{"product_id":"154900","title":"Mastering MongoDB 7.0 ","description":"\u003ccenter\u003e\u003cdiv style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/tmgdisk01.cafe24.com\/images\/vs\/4172\/sv\/3jYDsmH38VIeT0XIiYJ5f6ZyKQ04Hz.png?v=1765082903\" style=\"max-width:100%;max-height:10px\"\u003e\u003c\/div\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\u003ccenter\u003e\n\n\u003cdiv style=\"width:95%\"\u003e\n\n\u003cdiv style=\"text-align:center;font-size:30px;font-weight:bolder;line-height:1.6em\"\u003e Mastering MongoDB 7.0 \u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"border-bottom:1px;border-bottom-style:dotted;border-color:;padding-bottom:20px\"\u003e\u003ccenter\u003e\u003ctable align=\"center\" width=\"100%\"\u003e\u003ctbody style=\"border:0px\"\u003e\n\n\u003ctr\u003e\u003ctd align=\"center\" style=\"line-height:1.2em;text-align:center;font-size:18px;color:black;font-weight:bold;padding-bottom:20px;\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\u003ctr\u003e\u003ctd style=\"text-align:center\"\u003e\u003cimg src=\"https:\/\/image.yes24.com\/goods\/145719322\/XL\" style=\"max-width:100%;height:auto\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\n\n\n\u003c\/tbody\u003e\u003c\/table\u003e\u003c\/center\u003e\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;{split_style6}padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e Description \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;word-break:break-all;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eBook Introduction\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\u003cdiv\u003e \u003cb\u003eMongoDB technologies needed to build efficient, secure, and high-performance applications\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e This is the ultimate guide that covers everything from using MongoDB to its advanced features.\u003cbr\u003e We begin with MongoDB architecture, developer tools, and database connectivity, then explore advanced queries, including aggregation pipelines and multi-document ACID transactions, and introduce cutting-edge features useful for AI applications, such as Atlas vector search.\u003cbr\u003e This is the first official book written by MongoDB contributors, covering advanced technologies such as Atlas search, RBAC, auditing, and encryption in depth.\u003cbr\u003e The translator, a MongoDB expert, added the contents of version 8.0 as an appendix to the Korean version.\u003cbr\u003e\u003cbr\u003e\n\u003c\/div\u003e\u003c\/div\u003e\n\u003cdiv\u003e\u003cul\u003e\u003cli\u003e You can preview some of the book's contents.\u003cbr\u003e \u003cspan\u003ePreview\u003c\/span\u003e\n\n\u003c\/li\u003e\u003c\/ul\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eindex\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e About the Author and Translator xiv\u003cbr\u003e Introduction to the Technical Reviewer xvii\u003cbr\u003e Translator's Preface xix\u003cbr\u003e Recommendation xxi \u003cbr\u003eBeta Reader Review xxiv\u003cbr\u003e Author's Note xxvii\u003cbr\u003e About this book xxix\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 1 Introduction to MongoDB 1\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 1.1 Who Uses MongoDB? 1\u003cbr\u003e 1.2 Why Developers Prefer MongoDB 2\u003cbr\u003e 1.3 Efficiency of the Inherent Complexity of the MongoDB Database 4\u003cbr\u003e 1.4 Summary 6\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 2 MongoDB Architecture 7\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 2.1 Replication and Sharding 8\u003cbr\u003e 2.2 Replication 8\u003cbr\u003e 2.3 Sharding 17\u003cbr\u003e 2.4 New Sharding Cluster Features in MongoDB 7.0 32\u003cbr\u003e 2.5 Summary 33\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 3 DEVELOPER TOOLS 35\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 3.1 Technical Requirements 36\u003cbr\u003e 3.2 Introduction to Development Tools 36\u003cbr\u003e 3.3 MongoDB Shell 38\u003cbr\u003e 3.4 MongoDB CLI 44\u003cbr\u003e 3.5 MongoDB Compass 48\u003cbr\u003e 3.6 MongoDB for VS Code 