Jamel  O'Reilly

Jamel O'Reilly

1660003560

XCGLogger: The Original Debug Log Module for Use in Swift Projects

tl;dr

XCGLogger is the original debug log module for use in Swift projects.

Swift does not include a C preprocessor so developers are unable to use the debug log #define macros they would use in Objective-C. This means our traditional way of generating nice debug logs no longer works. Resorting to just plain old print calls means you lose a lot of helpful information, or requires you to type a lot more code.

XCGLogger allows you to log details to the console (and optionally a file, or other custom destinations), just like you would have with NSLog() or print(), but with additional information, such as the date, function name, filename and line number.

Go from this:

Simple message

to this:

2014-06-09 06:44:43.600 [Debug] [AppDelegate.swift:40] application(_:didFinishLaunchingWithOptions:): Simple message

Example

Example

Communication (Hat Tip AlamoFire)

  • If you need help, use Stack Overflow (Tag 'xcglogger').
  • If you'd like to ask a general question, use Stack Overflow.
  • If you've found a bug, open an issue.
  • If you have a feature request, open an issue.
  • If you want to contribute, submit a pull request.
  • If you use XCGLogger, please Star the project on GitHub

Installation

Git Submodule

Execute:

git submodule add https://github.com/DaveWoodCom/XCGLogger.git

in your repository folder.

Carthage

Add the following line to your Cartfile.

github "DaveWoodCom/XCGLogger" ~> 7.0.1

Then run carthage update --no-use-binaries or just carthage update. For details of the installation and usage of Carthage, visit its project page.

Developers running 5.0 and above in Swift will need to add $(SRCROOT)/Carthage/Build/iOS/ObjcExceptionBridging.framework to their Input Files in the Copy Carthage Frameworks Build Phase.

CocoaPods

Add something similar to the following lines to your Podfile. You may need to adjust based on your platform, version/branch etc.

source 'https://github.com/CocoaPods/Specs.git'
platform :ios, '8.0'
use_frameworks!

pod 'XCGLogger', '~> 7.0.1'

Specifying the pod XCGLogger on its own will include the core framework. We're starting to add subspecs to allow you to include optional components as well:

pod 'XCGLogger/UserInfoHelpers', '~> 7.0.1': Include some experimental code to help deal with using UserInfo dictionaries to tag log messages.

Then run pod install. For details of the installation and usage of CocoaPods, visit its official web site.

Note: Before CocoaPods 1.4.0 it was not possible to use multiple pods with a mixture of Swift versions. You may need to ensure each pod is configured for the correct Swift version (check the targets in the pod project of your workspace). If you manually adjust the Swift version for a project, it'll reset the next time you run pod install. You can add a post_install hook into your podfile to automate setting the correct Swift versions. This is largely untested, and I'm not sure it's a good solution, but it seems to work:

post_install do |installer|
    installer.pods_project.targets.each do |target|
        if ['SomeTarget-iOS', 'SomeTarget-watchOS'].include? "#{target}"
            print "Setting #{target}'s SWIFT_VERSION to 4.2\n"
            target.build_configurations.each do |config|
                config.build_settings['SWIFT_VERSION'] = '4.2'
            end
        else
            print "Setting #{target}'s SWIFT_VERSION to Undefined (Xcode will automatically resolve)\n"
            target.build_configurations.each do |config|
                config.build_settings.delete('SWIFT_VERSION')
            end
        end
    end

    print "Setting the default SWIFT_VERSION to 3.2\n"
    installer.pods_project.build_configurations.each do |config|
        config.build_settings['SWIFT_VERSION'] = '3.2'
    end
end

You can adjust that to suit your needs of course.

Swift Package Manager

Add the following entry to your package's dependencies:

.Package(url: "https://github.com/DaveWoodCom/XCGLogger.git", majorVersion: 7)

Backwards Compatibility

Use:

  • XCGLogger version 7.0.1 for Swift 5.0
  • XCGLogger version 6.1.0 for Swift 4.2
  • XCGLogger version 6.0.4 for Swift 4.1
  • XCGLogger version 6.0.2 for Swift 4.0
  • XCGLogger version 5.0.5 for Swift 3.0-3.2
  • XCGLogger version 3.6.0 for Swift 2.3
  • XCGLogger version 3.5.3 for Swift 2.2
  • XCGLogger version 3.2 for Swift 2.0-2.1
  • XCGLogger version 2.x for Swift 1.2
  • XCGLogger version 1.x for Swift 1.1 and below.

Basic Usage (Quick Start)

This quick start method is intended just to get you up and running with the logger. You should however use the advanced usage below to get the most out of this library.

Add the XCGLogger project as a subproject to your project, and add the appropriate library as a dependency of your target(s). Under the General tab of your target, add XCGLogger.framework and ObjcExceptionBridging.framework to the Embedded Binaries section.

Then, in each source file:

import XCGLogger

In your AppDelegate (or other global file), declare a global constant to the default XCGLogger instance.

let log = XCGLogger.default

In the

application(_ application: UIApplication, didFinishLaunchingWithOptions launchOptions: [UIApplicationLaunchOptionsKey: Any]? = nil) // iOS, tvOS

or

applicationDidFinishLaunching(_ notification: Notification) // macOS

function, configure the options you need:

log.setup(level: .debug, showThreadName: true, showLevel: true, showFileNames: true, showLineNumbers: true, writeToFile: "path/to/file", fileLevel: .debug)

The value for writeToFile: can be a String or URL. If the file already exists, it will be cleared before we use it. Omit the parameter or set it to nil to log to the console only. You can optionally set a different log level for the file output using the fileLevel: parameter. Set it to nil or omit it to use the same log level as the console.

