): + total = random.randint(50, 1000) + part = random.randint(1, total) + pct = round(part * 100 / total, 2) + questions.append(make_question(qtid, + f"What percentage is {part} of {total}?", str(pct) + "%", + [str(round(pct + random.uniform(-10, 10), 2)) + "%" for _ in range(3)], + f"{part}/{total} Ɨ 100 = {pct}%", 1)) + + qtid = get_qtid(conn, SUBJECT, "Percentage", "Basic Percentage", "Percentage change") + if qtid: + for _ in range(count // 4): + old = random.randint(100, 5000) + change = random.randint(5, 50) + direction = random.choice(["increased", "decreased"]) + new_val = old + old * change // 100 if direction == "increased" else old - old * change // 100 + questions.append(make_question(qtid, + f"If a value {direction} from {old} to {new_val}, what is the percentage change?", + str(change) + "%", [str(change + i) + "%" for i in [2, -3, 5]], + f"Change = {abs(new_val-old)}/{old} Ɨ 100 = {change}%", 1)) + + # Successive percentage + qtid = get_qtid(conn, SUBJECT, "Percentage", "Successive Percentage", "Net percentage change") + if qtid: + for _ in range(count // 4): + p1, p2 = random.randint(5, 40), random.randint(5, 40) + net = round(p1 + p2 + p1 * p2 / 100, 2) + questions.append(make_question(qtid, + f"If a price increases by {p1}% and then by {p2}%, what is the net percentage increase?", + str(net) + "%", nearby_wrong_float(net), + f"Net = {p1} + {p2} + ({p1}Ɨ{p2})/100 = {net}%", 2)) + return questions + + +def gen_profit_loss(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Profit and Loss", "Basic Profit and Loss", "Find profit/loss percentage") + if qtid: + for _ in range(count // 3): + cp = random.randint(100, 5000) + margin = random.randint(5, 50) + is_profit = random.choice([True, False]) + sp = cp + cp * margin // 100 if is_profit else cp - cp * margin // 100 + word = "profit" if is_profit else "loss" + questions.append(make_question(qtid, + f"An article bought for ā‚¹{cp} is sold for ā‚¹{sp}. Find the {word} percentage.", + str(margin) + "%", [str(margin + i) + "%" for i in [2, -3, 5]], + f"{word.title()} = {abs(sp-cp)}/{cp} Ɨ 100 = {margin}%", 1)) + + qtid = get_qtid(conn, SUBJECT, "Profit and Loss", "Discount and Marked Price", "Find selling price after discount") + if qtid: + for _ in range(count // 3): + mp = random.randint(200, 10000) + d = random.choice([5, 10, 15, 20, 25, 30, 40, 50]) + sp = mp - mp * d // 100 + questions.append(make_question(qtid, + f"The marked price of an article is ā‚¹{mp}. If a discount of {d}% is given, find the selling price.", + f"ā‚¹{sp}", [f"ā‚¹{sp + i*10}" for i in [1, -2, 3]], + f"SP = {mp} - {d}% of {mp} = ā‚¹{sp}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Profit and Loss", "Discount and Marked Price", "Find single equivalent discount") + if qtid: + for _ in range(count // 3): + d1, d2 = random.choice([10,15,20,25,30]), random.choice([5,10,15,20]) + eq = round(d1 + d2 - d1 * d2 / 100, 2) + questions.append(make_question(qtid, + f"Find the single equivalent discount for successive discounts of {d1}% and {d2}%.", + str(eq) + "%", nearby_wrong_float(eq), + f"Equivalent = {d1} + {d2} - ({d1}Ɨ{d2})/100 = {eq}%", 2)) + return questions + + +def gen_ratio(conn, count=1800): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Ratio and Proportion", "Basic Ratio", "Divide in given ratio") + if qtid: + for _ in range(count // 4): + a, b = random.randint(1, 10), random.randint(1, 10) + total = (a + b) * random.randint(10, 100) + part_a, part_b = total * a // (a + b), total * b // (a + b) + questions.append(make_question(qtid, + f"Divide ā‚¹{total} in the ratio {a}:{b}. Find the larger share.", + f"ā‚¹{max(part_a, part_b)}", [f"ā‚¹{max(part_a,part_b) + i*10}" for i in [1,-2,3]], + f"Larger share = {total} Ɨ {max(a,b)}/{a+b} = ā‚¹{max(part_a,part_b)}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Ratio and Proportion", "Mixture and Alligation", "Mean price of mixture") + if qtid: + for _ in range(count // 4): + p1, p2 = random.randint(20, 60), random.randint(60, 120) + q1, q2 = random.randint(1, 10), random.randint(1, 10) + mean = round((p1*q1 + p2*q2) / (q1+q2), 2) + questions.append(make_question(qtid, + f"If {q1} kg of rice at ā‚¹{p1}/kg is mixed with {q2} kg of rice at ā‚¹{p2}/kg, find the price of the mixture per kg.", + f"ā‚¹{mean}", [f"ā‚¹{round(mean+i,2)}" for i in [2,-3,5]], + f"Mean = ({p1}Ɨ{q1} + {p2}Ɨ{q2})/{q1+q2} = ā‚¹{mean}", 2)) + + qtid = get_qtid(conn, SUBJECT, "Ratio and Proportion", "Partnership", "Divide profit among partners") + if qtid: + for _ in range(count // 4): + inv_a = random.randint(1000, 10000) + inv_b = random.randint(1000, 10000) + profit = random.randint(5000, 50000) + share_a = round(profit * inv_a / (inv_a + inv_b)) + questions.append(make_question(qtid, + f"A invests ā‚¹{inv_a} and B invests ā‚¹{inv_b}. Total profit is ā‚¹{profit}. Find A's share.", + f"ā‚¹{share_a}", [f"ā‚¹{share_a + i*100}" for i in [1,-2,3]], + f"A's share = {profit} Ɨ {inv_a}/({inv_a}+{inv_b}) = ā‚¹{share_a}", 2)) + + qtid = get_qtid(conn, SUBJECT, "Ratio and Proportion", "Proportion", "Find fourth proportional") + if qtid: + for _ in range(count // 4): + a, b, c = random.randint(2, 20), random.randint(2, 20), random.randint(2, 20) + d = b * c // a if a != 0 else 1 + if a * d == b * c: + questions.append(make_question(qtid, + f"Find the fourth proportional to {a}, {b}, and {c}.", + str(d), nearby_wrong(d), + f"a:b = c:d ā†’ d = bƗc/a = {b}Ɨ{c}/{a} = {d}", 1)) + return questions + + +def gen_average(conn, count=1200): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Average", "Simple Average", "Find average") + if qtid: + for _ in range(count // 3): + n = random.randint(3, 8) + nums = [random.randint(10, 100) for _ in range(n)] + avg = round(sum(nums) / n, 2) + nums_str = ", ".join(map(str, nums)) + questions.append(make_question(qtid, + f"Find the average of {nums_str}.", + str(avg), nearby_wrong_float(avg), + f"Average = {sum(nums)}/{n} = {avg}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Average", "Simple Average", "Average after adding/removing") + if qtid: + for _ in range(count // 3): + n = random.randint(5, 15) + avg = random.randint(20, 80) + new_val = random.randint(avg + 5, avg + 50) + new_avg = round((avg * n + new_val) / (n + 1), 2) + questions.append(make_question(qtid, + f"The average of {n} numbers is {avg}. When a new number {new_val} is added, what is the new average?", + str(new_avg), nearby_wrong_float(new_avg), + f"New avg = ({avg}Ɨ{n} + {new_val})/{n+1} = {new_avg}", 2)) + + qtid = get_qtid(conn, SUBJECT, "Average", "Age Problems", "Average age of family") + if qtid: + for _ in range(count // 3): + n = random.randint(3, 6) + avg_age = random.randint(20, 40) + baby_age = random.randint(1, 5) + new_avg = round((avg_age * n + baby_age) / (n + 1), 2) + questions.append(make_question(qtid, + f"The average age of {n} members of a family is {avg_age} years. A baby of {baby_age} year(s) is born. Find the new average age.", + str(new_avg) + " years", [str(round(new_avg+i,2)) + " years" for i in [1,-2,3]], + f"New avg = ({avg_age}Ɨ{n} + {baby_age})/{n+1} = {new_avg} years", 1)) + return questions + + +def gen_time_work(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Time and Work", "Basic Time and Work", "Find combined time") + if qtid: + for _ in range(count // 3): + a, b = random.randint(5, 30), random.randint(5, 30) + combined = round(a * b / (a + b), 2) + questions.append(make_question(qtid, + f"A can do a work in {a} days and B can do it in {b} days. In how many days can they do it together?", + str(combined) + " days", [str(round(combined+i,2)) + " days" for i in [1,-2,3]], + f"Together = {a}Ɨ{b}/({a}+{b}) = {combined} days", 2)) + + qtid = get_qtid(conn, SUBJECT, "Time and Work", "Pipes and Cisterns", "Time to fill tank") + if qtid: + for _ in range(count // 3): + a, b = random.randint(5, 30), random.randint(5, 30) + combined = round(a * b / (a + b), 2) + questions.append(make_question(qtid, + f"Two pipes can