53\u003cbr\u003e 3.7 Summary 55\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 4 Connecting to MongoDB 57\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 4.1 Connection Method 57\u003cbr\u003e 4.2 Summary 72\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 5 CRUD Operations and Basic Queries 74\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 5.1 Technical Requirements 74\u003cbr\u003e 5.2 Basic MongoDB Data Operations 75\u003cbr\u003e 5.3 CRUD Processing Using Ruby Driver 85\u003cbr\u003e 5.4 CRUD Processing Using the Python Driver 94\u003cbr\u003e 5.5 Regular Expressions 102\u003cbr\u003e 5.6 Management Functions 104\u003cbr\u003e 5.7 Secure Access to MongoDB 107\u003cbr\u003e 5.8 MongoDB Stable API 110 \u003cbr\u003e5.9 Summary 112\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 6 Schema Design and Data Modeling 113\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 6.1 Schema Design for Relational Databases 114\u003cbr\u003e 6.2 Schema Design for MongoDB 116\u003cbr\u003e 6.3 Data Modeling in MongoDB 117\u003cbr\u003e 6.4 MongoDB Database Modeling: Design Principles and Recommended Practices 122\u003cbr\u003e 6.5 Design Patterns and Schema Design 122\u003cbr\u003e 6.6 Summary 129\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 7 Advanced MongoDB Queries 130\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 7.1 Introduction to the Aggregation Framework 130\u003cbr\u003e 7.2 Benefits of MongoDB Aggregations 132\u003cbr\u003e 7.3 Aggregation Stage 133\u003cbr\u003e 7.4 Query Techniques 147\u003cbr\u003e 7.5 Indexes and Query Optimization 164\u003cbr\u003e 7.6 MongoDB Location-Based Data Processing 169\u003cbr\u003e 7.7 Summary 172\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 8 Tally 173\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 8.1 Technical Requirements 174\u003cbr\u003e 8.2 MongoDB Aggregation Framework 174\u003cbr\u003e 8.3 Basic Aggregation Operators 179\u003cbr\u003e 8.4 Best Practices 192\u003cbr\u003e 8.5 Summary 194\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 9 Multi-Document ACID Transactions 195\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 9.1 Why are transactions useful? 196\u003cbr\u003e 9.2 ACID Properties 196\u003cbr\u003e 9.3 MongoDB Implementation of ACID 199\u003cbr\u003e 9.4 Best Practices 212\u003cbr\u003e 9.5 Summary 213\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 10: INDEX OPTIMIZATION 214\u003c\/b\u003e\u003cbr\u003e \u003cbr\u003e10.1 Introduction to Index 215\u003cbr\u003e 10.2 Index Types 220\u003cbr\u003e 10.3 Index Optimization Best Practices 240\u003cbr\u003e 10.4 Summary 240\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 11 MongoDB Atlas 242\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 11.1 MongoDB Atlas as a Database Service 243\u003cbr\u003e 11.2 Atlas Developer Data Platform 255\u003cbr\u003e 11.3 Atlas Vector Search and Its Role in AI Applications 255\u003cbr\u003e 11.4 Atlas Application Services 259\u003cbr\u003e 11.5 Atlas Data API 262\u003cbr\u003e 11.6 Atlas Data Lake 265\u003cbr\u003e 11.7 Atlas Data Federation 266\u003cbr\u003e 11.8 Atlas Stream Processing 269\u003cbr\u003e 11.9 Atlas SQL Interface 272\u003cbr\u003e 11.10 MongoDB Atlas Chart 274\u003cbr\u003e 11.11 Operational Integration: Atlas Kubernetes Operator 277\u003cbr\u003e 11.12 Atlas CLI 280\u003cbr\u003e 11.13 Summary 282\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 12 MongoDB Monitoring and Backup 283\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 12.1 MongoDB Monitoring 283\u003cbr\u003e 12.2 What Should I Monitor? 