Then, whenever you'd like to log something, use one of the convenience methods:

log.verbose("A verbose message, usually useful when working on a specific problem")
log.debug("A debug message")
log.info("An info message, probably useful to power users looking in console.app")
log.notice("A notice message")
log.warning("A warning message, may indicate a possible error")
log.error("An error occurred, but it's recoverable, just info about what happened")
log.severe("A severe error occurred, we are likely about to crash now")
log.alert("An alert error occurred, a log destination could be made to email someone")
log.emergency("An emergency error occurred, a log destination could be made to text someone")

The different methods set the log level of the message. XCGLogger will only print messages with a log level that is greater to or equal to its current log level setting. So a logger with a level of .error will only output log messages with a level of .error, .severe, .alert, or .emergency.

Advanced Usage (Recommended)

XCGLogger aims to be simple to use and get you up and running quickly with as few as 2 lines of code above. But it allows for much greater control and flexibility.

A logger can be configured to deliver log messages to a variety of destinations. Using the basic setup above, the logger will output log messages to the standard Xcode debug console, and optionally a file if a path is provided. It's quite likely you'll want to send logs to more interesting places, such as the Apple System Console, a database, third party server, or another application such as NSLogger. This is accomplished by adding the destination to the logger.

Here's an example of configuring the logger to output to the Apple System Log as well as a file.

// Create a logger object with no destinations
let log = XCGLogger(identifier: "advancedLogger", includeDefaultDestinations: false)

// Create a destination for the system console log (via NSLog)
let systemDestination = AppleSystemLogDestination(identifier: "advancedLogger.systemDestination")

// Optionally set some configuration options
systemDestination.outputLevel = .debug
systemDestination.showLogIdentifier = false
systemDestination.showFunctionName = true
systemDestination.showThreadName = true
systemDestination.showLevel = true
systemDestination.showFileName = true
systemDestination.showLineNumber = true
systemDestination.showDate = true

// Add the destination to the logger
log.add(destination: systemDestination)

// Create a file log destination
let fileDestination = FileDestination(writeToFile: "/path/to/file", identifier: "advancedLogger.fileDestination")

// Optionally set some configuration options
fileDestination.outputLevel = .debug
fileDestination.showLogIdentifier = false
fileDestination.showFunctionName = true
fileDestination.showThreadName = true
fileDestination.showLevel = true
fileDestination.showFileName = true
fileDestination.showLineNumber = true
fileDestination.showDate = true

// Process this destination in the background
fileDestination.logQueue = XCGLogger.logQueue

// Add the destination to the logger
log.add(destination: fileDestination)

// Add basic app info, version info etc, to the start of the logs
log.logAppDetails()

You can configure each log destination with different options depending on your needs.

Another common usage pattern is to have multiple loggers, perhaps one for UI issues, one for networking, and another for data issues.

Each log destination can have its own log level. As a convenience, you can set the log level on the log object itself and it will pass that level to each destination. Then set the destinations that need to be different.

Note: A destination object can only be added to one logger object, adding it to a second will remove it from the first.

Initialization Using A Closure

Alternatively you can use a closure to initialize your global variable, so that all initialization is done in one place

let log: XCGLogger = {
    let log = XCGLogger(identifier: "advancedLogger", includeDefaultDestinations: false)

    // Customize as needed
    
    return log
}()

Note: This creates the log object lazily, which means it's not created until it's actually needed. This delays the initial output of the app information details. Because of this, I recommend forcing the log object to be created at app launch by adding the line let _ = log at the top of your didFinishLaunching method if you don't already log something on app launch.

Log Anything

You can log strings:

log.debug("Hi there!")

or pretty much anything you want:

log.debug(true)
log.debug(CGPoint(x: 1.1, y: 2.2))
log.debug(MyEnum.Option)
log.debug((4, 2))
log.debug(["Device": "iPhone", "Version": 7])

Filtering Log Messages

New to XCGLogger 4, you can now create filters to apply to your logger (or to specific destinations). Create and configure your filters (examples below), and then add them to the logger or destination objects by setting the optional filters property to an array containing the filters. Filters are applied in the order they exist in the array. During processing, each filter is asked if the log message should be excluded from the log. If any filter excludes the log message, it's excluded. Filters have no way to reverse the exclusion of another filter.

If a destination's filters property is nil, the log's filters property is used instead. To have one destination log everything, while having all other destinations filter something, add the filters to the log object and set the one destination's filters property to an empty array [].

Note: Unlike destinations, you can add the same filter object to multiple loggers and/or multiple destinations.

Filter by Filename

To exclude all log messages from a specific file, create an exclusion filter like so:

log.filters = [FileNameFilter(excludeFrom: ["AppDelegate.swift"], excludePathWhenMatching: true)]

excludeFrom: takes an Array<String> or Set<String> so you can specify multiple files at the same time.

excludePathWhenMatching: defaults to true so you can omit it unless you want to match path's as well.

To include log messages only for a specific set to files, create the filter using the includeFrom: initializer. It's also possible to just toggle the inverse property to flip the exclusion filter to an inclusion filter.

Filter by Tag

In order to filter log messages by tag, you must of course be able to set a tag on the log messages. Each log message can now have additional, user defined data attached to them, to be used by filters (and/or formatters etc). This is handled with a userInfo: Dictionary<String, Any> object. The dictionary key should be a namespaced string to avoid collisions with future additions. Official keys will begin with com.cerebralgardens.xcglogger. The tag key can be accessed by XCGLogger.Constants.userInfoKeyTags. You definitely don't want to be typing that, so feel free to create a global shortcut: let tags = XCGLogger.Constants.userInfoKeyTags. Now you can easily tag your logs:

let sensitiveTag = "Sensitive"
log.debug("A tagged log message", userInfo: [tags: sensitiveTag])

The value for tags can be an Array<String>, Set<String>, or just a String, depending on your needs. They'll all work the same way when filtered.