fill a tank in {a} hours and {b} hours respectively. How long to fill the tank if both are opened?", + str(combined) + " hours", [str(round(combined+i,2)) + " hours" for i in [1,-2,3]], + f"Together = {a}Ɨ{b}/({a}+{b}) = {combined} hours", 2)) + + qtid = get_qtid(conn, SUBJECT, "Time and Work", "Work and Wages", "Divide wages") + if qtid: + for _ in range(count // 3): + da, db = random.randint(5, 20), random.randint(5, 20) + wage = random.randint(1000, 10000) + eff_a, eff_b = 1/da, 1/db + share_a = round(wage * eff_a / (eff_a + eff_b)) + questions.append(make_question(qtid, + f"A can do a work in {da} days and B in {db} days. For a total wage of ā‚¹{wage}, find A's share.", + f"ā‚¹{share_a}", [f"ā‚¹{share_a + i*50}" for i in [1,-2,3]], + f"A's share = ā‚¹{wage} Ɨ (1/{da}) / (1/{da} + 1/{db}) = ā‚¹{share_a}", 2)) + return questions + + +def gen_speed_distance(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Time, Speed and Distance", "Basic Speed and Distance", "Average speed") + if qtid: + for _ in range(count // 4): + s1, s2 = random.randint(20, 80), random.randint(20, 80) + avg = round(2 * s1 * s2 / (s1 + s2), 2) + questions.append(make_question(qtid, + f"A person goes from A to B at {s1} km/h and returns at {s2} km/h. Find the average speed.", + str(avg) + " km/h", [str(round(avg+i,2)) + " km/h" for i in [2,-3,5]], + f"Avg speed = 2Ɨ{s1}Ɨ{s2}/({s1}+{s2}) = {avg} km/h", 2)) + + qtid = get_qtid(conn, SUBJECT, "Time, Speed and Distance", "Trains", "Train passing pole") + if qtid: + for _ in range(count // 4): + length = random.randint(100, 500) + speed_kmh = random.randint(36, 144) + speed_ms = round(speed_kmh * 5 / 18, 2) + time = round(length / speed_ms, 2) + questions.append(make_question(qtid, + f"A train {length}m long passes a pole in {time} seconds. Find its speed in km/h.", + str(speed_kmh) + " km/h", [str(speed_kmh + i) + " km/h" for i in [4,-6,9]], + f"Speed = {length}/{time} m/s = {speed_kmh} km/h", 2)) + + qtid = get_qtid(conn, SUBJECT, "Time, Speed and Distance", "Boats and Streams", "Find speed in still water") + if qtid: + for _ in range(count // 4): + boat = random.randint(10, 30) + stream = random.randint(2, 8) + ds = boat + stream + us = boat - stream + questions.append(make_question(qtid, + f"A boat goes {ds} km/h downstream and {us} km/h upstream. Find speed in still water.", + str(boat) + " km/h", [str(boat + i) + " km/h" for i in [1, -2, 3]], + f"Speed = ({ds}+{us})/2 = {boat} km/h", 1)) + + qtid = get_qtid(conn, SUBJECT, "Time, Speed and Distance", "Basic Speed and Distance", "Find distance") + if qtid: + for _ in range(count // 4): + speed = random.randint(20, 100) + time = random.randint(1, 10) + dist = speed * time + questions.append(make_question(qtid, + f"A car travels at {speed} km/h for {time} hours. Find the distance covered.", + str(dist) + " km", nearby_wrong(dist), + f"Distance = {speed} Ɨ {time} = {dist} km", 1)) + return questions + + +def gen_interest(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Interest", "Simple Interest", "Find SI") + if qtid: + for _ in range(count // 3): + p = random.choice([1000, 2000, 5000, 8000, 10000, 15000, 20000]) + r = random.choice([4, 5, 6, 8, 10, 12, 15]) + t = random.randint(1, 5) + si = p * r * t // 100 + questions.append(make_question(qtid, + f"Find the simple interest on ā‚¹{p} at {r}% per annum for {t} years.", + f"ā‚¹{si}", [f"ā‚¹{si + i*50}" for i in [1,-2,3]], + f"SI = {p}Ɨ{r}Ɨ{t}/100 = ā‚¹{si}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Interest", "Compound Interest", "Find CI") + if qtid: + for _ in range(count // 3): + p = random.choice([1000, 2000, 5000, 10000]) + r = random.choice([5, 10, 15, 20]) + t = random.choice([1, 2, 3]) + amt = round(p * (1 + r/100)**t, 2) + ci = round(amt - p, 2) + questions.append(make_question(qtid, + f"Find the compound interest on ā‚¹{p} at {r}% for {t} year(s).", + f"ā‚¹{ci}", [f"ā‚¹{round(ci+i*20,2)}" for i in [1,-2,3]], + f"CI = {p}(1+{r}/100)^{t} - {p} = ā‚¹{ci}", 2)) + + qtid = get_qtid(conn, SUBJECT, "Interest", "Compound Interest", "Difference between CI and SI") + if qtid: + for _ in range(count // 3): + p = random.choice([1000, 2000, 5000, 10000]) + r = random.choice([5, 10, 15, 20]) + si = p * r * 2 // 100 + ci = round(p * (1 + r/100)**2 - p, 2) + diff = round(ci - si, 2) + questions.append(make_question(qtid, + f"Find the difference between CI and SI on ā‚¹{p} at {r}% for 2 years.", + f"ā‚¹{diff}", [f"ā‚¹{round(diff+i*5,2)}" for i in [1,-2,3]], + f"Diff = PƗ(r/100)Ā² = {p}Ɨ({r}/100)Ā² = ā‚¹{diff}", 2)) + return questions + + +def gen_algebra(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Algebra", "Linear Equations", "Solve for x") + if qtid: + for _ in range(count // 4): + a = random.randint(2, 15) + x = random.randint(1, 30) + b = random.randint(1, 50) + c = a * x + b + questions.append(make_question(qtid, + f"Solve: {a}x + {b} = {c}", + f"x = {x}", [f"x = {x+i}" for i in [1,-2,3]], + f"{a}x = {c} - {b} = {c-b}, x = {x}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Algebra", "Algebraic Identities", "Find value of expression") + if qtid: + for _ in range(count // 4): + a, b = random.randint(2, 20), random.randint(1, 15) + val = a*a + b*b + 2*a*b # (a+b)Ā² + questions.append(make_question(qtid, + f"If a = {a} and b = {b}, find aĀ² + bĀ² + 2ab.", + str(val), nearby_wrong(val), + f"aĀ² + bĀ² + 2ab = (a+b)Ā² = ({a}+{b})Ā² = {val}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Algebra", "Surds and Indices", "Find value") + if qtid: + for _ in range(count // 4): + base = random.randint(2, 10) + exp = random.randint(2, 5) + val = base ** exp + questions.append(make_question(qtid, + f"Find the value of {base}^{exp}.", + str(val), nearby_wrong(val), + f"{base}^{exp} = {val}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Algebra", "Quadratic Equations", "Sum and product of roots") + if qtid: + for _ in range(count // 4): + r1, r2 = random.randint(-10, 10), random.randint(-10, 10) + a = 1 + b = -(r1 + r2) + c = r1 * r2 + s = r1 + r2 + questions.append(make_question(qtid, + f"Find the sum of roots of xĀ² + ({b})x + ({c}) = 0.", + str(s), nearby_wrong(s), + f"Sum = -b/a = {s}", 1)) + return questions + + +def gen_geometry(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Geometry", "Triangles", "Find angle in triangle") + if qtid: + for _ in range(count // 4): + a = random.randint(20, 80) + b = random.randint(20, 160 - a) + c = 180 - a - b + questions.append(make_question(qtid, + f"In a triangle, two angles are {a}Ā° and {b}Ā°. Find the third angle.", + f"{c}Ā°", [f"{c+i}Ā°" for i in [5,-10,15]], + f"Third angle = 180 - {a} - {b} = {c}Ā°", 1)) + + qtid = get_qtid(conn, SUBJECT, "Geometry", "Circles", "Tangent properties") + if qtid: + for _ in range(count // 4): + r = random.randint(3, 20) + d = random.randint(r + 5, r + 30) + tangent = round(math.sqrt(d*d - r*r), 2) + questions.append(make_question(qtid, + f"The radius of a circle is {r} cm and a point is {d} cm from the center. Find the length of the tangent.", + str(tangent) + " cm", [str(round(tangent+i,2)) + " cm" for i in [1,-2,3]], + f"Tangent = āˆš({d}Ā²-{r}Ā²) = {tangent} cm", 2)) + + qtid = get_qtid(conn, SUBJECT, "Geometry", "Coordinate Geometry", "Find distance between points") + if qtid: + for _ in range(count // 4): + x1, y1 = random.randint(-10, 10), random.randint(-10, 10) + x2, y2 = random.randint(-10, 10), random.randint(-10, 10) + dist = round(math.sqrt((x2-x1)**2 + (y2-y1)**2), 2) + questions.append(make_question(qtid, + f"Find the distance between ({x1}, {y1}) and ({x2}, {y2}).", + str(dist), nearby_wrong_float(dist), + f"Distance = āˆš[({x2}-{x1})Ā² + ({y2}-{y1})Ā²] = {dist}", 2)) + + qtid = get_qtid(conn, SUBJECT, "Geometry", "Lines and Angles", "Find angle value") + if qtid: + for _ in range(count // 4): + angle = random.randint(10, 170) + supp = 180 - angle + questions.append(make_question(qtid, + f"Find the supplement of {angle}Ā°.", + f"{supp}Ā°", [f"{supp+i}Ā°" for i in [5,-10,15]], + f"Supplement = 180 - {angle} = {supp}Ā°", 1)) + return questions + + +def gen_mensuration(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Mensuration", "2D Figures", "Find area") + if qtid: + for _ in range(count // 4): + l, w = random.randint(5, 50), random.randint(5, 50) + area = l * w + questions.append(make_question(qtid, + f"Find the area of a rectangle with length {l} cm and width {w} cm.", + f"{area} cmĀ²", [f"{area+i*5} cmĀ²" for i in [1,-2,3]], + f"Area = {l} Ɨ {w} = {area} cmĀ²", 1)) + for _ in range(count // 4): + r = random.randint(3, 25) + area = round(math.pi * r * r, 2) + questions.append(make_question(qtid, + f"Find the area of a circle with radius {r} cm. (Use Ļ€ = 3.14)", + str(round(3.14 * r * r, 2)) + " cmĀ²", + [str(round(3.14 * r * r + i * 5, 2)) + " cmĀ²" for i in [1, -2, 3]], + f"Area = Ļ€rĀ² = 3.14 Ɨ {r}Ā² = {round(3.14*r*r,2)} cmĀ²", 1)) + + qtid = get_qtid(conn, SUBJECT, "Mensuration", "3D Figures", "Find volume") + if qtid: + for _ in range(count // 4): + l, w, h = random.randint(3, 20), random.randint(3, 20), random.randint(3, 20) + vol = l * w * h + questions.append(make_question(qtid, + f"Find the volume of a cuboid with dimensions {l}Ɨ{w}Ɨ{h} cm.", + f"{vol} cmĀ³", [f"{vol+i*10} cmĀ³" for i in [1,-2,3]], + f"Volume = {l}Ɨ{w}Ɨ{h} = {vol} cmĀ³", 1)) + + qtid = get_qtid(conn, SUBJECT, "Mensuration", "3D Figures", "Find surface area") + if qtid: + for _ in range(count // 4): + a = random.randint(3, 20) + sa = 6 * a * a + questions.append(make_question(qtid, + f"Find the total surface area of a cube with side {a} cm.", + f"{sa} cmĀ²", [f"{sa+i*6} cmĀ²" for i in [1,-2,3]], + f"TSA = 6aĀ² = 6Ɨ{a}Ā² = {sa} cmĀ²", 1)) + return questions + + +def gen_trigonometry(conn, count=1500): + questions = [] + trig_vals = {0: {'sin': 0, 'cos': 1, 'tan': 0}, + 30: {'sin': 0.5, 'cos': 0.866, 'tan': 0.577}, + 45: {'sin': 0.707, 'cos': 0.707, 'tan': 1}, + 60: {'sin': 0.866, 'cos': 0.5, 'tan': 1.732}, + 90: {'sin': 1, 'cos': 0, 'tan': 'undefined'}} + + qtid = get_qtid(conn, SUBJECT, "Trigonometry", "Trigonometric Ratios", "Find value of expression") + if qtid: + for _ in range(count // 3): + ang = random.choice([0, 30, 45, 60]) + func = random.choice(['sin', 'cos', 'tan']) + val = trig_vals[ang][func] + if isinstance(val, (int, float)): + questions.append(make_question(qtid, + f"Find the value of {func}({ang}Ā°).", + str(val), nearby_wrong_float(val if val != 0 else 0.5), + f"{func}({ang}Ā°) = {val}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Trigonometry", "Trigonometric Identities", "Find value given condition") + if qtid: + for _ in range(count // 3): + ang = random.choice([30, 45, 60]) + val = trig_vals[ang]['sin']**2 + trig_vals[ang]['cos']**2 + questions.append(make_question(qtid, + f"Find the value of sinĀ²({ang}Ā°) + cosĀ²({ang}Ā°).", + "1", ["0", "2", "0.5"], + f"sinĀ²Īø + cosĀ²Īø = 1 (identity)", 1)) + + qtid = get_qtid(conn, SUBJECT, "Trigonometry", "Heights and Distances", "Find height of tower") + if qtid: + for _ in range(count // 3): + dist = random.randint(20, 100) + ang = random.choice([30, 45, 60]) + height = round(dist * trig_vals[ang]['tan'], 2) if ang != 90 else dist + questions.append(make_question(qtid, + f"From a point {dist}m from the base of a tower, the angle of elevation is {ang}Ā°. Find the height.", + str(height) + " m", [str(round(height+i,2)) + " m" for i in [2,-5,8]], + f"h = {dist} Ɨ tan({ang}Ā°) = {height} m", 2)) + return questions + + +def gen_di(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Data Interpretation", "Table", "Calculate from table") + if qtid: + for _ in range(count // 2): + vals = [random.randint(100, 1000) for _ in range(5)] + total = sum(vals) + avg = round(total / 5, 2) + years = ["2019", "2020", "2021", "2022", "2023"] + table = ", ".join(f"{y}: {v}" for y, v in zip(years, vals)) + questions.append(make_question(qtid, + f"Production (in units) - {table}. Find the total production.", + str(total), nearby_wrong(total), + f"Total = {'+'.join(map(str, vals))} = {total}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Data Interpretation", "Table", "Percentage calculation") + if qtid: + for _ in range(count // 2): + vals = [random.randint(100, 1000) for _ in range(5)] + idx = random.randint(0, 4) + total = sum(vals) + pct = round(vals[idx] * 100 / total, 2) + years = ["2019", "2020", "2021", "2022", "2023"] + table = ", ".join(f"{y}: {v}" for y, v in zip(years, vals)) + questions.append(make_question(qtid, + f"Sales - {table}. What percentage of total sales occurred in {years[idx]}?", + str(pct) + "%", [str(round(pct+i,2)) + "%" for i in [2,-3,5]], + f"{vals[idx]}/{total} Ɨ 100 = {pct}%", 2)) + return questions + + +def gen_statistics(conn, count=800): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Statistics", "Mean, Median and Mode", "Find mean") + if qtid: + for _ in range(count // 3): + n = random.randint(5, 10) + nums = sorted([random.randint(1, 100) for _ in range(n)]) + mean = round(sum(nums) / n, 2) + questions.append(make_question(qtid, + f"Find the mean of: {', '.join(map(str, nums))}", + str(mean), nearby_wrong_float(mean), + f"Mean = {sum(nums)}/{n} = {mean}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Statistics", "Mean, Median and Mode", "Find median") + if qtid: + for _ in range(count // 3): + n = random.choice([5, 7, 9]) + nums = sorted([random.randint(1, 100) for _ in range(n)]) + median = nums[n // 2] + questions.append(make_question(qtid, + f"Find the median of: {', '.join(map(str, nums))}", + str(median), nearby_wrong(median), + f"Sorted: {nums}, Median = {median}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Statistics", "Mean, Median and Mode", "Find mode") + if qtid: + for _ in range(count // 3): + mode_val = random.randint(1, 50) + nums = [mode_val] * 3 + [random.randint(1, 100) for _ in range(4)] + random.shuffle(nums) + questions.append(make_question(qtid, + f"Find the mode of: {', '.join(map(str, nums))}", + str(mode_val), nearby_wrong(mode_val), + f"Mode = {mode_val} (appears most)", 1)) + return questions + + +def generate_all(conn): + """Generate all Quantitative Aptitude questions.""" + generators = [ + ("Number System", gen_number_system, 800), + ("HCF/LCM", gen_hcf_lcm, 500), + ("Simplification", gen_simplification, 600), + ("Percentage", gen_percentage, 2500), + ("Profit & Loss", gen_profit_loss, 2500), + ("Ratio & Proportion", gen_ratio, 2200), + ("Average", gen_average, 1500), + ("Time & Work", gen_time_work, 1800), + ("Speed & Distance", gen_speed_distance, 2500), + ("Interest", gen_interest, 2000), + ("Algebra", gen_algebra, 2500), + ("Geometry", gen_geometry, 2500), + ("Mensuration", gen_mensuration, 2500), + ("Trigonometry", gen_trigonometry, 2000), + ("Data Interpretation", gen_di, 2000), + ("Statistics", gen_statistics, 1200), + ] + + total = 0 + all_questions = [] + for name, gen_func, count in generators: + questions = gen_func(conn, count) + all_questions.extend(questions) + print(f" {name}: {len(questions)} questions") + total += len(questions) + + # Insert in batches + batch_size = 5000 + for i in range(0, len(all_questions), batch_size): + insert_questions_batch(conn, all_questions[i:i+batch_size]) + + print(f" TOTAL Quantitative Aptitude: {total}") + return total + + +if __name__ == '__main__': + conn = get_db() + print("Generating Quantitative Aptitude questions...") + generate_all(conn) + conn.close() diff --git a/generators/reasoning_generator.py b/generators/reasoning_generator.py new file mode 100644 index 0000000..859029b --- /dev/null +++ b/generators/reasoning_generator.py @@ -0,0 +1,510 @@ +#!