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Every computational process involves managing data over time. Elements arrive, they wait, and eventually they're processed. The *order* in which we process waiting elements is not arbitrary—it profoundly affects the behavior, correctness, and efficiency of our algorithms. Consider a simple question: **"When multiple items are waiting to be processed, which one should we handle next?"** This seemingly innocent question has deep implications. The answer depends on: - **Temporal relationships**: Does the order of arrival matter? - **Dependency constraints**: Must certain items be processed before others? - **Recency requirements**: Is the most recent or the oldest item more relevant? - **Fairness considerations**: Should items wait equally long? LIFO and FIFO represent the two purest answers to this question. LIFO says: *"Process the most recently arrived item first."* FIFO says: *"Process the item that has been waiting longest."* Neither is universally correct—each is appropriate for different problem domains.73:T4b1,**Last-In, First-Out (LIFO)** is the ordering principle where the most recently added element is the first one to be removed. If you add elements A, then B, then C to a LIFO structure, the removal order is C, B, A—the reverse of the insertion order. ### The Core Intuition LIFO embodies the concept of **recency priority**. It operates on the premise that the most recent item is the most immediately relevant. This seems counterintuitive at first—why would we ignore older items in favor of newer ones? The answer lies in understanding **nesting** and **hierarchical relationships**. LIFO naturally represents situations where: 1. **Each new item depends on completing previous context**: Like nested function calls, where you must complete inner functions before returning to outer ones. 2. **The most recent action needs to be undone first**: You can't undo your third-to-last action without first undoing the last two. 3. **Processing involves recursively diving deeper, then unwinding**: Like exploring a maze depth-first—you go as deep as possible, then backtrack. 4. **Matching paired delimiters**: The most recently opened parenthesis must match the first closing one encountered.74:T468,# LIFO (Stack) creates Depth-First behavior def depth_first_traversal(root): """Using a stack for LIFO traversal""" stack = [root] # Start with root result = [] while stack: node = stack.pop() # LIFO: get most recent result.append(node.value) # Push children - they'll be processed before siblings for child in reversed(node.children): stack.append(child) return result # For tree: A -> [B, C], B -> [D, E], C -> [F] # Order: A, B, D, E, C, F (depth-first) # FIFO (Queue) creates Breadth-First behavior from collections import deque def breadth_first_traversal(root): """Using a queue for FIFO traversal""" queue = deque([root]) # Start with root result = [] while queue: node = queue.popleft() # FIFO: get oldest result.append(node.value) # Enqueue children - processed after all siblings for child in node.children: queue.append(child) return result # For tree: A -> [B, C], B -> [D, E], C -> [F] # Order: A, B, C, D, E, F (breadth-first)75:T4de,// LIFO (Stack) creates Depth-First behavior function depthFirstTraversal(root: TreeNode): T[] { const stack: TreeNode[] = [root]; // Start with root const result: T[] = []; while (stack.length > 0) { const node = stack.pop()!; // LIFO: get most recent result.push(node.value); // Push children - they'll be processed before siblings for (let i = node.children.length - 1; i >= 0; i--) { stack.push(node.children[i]); } } return result; // For tree: A -> [B, C], B -> [D, E], C -> [F] // Order: A, B, D, E, C, F (depth-first) } // FIFO (Queue) creates Breadth-First behavior function breadthFirstTraversal(root: TreeNode): T[] { const queue: TreeNode[] = [root]; // Start with root const result: T[] = []; while (queue.length > 0) { const node = queue.shift()!; // FIFO: get oldest result.push(node.value); // Enqueue children - processed after all siblings for (const child of node.children) { queue.push(child); } } return