285\u003cbr\u003e 12.3 Monitoring WiredTiger Memory Usage 291\u003cbr\u003e 12.4 Page Fault Tracing 291\u003cbr\u003e 12.5 Working Set Calculation 293 \u003cbr\u003e12.6 MongoDB Reporting Tools Overview 294\u003cbr\u003e 12.7 Hosting Monitoring Tools Overview 295\u003cbr\u003e 12.8 How to Backup MongoDB 297\u003cbr\u003e 12.9 Common Mistakes and Pitfalls in MongoDB Monitoring and Backups 302\u003cbr\u003e 12.10 Summary 304\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 13 Atlas Search 305\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 13.1 MongoDB Atlas Search 306\u003cbr\u003e 13.2 The Technical Structure and Operation of the Atlas Search Index 309\u003cbr\u003e 13.3 Apache Lucene 328\u003cbr\u003e 13.4 Summary 331\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 14 Integrating Applications with MongoDB 333\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 14.1 Technical Requirements 333\u003cbr\u003e 14.2 Integrating Applications with MongoDB 334\u003cbr\u003e 14.3 MongoDB Kubernetes Operator 336\u003cbr\u003e 14.4 Integrating Terraform and MongoDB 340\u003cbr\u003e 14.5 Using Versell with MongoDB 344\u003cbr\u003e 14.6 Integrating Datadog and MongoDB 348\u003cbr\u003e 14.7 Integrating Prometheus and MongoDB 353\u003cbr\u003e 14.8 Integrating Webhooks with MongoDB 357\u003cbr\u003e 14.9 Phaser Duty Integrated 361\u003cbr\u003e 14.10 Summary 365\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 15 Security 367\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 15.1 Authentication Method 368\u003cbr\u003e 15.2 Role-Based Access Control (RBAC) 385\u003cbr\u003e 15.3 Summary 396\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 16 Gratitude 397\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 16.1 MongoDB Auditing and Logging 398 \u003cbr\u003e16.2 Auditable Event Types 401\u003cbr\u003e 16.3 Enabling Auditing in MongoDB 402\u003cbr\u003e 16.4 Case Study: The Role of Auditing in Compliance 410\u003cbr\u003e 16.5 Troubleshooting Auditing Issues in MongoDB 411\u003cbr\u003e 16.6 Summary 413\u003cbr\u003e\u003cbr\u003e \u003cb\u003eCHAPTER 17: Encryption 414\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e 17.1 Encryption Types 415\u003cbr\u003e 17.2 Encryption in Transit 416\u003cbr\u003e 17.3 Encryption at Rest 421\u003cbr\u003e 17.4 Client-Side Encryption 426\u003cbr\u003e 17.5 Summary 432\u003cbr\u003e\u003cbr\u003e \u003cb\u003eAPPENDIX A New Features and Improvements in MongoDB 8.0 433\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e A.1 Supported Platforms and Operating Systems 433\u003cbr\u003e A.2 Enhanced Monitoring and Performance Analysis Capabilities 433\u003cbr\u003e A.3 Enhanced Security Features 434\u003cbr\u003e A.4 Enhanced Flexibility of Sharding Functions 434\u003cbr\u003e A.5 Replication Performance Improvements 435\u003cbr\u003e A.6 System Management Function Improvements 435\u003cbr\u003e A.7 Performance Optimization 436\u003cbr\u003e A.8 Precautions when upgrading 437\u003cbr\u003e\u003cbr\u003e \u003cb\u003eAPPENDIX B MongoDB 8.0 Compatibility Guide and Major Changes 438\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e B.1 New Changes in Query Behavior 438\u003cbr\u003e B.2 Deprecated Features 439\u003cbr\u003e B.3 Major changes for performance improvements 439\u003cbr\u003e B.4 Additional Improvements 440\u003cbr\u003e B.5 Finish 440\u003cbr\u003e\u003cbr\u003e Search 441\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e  \u003ch5\u003e\n\u003cb\u003eDetailed image\u003c\/b\u003e \u003c\/h5\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003cdiv\u003e\u003cimg src=\"https:\/\/image.yes24.com\/momo\/TopCate5284\/MidCate003\/528320453.jpg\" border=\"0\" alt=\"Detailed Image 1\"\u003e\u003c\/div\u003e\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003eInto the book\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e Just 10 years ago, MongoDB was a niche product.\u003cbr\u003e It was a young database that was attractive only to leading developers.\u003cbr\u003e But today, MongoDB is used across a wide variety of industries, with use cases spanning all sorts of situations and types of data stored.\u003cbr\u003e The world's largest banks, automakers, government agencies, and gaming companies use MongoDB in their production applications.\u003cbr\u003e Some of the most notable companies using MongoDB include Coinbase, Epic Games, Morgan Stanley, Adobe, Tesla, Canva, Ulta Beauty, Cathay Pacific, Dongwha, and Vodafone.