Mac Developer Guide

This Mac dev tool has been recommended for its ease of use as well as its integration into the command line. Xcode is an integrated development environment that offers a comprehensive set of Mac developer tools - everything programmers need to build great applications for Mac, iPhone, iPad, Apple TV, and Apple Watch. To view the latest developer news. Provide a delightful and optimized Mac experience using your existing code. Tutorial Learn Mac Catalyst Build a native Mac app from the same code base as your iPad app. Article Choose a User Interface Idiom Update your app to use the Mac idiom, instead of scaling to match iPad.

Table of Contents

Preface

1. Foreword

2. Who should read this document?

3. Acknowledgements

4. About this document

5. Where to get the latest copy of this document?

6. Providing feedback about this document

7. Typographic Conventions

7.1. Admonitions

7.2. Shell Prompt and Source Code Examples

I. Wireshark Build Environment

1. Introduction

1.1. Introduction

1.2. What is Wireshark?

1.3. Supported Platforms

1.3.1. Unix and Unix-like platforms

1.3.2. Microsoft Windows

1.4. Development and maintenance of Wireshark

1.4.1. Programming languages used

1.4.2. Open Source Software

1.5. Releases and distributions

1.5.1. Binary distributions

1.5.2. Source code distributions

1.6. Automated Builds (Buildbot)

1.6.1. Advantages

1.6.2. What does the Buildbot do?

1.7. Reporting problems and getting help

1.7.1. Website

1.7.2. Wiki

1.7.3. FAQ

1.7.4. Other sources

1.7.5. Q&A Site

1.7.6. Mailing Lists

1.7.7. Bug database (Bugzilla)

1.7.8. Reporting Problems

1.7.9. Reporting Crashes on UNIX-like platforms

1.7.10. Reporting Crashes on Windows platforms

2. Quick Setup

2.1. UNIX: Installation

2.2. Win32/64: Step-by-Step Guide

2.2.1. Recommended: Install Chocolatey

2.2.2. Install Microsoft Visual Studio

2.2.3. Install Qt

2.2.4. Install Python

2.2.5. Install Perl

2.2.6. Install Git

2.2.7. Install CMake

2.2.8. Install Asciidoctor, Xsltproc, And DocBook

2.2.9. Install winflexbison

2.2.10. Install and Prepare Sources

2.2.11. Open a Visual Studio Command Prompt

2.2.12. Generate the build files

2.2.13. Build Wireshark

2.2.14. Debug Environment Setup

2.2.15. Optional: Create User's and Developer's Guide

2.2.16. Optional: Create a Wireshark Installer

3. Work with the Wireshark sources

3.1. Introduction

3.2. The Wireshark Git repository

3.2.1. Git Naming Conventions

3.3. Browsing And Searching The Source Code

3.4. Obtaining The Wireshark Sources

3.4.1. Git Over SSH Or HTTPS

3.4.2. Development Snapshots

3.4.3. Official Source Releases

3.5. Update Your Wireshark Sources

3.5.1. Update Using Git

3.6. Build Wireshark

3.6.1. Building on Unix

3.6.2. Windows Native

3.7. Run Your Version Of Wireshark

3.7.1. Unix-Like Platforms

3.7.2. Windows Native

3.8. Debug Your Version Of Wireshark

3.8.1. Unix-Like Platforms

3.8.2. Windows Native

3.9. Make Changes To The Wireshark Sources

3.10. Contribute Your Changes

3.10.1. Creating Merge Requests

3.10.2. Updating Merge Requests

3.10.3. Some Tips For A Good Patch

3.10.4. Writing a Good Commit Message

3.10.5. Code Requirements

3.10.6. Backporting A Change

3.11. Binary Packaging

3.11.1. Packaging Guidelines

3.11.2. Debian: .deb Packages

3.11.3. Red Hat: .rpm Packages

3.11.4. macOS: .dmg Packages

3.11.5. Windows: NSIS .exe Installer

3.11.6. Windows: PortableApps .paf.exe Package

3.12. Mime Types

3.12.1. Display Filter

3.12.2. Coloring Rules

3.12.3. Filter List

3.12.4. Column List

4. Tool Reference

4.1. Introduction

4.2. Chocolatey

4.3. CMake

4.4. GNU Compiler Toolchain (UNIX And UNIX-like Platforms)

4.4.1. gcc (GNU Compiler Collection)