Depending on your workflow and usage, you'll probably create faster methods to set up the userInfo dictionary. See below for other possible shortcuts.

Now that you have your logs tagged, you can filter easily:

log.filters = [TagFilter(excludeFrom: [sensitiveTag])]

Just like the FileNameFilter, you can use includeFrom: or toggle inverse to include only log messages that have the specified tags.

Filter by Developer

Filtering by developer is exactly like filtering by tag, only using the userInfo key of XCGLogger.Constants.userInfoKeyDevs. In fact, both filters are subclasses of the UserInfoFilter class that you can use to create additional filters. See Extending XCGLogger below.

Mixing and Matching

In large projects with multiple developers, you'll probably want to start tagging log messages, as well as indicate the developer that added the message.

While extremely flexible, the userInfo dictionary can be a little cumbersome to use. There are a few possible methods you can use to simply things. I'm still testing these out myself so they're not officially part of the library yet (I'd love feedback or other suggestions).

I have created some experimental code to help create the UserInfo dictionaries. (Include the optional UserInfoHelpers subspec if using CocoaPods). Check the iOS Demo app to see it in use.

There are two structs that conform to the UserInfoTaggingProtocol protocol. Tag and Dev.

You can create an extension on each of these that suit your project. For example:

extension Tag {
    static let sensitive = Tag("sensitive")
    static let ui = Tag("ui")
    static let data = Tag("data")
}

extension Dev {
    static let dave = Dev("dave")
    static let sabby = Dev("sabby")
}

Along with these types, there's an overloaded operator | that can be used to merge them together into a dictionary compatible with the UserInfo: parameter of the logging calls.

Then you can log messages like this:

log.debug("A tagged log message", userInfo: Dev.dave | Tag.sensitive)

There are some current issues I see with these UserInfoHelpers, which is why I've made it optional/experimental for now. I'd love to hear comments/suggestions for improvements.

  1. The overloaded operator | merges dictionaries so long as there are no Sets. If one of the dictionaries contains a Set, it'll use one of them, without merging them. Preferring the left hand side if both sides have a set for the same key.
  2. Since the userInfo: parameter needs a dictionary, you can't pass in a single Dev or Tag object. You need to use at least two with the | operator to have it automatically convert to a compatible dictionary. If you only want one Tag for example, you must access the .dictionary parameter manually: userInfo: Tag("Blah").dictionary.

Selectively Executing Code

All log methods operate on closures. Using the same syntactic sugar as Swift's assert() function, this approach ensures we don't waste resources building log messages that won't be output anyway, while at the same time preserving a clean call site.

For example, the following log statement won't waste resources if the debug log level is suppressed:

log.debug("The description of \(thisObject) is really expensive to create")

Similarly, let's say you have to iterate through a loop in order to do some calculation before logging the result. In Objective-C, you could put that code block between #if #endif, and prevent the code from running. But in Swift, previously you would need to still process that loop, wasting resources. With XCGLogger it's as simple as:

log.debug {
    var total = 0.0
    for receipt in receipts {
        total += receipt.total
    }

    return "Total of all receipts: \(total)"
}

In cases where you wish to selectively execute code without generating a log line, return nil, or use one of the methods: verboseExec, debugExec, infoExec, warningExec, errorExec, and severeExec.

Custom Date Formats

You can create your own DateFormatter object and assign it to the logger.

let dateFormatter = DateFormatter()
dateFormatter.dateFormat = "MM/dd/yyyy hh:mma"
dateFormatter.locale = Locale.current
log.dateFormatter = dateFormatter

Enhancing Log Messages With Colour

XCGLogger supports adding formatting codes to your log messages to enable colour in various places. The original option was to use the XcodeColors plug-in. However, Xcode (as of version 8) no longer officially supports plug-ins. You can still view your logs in colour, just not in Xcode at the moment. You can use the ANSI colour support to add colour to your fileDestination objects and view your logs via a terminal window. This gives you some extra options such as adding Bold, Italics, or (please don't) Blinking!

Once enabled, each log level can have its own colour. These colours can be customized as desired. If using multiple loggers, you could alternatively set each logger to its own colour.

An example of setting up the ANSI formatter:

if let fileDestination: FileDestination = log.destination(withIdentifier: XCGLogger.Constants.fileDestinationIdentifier) as? FileDestination {
    let ansiColorLogFormatter: ANSIColorLogFormatter = ANSIColorLogFormatter()
    ansiColorLogFormatter.colorize(level: .verbose, with: .colorIndex(number: 244), options: [.faint])
    ansiColorLogFormatter.colorize(level: .debug, with: .black)
    ansiColorLogFormatter.colorize(level: .info, with: .blue, options: [.underline])
    ansiColorLogFormatter.colorize(level: .notice, with: .green, options: [.italic])
    ansiColorLogFormatter.colorize(level: .warning, with: .red, options: [.faint])
    ansiColorLogFormatter.colorize(level: .error, with: .red, options: [.bold])
    ansiColorLogFormatter.colorize(level: .severe, with: .white, on: .red)
    ansiColorLogFormatter.colorize(level: .alert, with: .white, on: .red, options: [.bold])
    ansiColorLogFormatter.colorize(level: .emergency, with: .white, on: .red, options: [.bold, .blink])
    fileDestination.formatters = [ansiColorLogFormatter]
}

As with filters, you can use the same formatter objects for multiple loggers and/or multiple destinations. If a destination's formatters property is nil, the logger's formatters property will be used instead.

