Introduction To Data Systems: Building From Python

Preface
	Who Is This Book for?
	Philosophy of This Book
	Web Resources
	To Students
	To Instructors
	Software Assumptions
	Online Corrigenda
	Acknowledgments
Contents
Part I Foundation
	1 Introduction
		1.1 A Broad View of Data Systems
			1.1.1 Reading Questions
		1.2 The Sources of Data
			1.2.1 Reading Questions
		1.3 The Forms of Data
			1.3.1 Reading Questions
		1.4 Book Organization
			1.4.1 Exercises
	2 File Systems and File Processing
		2.1 File Systems
			2.1.1 Hierarchical Organization
			2.1.2 Paths
			2.1.3 Python File System and Path Facilities
			2.1.4 Reading Questions
			2.1.5 Exercises
		2.2 File Level Operations
			2.2.1 File Open and Close
			2.2.2 Text File Encoding
			2.2.3 Reading Questions
			2.2.4 Exercises
		2.3 Processing Files for Data
			2.3.1 Single Data Item per Line
			2.3.2 Multiple Data Items per Line
			2.3.3 Reading Questions
			2.3.4 Exercises
		2.4 JSON File Processing
			2.4.1 Writing Data Structures to JSON
			2.4.2 Reading Data Structures from JSON
			2.4.3 Reading Questions
			2.4.4 Exercises
	3 Python Native Data Structures
		3.1 List Patterns
			3.1.1 Accumulation
			3.1.2 Unary Vector Operations
			3.1.3 Binary Vector Operations
			3.1.4 Filter
			3.1.5 Reduction
			3.1.6 Reading Questions
			3.1.7 Exercises
				3.1.7.1 Accumulation
				3.1.7.2 Unary Vector Operations
				3.1.7.3 Binary Vector Operations
				3.1.7.4 Filtering
		3.2 Dictionaries
			3.2.1 Reading Questions
			3.2.2 Exercises
		3.3 Python Features
			3.3.1 Functions as Objects
			3.3.2 Lambda Functions
			3.3.3 List Comprehensions
			3.3.4 Reading Questions
			3.3.5 Exercises
				3.3.5.1 Functions as Objects
				3.3.5.2 Mapping Functions
				3.3.5.3 Lambda Functions
				3.3.5.4 List Comprehensions
		3.4 Representing General Data Sets
			3.4.1 Dictionary of Lists
			3.4.2 List of Lists
			3.4.3 List of Dictionaries
			3.4.4 Reading Questions
			3.4.5 Exercises
	4 Regular Expressions
		4.1 Motivation
			4.1.1 Reading Questions
		4.2 Terminology
			4.2.1 Reading Questions
		4.3 The Regular Expression Language
			4.3.1 Literal Characters
			4.3.2 Single Character Wildcard Matching
				4.3.2.1 Dot
				4.3.2.2 Predefined Single Character Sets
				4.3.2.3 User-Defined Single Character Sets
			4.3.3 Repetition
			4.3.4 Disjunction
			4.3.5 Boundaries/Anchors
			4.3.6 Grouping
			4.3.7 Flags
				4.3.7.1 Case Insensitive
				4.3.7.2 Multi-line
				4.3.7.3 Single Line
			4.3.8 Reading Questions
			4.3.9 Exercises
		4.4 Python Programming with Regular Expressions
			4.4.1 Specifying Patterns
			4.4.2 The re Module Interface
			4.4.3 Reading Questions
			4.4.4 Exercises
Part II Data Systems: The Data Models
	5 Data Systems Models
		5.1 Data Model Framework
			5.1.1 Structure
			5.1.2 Operations
			5.1.3 Constraints
			5.1.4 Reading Questions
		5.2 Tabular Model Overview
			5.2.1 Structure
			5.2.2 Operations
			5.2.3 Constraints
			5.2.4 Reading Questions
		5.3 Relational Model Overview
			5.3.1 Structure
			5.3.2 Operations
			5.3.3 Constraints
			5.3.4 Reading Questions
		5.4 Hierarchical Model Overview
			5.4.1 Structure
			5.4.2 Operations