result; // For tree: A -> [B, C], B -> [D, E], C -> [F] // Order: A, B, C, D, E, F (breadth-first) }76:T437,One of LIFO's most powerful properties is its natural ability to **reverse sequences**. This isn't merely a curiosity—it's a fundamental capability that makes stacks the go-to structure for many problems. ### How Reversal Works When you push elements A, B, C, D onto a stack (in that order) and then pop them all, you get D, C, B, A. The stack has reversed the sequence with zero additional logic. This happens because: 1. Each new element is placed 'on top' of previous elements 2. Only the top element is accessible for removal 3. Therefore, the last element placed is the first removed ### Why Reversal Matters **String/Array Reversal**: The classic example—push all characters, then pop them all. **Palindrome Checking**: Push the first half, then compare with the second half. **Undo Operations**: The most recent action is undone first—a natural reversal. **Expression Conversion**: Infix to postfix conversion (Shunting Yard) relies on reversal to reorder operators. **Backtracking**: Returning through visited states happens in reverse order of visitation.77:T4c2,from collections import deque def shortest_path_bfs(grid, start, end): """ FIFO naturally finds shortest paths in unweighted graphs. The invariant: when we dequeue a cell, we've found the shortest path to it, because FIFO ensures we visit cells in order of their distance from the start. """ rows, cols = len(grid), len(grid[0]) queue = deque([(start, 0)]) # (position, distance) visited = {start} while queue: (row, col), dist = queue.popleft() # FIFO: process closest first if (row, col) == end: return dist # First time we reach end = shortest path # Explore all neighbors for dr, dc in [(0, 1), (0, -1), (1, 0), (-1, 0)]: nr, nc = row + dr, col + dc if (0 <= nr < rows and 0 <= nc < cols and (nr, nc) not in visited and grid[nr][nc] != '#'): # '#' = wall visited.add((nr, nc)) queue.append(((nr, nc), dist + 1)) return -1 # No path exists # The key insight: FIFO ensures we process all distance-k cells # before any distance-(k+1) cells, guaranteeing shortest path.46:["$","$L71",null,{"owner":"anonymous","state":{"mutations":[],"queries":[{"dehydratedAt":1792378592909,"state":{"data":{"json":{"archivedAt":null,"id":"seed_a45eefd7ace053183db2aca078e8dfbc","slug":"data-structures-algorithms","title":"Data Structures & Algorithms","description":"Build strong algorithmic 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Structures & Algorithms","topic":"Stacks vs Queues — Comparison & Use Cases","title":"Stacks vs Queues — Comparison & Use Cases","description":"Master the art of choosing between stacks and queues. This module provides a comprehensive comparison of LIFO and FIFO principles, explores when each data structure shines, and develops your intuition for recognizing which structure solves a problem most elegantly.","difficulty":"BEGINNER","estimatedMinutes":50,"pages":[{"id":"seed_3d1f7a07cedc0cbc46024a2266bc444f","title":"LIFO vs FIFO Summary","order":0,"content":[{"id":"opening-hook","title":"Two Principles, Two Worldviews","content":[{"data":{"content":"In the realm of data structures, few distinctions are as fundamental—or as consequential—as the difference between **Last-In-First-Out (LIFO)** and **First-In-First-Out (FIFO)** ordering. These two principles represent fundamentally different philosophies about how data should be organized, accessed, and processed. They are the philosophical bedrock upon which stacks and queues are built.\n\nUnderstanding LIFO and FIFO isn't merely about memorizing definitions. It's about developing an *intuition* that allows you to instantly recognize which principle applies to a given problem. A seasoned engineer doesn't consciously think \"should I use LIFO or FIFO here?\"—they *see* the problem and the appropriate ordering principle reveals itself naturally.\n\nThis page will build that intuition systematically, exploring each principle in depth, comparing their behavioral characteristics, and establishing the mental framework that will guide your data structure decisions throughout your career."