See Extending XCGLogger below for info on creating your own custom formatters.

Alternate Configurations

By using Swift build flags, different log levels can be used in debugging versus staging/production. Go to Build Settings -> Swift Compiler - Custom Flags -> Other Swift Flags and add -DDEBUG to the Debug entry.

#if DEBUG
    log.setup(level: .debug, showThreadName: true, showLevel: true, showFileNames: true, showLineNumbers: true)
#else
    log.setup(level: .severe, showThreadName: true, showLevel: true, showFileNames: true, showLineNumbers: true)
#endif

You can set any number of options up in a similar fashion. See the updated iOSDemo app for an example of using different log destinations based on options, search for USE_NSLOG.

Background Log Processing

By default, the supplied log destinations will process the logs on the thread they're called on. This is to ensure the log message is displayed immediately when debugging an application. You can add a breakpoint immediately after a log call and see the results when the breakpoint hits.

However, if you're not actively debugging the application, processing the logs on the current thread can introduce a performance hit. You can now specify a destination process its logs on a dispatch queue of your choice (or even use a default supplied one).

fileDestination.logQueue = XCGLogger.logQueue

or even

fileDestination.logQueue = DispatchQueue.global(qos: .background)

This works extremely well when combined with the Alternate Configurations method above.

#if DEBUG
    log.setup(level: .debug, showThreadName: true, showLevel: true, showFileNames: true, showLineNumbers: true)
#else
    log.setup(level: .severe, showThreadName: true, showLevel: true, showFileNames: true, showLineNumbers: true)
    if let consoleLog = log.logDestination(XCGLogger.Constants.baseConsoleDestinationIdentifier) as? ConsoleDestination {
        consoleLog.logQueue = XCGLogger.logQueue
    }
#endif

Append To Existing Log File

When using the advanced configuration of the logger (see Advanced Usage above), you can now specify that the logger append to an existing log file, instead of automatically overwriting it.

Add the optional shouldAppend: parameter when initializing the FileDestination object. You can also add the appendMarker: parameter to add a marker to the log file indicating where a new instance of your app started appending. By default we'll add -- ** ** ** -- if the parameter is omitted. Set it to nil to skip appending the marker.

let fileDestination = FileDestination(writeToFile: "/path/to/file", identifier: "advancedLogger.fileDestination", shouldAppend: true, appendMarker: "-- Relauched App --")

Automatic Log File Rotation

When logging to a file, you have the option to automatically rotate the log file to an archived destination, and have the logger automatically create a new log file in place of the old one.

Create a destination using the AutoRotatingFileDestination class and set the following properties:

targetMaxFileSize: Auto rotate once the file is larger than this

targetMaxTimeInterval: Auto rotate after this many seconds

targetMaxLogFiles: Number of archived log files to keep, older ones are automatically deleted

Those are all guidelines for the logger, not hard limits.

Extending XCGLogger

You can create alternate log destinations (besides the built in ones). Your custom log destination must implement the DestinationProtocol protocol. Instantiate your object, configure it, and then add it to the XCGLogger object with add(destination:). There are two base destination classes (BaseDestination and BaseQueuedDestination) you can inherit from to handle most of the process for you, requiring you to only implement one additional method in your custom class. Take a look at ConsoleDestination and FileDestination for examples.

You can also create custom filters or formatters. Take a look at the provided versions as a starting point. Note that filters and formatters have the ability to alter the log messages as they're processed. This means you can create a filter that strips passwords, highlights specific words, encrypts messages, etc.

Contributing

XCGLogger is the best logger available for Swift because of the contributions from the community like you. There are many ways you can help continue to make it great.

  1. Star the project on GitHub.
  2. Report issues/bugs you find.
  3. Suggest features.
  4. Submit pull requests.
  5. Download and install one of my apps: https://www.cerebralgardens.com/apps/ Try my newest app: All the Rings.
  6. You can visit my Patreon and contribute financially.

Note: when submitting a pull request, please use lots of small commits verses one huge commit. It makes it much easier to merge in when there are several pull requests that need to be combined for a new version.

To Do

  • Add more examples of some advanced use cases
  • Add additional log destination types
  • Add Objective-C support
  • Add Linux support

More

If you find this library helpful, you'll definitely find this other tool helpful:

Watchdog: https://watchdogforxcode.com/

Also, please check out some of my other projects:

Author: DaveWoodCom
Source Code: https://github.com/DaveWoodCom/XCGLogger
License: MIT license

#ios #swift 

What is GEEK

Buddha Community

XCGLogger: The Original Debug Log Module for Use in Swift Projects
Connor Mills

Connor Mills

1670560264

Understanding Arrays in Python

Learn how to use Python arrays. Create arrays in Python using the array module. You'll see how to define them and the different methods commonly used for performing operations on them.
 

The artcile covers arrays that you create by importing the array module. We won't cover NumPy arrays here.

Table of Contents

  1. Introduction to Arrays
    1. The differences between Lists and Arrays
    2. When to use arrays
  2. How to use arrays
    1. Define arrays
    2. Find the length of arrays
    3. Array indexing
    4. Search through arrays
    5. Loop through arrays
    6. Slice an array
  3. Array methods for performing operations
    1. Change an existing value
    2. Add a new value
    3. Remove a value
  4. Conclusion

Let's get started!


What are Python Arrays?

Arrays are a fundamental data structure, and an important part of most programming languages. In Python, they are containers which are able to store more than one item at the same time.