\u003cbr\u003e\u003cbr\u003e --- p.1\u003cbr\u003e\u003cbr\u003e Mongoid is a leading ODM for MongoDB, allowing developers to intuitively and efficiently handle MongoDB databases in the Ruby on Rails framework. \u003cbr\u003eWhile low-level drivers offer great flexibility, Mongoid provides high-level abstractions that integrate well with Rails' naming conventions, improving developer productivity.\u003cbr\u003e This seamless integration simplifies tasks like schema definition, query writing, and data modeling, allowing developers to focus on application logic rather than database implementation. Like an ORM, an ODM minimizes the gap between the model and the database.\u003cbr\u003e --- pp.91-92\u003cbr\u003e\u003cbr\u003e One of MongoDB's most notable features is its flexible document structure.\u003cbr\u003e It supports BSON documents and arrays with nesting up to 100 levels, which provides practical benefits beyond just technical features.\u003cbr\u003e This deep structure not only maximizes the flexibility of the database, but also allows you to organize data in a way that is optimized for your application's needs. \u003cbr\u003eIn particular, these structural features provide three key advantages:\u003cbr\u003e First, it greatly reduces the need for complex join operations.\u003cbr\u003e It also makes the data retrieval process efficient and finally simplifies query writing.\u003cbr\u003e\u003cbr\u003e --- p.117\u003cbr\u003e\u003cbr\u003e The $gt(greater than) operator is used to search for data that exceeds a specified value.\u003cbr\u003e For example, it is effective for tasks such as finding products above a certain price or viewing transaction details after a reference date.\u003cbr\u003e On the other hand, the $lt (less than) operator is used to find data that is less than a specified value.\u003cbr\u003e This is useful in situations such as identifying products whose inventory quantity is below a certain threshold or retrieving records from a specific period of time.\u003cbr\u003e --- p.153\u003cbr\u003e\u003cbr\u003e A key feature of composite indexes is the support for a variety of queries that utilize prefixes on the index fields. \u003cbr\u003eFor example, the composite index in the example above supports queries that combine author and ISBN code, as well as queries that use only the author field, which is the first field in the index.\u003cbr\u003e On the other hand, queries performed on ISBN codes alone cannot utilize the index and result in a full collection scan.\u003cbr\u003e (…) Composite indexes store document references in the order of their defined fields.\u003cbr\u003e Figure 10.4 is an example showing this structure.\u003cbr\u003e First, you can see that the sorting is done in ascending order (alphabetical order) based on the userid, and then the scores are sorted in descending order within each userid.\u003cbr\u003e\u003cbr\u003e --- p.222\u003cbr\u003e\u003cbr\u003e Vector search is a technique for searching based on the meaning of data.\u003cbr\u003e This technology uses a machine learning model called an encoder to convert various data such as text, audio, and images into high-dimensional vectors. \u003cbr\u003eThe vectors generated in this way contain the semantic characteristics of the data, so we can find vectors that are close to each other in a high-dimensional space and identify similar content.\u003cbr\u003e These vector searches can effectively complement traditional keyword-based searches.\u003cbr\u003e In particular, it has recently attracted significant attention because it can provide additional information that goes beyond the limitations of large language models (LLMs).\u003cbr\u003e In real-world search, it has the advantage of being able to find relevant results even when the exact search term is unknown, and its usefulness has been proven in various fields such as natural language processing and recommendation systems.