},"type":"text"},{"data":{"icon":"Target","title":"What You Will Master","content":"By the end of this page, you will deeply understand both LIFO and FIFO as cognitive models for data ordering. You'll be able to articulate precisely why each principle exists, what problems each naturally solves, and how to recognize the signature patterns that suggest one over the other.","variant":"info"},"type":"callout"}]},{"id":"philosophy-of-ordering","title":"The Philosophy of Data Ordering","content":[{"data":{"content":"$72"},"type":"text"},{"data":{"icon":"Info","title":"Beyond Simple Ordering","content":"LIFO and FIFO are not the only ordering disciplines. Priority queues order by importance, not arrival time. But LIFO and FIFO are the foundational primitives—more complex orderings often build upon or combine these basic principles.","variant":"note"},"type":"callout"}],"titleType":"number","titleNumber":1},{"id":"lifo-deep-dive","title":"LIFO — Last-In, First-Out: A Deep Examination","content":[{"data":{"content":"$73"},"type":"text"},{"data":{"items":["**Reversal by nature**: LIFO automatically reverses the order of elements—inserting A, B, C and removing gives C, B, A.","**Temporal locality**: Only the most recent element is accessible. Older elements are hidden until newer ones are removed.","**Implicit nesting**: The structure naturally represents nested or recursive relationships.","**Backtracking support**: Returning to previous states happens automatically by removing recent additions.","**Single point of action**: All operations (add, remove, view) happen at the same end—the top."],"title":{"icon":"Zap","text":"LIFO Behavioral Characteristics","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"content":"### Physical and Conceptual Analogies\n\n**The Stack of Plates**: Imagine cafeteria plates stacked vertically. You can only take from the top (the last plate placed) and add to the top. Plates at the bottom remain inaccessible until all plates above them are removed.\n\n**The Browser Back Button**: Your browser maintains a history stack. Each page visit pushes onto the stack. Clicking 'back' pops the most recent page, revealing the one before it. You must go back through pages in the exact reverse order you visited them.\n\n**Nested Container Boxes**: Imagine boxes nested inside each other. To reach an inner box, you must first remove all the boxes that contain it—the outermost box was placed last and must be removed first.\n\n**Function Call Returns**: When function A calls function B, which calls function C, the returns must happen in reverse order: C returns to B, B returns to A. The last function called is the first to return."},"type":"text"},{"data":{"icon":"Lightbulb","title":"The LIFO Mental Model","content":"When you encounter a problem involving depth-first exploration, undo/redo operations, matching nested structures, or reversing sequences—think LIFO. The key insight is that LIFO naturally handles 'going deep then coming back up' patterns.","variant":"tip"},"type":"callout"}],"titleType":"number","titleNumber":2},{"id":"fifo-deep-dive","title":"FIFO — First-In, First-Out: A Deep Examination","content":[{"data":{"content":"**First-In, First-Out (FIFO)** is the ordering principle where the element that has been in the structure longest is the first one to be removed. If you add elements A, then B, then C to a FIFO structure, the removal order is A, B, C—identical to the insertion order.\n\n### The Core Intuition\n\nFIFO embodies the concept of **fairness** and **sequential processing**. It operates on the premise that items should be processed in the order they arrived—no cutting in line.\n\nFIFO naturally represents situations where:\n\n1. **Order preservation matters**: You want to process items in exactly the sequence they arrived.\n\n2. **Fairness is required**: All items should wait an equal amount of time relative to their arrival.\n\n3. **Level-by-level processing**: You want to handle all items at one 'distance' before moving to the next.\n\n4. **Breadth-first exploration**: Exploring all immediate neighbors before going deeper."