Specifically, they are an ordered collection of elements with every value being of the same data type. That is the most important thing to remember about Python arrays - the fact that they can only hold a sequence of multiple items that are of the same type.

What's the Difference between Python Lists and Python Arrays?

Lists are one of the most common data structures in Python, and a core part of the language.

Lists and arrays behave similarly.

Just like arrays, lists are an ordered sequence of elements.

They are also mutable and not fixed in size, which means they can grow and shrink throughout the life of the program. Items can be added and removed, making them very flexible to work with.

However, lists and arrays are not the same thing.

Lists store items that are of various data types. This means that a list can contain integers, floating point numbers, strings, or any other Python data type, at the same time. That is not the case with arrays.

As mentioned in the section above, arrays store only items that are of the same single data type. There are arrays that contain only integers, or only floating point numbers, or only any other Python data type you want to use.

When to Use Python Arrays

Lists are built into the Python programming language, whereas arrays aren't. Arrays are not a built-in data structure, and therefore need to be imported via the array module in order to be used.

Arrays of the array module are a thin wrapper over C arrays, and are useful when you want to work with homogeneous data.

They are also more compact and take up less memory and space which makes them more size efficient compared to lists.

If you want to perform mathematical calculations, then you should use NumPy arrays by importing the NumPy package. Besides that, you should just use Python arrays when you really need to, as lists work in a similar way and are more flexible to work with.

How to Use Arrays in Python

In order to create Python arrays, you'll first have to import the array module which contains all the necassary functions.

There are three ways you can import the array module:

  1. By using import array at the top of the file. This includes the module array. You would then go on to create an array using array.array().
import array

#how you would create an array
array.array()
  1. Instead of having to type array.array() all the time, you could use import array as arr at the top of the file, instead of import array alone. You would then create an array by typing arr.array(). The arr acts as an alias name, with the array constructor then immediately following it.
import array as arr

#how you would create an array
arr.array()
  1. Lastly, you could also use from array import *, with * importing all the functionalities available. You would then create an array by writing the array() constructor alone.
from array import *

#how you would create an array
array()

How to Define Arrays in Python

Once you've imported the array module, you can then go on to define a Python array.

The general syntax for creating an array looks like this:

variable_name = array(typecode,[elements])

Let's break it down:

  • variable_name would be the name of the array.
  • The typecode specifies what kind of elements would be stored in the array. Whether it would be an array of integers, an array of floats or an array of any other Python data type. Remember that all elements should be of the same data type.
  • Inside square brackets you mention the elements that would be stored in the array, with each element being separated by a comma. You can also create an empty array by just writing variable_name = array(typecode) alone, without any elements.

Below is a typecode table, with the different typecodes that can be used with the different data types when defining Python arrays:

TYPECODEC TYPEPYTHON TYPESIZE
'b'signed charint1
'B'unsigned charint1
'u'wchar_tUnicode character2
'h'signed shortint2
'H'unsigned shortint2
'i'signed intint2
'I'unsigned intint2
'l'signed longint4
'L'unsigned longint4
'q'signed long longint8
'Q'unsigned long longint8
'f'floatfloat4
'd'doublefloat8

Tying everything together, here is an example of how you would define an array in Python:

import array as arr 

numbers = arr.array('i',[10,20,30])


print(numbers)

#output

#array('i', [10, 20, 30])

Let's break it down:

  • First we included the array module, in this case with import array as arr .
  • Then, we created a numbers array.
  • We used arr.array() because of import array as arr .
  • Inside the array() constructor, we first included i, for signed integer. Signed integer means that the array can include positive and negative values. Unsigned integer, with H for example, would mean that no negative values are allowed.
  • Lastly, we included the values to be stored in the array in square brackets.

Keep in mind that if you tried to include values that were not of i typecode, meaning they were not integer values, you would get an error:

import array as arr 

numbers = arr.array('i',[10.0,20,30])


print(numbers)

#output

#Traceback (most recent call last):
# File "/Users/dionysialemonaki/python_articles/demo.py", line 14, in <module>
#   numbers = arr.array('i',[10.0,20,30])
#TypeError: 'float' object cannot be interpreted as an integer

In the example above, I tried to include a floating point number in the array. I got an error because this is meant to be an integer array only.

Another way to create an array is the following:

from array import *

#an array of floating point values
numbers = array('d',[10.0,20.0,30.0])

print(numbers)

#output

#array('d', [10.0, 20.0, 30.0])

The example above imported the array module via from array import * and created an array numbers of float data type. This means that it holds only floating point numbers, which is specified with the 'd' typecode.

How to Find the Length of an Array in Python

To find out the exact number of elements contained in an array, use the built-in len() method.

It will return the integer number that is equal to the total number of elements in the array you specify.

import array as arr 

numbers = arr.array('i',[10,20,30])


print(len(numbers))

#output
# 3

In the example above, the array contained three elements – 10, 20, 30 – so the length of numbers is 3.

Array Indexing and How to Access Individual Items in an Array in Python

Each item in an array has a specific address. Individual items are accessed by referencing their index number.

Indexing in Python, and in all programming languages and computing in general, starts at 0. It is important to remember that counting starts at 0 and not at 1.

To access an element, you first write the name of the array followed by square brackets. Inside the square brackets you include the item's index number.

The general syntax would look something like this:

array_name[index_value_of_item]

Here is how you would access each individual element in an array:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers[0]) # gets the 1st element
print(numbers[1]) # gets the 2nd element
print(numbers[2]) # gets the 3rd element

#output

#10
#20
#30

Remember that the index value of the last element of an array is always one less than the length of the array. Where n is the length of the array, n - 1 will be the index value of the last item.