			5.4.3 Constraints
			5.4.4 Reading Questions
	6 Tabular Model: Structure and Formats
		6.1 Tidy Data
			6.1.1 Reading Questions
			6.1.2 Exercises
		6.2 Tabular Data Format
			6.2.1 Format Background
			6.2.2 Format for Tabular Data
				6.2.2.1 Tabular Format Design
			6.2.3 Tabular Format File Processing
				6.2.3.1 CSV Parsing [Optional]
			6.2.4 Reading Questions
			6.2.5 Exercises
		6.3 Tabular Structure as pandas DataFrame
			6.3.1 DataFrame Creation
			6.3.2 Operations Involving Whole Data Frames
			6.3.3 Reading Questions
			6.3.4 Exercises
	7 Tabular Model: Access Operations and Pandas
		7.1 Tabular Operations Overview
			7.1.1 Access Operations
			7.1.2 Computational Operations
			7.1.3 Mutation Operations
			7.1.4 Advanced Operations
			7.1.5 Reading Questions
		7.2 Preliminaries and Example Data Sets
			7.2.1 Reading Questions
		7.3 Access and Computation Operations
			7.3.1 Single Column Projection and Vector Operations
			7.3.2 Multi-Column Projection of a DataFrame
			7.3.3 Row Selection by Slice
				7.3.3.1 Position Slicing for Selecting Rows
				7.3.3.2 Index Slicing for Selecting Rows
			7.3.4 Row Selection by Condition
			7.3.5 Combinations of Projection and Selection
				7.3.5.1 Access a Single Element
				7.3.5.2 Querying a Single Column or Single Row
				7.3.5.3 Querying a Subset of a Single Column or Single Row
				7.3.5.4 Generalized Projection and Selection
			7.3.6 Iteration over Rows and Columns
			7.3.7 Reading Questions
			7.3.8 Exercises
	8 Tabular Model: Advanced Operations and Pandas
		8.1 Aggregating and Grouping Data
			8.1.1 Aggregating Single Series
			8.1.2 Aggregating a Data Frame
			8.1.3 Aggregating Selected Rows
			8.1.4 General Partitioning and GroupBy
			8.1.5 Indicators Grouping Example
			8.1.6 Reading Questions
			8.1.7 Exercises
		8.2 Mutation Operations for a Data Frame
			8.2.1 Operations to Delete Columns and Rows
				8.2.1.1 Single Column Deletion
				8.2.1.2 Multiple Column Deletion
				8.2.1.3 Row Deletion
			8.2.2 Operation to Add a Column
			8.2.3 Updating Columns
				8.2.3.1 Update Entire Column
				8.2.3.2 Selective Column Assignment
			8.2.4 Reading Questions
			8.2.5 Exercises
		8.3 Combining Tables
			8.3.1 Concatenating Data Frames Along the Row Dimension
				8.3.1.1 Meaningful Row Index
				8.3.1.2 Meaningful Index with Levels
				8.3.1.3 No Meaningful Index
			8.3.2 Concatenating Data Frames Along the Column Dimension
				8.3.2.1 Single Level Row Index and New Columns
				8.3.2.2 Introducing a Column Level
			8.3.3 Joining/Merging Data Frames
				8.3.3.1 Using Index Level
				8.3.3.2 Using Specific Columns
			8.3.4 Reading Questions
			8.3.5 Exercises
		8.4 Missing Data Handling
			8.4.1 Reading Questions
	9 Tabular Model: Transformations and Constraints
		9.1 Tabular Model Constraints
			9.1.1 Reading Questions
			9.1.2 Exercises
		9.2 Tabular Transformations
			9.2.1 Transpose
			9.2.2 Melt
				9.2.2.1 [Optional] Stack Examples
			9.2.3 Pivot
				9.2.3.1 Pivot Table
			9.2.4 Reading Questions
			9.2.5 Exercises
		9.3 Normalization: A Series of Vignettes
			9.3.1 Column Values as Mashup
				9.3.1.1 Example: Code and Country Mashup