},"type":"text"},{"data":{"items":["**Order preservation**: FIFO maintains insertion order—elements exit in the same sequence they entered.","**Fairness property**: No element 'cuts in line'. Older elements are always processed before newer ones.","**Wave propagation**: Naturally represents spread or propagation where you process all items at distance N before distance N+1.","**Scheduling semantics**: First-come-first-served is the natural model for fair task processing.","**Two points of action**: Operations happen at opposite ends—additions at the rear, removals from the front."],"title":{"icon":"CheckCircle","text":"FIFO Behavioral Characteristics","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"content":"### Physical and Conceptual Analogies\n\n**The Queue of People**: People line up at a checkout counter. The person who arrived first gets served first. New arrivals join at the end. This is the quintessential FIFO model.\n\n**The Print Queue**: Documents sent to a printer wait in a queue. The first document submitted is the first to print. Late arrivals wait their turn.\n\n**A Water Pipe**: Water entering a pipe first exits first. There's no way for later water to 'jump ahead' of earlier water.\n\n**Breadth-First Search**: Exploring a maze level by level. You visit all cells one step away before cells two steps away. The queue ensures you process cells in order of distance from the start.\n\n**Assembly Line**: Products move along a conveyor belt, processed in the order they arrived at each station."},"type":"text"},{"data":{"icon":"Lightbulb","title":"The FIFO Mental Model","content":"When you encounter a problem involving first-come-first-served processing, level-order traversal, shortest path in unweighted graphs, order-preserving buffering, or fair scheduling—think FIFO. The key insight is that FIFO naturally handles 'process everything at this level before going deeper' patterns.","variant":"tip"},"type":"callout"}],"titleType":"number","titleNumber":3},{"id":"side-by-side-comparison","title":"LIFO vs FIFO: Side-by-Side Comparison","content":[{"data":{"content":"Now that we've examined each principle individually, let's put them side by side to crystallize their differences and similarities."},"type":"text"},{"data":{"rows":[["Core Principle","Last-In, First-Out","First-In, First-Out"],["Removal Order","Reverse of insertion order","Same as insertion order"],["Analogy","Stack of plates, browser history","Line of people, print queue"],["Fairness","Unfair—newer items processed first","Fair—older items processed first"],["Access Point(s)","Single end (the top)","Two ends (front and rear)"],["Natural Pattern","Depth-first, nested structures","Breadth-first, level-order"],["Reversal Effect","Reverses element order naturally","Preserves element order"],["Mental Model","Going deep, then coming back up","Spreading outward level by level"]],"caption":"Fundamental Comparison of LIFO and FIFO","headers":["Aspect","LIFO (Stack)","FIFO (Queue)"]},"type":"table"},{"data":{"left":[{"data":{"items":["Undo/redo operations","Function call management","Parsing nested structures","Depth-first graph traversal","Backtracking algorithms","Expression evaluation","Browser history navigation"],"title":{"icon":"Target","text":"When LIFO Shines","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"}],"right":[{"data":{"items":["Task scheduling","Order-preserving buffers","Breadth-first traversal","Shortest path algorithms","Message queues","Print spooling","CPU scheduling (round-robin)"],"title":{"icon":"Target","text":"When FIFO Shines","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"}]},"type":"two-column"}],"titleType":"number","titleNumber":4},{"id":"behavioral-consequences","title":"Behavioral Consequences of Each Principle","content":[{"data":{"content":"The choice between LIFO and FIFO isn't merely aesthetic—it has profound behavioral consequences for your algorithms.\n\n### LIFO Creates Depth-First Behavior\n\nWhen you use LIFO for traversal or exploration, you naturally get **depth-first** behavior. Consider exploring a tree:\n\n1. Start at the root, push it onto the stack\n2. Pop the root, push all its children\n3. Pop a child (the last one pushed), push *its* children\n4. Continue...