/usr/bin/env python3 +""" +General Intelligence & Reasoning Question Generator for SSC CGL. +Generates ~25,000 template-based reasoning questions. +""" +import random +import string +import sys +import os + +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) +from generators.base import make_question, get_qtid, nearby_wrong, get_db, insert_questions_batch + +SUBJECT = "General Intelligence and Reasoning" + + +# ============ VERBAL REASONING ============ + +def gen_number_analogy(conn, count=700): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Verbal Reasoning", "Analogy", "Number analogy") + if not qtid: return questions + for _ in range(count): + a = random.randint(2, 20) + ops = [ + (a*a, lambda x: x*x, "square"), + (a*a*a, lambda x: x*x*x, "cube"), + (a*2, lambda x: x*2, "double"), + (a+5, lambda x: x+5, "add 5"), + ] + result_a, func, rule = random.choice(ops) + b = random.randint(2, 20) + while b == a: + b = random.randint(2, 20) + result_b = func(b) + questions.append(make_question(qtid, + f"{a} : {result_a} :: {b} : ?", + str(result_b), nearby_wrong(result_b), + f"Rule: {rule}. {a}ā†’{result_a}, {b}ā†’{result_b}", 1)) + return questions + + +def gen_letter_analogy(conn, count=500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Verbal Reasoning", "Analogy", "Letter analogy") + if not qtid: return questions + for _ in range(count): + shift = random.randint(1, 5) + a = random.randint(0, 20) + pair1 = chr(65+a) + chr(65+a+shift) + b = random.randint(0, 20) + while b == a: + b = random.randint(0, 20) + pair2_q = chr(65+b) + pair2_a = chr(65+b+shift) + wrongs = [chr(65 + (b+shift+i) % 26) for i in [1, 2, -1]] + questions.append(make_question(qtid, + f"{pair1} : {pair2_q}?", + pair2_q + pair2_a, [pair2_q + w for w in wrongs], + f"Shift by {shift}: {pair1} ā†’ {pair2_q}{pair2_a}", 1)) + return questions + + +def gen_classification(conn, count=1500): + questions = [] + # Number classification (odd one out) + qtid = get_qtid(conn, SUBJECT, "Verbal Reasoning", "Classification", "Number classification") + if qtid: + for _ in range(count // 2): + t = random.choice(["even", "odd", "prime", "square"]) + if t == "even": + group = [random.randint(1, 50) * 2 for _ in range(3)] + odd_one = random.randint(1, 50) * 2 + 1 + elif t == "odd": + group = [random.randint(0, 49) * 2 + 1 for _ in range(3)] + odd_one = random.randint(1, 50) * 2 + elif t == "prime": + primes = [2,3,5,7,11,13,17,19,23,29,31,37,41,43,47] + group = random.sample(primes, 3) + odd_one = random.choice([4,6,8,9,10,12,14,15,16,18,20,21,22]) + else: + squares = [1,4,9,16,25,36,49,64,81,100] + group = random.sample(squares, 3) + odd_one = random.choice([2,3,5,6,7,8,10,11,12,13,14,15]) + all_opts = group + [odd_one] + random.shuffle(all_opts) + questions.append(make_question(qtid, + f"Find the odd one out: {', '.join(map(str, all_opts))}", + str(odd_one), [str(x) for x in group], + f"{odd_one} is not {t}", 1)) + + qtid = get_qtid(conn, SUBJECT, "Verbal Reasoning", "Classification", "Word classification") + if qtid: + word_groups = [ + (["Apple", "Mango", "Banana", "Orange"], "Carrot", "Fruits"), + (["Dog", "Cat", "Lion", "Tiger"], "Eagle", "Mammals"), + (["Red", "Blue", "Green", "Yellow"], "Square", "Colors"), + (["Delhi", "Mumbai", "Chennai", "Kolkata"], "India", "Cities"), + (["Pen", "Pencil", "Marker", "Crayon"], "Book", "Writing tools"), + (["Piano", "Guitar", "Violin", "Flute"], "Painting", "Instruments"), + (["January", "March", "May", "July"], "Monday", "Months"), + (["Mercury", "Venus", "Mars", "Jupiter"], "Moon", "Planets"), + (["Nile", "Amazon", "Ganges", "Thames"], "Sahara", "Rivers"), + (["Football", "Cricket", "Tennis", "Hockey"], "Chess", "Outdoor sports"), + ] + for _ in range(count // 2): + group, odd, reason = random.choice(word_groups) + display = random.sample(group[:3], 3) + [odd] + random.shuffle(display) + questions.append(make_question(qtid, + f"Find the odd one out: {', '.join(display)}", + odd, [x for x in display if x != odd][:3], + f"{odd} is not in the category: {reason}", 1)) + return questions + + +def gen_number_series(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Verbal Reasoning", "Number Series", "Find next number") + if not qtid: return questions + for _ in range(count): + series_type = random.choice(["add", "multiply", "square", "alternate", "diff"]) + if series_type == "add": + start = random.randint(1, 50) + d = random.randint(2, 15) + series = [start + i * d for i in range(5)] + ans = start + 5 * d + elif series_type == "multiply": + start = random.randint(1, 5) + r = random.choice([2, 3]) + series = [start * (r ** i) for i in range(5)] + ans = start * (r ** 5) + elif series_type == "square": + start = random.randint(1, 8) + series = [(start + i) ** 2 for i in range(5)] + ans = (start + 5) ** 2 + elif series_type == "alternate": + a, b = random.randint(1, 10), random.randint(1, 10) + series = [] + for i in range(5): + series.append(series[-1] + a if i % 2 == 0 else series[-1] + b) if series else series.append(random.randint(1, 20)) + if i == 0: + continue + if i % 2 == 1: + series[-1] = series[-2] + a + else: + series[-1] = series[-2] + b + ans = series[-1] + (a if len(series) % 2 == 1 else b) + else: # increasing difference + start = random.randint(1, 10) + series = [start] + d = random.randint(1, 5) + for i in range(4): + series.append(series[-1] + d + i) + ans = series[-1] + d + 4 + + series_str = ", ".join(map(str, series)) + questions.append(make_question(qtid, + f"Find the next number in the series: {series_str}, ?", + str(ans), nearby_wrong(ans), + f"Pattern: {series_type}. Next = {ans}", random.choice([1, 2]))) + return questions + + +def gen_coding_decoding(conn, count=2000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Verbal Reasoning", "Coding-Decoding", "Letter coding") + if qtid: + for _ in range(count // 2): + shift = random.randint(1, 5) + word = random.choice(["COME", "GONE", "HELP", "LOVE", "MIND", "PLAY", "ROSE", "SING", "TALK", "WIND", + "BACK", "DEEP", "FAST", "GIRL", "HOME", "JUST", "KING", "LAMP", "NAME", "OPEN"]) + coded = "".join(chr((ord(c) - 65 + shift) % 26 + 65) for c in word) + word2 = random.choice(["BALL", "CAKE", "DARK", "EASY", "FISH", "GOOD", "HAND", "IDOL", "JOKE", "KEEP"]) + coded2 = "".join(chr((ord(c) - 65 + shift) % 26 + 65) for c in word2) + wrongs = [] + for s in [shift+1, shift-1, shift+2]: + wrongs.append("".join(chr((ord(c) - 65 + s) % 26 + 65) for c in word2)) + questions.append(make_question(qtid, + f"If {word} is coded as {coded}, then {word2} is coded as?", + coded2, wrongs, + f"Each letter shifted by +{shift}", 2)) + + qtid = get_qtid(conn, SUBJECT, "Verbal Reasoning", "Coding-Decoding", "Number coding") + if qtid: + for _ in range(count // 2): + word = random.choice(["CAT", "DOG", "SUN", "PEN", "CUP", "BOX", "HAT", "MAP", "JAR", "FAN"]) + code = [random.randint(1, 9) for _ in word] + code_str = "".join(map(str, code)) + word2 = random.choice(["BAT", "LOG", "RUN", "HEN", "BUS", "FOX", "RAT", "TAP"]) + # Same position mapping + mapping = {c: str(v) for c, v in zip(word, code)} + code2 = "".join(mapping.get(c, str(random.randint(1, 9))) for c in word2) + wrongs = [str(int(code2) + i) for i in [11, -22, 33]] + questions.append(make_question(qtid, + f"If {word} = {code_str}, then {word2} = ?", + code2, wrongs, + f"Letter-to-number mapping from {word}={code_str}", 2)) + return questions + + +# ============ LOGICAL REASONING ============ + +def gen_blood_relations(conn, count=1500): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Logical Reasoning", "Blood Relations", "Direct relation") + if not qtid: return questions + + templates = [ + ("A is the father of B. B is the sister of C. What is A to C?", "Father", ["Uncle", "Brother", "Grandfather"]), + ("A is the mother of B. B is the brother of C. What is A to C?", "Mother", ["Aunt", "Sister", "Grandmother"]), + ("A is the brother of B. B is the son of C. What is A to C?", "Son", ["Nephew", "Brother", "Father"]), + ("A is the sister of B. B is the daughter of C. What is A to C?", "Daughter", ["Niece", "Sister", "Mother"]), + ("A is the husband of B. B is the mother of C. What is A to C?", "Father", ["Uncle", "Brother", "Grandfather"]), + ("A is the wife of B. B is the father of C. What is A to C?", "Mother", ["Aunt", "Sister", "Grandmother"]), + ("A's father