				9.3.1.2 Example: Year and Month Mashup
			9.3.2 One Relational Mapping per Row
				9.3.2.1 Example: One Value Column and One Index Column
				9.3.2.2 Example: One Value Column and Two Index Columns
			9.3.3 Columns as Values and Mashups
				9.3.3.1 Example: Single Variable with Multiple Years
				9.3.3.2 Example: Multiple Variables with Multiple Years
			9.3.4 Exactly One Table per Logical Mapping
				9.3.4.1 Example: Variable Values as Two Tables
				9.3.4.2 Example: Separate Logical Mappings in a Single Table
			9.3.5 Reading Questions
		9.4 Recognizing Messy Data
			9.4.1 Focus on Each Column as Exactly One Variable (TidyData1)
			9.4.2 Focus on Each Row Giving Exactly One Mapping (TidyData2)
			9.4.3 Focus on Each Table Representing One Data Set (TidyData3)
			9.4.4 Reading Questions
			9.4.5 Exercises
	10 Relational Model: Structure and Architecture
		10.1 Background
			10.1.1 Motivation and Requirements
			10.1.2 The Relational Database Solution
			10.1.3 Types of Relational Databases
			10.1.4 Reading Questions
		10.2 Structure
			10.2.1 Single Table Characteristics
				10.2.1.1 Functional Dependencies
				10.2.1.2 Table Keys
				10.2.1.3 Illustrative Example
			10.2.2 Multiple Table Characteristics
			10.2.3 Reading Questions
		10.3 Database Architecture
			10.3.1 Reading Questions
	11 Relational Model: Single Table Operations
		11.1 Example Data Sets
			11.1.1 Reading Questions
		11.2 Projecting Column Fields
			11.2.1 Single Column Field Projection
			11.2.2 Multiple Column Field Projection
			11.2.3 Simple Subquery
			11.2.4 Ordering Results
			11.2.5 Reading Questions
			11.2.6 Exercises
		11.3 Selecting and Filtering Rows
			11.3.1 Uniqueness Filtering
			11.3.2 Row Selection by Filtering
			11.3.3 Missing Values
			11.3.4 Additional Examples
			11.3.5 Reading Questions
			11.3.6 Exercises
		11.4 Column-Vector Operations
			11.4.1 Reading Questions
			11.4.2 Exercises
		11.5 Aggregation
			11.5.1 Counting Rows for Fields
			11.5.2 Reading Questions
			11.5.3 Exercises
		11.6 Partitioning and Aggregating
			11.6.1 Reading Questions
			11.6.2 Exercises
	12 Relational Model: Multiple Tables Operations
		12.1 Preliminaries and Example Data Set
			12.1.1 Data Set: The school Database Schema
			12.1.2 Table Relationships
			12.1.3 SQL Execution Plan
			12.1.4 Reading Questions
			12.1.5 Exercises
		12.2 Overview of Join Operations
		12.3 Inner Joins
			12.3.1 Two Table SQL Inner Join
			12.3.2 [Optional] Cartesian Product-Based Inner Join
			12.3.3 Inner Join to Fill Redundant Fields
			12.3.4 Three-Table Join
			12.3.5 Join Table from a Subquery
			12.3.6 Reading Questions
			12.3.7 Exercises
		12.4 Outer Joins
			12.4.1 Left and Right Joins
			12.4.2 Full Outer Join
			12.4.3 Reading Questions
			12.4.4 Exercises
		12.5 Partitioning and Grouping Information
			12.5.1 Reading Questions
			12.5.2 Exercises
		12.6 Subqueries
			12.6.1 Reading Questions
			12.6.2 Exercises
	13 Relational Model: Database Programming
		13.1 Making Connections
			13.1.1 The Connection String
			13.1.2 Connecting and Closing
			13.1.3 Reading Questions
			13.1.4 Exercises