\n\nThe result? You dive deep into one branch before backtracking and exploring siblings. The most recently discovered node is always explored next.\n\n### FIFO Creates Breadth-First Behavior\n\nWhen you use FIFO for traversal, you naturally get **breadth-first** behavior:\n\n1. Start at the root, enqueue it\n2. Dequeue the root, enqueue all its children\n3. Dequeue the first child (added first), enqueue *its* children\n4. Continue...\n\nThe result? You explore all nodes at depth 1 before any at depth 2, all at depth 2 before any at depth 3. The oldest discovered node is always explored next."},"type":"text"},{"data":{"fileName":"traversal_comparison.py","languages":[{"code":"$74","label":"Python","value":"python"},{"code":"$75","label":"TypeScript","value":"typescript"}]},"type":"code"},{"data":{"icon":"AlertCircle","title":"The Same Algorithm, Different Data Structure, Different Behavior","content":"Notice how the traversal algorithm structure is nearly identical—only the data structure changes! This demonstrates a profound principle: the choice of LIFO vs FIFO fundamentally transforms algorithm behavior without changing the algorithm's logical structure.","variant":"warning"},"type":"callout"}],"titleType":"number","titleNumber":5},{"id":"reversal-property","title":"The Reversal Property of LIFO","content":[{"data":{"content":"$76"},"type":"text"},{"data":{"fileName":"reversal_examples.py","languages":[{"code":"def reverse_string_with_stack(s: str) -> str:\n \"\"\"LIFO naturally reverses a sequence\"\"\"\n stack = []\n \n # Push all characters\n for char in s:\n stack.append(char)\n \n # Pop all characters - they come out reversed\n reversed_chars = []\n while stack:\n reversed_chars.append(stack.pop())\n \n return ''.join(reversed_chars)\n\n# Example: reverse_string_with_stack(\"hello\") -> \"olleh\"\n\ndef is_palindrome_with_stack(s: str) -> bool:\n \"\"\"Use stack to check palindrome\"\"\"\n stack = []\n n = len(s)\n \n # Push first half\n for i in range(n // 2):\n stack.append(s[i])\n \n # Determine start of second half (skip middle if odd length)\n start = (n + 1) // 2\n \n # Compare second half with reversed first half\n for i in range(start, n):\n if stack.pop() != s[i]:\n return False\n \n return True\n\n# Example: is_palindrome_with_stack(\"racecar\") -> True","label":"Python","value":"python"}]},"type":"code"},{"data":{"content":"### FIFO Preserves Order\n\nIn contrast, FIFO *preserves* order. Elements exit in the same sequence they entered. This matters when:\n\n- **Order-sensitive processing**: Tasks must execute in submission order\n- **Message ordering**: Messages must be delivered in send order\n- **Sequence integrity**: The output sequence must match the input sequence"},"type":"text"},{"data":{"icon":"Info","title":"Reversal as a Feature","content":"When you need to reverse something—whether it's the order of operations, the direction of traversal, or the sequence of elements—LIFO provides that reversal as an intrinsic property, not extra work.","variant":"note"},"type":"callout"}],"titleType":"number","titleNumber":6},{"id":"matching-and-nesting","title":"Matching and Nesting: LIFO's Sweet Spot","content":[{"data":{"content":"LIFO has a unique and powerful relationship with **nested structures**. Whenever you have matched pairs that can nest inside each other, LIFO is almost certainly the right tool.\n\n### The Nesting Insight\n\nConsider matched parentheses: `((()))`\n\nThe key observation is that **the most recently opened parenthesis must be closed first**. You can't close the outer `(` before closing the inner `(` it contains.\n\nThis is precisely what LIFO provides! When you encounter an opening delimiter, push it. When you encounter a closing delimiter, pop and verify it matches.