Python Data Persistence: With SQL and NOSQL Databases
- Length: 316 pages
- Edition: 1
- Language: English
- Publisher: BPB Publications
- Publication Date: 2019-08-16
- ISBN-10: 9388511751
- ISBN-13: 9789388511759
- Sales Rank: #2260901 (See Top 100 Books)
Designed to provide an insight into the SQL and MySQL database concepts using python.
Key Features
- A practical approach
- Ample code examples
- A Quick Start Guide to Python for beginners
Description
Python is becoming increasingly popular among data scientists. However, analysis and visualization tools need to interact with the data stored in various formats such as relational and NOSQL databases.
This book aims to make the reader proficient in interacting with databases such as MySQL, SQLite, MongoDB, and Cassandra.
This book assumes that the reader has no prior knowledge of programming. Hence, basic programming concepts, key concepts of OOP, serialization and data persistence have been explained in such a way that it is easy to understand. NOSQL is an emerging technology. Using MongoDB and Cassandra, the two widely used NOSQL databases are explained in detail.
The knowhow of handling databases using Python will certainly be helpful for readers pursuing a career in Data Science.
What Will You Learn
- Python basics and programming fundamentals
- Serialization libraries pickle, CSV, JSON, and XML
- DB-AP and, SQLAlchemy
- Python with Excel documents
- Python with MongoDB and Cassandra
Who This Book Is For
Students and professionals who want to become proficient at database tools for a successful career in data science.
About the Author
Malhar Lathkar is an Independent software professional / Programming technologies trainer/E-Learning Subject matter Expert. He is a of Director Institute of Programming Language Studies, having an academic experience of 33 years. His expertise is in Java, Python, C#, IoT, PHP, databases.
His linkedIn: linkedin.com/in/malharlathkar
His blog: indsport.blogspot.com
Cover Page Title Page Copyright Page Preface About the Author Code Bundle Table of Contents 1. Getting Started 1.1 Installation 1.2 Interactive Mode 1.3 Scripting Mode 1.4 Identifiers 1.5 Statements 1.6 Indents 1.7 Comments 1.8 Data Types 1.9 Variables 1.10 Built-in Functions 1.11 Methods of Built-in Data Type Classes 2. Program Flow Control 2.1 Decision Control 2.2 Repetition 2.3 while Statement 2.4 for Keyword 2.5 Using Range 2.6 for loop with Dictionary 2.7 Repetition Control 2.8 Nested Loops 2.9 List Comprehension 3. Structured Python 3.1 Function 3.2 math Module 3.3 os module 3.4 sys Module 3.5 User Defined Functions 3.6 Function with Parameters 3.7 return Keyword 3.8 Required Arguments 3.9 Parameter with Default Value 3.10 Keyword Arguments 3.11 Function with Variable Arguments 3.12 User Defined Modules 3.13 Package 3.14 Virtual Environment 4. Python - OOP 4.1 Class Keyword 4.2 Constructor 4.3 __slots__ 4.4 Getters/setters 4.5 property() Function 4.6 @property Decorator 4.7 Class Level Attributes and Methods 4.8 Inheritance 4.9 Overriding 4.10 Magic Methods 5. File IO 5.1 Opening File 5.2 Writing to File 5.3 Reading a File 5.4 Write/Read Binary File 5.5 Simultaneous Read/Write 5.6 File Handling using os Module 5.7 File/Directory Management Functions 5.8 Exceptions 6. Object Serialization 6.1 pickle Module 6.2 shelve Module 6.3 dbm Modules 6.4 csv module 6.5 json Module 6.6 xml Package 6.7 plistlib Module 7. RDBMS Concepts 7.1 Drawbacks of Flat File 7.2 Relational Database 7.3 RDBMS Products 7.4 SQLite Installation 7.5 SQLite Data Types 7.6 CREATE TABLE 7.7 Constraints 7.8 INSERT Statement 7.9 SELECT Statement 7.10 UPDATE Statement 7.11 DELETE Statement 7.12 ALTER TABLE statement 7.13 DROP TABLE Statement 7.14 Transaction Control 7.15 MySQL 7.16 SQLiteStudio 8. Python DB-API 8.1 sqlite3 Module 8.2 Connection Object 8.3 Cursor Object 8.4 Creating Table 8.5 Inserting Rows 8.6 Updating Data 8.7 Deleting Rows 8.8 ResultSet Object 8.9 User Defined Functions 8.10 Row Object 8.11 Backup and Restore Database 8.12 Using pymysql Module 8.13 pyodbc Module 9. Python - SQLAlchemy 9.1 What is ORM? 9.2 SQLAlchemy ORM 9.3 ORM - Table Object and Mapped Class 9.4 ORM - Session object 9.5 ORM - Add Data 9.6 ORM - Querying 9.7 ORM - Filter criteria 9.8 ORM - Update Data 9.9 ORM - Relationships 9.10 Querying related tables (ORM) 9.11 SQLAlchemy Core 9.12 Core - Inserting Records 9.13 Core - Updating Records 10. Python and Excel 10.1 Excel with openpyxml 10.2 Creating a workbook 10.3 Read Data from Worksheet 10.4 Read Cell Range to List 10.5 Merge and Center 10.6 Define Formula 10.7 Copy Formula 10.8 Charts 10.9 Insert Image 10.10 Excel with Pandas 10.11 Pandas DataFrame to Excel 10.12 Read worksheet to Pandas DataFrame 11. Python – PyMongo 11.1 What is NOSQL? 11.2 MongoDB 11.3 Installation of MongoDB 11.4 MongoDB - Create Database 11.5 MongoDB - Insert Document 11.6 MongoDB - Querying Collection 11.7 MongoDB – Update Document 11.8 MongoDB – Delete Document 11.9 PyMongo Module 11.10 PyMongo – Add Collection 11.11 PyMongo – Querying Collection 11.12 PyMongo – Update Document 11.13 PyMongo – Relationships 12. Python - Cassandra 12.1 Cassandra Architecture 12.2 Installation 12.3 CQL Shell 12.4 Create Keyspace 12.5 Inserting Rows 12.6 Querying Cassandra Table 12.7 Table with Compound Partition Key 12.8 Python Cassandra Driver 12.9 Parameterized Queries 12.10 User-defined Types Appendix A: Alternate Python Implementations Appendix B: Alternate Python Distributions Appendix C: Built-in Functions Appendix D: Built-in Modules Appendix E: Magic Methods Appendix F: SQLite Dot Commands Appendix G: ANSI SQL Statements Appendix H: PyMongo API Methods Appendix I: Cassandra CQL Shell Commands
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