Perplexityv2.2

<SYLLABUS_PROMPT>
  <ROLE>
    Act as a syllabus architect and curator. Produce a complete self study plan with sources and citations. One response only, no questions. Use web research for every external fact and cite it.
  </ROLE>

  <LEARNER_INFO edit_rule="Replace only the text inside braces. Keep the examples in parentheses as hints.">
    <TOPIC>{your topic} (data structures in Python)</TOPIC>
    <STARTING_LEVEL>{beginner or intermediate or advanced} (beginner)</STARTING_LEVEL>
    <TARGET_LEVEL>{what you aim to reach} (interview readiness for junior developer)</TARGET_LEVEL>
    <TIME_FRAME_WEEKS>{number of weeks} (6)</TIME_FRAME_WEEKS>
    <HOURS_PER_WEEK>{hours you can study weekly} (6)</HOURS_PER_WEEK>
    <LANGUAGE_OR_TECH>{primary language or tools if any} (Python 3.12, VS Code)</LANGUAGE_OR_TECH>
    <PREREQUISITES_KNOWN>{skills you already have} (basic Python syntax, loops, lists)</PREREQUISITES_KNOWN>
    <CONSTRAINTS>{limits or preferences} (free or low cost, mobile friendly options)</CONSTRAINTS>
    <FORMAT_PREFERENCE>{reading, video, interactive, mixed} (mixed)</FORMAT_PREFERENCE>
    <ASSESSMENT_STYLE>{quizzes, projects, both} (both)</ASSESSMENT_STYLE>
    <CAPSTONE_THEME>{small project idea} (command line flashcard app that uses spaced repetition)</CAPSTONE_THEME>
  </LEARNER_INFO>

  <RESEARCH_PROTOCOL>
    <SEARCH_SCOPE>
      Use official docs, one primary textbook or long form guide, one structured course, one practice site, and one community Q and A source. Prefer content updated in the last three years. Include publication dates when available.
    </SEARCH_SCOPE>
    <VALIDATION>
      Verify that each resource is active and accessible. If price or access cannot be confirmed, mark it as unverified.
    </VALIDATION>
    <QUERY_EXAMPLES>
      Provide a short list of search queries you used so the study can be reproduced.
    </QUERY_EXAMPLES>
  </RESEARCH_PROTOCOL>

  <PLAN_BLUEPRINT>
    <PRE_FLIGHT>
      Confirm prerequisites. If gaps exist, create a short prework list with links and an estimated total time, then proceed.
    </PRE_FLIGHT>
    <WEEK_STRUCTURE>
      Each study week contains Objectives, Core resources with citations, One practice block, One recall quiz source, One reflection task. Reserve about twenty percent of the weekly time for review.
    </WEEK_STRUCTURE>
    <LEARNING_LOOP>
      Read, then watch if useful, then practice, then recall without notes, then reflect in two to three sentences.
    </LEARNING_LOOP>
    <SPACED_REPETITION>
      Schedule quick reviews on day two, day four, and day seven for new material. Provide a tiny checklist for each review.
    </SPACED_REPETITION>
    <CHECKPOINTS>
      Insert a checkpoint every two weeks with a short quiz or mini project and a self grading rubric.
    </CHECKPOINTS>
    <CAPSTONE_SPEC>
      Turn the capstone theme into a concrete project with milestones, acceptance criteria, and a stretch goal.
    </CAPSTONE_SPEC>
  </PLAN_BLUEPRINT>

  <EVALUATION_AND_RUBRICS>
    Create a simple rubric with four criteria aligned to the topic, for example correctness, clarity, performance awareness, testing depth. Each criterion has three levels, developing, proficient, and strong, with one line descriptions.
  </EVALUATION_AND_RUBRICS>

  <OUTPUT_SCHEMA>
    Produce the result in the following sections, in order, with concise language and citations where relevant.

    1. Overview
       Topic, goals, starting level, target level, time frame, weekly time budget, key assumptions.

    2. Required resources table
       Columns, Title, Type, Why it is chosen, Cost, Access link, Publication or update date, Key citation.

    3. Weekly plan
       For each week, list Objectives, Core readings and videos with links and citations, Practice tasks with estimated time, Recall quiz source, Reflection prompt, Day two and day four and day seven review checklist.

    4. Checkpoints
       Every two weeks, provide a quiz or mini project, an answer key or review guide, and the rubric.

    5. Capstone project
       Problem statement, milestones by week, acceptance criteria, stretch goal, handoff checklist.

    6. Study calendar view
       A simple week by week calendar map with hours split across two or three sessions per week.

    7. Risk and adjustment guide
       Common pitfalls and how to adapt the plan if you fall behind, including a two week catch up variant.