\n\n### Why LIFO Works for Nesting\n\n1. **Each opening creates a new context**: Push captures 'entering' a new level\n2. **Matching closings are innermost first**: Pop captures 'exiting' the most recent level\n3. **Proper nesting ensures LIFO order**: Correctly nested structures close in LIFO order by definition"},"type":"text"},{"data":{"fileName":"nesting_with_lifo.py","languages":[{"code":"def is_balanced(expression: str) -> bool:\n \"\"\"\n LIFO naturally validates nested structures.\n \n The invariant: at any point, the stack contains all \n unmatched opening delimiters, with the most recent on top.\n \"\"\"\n stack = []\n matching = {')': '(', '}': '{', ']': '['}\n \n for char in expression:\n if char in '({[':\n # Opening delimiter: enter a new nesting level\n stack.append(char)\n elif char in ')}]':\n # Closing delimiter: must match most recent opening\n if not stack or stack.pop() != matching[char]:\n return False\n \n # All openings must have been matched\n return len(stack) == 0\n\n# Examples:\n# is_balanced(\"((()))\") -> True (properly nested)\n# is_balanced(\"([{}])\") -> True (mixed but properly nested)\n# is_balanced(\"((())\") -> False (unclosed opening)\n# is_balanced(\"([)]\") -> False (improperly interleaved)","label":"Python","value":"python"}]},"type":"code"},{"data":{"icon":"Lightbulb","title":"The Nesting Pattern","content":"Whenever you see nested or matched pairs—brackets, tags, blocks, scopes—think LIFO. The pattern of 'most recently opened must close first' is the defining characteristic of properly nested structures.","variant":"tip"},"type":"callout"}],"titleType":"number","titleNumber":7},{"id":"wave-propagation","title":"Wave Propagation: FIFO's Sweet Spot","content":[{"data":{"content":"Just as LIFO excels at nesting, FIFO excels at **wave propagation** and **level-order processing**. Whenever you need to process all items at one 'distance' before any at a greater distance, FIFO is your tool.\n\n### The Wave Insight\n\nImagine dropping a stone in a pond. Ripples spread outward in concentric circles. Each ring of the wave reaches points at the same distance from the center before moving to points farther away.\n\nFIFO naturally simulates this behavior:\n1. Enqueue the starting point (the stone's impact)\n2. Dequeue a point, enqueue its neighbors (one step farther)\n3. Since we process in FIFO order, all distance-1 points are dequeued before any distance-2 points\n4. This continues, processing layer by layer\n\n### Why FIFO Works for Wave Propagation\n\n- **Earlier discovered = closer**: Points discovered first are closer to the origin\n- **FIFO processes closer first**: FIFO always processes what we discovered earlier\n- **Result**: Natural distance-ordering without explicit distance tracking"},"type":"text"},{"data":{"fileName":"wave_propagation.py","languages":[{"code":"$77","label":"Python","value":"python"}]},"type":"code"},{"data":{"icon":"Lightbulb","title":"The Wave Pattern","content":"Whenever you need shortest paths, level-order traversal, or any processing where 'closer' items should be handled before 'farther' items—think FIFO. The pattern of 'process all at distance N before distance N+1' is naturally provided by FIFO.","variant":"tip"},"type":"callout"}],"titleType":"number","titleNumber":8},{"id":"summary","title":"Summary: Two Principles, Two Mindsets","content":[{"data":{"content":"We've explored LIFO and FIFO not just as ordering rules, but as **cognitive frameworks** for understanding how to process data over time. Let's consolidate the key insights:"},"type":"text"},{"data":{"type":"ordered","items":["**LIFO (Stack) embodies recency priority** — The most recently added item is processed first, creating reversal, depth-first behavior, and natural support for nesting.","**FIFO (Queue) embodies fairness and sequence preservation** — Items are processed in arrival order, creating breadth-first behavior and natural support for wave propagation.","**LIFO's superpower is handling nested/matched structures** — Wherever you see properly nested pairs, LIFO provides the exact processing order needed.","**FIFO's superpower is level-order processing** — Wherever you need to process items by distance from a source, FIFO naturally orders processing correctly.","**Same algorithm structure, different data structure, completely different