4.4.2. gdb (GNU Project Debugger)

4.4.3. make (GNU Make)

4.4.4. Ninja

4.5. Microsoft compiler toolchain (Windows native)

4.5.1. Official Toolchain Packages And Alternatives

4.5.2. cl.exe (C Compiler)

4.5.3. link.exe (Linker)

4.5.4. Visual C++ Runtime 'Redistributable' Files

4.5.5. Windows Platform SDK

4.6. Documentation Toolchain

4.6.1. Asciidoctor

4.6.2. DocBook XML and XSL

4.6.3. xsltproc

4.6.4. HTML Help

4.7. Debugger

4.7.1. Visual Studio Integrated Debugger

4.7.2. Debugging Tools For Windows

4.8. bash

4.9. Python

4.10. Perl

4.11. Flex

4.12. Git client

4.13. Git Powershell Extensions (Optional)

4.14. Git GUI Client (Optional)

4.15. patch (Optional)

4.16. Windows: NSIS (Optional)

4.17. Windows: WiX Toolset (Optional)

4.18. Windows: PortableApps (Optional)

5. Library Reference

5.1. Introduction

5.2. Binary Library Formats

5.3. Windows Automated Library Download

5.4. Qt

5.5. GLib And Supporting Libraries

5.6. c-ares

5.7. SMI (Optional)

5.8. zlib (Optional)

5.9. libpcap or Npcap (Optional, But Strongly Recommended)