		13.2 Executing Queries and Basic Retrieval of Results
			13.2.1 Basic Query and Fetching Results
				13.2.1.1 Result Data
				13.2.1.2 Native Data Structure to pandas
				13.2.1.3 Database Requests Directly through pandas
			13.2.2 Reading Questions
			13.2.3 Exercises
		13.3 More Advanced Techniques
			13.3.1 Record at a Time
				13.3.1.1 Result Proxy as an Iterator
				13.3.1.2 Fetch One
			13.3.2 Chunks
				13.3.2.1 Fetch Many
				13.3.2.2 Using Pandas with Chunk Size
			13.3.3 Working with Multiple Databases
			13.3.4 Reading Questions
			13.3.5 Exercises
		13.4 Incorporating Variables
			13.4.1 Python String Composition
			13.4.2 Binding Variables
				13.4.2.1 Prepare
				13.4.2.2 Bind
				13.4.2.3 Execute
			13.4.3 Reading Questions
			13.4.4 Exercises
	14 Relational Model: Design, Constraints, and Creation
		14.1 Motivation and Process
		14.2 Designing Tables
			14.2.1 Functional Dependencies
			14.2.2 Table Design: Advice and Best Practices
			14.2.3 Table Primary Key
			14.2.4 Reading Questions
			14.2.5 Exercises
		14.3 Table Fields
			14.3.1 Single Field Issues
			14.3.2 Field Relationship Issues
				14.3.2.1 List of Values in a Single Field
				14.3.2.2 Using Multiple Fields Instead of List of Values
			14.3.3 Field Data Types
			14.3.4 Field Design: Advice and Best Practices
			14.3.5 Reading Questions
			14.3.6 Exercises
		14.4 Relationships Between Tables
			14.4.1 Designing for Many-to-One Relationships
			14.4.2 Designing for Many-to-Many Relationships
			14.4.3 Reading Questions
			14.4.4 Exercises
		14.5 Table and Schema Creation
			14.5.1 Fields
			14.5.2 Table Constraints
				14.5.2.1 Primary Key
				14.5.2.2 Foreign Key
				14.5.2.3 CHECK Constraint
			14.5.3 Programming and Development Advice
			14.5.4 Reading Questions
			14.5.5 Exercises
		14.6 Table Population
			14.6.1 Examples
			14.6.2 Programming for Table Population
				14.6.2.1 Example 1: Table Population from Python List of Row Lists
				14.6.2.2 Example 2: Table Population using Python CSV DictReader
				14.6.2.3 Example 3: Table Population from a pandas DataFrame
				14.6.2.4 Example 4: Table Population Using pandas Method
			14.6.3 Reading Questions
			14.6.4 Exercises
	15 Hierarchical Model: Structure and Formats
		15.1 Motivation
		15.2 Representation of Trees
			15.2.1 Terminology
			15.2.2 Python Native Data Structures and Nesting
				15.2.2.1 Representing Graphs
				15.2.2.2 Representing Trees
			15.2.3 Traversals and Paths
			15.2.4 Reading Questions
		15.3 JSON
			15.3.1 Reading Questions
			15.3.2 Exercises
		15.4 XML
			15.4.1 XML Structure
			15.4.2 Extracting Data from an XML File
			15.4.3 Reading Questions
			15.4.4 Exercises
		Further Exploration
	16 Hierarchical Model: Operations and Programming
		16.1 Operations Overview
			16.1.1 Reading Questions
		16.2 JSON Procedural Programming
			16.2.1 Access and Traversal Operations Example
				16.2.1.1 Example: Simple Table in JSON
				Example: Simple Table in JSON
				16.2.1.2 Single Table from JSON with Additional Level
				Single Table from JSON with Additional Level
			16.2.2 Node Creation
			16.2.3 Node Attribute Updates
			16.2.4 Reading Questions