behavior** — Swapping between stack and queue transforms depth-first into breadth-first exploration.","**These are cognitive frameworks, not just data structures** — Internalizing LIFO and FIFO thinking helps you instantly recognize which applies to a problem."],"title":{"icon":"CheckCircle","text":"Key Takeaways","type":"icon","color":"primary","variant":"outline-circle"},"variant":"accent"},"type":"list"},{"data":{"icon":"CheckCircle","title":"Page Complete","content":"You now have a deep understanding of LIFO and FIFO as ordering principles. In the next pages, we'll explore specific scenarios where each structure shines—when stacks are the right choice, when queues excel, and how to recognize the signature patterns that point you toward the correct data structure.","variant":"success"},"type":"callout"}],"titleType":"number","titleNumber":9}],"isLocked":false},{"id":"seed_7e9f3c5f4c238eba213a6fa52915d5e3","title":"When to Use Stacks","order":1,"content":null,"isLocked":true},{"id":"seed_7dccc9306eb09250de2465f7fe60a823","title":"When to Use Queues","order":2,"content":null,"isLocked":true},{"id":"seed_6ad686ba540ad35c1c6ceeecc85e4267","title":"Recognizing the Right Structure for the Problem","order":3,"content":null,"isLocked":true}]}},"dataUpdateCount":1,"dataUpdatedAt":1792378592878,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["learningContent","getModule"],{"input":{"slug":"stacks-vs-queues-comparison"},"type":"query"}],"queryHash":"[[\"learningContent\",\"getModule\"],{\"input\":{\"slug\":\"stacks-vs-queues-comparison\"},\"type\":\"query\"}]"},{"dehydratedAt":1792378592943,"state":{"data":{"json":null},"dataUpdateCount":1,"dataUpdatedAt":1792378592902,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["learningContent","getProgress"],{"input":{"moduleId":"seed_20281a299b8600ad9159779c3f61a836"},"type":"query"}],"queryHash":"[[\"learningContent\",\"getProgress\"],{\"input\":{\"moduleId\":\"seed_20281a299b8600ad9159779c3f61a836\"},\"type\":\"query\"}]"},{"dehydratedAt":1792378592943,"state":{"data":{"json":null},"dataUpdateCount":1,"dataUpdatedAt":1792378592903,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["feedback","get"],{"input":{"contentType":"LEARNING_PAGE","contentId":"seed_7dccc9306eb09250de2465f7fe60a823"},"type":"query"}],"queryHash":"[[\"feedback\",\"get\"],{\"input\":{\"contentId\":\"seed_7dccc9306eb09250de2465f7fe60a823\",\"contentType\":\"LEARNING_PAGE\"},\"type\":\"query\"}]"},{"dehydratedAt":1792378592943,"state":{"data":{"json":null},"dataUpdateCount":1,"dataUpdatedAt":1792378592903,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["feedback","getUserLike"],{"input":{"contentType":"LEARNING_PAGE","contentId":"seed_7dccc9306eb09250de2465f7fe60a823"},"type":"query"}],"queryHash":"[[\"feedback\",\"getUserLike\"],{\"input\":{\"contentId\":\"seed_7dccc9306eb09250de2465f7fe60a823\",\"contentType\":\"LEARNING_PAGE\"},\"type\":\"query\"}]"},{"dehydratedAt":1792378592943,"state":{"data":{"json":[]},"dataUpdateCount":1,"dataUpdatedAt":1792378592903,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"success","fetchStatus":"idle"},"queryKey":[["highlights","getHighlights"],{"input":{"contentType":"LEARNING_PAGE","contentId":"seed_7dccc9306eb09250de2465f7fe60a823"},"type":"query"}],"queryHash":"[[\"highlights\",\"getHighlights\"],{\"input\":{\"contentId\":\"seed_7dccc9306eb09250de2465f7fe60a823\",\"contentType\":\"LEARNING_PAGE\"},\"type\":\"query\"}]"},{"dehydratedAt":1792378592943,"state":{"data":"$undefined","dataUpdateCount":0,"dataUpdatedAt":0,"error":null,"errorUpdateCount":0,"errorUpdatedAt":0,"fetchFailureCount":0,"fetchFailureReason":null,"fetchMeta":null,"isInvalidated":false,"status":"pending","fetchStatus":"fetching"},"queryKey":[["highlights","getPopularHighlights"],{"input":{"contentType":"LEARNING_PAGE","contentId":"seed_7dccc9306eb09250de2465f7fe60a823","minCount":2},"type":"query"}],"queryHash":"[[\"highlights\",\"getPopularHighlights\"],{\"input\":{\"contentId\":\"seed_7dccc9306eb09250de2465f7fe60a823\",\"contentType\":\"LEARNING_PAGE\",\"minCount\":2},\"type\":\"query\"}]","promise":"$@78"}]},"children":"$L79"}]