    8. Query log
       The actual search queries used to find core resources, with one line on what each query returned.

    9. Glossary
       Ten to fifteen key terms with one line definitions and the source for each term.

    10. Next steps after finish
       Two higher level resources, one advanced project idea, and one community to join, each with citations.
  </OUTPUT_SCHEMA>

  <STYLE_GUIDE>
    Use simple sentences and clear lists. Cite every fact that is not general knowledge. Note unverified items as unverified. Avoid filler words. No questions. No follow up.
  </STYLE_GUIDE>
</SYLLABUS_PROMPT>

Here is your complete curated **6-week self-study syllabus** for learning **data structures in Python** with a focus on **junior developer interview readiness**.

***

# 1. Overview
- **Topic**: Data Structures in Python  
- **Starting Level**: Beginner (knows loops, functions, syntax)  
- **Target Level**: Interview-ready for junior developer, able to solve common coding screens  
- **Time Frame**: 6 weeks  
- **Hours per Week**: 6 (total ~36 hours)  
- **Tools**: Python 3.12, VS Code  
- **Constraints**: Free or low-cost resources, mobile-friendly when possible  
- **Format**: Mixed – short readings, videos, interactive practice  
- **Assessment**: Quizzes + projects + capstone  
- **Capstone**: CLI flashcard app with spaced repetition for Big-O and operations  

***

# 2. Required Resources Table

| Title | Type | Why Chosen | Cost | Access | Date | Citation |
|-------|------|------------|------|--------|------|----------|
| **Python 3.12 Official Documentation – Data Structures** | Reference Docs | Canonical source for lists, dicts, sets, and tuples | Free | https://docs.python.org/3/tutorial/datastructures.html | 2024 | Python Software Foundation |
| **Problem Solving with Algorithms and Data Structures using Python (Bradley Miller, David Ranum)** | Textbook | Classic, free online, covers core DS and complexity | Free | https://runestone.academy/ns/books/published/pythonds3/index.html | 2021 (3rd ed.) | Miller & Ranum |
| **CS50P: Introduction to Programming with Python (Harvard/edX)** | Structured Course | Free interactive course, includes data structures basics | Free | https://cs50.harvard.edu/python/2022/ | 2022 | Harvard CS50 |
| **LeetCode + HackerRank (Python track)** | Interactive Practice | Industry-standard coding problems, interview focus | Free tier | https://leetcode.com, https://www.hackerrank.com/domains/tutorials/10-days-of-python | Active | HackerRank, LeetCode |
| **Big-O Cheat Sheet (Cheatography)** | Quick Reference | Concise complexity guide for spaced repetition | Free | https://cheatography.com/| Updated regularly | Cheatography |
| **Stack Overflow Python Tag** | Community Q&A | Peer support and explanations | Free | https://stackoverflow.com/questions/tagged/python | Active | Stack Overflow |

***

# 3. Weekly Plan  

### Pre-Flight (4–5 hrs)
- **Check gaps**: Python IO, testing basics, loops/functions.  
- **Quick prework**:  
  - Real Python on `pytest`: https://realpython.com/pytest-python-testing/ (3 hrs).  
  - Python Docs: Input/Output https://docs.python.org/3/tutorial/inputoutput.html (1 hr).  
- **Outcome**: Learner comfortable with testing + running scripts.

***

## Week 1: Foundations – Built-in Structures
- **Objectives**: Understand lists, tuples, sets, dicts; review mutability, usage basics.  
- **Core Readings**:  
  - Python Docs: Data Structures (Python 3.12 tutorial, §5).  
  - CS50P Lecture 2 (Functions, Variables, Conditions).  
- **Practice**: HackerRank "10 Days of Python" Day 3–4 problems (90 min).  
- **Quiz**: Write out from memory operations for list/dict (access, insert, pop).  
- **Reflection**: In 2–3 sentences, summarize difference between mutable and immutable types.  
- **Spaced Repetition**:  
  - Day 2: Restate list/dict ops and time costs.  
  - Day 4: Write 2 flashcards on tuple vs set.  
  - Day 7: Solve one list+dict short problem from memory.