			16.2.5 Exercises
		16.3 XML Procedural Operations
			16.3.1 Reading and Traversing XML Data
				16.3.1.1 Indicators Example
				16.3.1.2 School Example
				16.3.1.3 Wrangling Instructors
				16.3.1.4 Wrangling Departments
				16.3.1.5 Wrangling Courses
			16.3.2 Creating XML Data
			16.3.3 Further Operations
			16.3.4 Reading Questions
			16.3.5 Exercises
		16.4 XPath
			16.4.1 Paths in XML Documents
			16.4.2 Paths and Expressions in XPath
			16.4.3 XPath Syntax
			16.4.4 XPath Axes
			16.4.5 XPath Predicates and Built-in Functions
			16.4.6 Python Programming with XPath
			16.4.7 Case Study Example
			16.4.8 Reading Questions
			16.4.9 Exercises
		Further Reading
	17 Hierarchical Model: Constraints
		17.1 Motivation
			17.1.1 Reading Questions
		17.2 Well-Formed XML
			17.2.1 Reading Questions
		17.3 Document Type Definition
			17.3.1 Declaring Elements
			17.3.2 Declaring Attributes and Entities
			17.3.3 Example DTD Declarations
			17.3.4 DTD Validation of an XML Document
			17.3.5 Exercises
		17.4 XML Schema
			17.4.1 Root of an XML Schema
			17.4.2 Declaring Elements and Attributes
			17.4.3 XSD Types
			17.4.4 XSD Restrictions
			17.4.5 An XSD Example
			17.4.6 Validating an XML Document
			17.4.7 Exercises
		17.5 JSON Schema
			17.5.1 Basics of JSON Schema
			17.5.2 Validating a JSON Document Using a JSON Schema
			17.5.3 Exercises
Part III Data Systems: The Data Sources
	18 Overview of Data Systems Sources
		18.1 Architecture
		18.2 Data Sources
			18.2.1 Local Files
			18.2.2 Database Systems
			18.2.3 Web Servers
			18.2.4 API Service
			18.2.5 Reading Questions
	19 Networking and Client–Server
		19.1 The Network Architecture
			19.1.1 Host Addressing
			19.1.2 Packet Switching and Routing
			19.1.3 Summary Characteristics of the Network
			19.1.4 Reading Questions
		19.2 The Network Protocol Stack
			19.2.1 Media Access Protocol Layer
			19.2.2 Network Protocol Layer
			19.2.3 Transport Protocol Layer
			19.2.4 The Socket Interface
			19.2.5 Application Protocols
			19.2.6 Reading Questions
		19.3 Client–Server Model
			19.3.1 Server Application
			19.3.2 Client Application
			19.3.3 Reading Questions
	20 The HyperText Transfer Protocol
		20.1 Identifying Resources with URLs and URIs
			20.1.1 Host Locations
				Host Locations
			20.1.2 Resource Paths
				Resource Paths
			20.1.3 URL Syntax
			20.1.4 Reading Questions
		20.2 HTTP Definition
			20.2.1 Message Format
			20.2.2 Request Messages
			20.2.3 Connections and Message Exchange
				20.2.3.1 Client-Side HTTP Steps
				Client-Side HTTP Steps
			20.2.4 Socket Level Programming Examples
				20.2.4.1 Example of Socket-Based GET Request
				Example Socket-Based GET Request
				20.2.4.2 Example of Socket-Based POST Request
				Example Socket-Based POST Request
			20.2.5 Request Header Lines
			20.2.6 Response Messages
			20.2.7 Redirection
			20.2.8 Reading Questions
			20.2.9 Exercises
		20.3 Programming HTTP Using Requests
			20.3.1 GET Requests
				20.3.1.1 Example 1: GET of HTML
				Example 1: GET of HTML
				20.3.1.2 Example 2: GET Specifying Headers for Request
				Example 2: GET Specifying Headers for Request