Note that you can also access each individual element using negative indexing.

With negative indexing, the last element would have an index of -1, the second to last element would have an index of -2, and so on.

Here is how you would get each item in an array using that method:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers[-1]) #gets last item
print(numbers[-2]) #gets second to last item
print(numbers[-3]) #gets first item
 
#output

#30
#20
#10

How to Search Through an Array in Python

You can find out an element's index number by using the index() method.

You pass the value of the element being searched as the argument to the method, and the element's index number is returned.

import array as arr 

numbers = arr.array('i',[10,20,30])

#search for the index of the value 10
print(numbers.index(10))

#output

#0

If there is more than one element with the same value, the index of the first instance of the value will be returned:

import array as arr 


numbers = arr.array('i',[10,20,30,10,20,30])

#search for the index of the value 10
#will return the index number of the first instance of the value 10
print(numbers.index(10))

#output

#0

How to Loop through an Array in Python

You've seen how to access each individual element in an array and print it out on its own.

You've also seen how to print the array, using the print() method. That method gives the following result:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers)

#output

#array('i', [10, 20, 30])

What if you want to print each value one by one?

This is where a loop comes in handy. You can loop through the array and print out each value, one-by-one, with each loop iteration.

For this you can use a simple for loop:

import array as arr 

numbers = arr.array('i',[10,20,30])

for number in numbers:
    print(number)
    
#output
#10
#20
#30

You could also use the range() function, and pass the len() method as its parameter. This would give the same result as above:

import array as arr  

values = arr.array('i',[10,20,30])

#prints each individual value in the array
for value in range(len(values)):
    print(values[value])

#output

#10
#20
#30

How to Slice an Array in Python

To access a specific range of values inside the array, use the slicing operator, which is a colon :.

When using the slicing operator and you only include one value, the counting starts from 0 by default. It gets the first item, and goes up to but not including the index number you specify.


import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#get the values 10 and 20 only
print(numbers[:2])  #first to second position

#output

#array('i', [10, 20])

When you pass two numbers as arguments, you specify a range of numbers. In this case, the counting starts at the position of the first number in the range, and up to but not including the second one:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])


#get the values 20 and 30 only
print(numbers[1:3]) #second to third position

#output

#rray('i', [20, 30])

Methods For Performing Operations on Arrays in Python

Arrays are mutable, which means they are changeable. You can change the value of the different items, add new ones, or remove any you don't want in your program anymore.

Let's see some of the most commonly used methods which are used for performing operations on arrays.

How to Change the Value of an Item in an Array

You can change the value of a specific element by speficying its position and assigning it a new value:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#change the first element
#change it from having a value of 10 to having a value of 40
numbers[0] = 40

print(numbers)

#output

#array('i', [40, 20, 30])

How to Add a New Value to an Array

To add one single value at the end of an array, use the append() method:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 to the end of numbers
numbers.append(40)

print(numbers)

#output

#array('i', [10, 20, 30, 40])

Be aware that the new item you add needs to be the same data type as the rest of the items in the array.

Look what happens when I try to add a float to an array of integers:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 to the end of numbers
numbers.append(40.0)

print(numbers)

#output

#Traceback (most recent call last):
#  File "/Users/dionysialemonaki/python_articles/demo.py", line 19, in <module>
#   numbers.append(40.0)
#TypeError: 'float' object cannot be interpreted as an integer

But what if you want to add more than one value to the end an array?

Use the extend() method, which takes an iterable (such as a list of items) as an argument. Again, make sure that the new items are all the same data type.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integers 40,50,60 to the end of numbers
#The numbers need to be enclosed in square brackets

numbers.extend([40,50,60])

print(numbers)

#output

#array('i', [10, 20, 30, 40, 50, 60])

And what if you don't want to add an item to the end of an array? Use the insert() method, to add an item at a specific position.

The insert() function takes two arguments: the index number of the position the new element will be inserted, and the value of the new element.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 in the first position
#remember indexing starts at 0

numbers.insert(0,40)

print(numbers)

#output

#array('i', [40, 10, 20, 30])

How to Remove a Value from an Array

To remove an element from an array, use the remove() method and include the value as an argument to the method.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

numbers.remove(10)

print(numbers)

#output

#array('i', [20, 30])

With remove(), only the first instance of the value you pass as an argument will be removed.

See what happens when there are more than one identical values:


import array as arr 

#original array
numbers = arr.array('i',[10,20,30,10,20])

numbers.remove(10)

print(numbers)

#output

#array('i', [20, 30, 10, 20])

Only the first occurence of 10 is removed.

You can also use the pop() method, and specify the position of the element to be removed:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30,10,20])

#remove the first instance of 10
numbers.pop(0)

print(numbers)

#output

#array('i', [20, 30, 10, 20])

Conclusion

And there you have it - you now know the basics of how to create arrays in Python using the array module. Hopefully you found this guide helpful.

You'll start from the basics and learn in an interacitve and beginner-friendly way. You'll also build five projects at the end to put into practice and help reinforce what you learned.

Thanks for reading and happy coding!

Original article source at https://www.freecodecamp.org

#python 

How to Create Arrays in Python

In this tutorial, you'll know the basics of how to create arrays in Python using the array module. Learn how to use Python arrays. You'll see how to define them and the different methods commonly used for performing operations on them.