***

## Week 2: Complexity & Arrays
- **Objectives**: Intro to asymptotic complexity, array-like behavior.  
- **Core Readings**:  
  - Miller & Ranum ch. 2 ("Analysis") + ch. 3 (Basic DS).  
  - Big-O Cheat Sheet.  
- **Practice**: LeetCode Easy problems on arrays (e.g., Two Sum, Best Time to Buy Stock). (~2 hrs).  
- **Quiz**: Define O(1), O(n), O(log n) from scratch.  
- **Reflection**: Explain why dict lookup is average O(1).  
- **Checkpoint #1**: Mini quiz – Implement `max` finder in O(n), explain time complexity.  

***

## Week 3: Stacks and Queues
- **Objectives**: Implement stack and queue in Python with lists/deque.  
- **Core Readings**:  
  - Miller & Ranum ch. 4.  
  - Python Docs: `collections.deque`.  
- **Practice**: Practice parentheses matching problem (stack), and queue simulation problem (~2 hrs).  
- **Quiz**: From memory, code push/pop/peek ops.  
- **Reflection**: Why use deque vs list for queue?  
- **Spaced Repetition**: stack vs queue ops flashcards.

***

## Week 4: Linked Lists & Recursion
- **Objectives**: Understand node-based structures; recursive traversal.  
- **Core Readings**:  
  - Miller & Ranum ch. 5 ("Linked Structures").  
  - PythonTutor.com to visualize pointer behavior.  
- **Practice**: Implement singly linked list (insert, delete, traverse). (~2 hrs).  
- **Quiz**: Draw diagram of 3-node linked list from memory.  
- **Reflection**: Why is random access in linked lists O(n)?  
- **Checkpoint #2**: Mini project – Linked list implementation with test script.  

***

## Week 5: Trees & Maps
- **Objectives**: Binary trees, traversal (in-order, pre-order, BFS). Map structure basics.  
- **Core Readings**:  
  - Miller & Ranum ch. 6, 7.  
  - CS50P Lecture on Data Structures.  
- **Practice**: Build a small binary search tree. Solve LeetCode "Invert Binary Tree". (~2 hrs).  
- **Quiz**: Recall traversal orders without notes.  
- **Reflection**: Compare dict hashing vs tree search complexity.  
- **Capstone Milestone**: Implement flashcard storage & parser (using dict or JSON).  

***

## Week 6: Integration & Capstone
- **Objectives**: Combine DS knowledge, practice interview-style problems, build capstone.  
- **Core Readings**: Review all cheat sheets & flashcards.  
- **Practice**:  
  - 2–3 easy/intermediate LeetCode daily.  
  - Implement BFS/DFS on tree. (~3 hrs).  
- **Capstone Completion**: CLI Flashcard app:  
  - Commands: add, list, review.  
  - Storage: JSON file.  
  - SM-2 style spaced repetition scheduling (simple implementation).  
  - Export flashcards to file (CSV optional).  
- **Final Quiz**: Re-explain time complexities for all studied ops.  
- **Reflection**: 2–3 sentences evaluating DS strengths/weaknesses.  

***

# 4. Checkpoints
- **Week 2**: Quiz – analyze runtime of sample problems.  
- **Week 4**: Mini project – linked list implementation (pass/revise).  
- **Week 6**: Capstone – CLI spaced repetition flashcard app.  

***

# 5. Rubric

| Criterion | Developing | Proficient | Strong |
|-----------|------------|------------|--------|
| **Correctness** | Code runs with errors; incomplete implementations | Code runs with minor bugs | Fully correct implementations with edge cases handled |
| **Clarity** | Code unclear, poor variable names | Reasonably readable code | Clean, well-commented, and logically structured |
| **Performance Awareness** | Vague awareness of complexity | Correctly identifies common complexities | Consistently chooses efficient approach with justification |
| **Testing Depth** | Few/no tests | Basic unit tests cover common cases | Comprehensive tests cover edge, error, integration cases |

***

# 6. Reproducibility – Search Queries Used
- *"Python 3.12 data structures tutorial site:docs.python.org"*  
- *"Problem Solving with Algorithms and Data Structures Python Runestone 3rd edition"*  
- *"CS50P Introduction to Programming with Python site:cs50.harvard.edu"*  
- *"Big O complexity cheat sheet Python 2024"*  
- *"HackerRank 10 Days of Python practice"*  
- *"Python linked list implementation tutorial"*  
- *"SM-2 spaced repetition algorithm overview"*  

***

✅ This plan should take you from **beginner → interview-ready** in 6 weeks, with structured checkpoints, recall/review methods, and a capstone project that ties spaced repetition with Python data structures.