is B's son. What is B to A?", "Grandfather", ["Father", "Uncle", "Brother"]), + ("A's mother is B's daughter. What is B to A?", "Grandmother", ["Mother", "Aunt", "Sister"]), + ("A is B's brother's wife. What is A to B?", "Sister-in-law", ["Sister", "Cousin", "Aunt"]), + ("A is B's father's brother. What is A to B?", "Uncle", ["Father", "Cousin", "Grandfather"]), + ] + + for _ in range(count): + q_text, correct, wrongs = random.choice(templates) + names = random.sample(["P", "Q", "R", "S", "T", "M", "N", "X", "Y", "Z"], 3) + q_text = q_text.replace("A", names[0]).replace("B", names[1]).replace("C", names[2]) + questions.append(make_question(qtid, q_text, correct, wrongs, + f"Following family relationships, the answer is {correct}", 2)) + return questions + + +def gen_direction(conn, count=1200): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Logical Reasoning", "Direction and Distance", "Find final direction") + if not qtid: return questions + + directions = ["North", "South", "East", "West"] + turns = {"North": {"right": "East", "left": "West"}, + "South": {"right": "West", "left": "East"}, + "East": {"right": "South", "left": "North"}, + "West": {"right": "North", "left": "South"}} + + for _ in range(count): + start = random.choice(directions) + num_turns = random.randint(1, 3) + current = start + steps_desc = [f"starts facing {start}"] + for _ in range(num_turns): + turn = random.choice(["right", "left"]) + current = turns[current][turn] + steps_desc.append(f"turns {turn}") + wrong_dirs = [d for d in directions if d != current] + questions.append(make_question(qtid, + f"A person {', '.join(steps_desc)}. Which direction is the person facing now?", + current, wrong_dirs[:3], + f"After turns: {current}", 1)) + return questions + + +def gen_ranking(conn, count=1200): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Logical Reasoning", "Order and Ranking", "Find rank from top/bottom") + if not qtid: return questions + for _ in range(count): + total = random.randint(20, 60) + from_top = random.randint(1, total) + from_bottom = total - from_top + 1 + ask = random.choice(["top", "bottom"]) + if ask == "top": + questions.append(make_question(qtid, + f"In a row of {total} students, a student is {from_bottom}th from the bottom. What is the student's position from the top?", + str(from_top), nearby_wrong(from_top), + f"From top = Total - From bottom + 1 = {total} - {from_bottom} + 1 = {from_top}", 1)) + else: + questions.append(make_question(qtid, + f"In a row of {total} students, a student is {from_top}th from the top. What is the student's position from the bottom?", + str(from_bottom), nearby_wrong(from_bottom), + f"From bottom = Total - From top + 1 = {total} - {from_top} + 1 = {from_bottom}", 1)) + return questions + + +def gen_syllogism(conn, count=1000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Logical Reasoning", "Syllogism", "All/Some/No conclusions") + if not qtid: return questions + + templates = [ + ("All A are B. All B are C.", "All A are C", ["No A is C", "Some A are not C", "All C are A"]), + ("All A are B. Some B are C.", "Some A may be C", ["All A are C", "No A is C", "All C are A"]), + ("No A is B. All B are C.", "Some C are not A", ["All A are C", "No C is A", "All C are A"]), + ("Some A are B. All B are C.", "Some A are C", ["All A are C", "No A is C", "All C are A"]), + ("All A are B. No B is C.", "No A is C", ["Some A are C", "All A are C", "All C are A"]), + ] + categories = ["dogs", "cats", "birds", "students", "teachers", "doctors", "players", "singers", + "dancers", "painters", "writers", "engineers", "lawyers", "flowers", "trees"] + + for _ in range(count): + template, correct, wrongs = random.choice(templates) + cats = random.sample(categories, 3) + stmt = template.replace("A", cats[0].title()).replace("B", cats[1].title()).replace("C", cats[2].title()) + ans = correct.replace("A", cats[0].title()).replace("B", cats[1].title()).replace("C", cats[2].title()) + wrong_list = [w.replace("A", cats[0].title()).replace("B", cats[1].title()).replace("C", cats[2].title()) for w in wrongs] + questions.append(make_question(qtid, + f"Statements: {stmt}\nConclusion: Which follows?", + ans, wrong_list, f"Based on Venn diagram logic", 2)) + return questions + + +# ============ NON-VERBAL REASONING ============ + +def gen_mirror_image(conn, count=800): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Non-Verbal Reasoning", "Mirror and Water Image", "Mirror image of text/numbers") + if not qtid: return questions + for _ in range(count): + num = random.randint(100, 9999) + mirror = str(num)[::-1] + wrongs = [str(num + random.randint(1, 100)) for _ in range(3)] + questions.append(make_question(qtid, + f"What is the mirror image of the number {num} when a mirror is placed on the right side?", + mirror, wrongs, + f"Mirror reverses left-right: {num} ā†’ {mirror}", 1)) + return questions + + +def gen_dice(conn, count=800): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Non-Verbal Reasoning", "Dice and Cube", "Opposite face of dice") + if not qtid: return questions + for _ in range(count): + faces = list(range(1, 7)) + # Standard dice: opposite faces sum to 7 + num = random.randint(1, 6) + opp = 7 - num + questions.append(make_question(qtid, + f"On a standard die, what number is opposite to {num}?", + str(opp), [str(x) for x in range(1, 7) if x != num and x != opp][:3], + f"On a standard die, opposite faces sum to 7: {num} + {opp} = 7", 1)) + return questions + + +def gen_cube_painting(conn, count=600): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Non-Verbal Reasoning", "Dice and Cube", "Painted cube counting") + if not qtid: return questions + for _ in range(count): + n = random.randint(2, 6) + total = n ** 3 + three_face = 8 # corners + two_face = (n - 2) * 12 if n > 2 else 0 + one_face = (n - 2) ** 2 * 6 if n > 2 else 0 + no_face = (n - 2) ** 3 if n > 2 else 0 + ask = random.choice(["three", "two", "one", "no"]) + ans_map = {"three": three_face, "two": two_face, "one": one_face, "no": no_face} + ans = ans_map[ask] + questions.append(make_question(qtid, + f"A cube of side {n} is painted on all faces and then cut into {total} unit cubes. How many cubes have {ask} face(s) painted?", + str(ans), nearby_wrong(ans), + f"For {n}Ɨ{n}Ɨ{n} cube: {ask} faces painted = {ans}", 2)) + return questions + + +# ============ MATHEMATICAL REASONING ============ + +def gen_math_operations(conn, count=1000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Mathematical Reasoning", "Mathematical Operations", "Symbol substitution") + if not qtid: return questions + ops = {'+': lambda a, b: a + b, '-': lambda a, b: a - b, + 'Ɨ': lambda a, b: a * b, 'Ć·': lambda a, b: a // b} + symbols = ['@', '#', '$', '&', '*', '!'] + for _ in range(count): + op_pairs = random.sample(list(ops.keys()), 2) + sym_pairs = random.sample(symbols, 2) + a, b, c = random.randint(2, 20), random.randint(2, 20), random.randint(2, 20) + mapping_text = f"{sym_pairs[0]} means '{op_pairs[0]}' and {sym_pairs[1]} means '{op_pairs[1]}'" + expr_text = f"{a} {sym_pairs[0]} {b} {sym_pairs[1]} {c}" + result = ops[op_pairs[1]](ops[op_pairs[0]](a, b), c) + questions.append(make_question(qtid, + f"If {mapping_text}, find: {expr_text}", + str(result), nearby_wrong(result), + f"Replace symbols: {a} {op_pairs[0]} {b} {op_pairs[1]} {c} = {result}", 2)) + return questions + + +def gen_number_puzzles(conn, count=800): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Mathematical Reasoning", "Number Puzzles", "Find missing number in grid") + if not qtid: return questions + for _ in range(count): + # 3x3 grid where rows/cols sum to same value + a, b = random.randint(1, 20), random.randint(1, 20) + c = a + b + d = random.randint(1, 20) + e = c - d + random.randint(1, 10) + missing = a + d - e + b # Some pattern + # Simpler: row sums are equal + r1 = [random.randint(1, 20) for _ in range(3)] + target = sum(r1) + r2_a, r2_b = random.randint(1, 15), random.randint(1, 15) + r2_c = target - r2_a - r2_b + if r2_c > 0: + questions.append(make_question(qtid, + f"In a grid, row 1 is [{r1[0]}, {r1[1]}, {r1[2]}] (sum={target}). Row 2 is [{r2_a}, {r2_b}, ?]