5.10. GnuTLS (Optional)

5.11. Gcrypt

5.12. Kerberos (Optional)

5.13. LUA (Optional)

5.14. MaxMindDB (Optional)

5.15. WinSparkle (Optional)

II. Wireshark Development

6. How Wireshark Works

6.1. Introduction

6.2. Overview

6.3. Capturing packets

6.4. Capture Files

6.5. Dissect packets

7. Introduction

7.1. Source overview

7.2. Coding Style

7.3. The GLib library

8. Packet Capture

8.1. How To Add A New Capture Type To Libpcap

8.2. Extcap: Developer Guide

8.2.1. Extcap command line interface

8.2.2. Extcap Arguments

8.2.3. Toolbar Controls

9. Packet Dissection

9.1. How packet dissection works

9.2. Adding a basic dissector

9.2.1. Setting up the dissector

9.2.2. Dissecting the protocol's details

9.2.3. Improving the dissection information

9.3. How to handle transformed data

9.4. How to reassemble split packets

9.4.1. How to reassemble split UDP packets

9.4.2. How to reassemble split TCP Packets

9.5. How to tap protocols

9.6. How to produce protocol stats

9.7. How to use conversations

9.8. idl2wrs: Creating dissectors from CORBA IDL files

9.8.1. What is it?

9.8.2. Why do this?

9.8.3. How to use idl2wrs

9.8.4. TODO

9.8.5. Limitations

9.8.6. Notes

10. Lua Support in Wireshark

10.1. Introduction

10.2. Example: Creating a Menu with Lua

10.3. Example: Dissector written in Lua

10.4. Example: Listener written in Lua

11. Wireshark's Lua API Reference Manual

11.1. Saving Capture Files

11.1.1. Dumper

11.1.2. PseudoHeader

11.2. Obtaining Dissection Data

11.2.1. Field

11.2.2. FieldInfo

11.2.3. Global Functions

11.3. GUI Support

11.3.1. ProgDlg

11.3.2. TextWindow

11.3.3. Global Functions

11.4. Post-Dissection Packet Analysis

11.4.1. Listener

11.5. Obtaining Packet Information

11.5.1. Address

11.5.2. Column

11.5.3. Columns

11.5.4. NSTime

11.5.5. Pinfo

11.5.6. PrivateTable

11.6. Functions For New Protocols And Dissectors

11.6.1. Dissector

11.6.2. DissectorTable

11.6.3. Pref

11.6.4. Prefs

11.6.5. Proto

11.6.6. ProtoExpert

11.6.7. ProtoField

11.6.8. Global Functions

11.7. Adding Information To The Dissection Tree

11.7.1. TreeItem

11.7.2. Example

11.8. Functions For Handling Packet Data

11.8.1. ByteArray

11.8.2. Tvb

11.8.3. TvbRange

11.9. Custom File Format Reading And Writing

11.9.1. CaptureInfo

11.9.2. CaptureInfoConst

11.9.3. File

11.9.4. FileHandler

11.9.5. FrameInfo

11.9.6. FrameInfoConst

11.9.7. Global Functions

11.10. Directory Handling Functions

11.10.1. Dir

11.10.2. Example

11.10.3. Example

11.11. Utility Functions

11.11.1. Global Functions

11.12. Handling 64-bit Integers

11.12.1. Int64

11.12.2. UInt64

11.13. Binary encode/decode support

11.13.1. Struct

11.14. GLib Regular Expressions

11.14.1. GRegex

12. User Interface

12.1. Introduction

12.2. The Qt Application Framework

12.2.1. User Experience Considerations

12.2.2. Qt Creator

12.2.3. Source Code Overview

12.2.4. Coding Practices and Naming Conventions

12.2.5. Other Issues and Information

12.3. Human Interface Reference Documents

13. Wireshark Tests

13.1. Quick Start

13.2. Test suite structure

13.2.1. Test Coverage And Availability

13.2.2. Suites, Cases, and Tests

13.2.3. pytest fixtures

13.3. Listing And Running Tests

13.4. Listing And Running Tests (pytest)

13.5. Adding Or Modifying Tests

14. Creating ASN.1 Dissectors

14.1. About ASN.1

14.2. ASN.1 Dissector Requirements

14.2.1. Building An ASN.1-Based Plugin

14.3. Understanding Error Messages

14.4. Hand-Massaging The ASN.1 File

14.5. Command Line Syntax

14.6. Generated Files

14.7. Step By Step Instructions

14.8. Hints For Using Asn2wrs

14.8.1. ANY And Parameterized Types

14.8.2. Tagged Assignments

14.8.3. Untagged CHOICEs

14.8.4. Imported Module Name Conflicts

14.9. Simple ASN.1-Based Dissector

14.10. Conformance (.cnf) Files

14.10.1. Example .cnf File

14.10.2. Example packet-protocol-template.h File

14.10.3. Example packet-protocol-template.c File

14.11. Conformance File Directive Reference

14.11.1. #.END

14.11.2. #.EXPORTS

14.11.3. #.FN_BODY

14.11.4. #.MODULE_IMPORT And #.INCLUDE

14.11.5. #.MODULE_IMPORT

14.11.6. #.INCLUDE

14.11.7. #.NO_EMIT And #.USER_DEFINED

14.11.8. #.PDU and #.PDU_NEW

14.11.9. #.REGISTER and #.REGISTER_NEW

15. This Document's License (GPL)

This guide will teach you how to use NeuroSky's ThinkGear SDK for Mac to write Mac applications that can utilize bio-signal data from NeuroSky's ThinkGear bio-sensors. This will enable your Mac apps to receive and use bio-signal data such as EEG acquired from NeuroSky's sensor hardware. The ThinkGear SDK is compatible with both the 32 and 64 bit versions of OS X.

This guide (and the entire ThinkGear SDK for Mac) is intended for programmers who are already familiar with standard Mac development using Xcode and Apple's Mac SDK. If you are not already familiar with developing for Mac, please first visit Apple's web site for instruction and tools to develop Mac apps.

If you are already familiar with creating typical Mac apps, then the next step is to make sure you have downloaded NeuroSky's ThinkGear SDK for Mac included with the Developer Tools for PC/Mac. Chances are, if you're reading this document, then you already have it.

Future revisions of the Mac OSX ThinkGear SDK will be updated to update the beta Mental Effort and Familiarity measurements.

ThinkGear SDK for Mac Contents

• ThinkGear SDK for Mac: Development Guide (this document mac_development_guide.pdf)
• ThinkGearTouch example project for Mac

You'll find the 'ThinkGear.framework' in the lib/ folder, and the 'HelloEEG' in the Sample Project/ folder within the ThinkGear SDK for Mac folder.

Supported ThinkGear Hardware

The ThinkGear SDK for Mac must be used with a ThinkGear-compatible hardware sensor device. The following ThinkGear-compatible hardware devices are currently supported:

• MindWave Mobile for use with an Mac device's built in Bluetooth

Before using any Mac application that uses the ThinkGear SDK for Mac OSX, make sure you have paired the ThinkGear sensor hardware to your Mac by carefully following the instructions in the User Manual that came with the corresponding ThinkGear hardware device.