This tutorialvideo on 'Arrays in Python' will help you establish a strong hold on all the fundamentals in python programming language. Below are the topics covered in this video:  
1:15 What is an array?
2:53 Is python list same as an array?
3:48  How to create arrays in python?
7:19 Accessing array elements
9:59 Basic array operations
        - 10:33  Finding the length of an array
        - 11:44  Adding Elements
        - 15:06  Removing elements
        - 18:32  Array concatenation
       - 20:59  Slicing
       - 23:26  Looping  


Python Array Tutorial – Define, Index, Methods

In this article, you'll learn how to use Python arrays. You'll see how to define them and the different methods commonly used for performing operations on them.

The artcile covers arrays that you create by importing the array module. We won't cover NumPy arrays here.

Table of Contents

  1. Introduction to Arrays
    1. The differences between Lists and Arrays
    2. When to use arrays
  2. How to use arrays
    1. Define arrays
    2. Find the length of arrays
    3. Array indexing
    4. Search through arrays
    5. Loop through arrays
    6. Slice an array
  3. Array methods for performing operations
    1. Change an existing value
    2. Add a new value
    3. Remove a value
  4. Conclusion

Let's get started!

What are Python Arrays?

Arrays are a fundamental data structure, and an important part of most programming languages. In Python, they are containers which are able to store more than one item at the same time.

Specifically, they are an ordered collection of elements with every value being of the same data type. That is the most important thing to remember about Python arrays - the fact that they can only hold a sequence of multiple items that are of the same type.

What's the Difference between Python Lists and Python Arrays?

Lists are one of the most common data structures in Python, and a core part of the language.

Lists and arrays behave similarly.

Just like arrays, lists are an ordered sequence of elements.

They are also mutable and not fixed in size, which means they can grow and shrink throughout the life of the program. Items can be added and removed, making them very flexible to work with.

However, lists and arrays are not the same thing.

Lists store items that are of various data types. This means that a list can contain integers, floating point numbers, strings, or any other Python data type, at the same time. That is not the case with arrays.

As mentioned in the section above, arrays store only items that are of the same single data type. There are arrays that contain only integers, or only floating point numbers, or only any other Python data type you want to use.

When to Use Python Arrays

Lists are built into the Python programming language, whereas arrays aren't. Arrays are not a built-in data structure, and therefore need to be imported via the array module in order to be used.

Arrays of the array module are a thin wrapper over C arrays, and are useful when you want to work with homogeneous data.

They are also more compact and take up less memory and space which makes them more size efficient compared to lists.

If you want to perform mathematical calculations, then you should use NumPy arrays by importing the NumPy package. Besides that, you should just use Python arrays when you really need to, as lists work in a similar way and are more flexible to work with.

How to Use Arrays in Python

In order to create Python arrays, you'll first have to import the array module which contains all the necassary functions.

There are three ways you can import the array module:

  • By using import array at the top of the file. This includes the module array. You would then go on to create an array using array.array().
import array

#how you would create an array
array.array()
  • Instead of having to type array.array() all the time, you could use import array as arr at the top of the file, instead of import array alone. You would then create an array by typing arr.array(). The arr acts as an alias name, with the array constructor then immediately following it.
import array as arr

#how you would create an array
arr.array()
  • Lastly, you could also use from array import *, with * importing all the functionalities available. You would then create an array by writing the array() constructor alone.
from array import *

#how you would create an array
array()

How to Define Arrays in Python

Once you've imported the array module, you can then go on to define a Python array.

The general syntax for creating an array looks like this:

variable_name = array(typecode,[elements])

Let's break it down:

  • variable_name would be the name of the array.
  • The typecode specifies what kind of elements would be stored in the array. Whether it would be an array of integers, an array of floats or an array of any other Python data type. Remember that all elements should be of the same data type.
  • Inside square brackets you mention the elements that would be stored in the array, with each element being separated by a comma. You can also create an empty array by just writing variable_name = array(typecode) alone, without any elements.

Below is a typecode table, with the different typecodes that can be used with the different data types when defining Python arrays:

TYPECODEC TYPEPYTHON TYPESIZE
'b'signed charint1
'B'unsigned charint1
'u'wchar_tUnicode character2
'h'signed shortint2
'H'unsigned shortint2
'i'signed intint2
'I'unsigned intint2
'l'signed longint4
'L'unsigned longint4
'q'signed long longint8
'Q'unsigned long longint8
'f'floatfloat4
'd'doublefloat8

Tying everything together, here is an example of how you would define an array in Python:

import array as arr 

numbers = arr.array('i',[10,20,30])


print(numbers)

#output

#array('i', [10, 20, 30])

Let's break it down:

  • First we included the array module, in this case with import array as arr .
  • Then, we created a numbers array.
  • We used arr.array() because of import array as arr .
  • Inside the array() constructor, we first included i, for signed integer. Signed integer means that the array can include positive and negative values. Unsigned integer, with H for example, would mean that no negative values are allowed.
  • Lastly, we included the values to be stored in the array in square brackets.

Keep in mind that if you tried to include values that were not of i typecode, meaning they were not integer values, you would get an error:

import array as arr 

numbers = arr.array('i',[10.0,20,30])


print(numbers)

#output

#Traceback (most recent call last):
# File "/Users/dionysialemonaki/python_articles/demo.py", line 14, in <module>
#   numbers = arr.array('i',[10.0,20,30])
#TypeError: 'float' object cannot be interpreted as an integer

In the example above, I tried to include a floating point number in the array. I got an error because this is meant to be an integer array only.

Another way to create an array is the following:

from array import *

#an array of floating point values
numbers = array('d',[10.0,20.0,30.0])

print(numbers)

#output

#array('d', [10.0, 20.0, 30.0])

The example above imported the array module via from array import * and created an array numbers of float data type. This means that it holds only floating point numbers, which is specified with the 'd' typecode.

How to Find the Length of an Array in Python

To find out the exact number of elements contained in an array, use the built-in len() method.