. Find the missing number if row sums are equal.", + str(r2_c), nearby_wrong(r2_c), + f"? = {target} - {r2_a} - {r2_b} = {r2_c}", 1)) + return questions + + +def gen_venn_diagram(conn, count=800): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Mathematical Reasoning", "Venn Diagram", "Count elements in region") + if not qtid: return questions + for _ in range(count): + total_a = random.randint(20, 100) + total_b = random.randint(20, 100) + both = random.randint(5, min(total_a, total_b)) + only_a = total_a - both + only_b = total_b - both + questions.append(make_question(qtid, + f"In a group, {total_a} like tea, {total_b} like coffee, and {both} like both. How many like only tea?", + str(only_a), nearby_wrong(only_a), + f"Only tea = {total_a} - {both} = {only_a}", 1)) + return questions + + +# ============ CRITICAL THINKING ============ + +def gen_statement_conclusion(conn, count=800): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Critical Thinking", "Statement and Conclusion", "Which conclusion follows") + if not qtid: return questions + templates = [ + ("All students who study hard pass the exam.", "Some who pass studied hard", ["No one studies hard", "Everyone fails", "Studying is not needed"]), + ("Regular exercise improves health.", "People who exercise are healthier", ["Exercise is harmful", "Health has no relation to exercise", "Only medicine improves health"]), + ("Reading improves vocabulary.", "People who read more have better vocabulary", ["Reading is useless", "Vocabulary cannot be improved", "TV improves vocabulary more"]), + ("Smoking causes cancer.", "Smokers are at higher risk of cancer", ["All smokers get cancer", "Cancer has no cause", "Smoking is healthy"]), + ("Water pollution affects marine life.", "Marine life is harmed by water pollution", ["Marine life thrives in pollution", "Pollution has no effect", "Only air pollution matters"]), + ] + for _ in range(count): + stmt, correct, wrongs = random.choice(templates) + questions.append(make_question(qtid, + f"Statement: {stmt}\nWhich conclusion logically follows?", + correct, wrongs, f"Direct logical inference", 2)) + return questions + + +def gen_letter_series(conn, count=1000): + questions = [] + qtid = get_qtid(conn, SUBJECT, "Verbal Reasoning", "Letter Series", "Find next letters") + if not qtid: return questions + for _ in range(count): + start = random.randint(0, 15) + skip = random.randint(1, 4) + series = [chr(65 + start + i * skip) for i in range(4) if start + i * skip < 26] + if len(series) < 4: + continue + nxt_idx = start + 4 * skip + if nxt_idx < 26: + ans = chr(65 + nxt_idx) + wrongs = [chr(65 + (nxt_idx + i) % 26) for i in [1, 2, -1]] + questions.append(make_question(qtid, + f"Find the next letter: {', '.join(series)}, ?", + ans, wrongs, + f"Skip {skip}: next = {ans}", 1)) + return questions + + +def generate_all(conn): + """Generate all Reasoning questions.""" + generators = [ + ("Number Analogy", gen_number_analogy, 700), + ("Letter Analogy", gen_letter_analogy, 500), + ("Classification", gen_classification, 2000), + ("Number Series", gen_number_series, 2000), + ("Letter Series", gen_letter_series, 1500), + ("Coding-Decoding", gen_coding_decoding, 2500), + ("Blood Relations", gen_blood_relations, 2000), + ("Direction & Distance", gen_direction, 1500), + ("Order & Ranking", gen_ranking, 1500), + ("Syllogism", gen_syllogism, 1500), + ("Mirror Image", gen_mirror_image, 1000), + ("Dice", gen_dice, 1000), + ("Cube Painting", gen_cube_painting, 800), + ("Math Operations", gen_math_operations, 1500), + ("Number Puzzles", gen_number_puzzles, 1200), + ("Venn Diagram", gen_venn_diagram, 1200), + ("Statement & Conclusion", gen_statement_conclusion, 1200), + ] + + total = 0 + all_questions = [] + for name, gen_func, count in generators: + questions = gen_func(conn, count) + all_questions.extend(questions) + print(f" {name}: {len(questions)} questions") + total += len(questions) + + batch_size = 5000 + for i in range(0, len(all_questions), batch_size): + insert_questions_batch(conn, all_questions[i:i+batch_size]) + + print(f" TOTAL Reasoning: {total}") + return total + + +if __name__ == '__main__': + conn = get_db() + print("Generating Reasoning questions...") + generate_all(conn) + conn.close() diff --git a/generators/run_all.py b/generators/run_all.py new file mode 100644 index 0000000..12662f4 --- /dev/null +++ b/generators/run_all.py @@ -0,0 +1,63 @@ +#!/usr/bin/env python3 +""" +Master script to generate all 100,000 SSC CGL questions. +Usage: python3 generators/run_all.py [--force] +""" +import sys +import os +import time + +sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..')) +from db.init import init_db, get_db, get_stats + +def main(): + force = '--force' in sys.argv + start = time.time() + + print("=" * 60) + print("SSCTopper - Question Generation Pipeline") + print("=" * 60) + + # Step 1: Initialize DB + print("\n[1/5] Initializing database...") + init_db(force=force) + + conn = get_db() + + # Step 2: Quantitative Aptitude + print("\n[2/5] Generating Quantitative Aptitude questions...") + from generators.quant_generator import generate_all as gen_quant + gen_quant(conn) + + # Step 3: Reasoning + print("\n[3/5] Generating Reasoning questions...") + from generators.reasoning_generator import generate_all as gen_reason + gen_reason(conn) + + # Step 4: English + print("\n[4/5] Generating English Language questions...") + from generators.english_generator import generate_all as gen_eng + gen_eng(conn) + + # Step 5: General Awareness + print("\n[5/5] Generating General Awareness questions...") + from generators.gk_generator import generate_all as gen_gk + gen_gk(conn) + + # Final stats + stats = get_stats(conn) + elapsed = time.time() - start + + print("\n" + "=" * 60) + print("GENERATION COMPLETE") + print("=" * 60) + for subject, count in stats.items(): + print(f" {subject}: {count:,}") + print(f"\n Time taken: {elapsed:.1f} seconds") + print("=" * 60) + + conn.close() + + +if __name__ == '__main__': + main() diff --git a/server.py b/server.py new file mode 100644 index 0000000..d680755 --- /dev/null +++ b/server.py @@ -0,0 +1,492 @@ +#!/usr/bin/env python3 +""" +SSCTopper Web Application - Zero-dependency Python web server. +Serves the SSC CGL question bank with syllabus browser and practice interface. +""" +import http.server +import json +import sqlite3 +import os +import sys +import urllib.parse +import hashlib +import uuid +import http.cookies +import urllib.request +import signal + +sys.path.insert(0, os.path.join(os.path.dirname(__file__))) +from db.init import DB_PATH, init_db, get_db + +PORT = 8080 +ROOT = os.path.dirname(os.path.abspath(__file__)) +GOOGLE_CLIENT_ID = "273072123939-dd82h4o1rt3k7811sri6qgsig73b3916.apps.googleusercontent.com" + + +class SSCHandler(http.server.BaseHTTPRequestHandler): + """HTTP request handler for SSCTopper.""" + + sessions = {} # session_id -> user_id + + def get_user_id(self): + cookie_header = self.headers.get('Cookie') + if not cookie_header: + return None + cookie = http.cookies.SimpleCookie(cookie_header) + session_id = cookie.get('session_id') + if not session_id: + return None + return self.sessions.get(session_id.value) + + def do_POST(self): + parsed = urllib.parse.urlparse(self.path) + path = parsed.path + + content_length = int(self.headers.get('Content-Length', 0)) + post_data = self.rfile.read(content_length).decode('utf-8') + try: + data = json.loads(post_data) + except: + data = {} + + if path == '/api/auth/signup': + self.handle_signup(data) + elif path == '/api/auth/login': + self.handle_login(data) + elif path == '/api/auth/google': + self.handle_google_login(data) + elif path == '/api/user/progress': + self.handle_progress(data) + else: + self.send_error(404) + + def