HelloEEG is a sample project we've included in the ThinkGear SDK for Mac that demonstrates how to setup, connect, and handle data to a ThinkGear device. Add the project to your Xcode enviornment by following these steps: Adobe premiere pro cc mac download.

Mac Developer Guide Free

1. Browse in the TG-SDK to select the Sample Projects/HelloEEG directory
2. select Product → Run to compile, link and start HelloEEG in the Xcode emulator.

Note: If HelloEEG does not compile and you see the following error, try deleting and re-adding ThinkGear.framework under Frameworks and Libraries from the menu shown below.

1. Click ThinkGear.framework and then click the - button.
2. Find and add ThinkGear.framework in TG-SDK –> TG-SDK For Mac –> lib –> ThinkGear.framework

If HelloEEG is run without connecting the ThinkGear-enabled headset, the application should look like this:

Once the headset is connected, run the application once again. The application should now look like this:

If the Poor Signal data reads 0, Meditation and Attention data should be fluctuating every second. If Poor Signal reads something other than 0, re-adjust the headset accordingly until Poor Signal data goes down to 0.

At this point, you should be able to browse the code, make modifications, compile, and deploy the app to your device or emulator just like any typical OS X application.

For most applications, using the ThinkGear Mac API is recommended. It reduces the complexity of managing ThinkGear accessory connections and handles parsing of the data stream from these ThinkGear accessories. To make an application, all you need to do is to import a library, and assign a delegate object to which accessory event notifications will be dispatched.

Some limitations of the ThinkGear for Mac API include:

• Can only communicate with one attached ThinkGear-enabled accessory

Configuring Your Environment

Add ThinkGear.framework to your project.

1. Select your target
2. Expand Link Binary With Libraries
3. Click on + and select ThinkGear.framework and click Add

Your project window should now look similar to this:

App Sandbox

Creating ThinkGear Object

A ThinkGear object is used to manage a single connection to a single ThinkGear hardware device.

• Declare a ThinkGearObjc object in the header(.h) file

• Initialize the thinkGear in your implementation(.m) file

Connecting to ThinkGear Hardware Device

Simple add the following code to your implementation(.m) file:

Handling Data Receipt

To receive the message from ThinkGear SDK, the dataRecieved: method must be implemented. In the header (.h) file, add the following method definition:

And in the implementation (.m) file, implement the method.

Poor Signal

This integer value provides an indication of how good or how poor the bio-signal is at the sensor. This value is typically output by all ThinkGear hardware devices once per second.

This is an extremely important value for any app using ThinkGear sensor hardware to always read, understand, and handle. The value is stored in the key of 'poorSignal'.

Mac Developer Guide App

Raw Data

This data type supplies the raw sample values acquired at the bio-sensor. The sampling rate (and therefore output rate), possible range of values, and interpretations of those values (conversion from raw units to volt) for this data type are dependent on the hardware characteristics of the ThinkGear hardware device performing the sampling. Facetime camera not working on mac. You must refer to the documented development specs of each type of ThinkGear hardware that your app will support for details.

As an example, the majority of ThinkGear devices sample at 512Hz, with a possible value range of -32768 to 32767.

As another example, to convert TGAT-based EEG sensor values (such as TGAT, TGAM, MindWave, MindWave Mobile) to voltage values, use the following conversion:

Attention

Once the headset is connected, run the application once again. The application should now look like this:

If the Poor Signal data reads 0, Meditation and Attention data should be fluctuating every second. If Poor Signal reads something other than 0, re-adjust the headset accordingly until Poor Signal data goes down to 0.

At this point, you should be able to browse the code, make modifications, compile, and deploy the app to your device or emulator just like any typical OS X application.

For most applications, using the ThinkGear Mac API is recommended. It reduces the complexity of managing ThinkGear accessory connections and handles parsing of the data stream from these ThinkGear accessories. To make an application, all you need to do is to import a library, and assign a delegate object to which accessory event notifications will be dispatched.

Some limitations of the ThinkGear for Mac API include:

• Can only communicate with one attached ThinkGear-enabled accessory

Configuring Your Environment

Add ThinkGear.framework to your project.