				20.3.1.3 Example 3: GET with Query Parameters
				Example 3: GET with Query Parameters
			20.3.2 POST Requests
				20.3.2.1 Example 1: POST with Form Data Body
				Example 1: POST with Form Data Body
				20.3.2.2 Example 2: POST with JSON Body
			20.3.3 Response Attributes
			20.3.4 Reading Questions
			20.3.5 Exercises
		20.4 Command Line HTTP with curl
			20.4.1 Basics
				20.4.1.1 Options Controlling Output
				20.4.1.2 Options to Show Response Metadata
			20.4.2 Sending Custom Request Header Lines
			20.4.3 Query Parameters
			20.4.4 POST Requests
				20.4.4.1 POST with No Body
				POST with no Body
				20.4.4.2 POST with Form Data
				POST with Form Data
				20.4.4.3 POST with JSON Data
				POST with JSON Data
			20.4.5 Exploring Further
			20.4.6 Exercises
	21 Interlude: Client Data Acquisition
		21.1 Encoding and Decoding
			21.1.1 Python Strings and Bytes
				21.1.1.1 The Encode Operation: A String to Bytes
				The Encode Operation: a String to Bytes
				21.1.1.2 The Decode Operation: Bytes to a String
				The Decode Operation: Bytes to a String
			21.1.2 Prelude to Format Examples
			21.1.3 Reading Questions
			21.1.4 Exercises
		21.2 CSV Data
			21.2.1 CSV from File Data
			21.2.2 CSV from Network Data
				21.2.2.1 Option 1: From String Text
				Option 1: From String Text
				21.2.2.2 Option 2: From Underlying Bytes
				Option 2: From Underlying Bytes
			21.2.3 Reading Questions
			21.2.4 Exercises
		21.3 JSON Data
			21.3.1 JSON from File
			21.3.2 JSON from Network
				21.3.2.1 JSON from String Data in Response
				JSON from String Data in Response
				21.3.2.2 JSON from Bytes Data in Response Body
				JSON from Bytes Data in Response Body
			21.3.3 Reading Questions
			21.3.4 Exercises
		21.4 XML Data
			21.4.1 XML from File Data
			21.4.2 From Network
				21.4.2.1 Using Parse on Bytes
				Using parse on Bytes
				21.4.2.2 Using fromstring() with Bytes and Strings
				Using fromstring() with Bytes and Strings
			21.4.3 Reading Questions
			21.4.4 Exercises
	22 Web Scraping
		22.1 HTML Structure and Its Representation of Data Sets
			22.1.1 HTML Tables
			22.1.2 HTML Lists
			22.1.3 Reading Questions
		22.2 Web Scraping Examples
			22.2.1 Formulating Requests for HTML
			22.2.2 Simple Table
			22.2.3 Wikipedia Table
				22.2.3.1 Goal
				Goal
				22.2.3.2 Discovery
				Discovery
				22.2.3.3 Data Extraction
				Data Extraction
			22.2.4 POST to Submit a Form
				22.2.4.1 Goal
				Goal
				22.2.4.2 Discovery
				Discovery
				22.2.4.3 Request and Data Extraction
				Request and Data Extraction
			22.2.5 Reading Questions
			22.2.6 Exercises
	23 RESTful Application Programming Interfaces
		23.1 Motivation and Background
			23.1.1 General API Characteristics
			General API Characteristics
			23.1.2 Principles of REpresentational State Transfer (REST)
			Principles of REpresentational State Transfer (REST)
			23.1.3 Reading Questions
		23.2 HTTP for REST API Requests
			23.2.1 Endpoints
				23.2.1.1 Root Endpoint
				Root Endpoint
				23.2.1.2 Non-Root Endpoint
				Non-Root Endpoint
			23.2.2 Path Parameters
			23.2.3 Query Parameters
				23.2.3.1 Search for Movies
				Search for Movies