handle_google_login(self, data): + id_token = data.get('id_token') + if not id_token: + return self.json_response({'error': 'Missing ID token'}, 400) + + # Verify token with Google API (Zero-dependency way) + try: + url = f"https://oauth2.googleapis.com/tokeninfo?id_token={id_token}" + with urllib.request.urlopen(url) as response: + google_data = json.loads(response.read().decode()) + + # Check for error in Google response + if 'error_description' in google_data: + return self.json_response({'error': google_data['error_description']}, 401) + + # Security check: Verify audience (aud) matches our Client ID + aud = google_data.get('aud') + if aud != GOOGLE_CLIENT_ID: + return self.json_response({'error': 'Token was not issued for this application'}, 401) + + email = google_data.get('email') + name = google_data.get('name', email.split('@')[0]) + + if not email: + return self.json_response({'error': 'Email not provided by Google'}, 400) + + conn = get_db() + user = conn.execute("SELECT id, username FROM users WHERE email=?", (email,)).fetchone() + + if not user: + # Create new user with random password (cannot be guessed) + random_pass = str(uuid.uuid4()) + pass_hash = hashlib.sha256(random_pass.encode()).hexdigest() + try: + # Use email handle as username if possible, otherwise use full email + username = email.split('@')[0] + # Ensure username uniqueness (this is simple, could be better) + cursor = conn.execute("INSERT INTO users (username, email, password_hash) VALUES (?, ?, ?)", + (username, email, pass_hash)) + user_id = cursor.lastrowid + conn.commit() + username_final = username + except sqlite3.IntegrityError: + # Fallback to email as username + cursor = conn.execute("INSERT INTO users (username, email, password_hash) VALUES (?, ?, ?)", + (email, email, pass_hash)) + user_id = cursor.lastrowid + conn.commit() + username_final = email + else: + user_id = user[0] + username_final = user[1] + + conn.close() + + # Set session + session_id = str(uuid.uuid4()) + self.sessions[session_id] = user_id + + cookie = http.cookies.SimpleCookie() + cookie['session_id'] = session_id + cookie['session_id']['path'] = '/' + cookie['session_id']['httponly'] = True + + self.send_response(200) + self.send_header('Content-Type', 'application/json') + self.send_header('Set-Cookie', cookie.output(header='')) + self.end_headers() + self.wfile.write(json.dumps({'success': True, 'username': username_final}).encode()) + + except Exception as e: + print(f"Google Auth Error: {e}") + self.json_response({'error': 'Failed to verify Google account'}, 500) + + def handle_signup(self, data): + username = data.get('username') + email = data.get('email') + password = data.get('password') + + if not all([username, email, password]): + return self.json_response({'error': 'Missing fields'}, 400) + + password_hash = hashlib.sha256(password.encode()).hexdigest() + + conn = get_db() + try: + conn.execute("INSERT INTO users (username, email, password_hash) VALUES (?, ?, ?)", + (username, email, password_hash)) + conn.commit() + self.json_response({'success': True}) + except sqlite3.IntegrityError: + self.json_response({'error': 'Username or email already exists'}, 400) + finally: + conn.close() + + def handle_login(self, data): + username = data.get('username') + password = data.get('password') + + if not all([username, password]): + return self.json_response({'error': 'Missing fields'}, 400) + + password_hash = hashlib.sha256(password.encode()).hexdigest() + + conn = get_db() + user = conn.execute("SELECT id FROM users WHERE username=? AND password_hash=?", + (username, password_hash)).fetchone() + conn.close() + + if user: + session_id = str(uuid.uuid4()) + self.sessions[session_id] = user[0] + + cookie = http.cookies.SimpleCookie() + cookie['session_id'] = session_id + cookie['session_id']['path'] = '/' + cookie['session_id']['httponly'] = True + + self.send_response(200) + self.send_header('Content-Type', 'application/json') + self.send_header('Set-Cookie', cookie.output(header='')) + self.end_headers() + self.wfile.write(json.dumps({'success': True, 'username': username}).encode()) + else: + self.json_response({'error': 'Invalid credentials'}, 401) + + def handle_progress(self, data): + user_id = self.get_user_id() + if not user_id: + return self.json_response({'error': 'Unauthorized'}, 401) + + question_id = data.get('question_id') + is_correct = data.get('is_correct') + time_taken = data.get('time_taken', 0.0) + + if question_id is None or is_correct is None: + return self.json_response({'error': 'Missing fields'}, 400) + + conn = get_db() + conn.execute("INSERT INTO user_answers (user_id, question_id, is_correct, time_taken) VALUES (?, ?, ?, ?)", + (user_id, int(question_id), bool(is_correct), float(time_taken))) + conn.commit() + conn.close() + self.json_response({'success': True}) + + def do_GET(self): + parsed = urllib.parse.urlparse(self.path) + path = parsed.path + params = urllib.parse.parse_qs(parsed.query) + + if path == '/' or path == '/index.html': + self.serve_html() + elif path == '/robots.txt': + self.serve_static('robots.txt', 'text/plain') + elif path == '/sitemap.xml': + self.serve_static('sitemap.xml', 'application/xml') + elif path == '/api/syllabus': + self.api_syllabus() + elif path == '/api/questions': + self.api_questions(params) + elif path == '/api/stats': + self.api_stats() + elif path == '/api/mock-test': + self.api_mock_test(params) + elif path == '/api/user/profile': + self.api_user_profile() + else: + self.send_error(404) + + def api_user_profile(self): + user_id = self.get_user_id() + if not user_id: + return self.json_response({'error': 'Unauthorized'}, 401) + + # Parse timeframe + parsed = urllib.parse.urlparse(self.path) + params = urllib.parse.parse_qs(parsed.query) + timeframe = params.get('timeframe', ['overall'])[0] + + time_filter = "" + if timeframe == 'daily': + time_filter = "AND ua.answered_at >= datetime('now', '-1 day')" + elif timeframe == 'weekly': + time_filter = "AND ua.answered_at >= datetime('now', '-7 days')" + elif timeframe == 'monthly': + time_filter = "AND ua.answered_at >= datetime('now', 'start of month')" + + conn = get_db() + user = conn.execute("SELECT username, email, created_at FROM users WHERE id=?", (user_id,)).fetchone() + + # Get overall stats for timeframe + stats_query = f"SELECT COUNT(*), SUM(CASE WHEN is_correct=1 THEN 1 ELSE 0 END), AVG(time_taken) FROM user_answers ua WHERE user_id=? {time_filter}" + stats_row = conn.execute(stats_query, (user_id,)).fetchone() + total_attempts = stats_row[0] or 0 + correct_attempts = stats_row[1] or 0 + avg_time_overall = round(stats_row[2] or 0, 1) + + # Topic-wise progress with time tracking + topic_progress = [] + rows = conn.execute(f""" + SELECT t.id, t.name, st.name as subtopic, s.name as subject, + COUNT(DISTINCT q.id) as total_questions, + COUNT(DISTINCT ua.question_id) as answered_questions, + AVG(ua.time_taken) as avg_time + FROM topics t + JOIN subtopics st ON t.subtopic_id = st.id + JOIN subjects s ON st.subject_id = s.id + LEFT JOIN question_types qt ON qt.topic_id = t.id + LEFT JOIN questions q ON q.question_type_id = qt.id + LEFT JOIN user_answers ua ON ua.question_id = q.id AND ua.user_id = ? AND ua.is_correct = 1 {time_filter} + GROUP BY t.id + """, (user_id,)).fetchall() + + for r in rows: + topic_progress.append({ + 'topic_id': r[0], 'topic': r[1], 'subtopic': r[2], 'subject': r[3], + 'total': r[4], 'answered': r[5], + 'percent': round(r[5] * 100 / r[4], 1) if r[4] > 0 else 0, + 'avg_time': round(r[6] or 0, 1) + }) + + conn.close() + self.json_response({ + 'username': user[0], + 'email': user[1], + 'joined': user[2], + 'stats': { + 'total_attempts': total_attempts, + 'correct_attempts': correct_attempts, + 'accuracy': round(correct_attempts * 100 / total_attempts, 1) if total_attempts > 0 else 0, + 'avg_time': avg_time_overall + }, + 'topic_progress': topic_progress + }) + + def serve_html(self): + html_path = os.path.join(ROOT, 'static', 'index.html') + with open(html_path, 'r') as f: + content = f.read() + self.send_response(200) + self.send_header('Content-Type', 'text/html; charset=utf-8') + self.end_headers() + self.wfile.write(content.encode('utf-8')) + + def serve_static(self, filename, content_type): + file_path = os.path.join(ROOT, 'static', filename) + if not os.path.exists(file_path): + self.send_error(404) + return + with open(file_path, 'rb') as f: + content = f.read() + self.send_response(200) + self.send_header('Content-Type', content_type) + self.end_headers() + self.wfile.write(content) + + def json_response(self, data, status=200): + self.send_response(status) + self.send_header('Content-Type', 'application/json; charset=utf-8') + self.send_header('Access-Control-Allow-Origin', '*') + self.end_headers() + self.wfile.write(json.dumps(data, ensure_ascii=False).encode('utf-8')) + + def api_syllabus(self): + conn = get_db() + subjects = [] + for s in conn.execute("SELECT id, name, tier, description, target_questions FROM subjects").fetchall(): + subject = {'id': s[0], 'name': s[1], 'tier': s[2], 'description': s[3], 'target': s[4], 'subtopics': []} + for st in conn.execute("SELECT id, name, description FROM subtopics WHERE subject_id=?", (s[0],)).fetchall(): + subtopic = {'id': st[0], 'name': st[1], 'description': st[2], 'topics': []} + for t in conn.execute("SELECT id, name, description FROM topics WHERE subtopic_id=?", (st[0],)).fetchall(): + q_count = conn.execute("SELECT COUNT(*) FROM questions q JOIN question_types qt ON q.question_type_id=qt.id WHERE qt.topic_id=?", (t[0],)).fetchone()[0] + qtypes = [{'id': qt[0], 'name': qt[1]} for qt in conn.execute("SELECT id, name FROM question_types WHERE topic_id=?", (t[0],)).fetchall()] + subtopic['topics'].append({'id': t[0], 'name': t[1], 'description': t[2], 'question_count': q_count, 'question_types': qtypes}) + subject['subtopics'].append(subtopic) + # Count total questions for subject + subject['question_count'] = conn.execute(""" + SELECT COUNT(*) FROM questions q + JOIN question_types qt ON q.question_type_id = qt.id + JOIN topics t ON qt.topic_id = t.id + JOIN subtopics st ON t.subtopic_id = st.id + WHERE st.subject_id = ? + """, (s[0],)).fetchone()[0] + subjects.append(subject) + conn.close() + self.json_response(subjects) + + def api_questions(self, params): + conn = get_db() + topic_id = params.get('topic_id', [None])[0] + qtype_id = params.get('qtype_id', [None])[0] + subject_id = params.get('subject_id', [None])[0] + difficulty = params.get('difficulty', [None])[0] + limit = int(params.get('limit', ['20'])[0]) + offset = int(params.get('offset', ['0'])[0]) + + query = """SELECT q.id, q.question_text, q.option_a, q.option_b, q.option_c, q.option_d, + q.correct_option, q.explanation, q.difficulty, + qt.name as qtype_name, t.name as topic_name, st.name as subtopic_name, s.name as subject_name + FROM questions q + JOIN question_types qt ON q.question_type_id = qt.id + JOIN topics t ON qt.topic_id = t.id + JOIN subtopics st ON t.subtopic_id = st.id + JOIN subjects s ON st.subject_id = s.id + WHERE 1=1""" + args = [] + + if topic_id: + query += " AND t.id = ?" + args.append(int(topic_id)) + if qtype_id: + query += " AND qt.id = ?" + args.append(int(qtype_id)) + if subject_id: + query += " AND s.id = ?" + args.append(int(subject_id)) + if difficulty: + query += " AND q.difficulty = ?" + args.append(int(difficulty)) + + # Get total count + count_query = query.replace("SELECT q.id, q.question_text, q.option_a, q.option_b, q.option_c, q.option_d,\n q.correct_option, q.explanation, q.difficulty,\n qt.name as qtype_name, t.name as topic_name, st.name as subtopic_name, s.name as subject_name", "SELECT COUNT(*)") + total = conn.execute(count_query, args).fetchone()[0] + + query += " ORDER BY RANDOM() LIMIT ? OFFSET ?" + args.extend([limit, offset]) + + rows = conn.execute(query, args).fetchall() + questions = [] + for r in rows: + questions.append({ + 'id': r[0], 'question_text': r[1], + 'options': {'A': r[2], 'B': r[3], 'C': r[4], 'D': r[5]}, + 'correct_option': r[6], 'explanation': r[7], 'difficulty': r[8], + 'qtype': r[9], 'topic': r[10], 'subtopic': r[11], 'subject': r[12] + }) + conn.close() + self.json_response({'total': total, 'questions': questions}) + + def api_stats(self): + conn = get_db() + stats = {} + rows = conn.execute(""" + SELECT s.name, COUNT(q.id) FROM subjects s + LEFT JOIN subtopics st ON st.subject_id = s.id + LEFT JOIN topics t ON t.subtopic_id = st.id + LEFT JOIN question_types qt ON qt.topic_id = t.id + LEFT JOIN questions q ON q.question_type_id = qt.id + GROUP BY s.id + """).fetchall() + for r in rows: + stats[r[0]] = r[1] + total = conn.execute("SELECT COUNT(*) FROM questions").fetchone()[0] + stats['total'] = total + topic_count = conn.execute("SELECT COUNT(*) FROM topics").fetchone()[0] + stats['topic_count'] = topic_count + stats['subject_count'] = conn.execute("SELECT COUNT(*) FROM subjects").fetchone()[0] + conn.close() + self.json_response(stats) + + def api_mock_test(self, params): + conn = get_db() + subject_id = params.get('subject_id', [None])[0] + num = int(params.get('num', ['25'])[0]) + + query = """SELECT q.id, q.question_text, q.option_a, q.option_b, q.option_c, q.option_d, + q.correct_option, q.explanation, q.difficulty, + qt.name, t.name, st.name, s.name + FROM questions q + JOIN question_types qt ON q.question_type_id = qt.id + JOIN topics t ON qt.topic_id = t.id + JOIN subtopics st ON t.subtopic_id = st.id + JOIN subjects s ON st.subject_id = s.id""" + args = [] + if subject_id: + query += " WHERE s.id = ?" + args.append(int(subject_id)) + query += " ORDER BY RANDOM() LIMIT ?" + args.append(num) + + rows = conn.execute(query, args).fetchall() + questions = [] + for r in rows: + questions.append({ + 'id': r[0], 'question_text': r[1], + 'options': {'A': r[2], 'B': r[3], 'C': r[4], 'D': r[5]}, + 'correct_option': r[6], 'explanation': r[7], 'difficulty': r[8], + 'qtype': r[9], 'topic': r[10], 'subtopic': r[11], 'subject': r[12] + }) + conn.close() + self.json_response({'questions': questions, 'total': len(questions)}) + + def log_message(self, format, *args): + pass # Suppress access logs + + +def main(): + # Initialize DB if needed + if not os.path.exists(DB_PATH): + print("Database not found. Running generation pipeline...") + init_db() + + # Check if we have questions, if not, generate some + conn = get_db() + try: + count = conn.execute("SELECT COUNT(*) FROM questions").fetchone()[0] + if count == 0: + print("Database is empty. Generating question bank...") + from generators.run_all import main as generate + generate() + except Exception as e: + print(f"Error checking question count: {e}") + finally: + conn.close() + + server = http.server.HTTPServer(('0.0.0.0', PORT), SSCHandler) + print(f"\nšŸš€ SSCTopper running at http://localhost:{PORT}") + print(f" Database: {DB_PATH}") + print(f" Press Ctrl+C to stop\n") + + signal.signal(signal.SIGINT, lambda s, f: (server.shutdown(), sys.exit(0))) + + try: + server.serve_forever() + except KeyboardInterrupt: + server.shutdown() + + +if __name__ == '__main__': + main() diff --git a/static/index.html b/static/index.html new file mode 100644 index 0000000..5edc483 --- /dev/null +++ b/static/index.html @@ -0,0 +1,1036 @@ + + + + + + + SSCTopper | 100,000+ SSC CGL Practice Questions & Mock Tests + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
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+ + + + + + + + + \ No newline at end of file diff --git a/static/robots.txt b/static/robots.txt new file mode 100644 index 0000000..0f88040 --- /dev/null +++ b/static/robots.txt @@ -0,0 +1,4 @@ +User-agent: * +Allow: / + +Sitemap: https://ssctopper.com/sitemap.xml diff --git a/static/sitemap.xml b/static/sitemap.xml new file mode 100644 index 0000000..efef55c --- /dev/null +++ b/static/sitemap.xml @@ -0,0 +1,9 @@ + + + + https://ssctopper.com/ + 2026-03-29 + daily + 1.0 + +