1. Select your target
2. Expand Link Binary With Libraries
3. Click on + and select ThinkGear.framework and click Add

Your project window should now look similar to this:

App Sandbox

Creating ThinkGear Object

A ThinkGear object is used to manage a single connection to a single ThinkGear hardware device.

• Declare a ThinkGearObjc object in the header(.h) file

• Initialize the thinkGear in your implementation(.m) file

Connecting to ThinkGear Hardware Device

Simple add the following code to your implementation(.m) file:

Handling Data Receipt

To receive the message from ThinkGear SDK, the dataRecieved: method must be implemented. In the header (.h) file, add the following method definition:

And in the implementation (.m) file, implement the method.

Poor Signal

This integer value provides an indication of how good or how poor the bio-signal is at the sensor. This value is typically output by all ThinkGear hardware devices once per second.

This is an extremely important value for any app using ThinkGear sensor hardware to always read, understand, and handle. The value is stored in the key of 'poorSignal'.

Mac Developer Guide App

Raw Data

This data type supplies the raw sample values acquired at the bio-sensor. The sampling rate (and therefore output rate), possible range of values, and interpretations of those values (conversion from raw units to volt) for this data type are dependent on the hardware characteristics of the ThinkGear hardware device performing the sampling. Facetime camera not working on mac. You must refer to the documented development specs of each type of ThinkGear hardware that your app will support for details.

As an example, the majority of ThinkGear devices sample at 512Hz, with a possible value range of -32768 to 32767.

As another example, to convert TGAT-based EEG sensor values (such as TGAT, TGAM, MindWave, MindWave Mobile) to voltage values, use the following conversion:

Attention

This int value reports the current eSense™ Attention meter of the user, which indicates the intensity of a user's level of mental 'focus'or 'attention', such as that which occurs during intense concentration anddirected (but stable) mental activity. Its value ranges from 0 to 100.Distractions, wandering thoughts, lack of focus, or anxiety may lower theAttention meter levels. See eSense Meters below for details aboutinterpreting eSense levels in general.

The value is stored in the key of 'eSenseAttention'. It is typically outputonce a second.

Meditation

This unsigned one-byte value reports the current eSense™ Meditation meter ofthe user, which indicates the level of a user's mental 'calmness' or'relaxation'. Its value ranges from 0 to 100. Note that Meditation is ameasure of a person's mental levels, not physical levels, so simplyrelaxing all the muscles of the body may not immediately result in aheightened Meditation level. However, for most people in most normalcircumstances, relaxing the body often helps the mind to relax as well.Meditation is related to reduced activity by the active mental processes inthe brain, and it has long been an observed effect that closing one's eyesturns off the mental activities which process images from the eyes, soclosing the eyes is often an effective method for increasing the Meditationmeter level. Distractions, wandering thoughts, anxiety, agitation, andsensory stimuli may lower the Meditation meter levels. See eSense Metersbelow for details about interpreting eSense™ levels in general.

The value is stored in the key of 'eSenseMeditaion'. It is typically outputonce a second.

eSense Meters

For all the different types of eSense™ (i.e. Attention, Meditation), themeter value is reported on a relative eSense™ scale of 1 to 100. On thisscale, a value between 40 to 60 at any given moment in time is considered'neutral', and is similar in notion to 'baselines' that are established inconventional EEG measurement techniques (though the method for determining aThinkGear baseline is proprietary and may differ from conventional EEG). Avalue from 60 to 80 is considered 'slightly elevated', and may be interpretedas levels being possibly higher than normal (levels of Attention or Meditationthat may be higher than normal for a given person). Values from 80 to 100 areconsidered 'elevated', meaning they are strongly indicative of heightenedlevels of that eSense™.

Similarly, on the other end of the scale, a value between 20 to 40 indicates'reduced' levels of the eSense™, while a value between 1 to 20 indicates'strongly lowered' levels of the eSense™. These levels may indicate statesof distraction, agitation, or abnormality, according to the opposite ofeach eSense™.

Mac Developer Apps

BLINK

This int value reports the intensity of the user's most recent eye blink. Its value ranges from 1 to 255 and it is reported whenever an eye blink is detected. The value indicates the relative intensity of the blink, and has no units.

Mac Developer Account

The Detection of Blinks must be enabled.