			23.2.4 Header Parameters
			23.2.5 POST and POST Body
			23.2.6 Reading Questions
			23.2.7 Exercises
		23.3 Case Study
			23.3.1 Phase 1: Build a Table of Popular Movies
				23.3.1.1 Design a Function to Issue Request
				Design a Function to Issue Request
				23.3.1.2 Understand Results
				Understand Results
				23.3.1.3 Design Movie Table
				Design Movie Table
				23.3.1.4 Handle Multiple Pages
				Handle Multiple Pages
			23.3.2 Phase 2: Build Table of Top Cast Given Movie IDs
				23.3.2.1 Understand Movie Credits API
				Understand Movie Credits API
				23.3.2.2 Goal: Design Cast Table
				Goal: Design Cast Table
			23.3.3 Summary Comments
			23.3.4 Reading Questions
			23.3.5 Exercises
	24 Authentication and Authorization
		24.1 Background
			24.1.1 Principals
			24.1.2 Authentication and Authorization Concepts
			24.1.3 Impersonation
			24.1.4 Encryption, Keys, and Signatures
			24.1.5 Reading Questions
		24.2 Authentication and Privacy
			24.2.1 HTTPS
			24.2.2 HTTP Authentication
				24.2.2.1 Basic Authentication
				Basic Authentication
			24.2.3 Authentication Considerations
			24.2.4 Reading Questions
			24.2.5 Exercises
		24.3 Authorization
			24.3.1 OAuth2 Background
			24.3.2 Delegated Authority: Authorization Code Grant Flow
				24.3.2.1 Pre-Stage: Application Registration with Provider
				24.3.2.2 Stage 1: Client Obtains Code with Cooperating Resource Owner
				24.3.2.3 Stage 2: Client Exchanges Code for Bearer Token
				24.3.2.4 Stage 3: Client Acquires Data Using Token
				24.3.2.5 Stage 4: Client Exchanges Refresh Token for New Token
			24.3.3 OAuth Dance Walkthrough
				24.3.3.1 Build User Auth URL
				24.3.3.2 Delegation by Resource Owner
				24.3.3.3 Exchange Code for Token by Client
				24.3.3.4 Data Requests
			24.3.4 Reading Questions
			24.3.5 Exercises
A Custom Software
	A.1 The util Module
		A.1.1 buildURL
			Signature
			Description
			Parameters
			Return
		A.1.2 random_string
			Signature
			Description
			Parameters
			Return
		A.1.3 getLocalXML
			Signature
			Description
			Parameters
			Return
		A.1.4 read_creds
			Signature
			Description
			Parameters
			Return
		A.1.5 update_creds
			Signature
			Description
			Parameters
			Return
		A.1.6 print_text
			Signature
			Description
			Parameters
			Return
		A.1.7 print_data
			Signature
			Description
			Parameters
			Return
		A.1.8 print_xml
			Signature
			Description
			Parameters
			Return
		A.1.9 print_headers
			Signature
			Description
			Parameters
			Return
	A.2 The mysocket Module
		A.2.1 makeConnection
			Signature
			Description
			Parameters
			Return
		A.2.2 sendString
			Signature
			Description
			Parameters
			Return
		A.2.3 receiveTillClose
			Signature
			Description
			Parameters
			Return
		A.2.4 sendBytes
			Signature
			Description
			Parameters
			Return
		A.2.5 receiveTillSentinel
			Signature
			Description
			Parameters
			Return
		A.2.6 receiveBySize
			Signature
			Description
			Parameters
			Return
		A.2.7 sendCRLF
			Signature
			Description
			Parameters
			Return
		A.2.8 sendCRLFLines
			Signature
			Description
			Parameters
			Return
References
Index