\u003cbr\u003e\n\n\u003c\/div\u003e\n\u003cdiv\u003e --- pp.255-256\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003cbr\u003e\u003cdiv\u003e\u003ch5\u003e \u003cb\u003ePublisher's Review\u003c\/b\u003e\n\u003c\/h5\u003e\u003c\/div\u003e\n\u003cdiv\u003e\n\u003cdiv\u003e \u003cb\u003eThe long-awaited, best+latest MongoDB guidebook\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e Although MongoDB has steadily evolved in a developer-friendly direction, no related books have been published in Korea for some time. \u003cbr\u003eThis book is the first official MongoDB book written directly by MongoDB staff.\u003cbr\u003e The original book was written based on the latest version at the time of publication, 7.0, but later version 8.0 was released, and the contents of 8.0 were supplemented with notes and appendices. This Korean translation published by Jaypub is “Mastering MongoDB 7.0 (4th Edition).”\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e We begin with the fundamentals, including architecture and developer tools, that developers need to understand to utilize MongoDB. This book covers practical topics, including CRUD queries, schema design and data modeling, advanced queries, aggregation pipelines, multi-document ACID transactions, and index optimization, with hands-on examples.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e Next, we'll explore the Atlas Developer Data Platform and its related products, which enable you to fully leverage MongoDB as a DBaaS. It's notable for covering how to leverage cutting-edge products like Atlas Vector Search, which is useful for AI applications. \u003cbr\u003eWe then explore monitoring and backup, Atlas search, and integration with third-party applications, and cover more advanced topics such as security, auditing, and encryption, including RBAC.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e Among all the MongoDB books published in Korea, this one is the best in terms of scope and expertise.\u003cbr\u003e This is not an exaggeration, it is a fact.\u003cbr\u003e\u003cbr\u003e\u003cbr\u003e \u003cb\u003eKey Contents\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003e ● Run advanced queries to gain data insights\u003cbr\u003e ● Data transformation leveraging the powerful capabilities of the aggregation pipeline\u003cbr\u003e ● Ensure data integrity with multi-document ACID transactions\u003cbr\u003e ● Optimizing query performance using strategic indexing techniques\u003cbr\u003e ● Monitoring and backup using MongoDB Atlas\u003cbr\u003e ● Use powerful search features with Atlas Search\u003cbr\u003e ● RBAC, user management, and data encryption for security\u003cbr\u003e Auditing practices that ensure transparency and accountability \u003c\/div\u003e\n\u003cdiv\u003e\u003c\/div\u003e\n\u003c\/div\u003e\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cdiv style=\"width:95%;padding-top:20px;padding-bottom:20px\"\u003e\n\n\u003cdiv style=\"text-align:left;font-size:16px;font-weight:bold;padding-bottom:20px\"\u003e GOODS SPECIFICS \u003c\/div\u003e\n\n\u003cdiv style=\"text-align:left;font-size:14px;line-height:1.6em;\"\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eDate of issue:\u003c\/strong\u003e May 20, 2025\u003c\/div\u003e\n\n \u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e- \u003cstrong\u003ePage count, weight, size:\u003c\/strong\u003e 476 pages | 188*245*23mm\u003c\/div\u003e\n\n\u003cdiv style=\"width:100%;margin-bottom:5px;line-height:1.6em;font-size:14px\"\u003e - \u003cstrong\u003eISBN13:\u003c\/strong\u003e 9791194587217 \u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\n\u003c\/div\u003e\n\n\u003ccenter\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003ccenter\u003e\u003ctable\u003e\u003ctr\u003e\u003ctd style=\"height:10px\"\u003e\u003c\/td\u003e\u003c\/tr\u003e\u003c\/table\u003e\u003c\/center\u003e\n\n\u003cspan\u003e\u003c\/span\u003e\n\n\u003c\/center\u003e\n\n\n\u003c\/center\u003e","brand":"LIBRAIRIE COREENNE","offers":[{"title":"Default Title","offer_id":43893478686762,"sku":"154900","price":45.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0683\/2750\/5962\/files\/4f5e5ea0c4c185c0d5b7b26bd0a0b800.jpg?v=1765403306","url":"https:\/\/librairie.coreenne.fr\/en\/products\/154900","provider":"LIBRAIRIE COREENNE","version":"1.0","type":"link"}