It will return the integer number that is equal to the total number of elements in the array you specify.

import array as arr 

numbers = arr.array('i',[10,20,30])


print(len(numbers))

#output
# 3

In the example above, the array contained three elements – 10, 20, 30 – so the length of numbers is 3.

Array Indexing and How to Access Individual Items in an Array in Python

Each item in an array has a specific address. Individual items are accessed by referencing their index number.

Indexing in Python, and in all programming languages and computing in general, starts at 0. It is important to remember that counting starts at 0 and not at 1.

To access an element, you first write the name of the array followed by square brackets. Inside the square brackets you include the item's index number.

The general syntax would look something like this:

array_name[index_value_of_item]

Here is how you would access each individual element in an array:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers[0]) # gets the 1st element
print(numbers[1]) # gets the 2nd element
print(numbers[2]) # gets the 3rd element

#output

#10
#20
#30

Remember that the index value of the last element of an array is always one less than the length of the array. Where n is the length of the array, n - 1 will be the index value of the last item.

Note that you can also access each individual element using negative indexing.

With negative indexing, the last element would have an index of -1, the second to last element would have an index of -2, and so on.

Here is how you would get each item in an array using that method:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers[-1]) #gets last item
print(numbers[-2]) #gets second to last item
print(numbers[-3]) #gets first item
 
#output

#30
#20
#10

How to Search Through an Array in Python

You can find out an element's index number by using the index() method.

You pass the value of the element being searched as the argument to the method, and the element's index number is returned.

import array as arr 

numbers = arr.array('i',[10,20,30])

#search for the index of the value 10
print(numbers.index(10))

#output

#0

If there is more than one element with the same value, the index of the first instance of the value will be returned:

import array as arr 


numbers = arr.array('i',[10,20,30,10,20,30])

#search for the index of the value 10
#will return the index number of the first instance of the value 10
print(numbers.index(10))

#output

#0

How to Loop through an Array in Python

You've seen how to access each individual element in an array and print it out on its own.

You've also seen how to print the array, using the print() method. That method gives the following result:

import array as arr 

numbers = arr.array('i',[10,20,30])

print(numbers)

#output

#array('i', [10, 20, 30])

What if you want to print each value one by one?

This is where a loop comes in handy. You can loop through the array and print out each value, one-by-one, with each loop iteration.

For this you can use a simple for loop:

import array as arr 

numbers = arr.array('i',[10,20,30])

for number in numbers:
    print(number)
    
#output
#10
#20
#30

You could also use the range() function, and pass the len() method as its parameter. This would give the same result as above:

import array as arr  

values = arr.array('i',[10,20,30])

#prints each individual value in the array
for value in range(len(values)):
    print(values[value])

#output

#10
#20
#30

How to Slice an Array in Python

To access a specific range of values inside the array, use the slicing operator, which is a colon :.

When using the slicing operator and you only include one value, the counting starts from 0 by default. It gets the first item, and goes up to but not including the index number you specify.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#get the values 10 and 20 only
print(numbers[:2])  #first to second position

#output

#array('i', [10, 20])

When you pass two numbers as arguments, you specify a range of numbers. In this case, the counting starts at the position of the first number in the range, and up to but not including the second one:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])


#get the values 20 and 30 only
print(numbers[1:3]) #second to third position

#output

#rray('i', [20, 30])

Methods For Performing Operations on Arrays in Python

Arrays are mutable, which means they are changeable. You can change the value of the different items, add new ones, or remove any you don't want in your program anymore.

Let's see some of the most commonly used methods which are used for performing operations on arrays.

How to Change the Value of an Item in an Array

You can change the value of a specific element by speficying its position and assigning it a new value:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#change the first element
#change it from having a value of 10 to having a value of 40
numbers[0] = 40

print(numbers)

#output

#array('i', [40, 20, 30])

How to Add a New Value to an Array

To add one single value at the end of an array, use the append() method:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 to the end of numbers
numbers.append(40)

print(numbers)

#output

#array('i', [10, 20, 30, 40])

Be aware that the new item you add needs to be the same data type as the rest of the items in the array.

Look what happens when I try to add a float to an array of integers:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 to the end of numbers
numbers.append(40.0)

print(numbers)

#output

#Traceback (most recent call last):
#  File "/Users/dionysialemonaki/python_articles/demo.py", line 19, in <module>
#   numbers.append(40.0)
#TypeError: 'float' object cannot be interpreted as an integer

But what if you want to add more than one value to the end an array?

Use the extend() method, which takes an iterable (such as a list of items) as an argument. Again, make sure that the new items are all the same data type.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integers 40,50,60 to the end of numbers
#The numbers need to be enclosed in square brackets

numbers.extend([40,50,60])

print(numbers)

#output

#array('i', [10, 20, 30, 40, 50, 60])

And what if you don't want to add an item to the end of an array? Use the insert() method, to add an item at a specific position.

The insert() function takes two arguments: the index number of the position the new element will be inserted, and the value of the new element.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

#add the integer 40 in the first position
#remember indexing starts at 0

numbers.insert(0,40)

print(numbers)

#output

#array('i', [40, 10, 20, 30])

How to Remove a Value from an Array

To remove an element from an array, use the remove() method and include the value as an argument to the method.

import array as arr 

#original array
numbers = arr.array('i',[10,20,30])

numbers.remove(10)

print(numbers)

#output

#array('i', [20, 30])

With remove(), only the first instance of the value you pass as an argument will be removed.

See what happens when there are more than one identical values:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30,10,20])

numbers.remove(10)

print(numbers)

#output

#array('i', [20, 30, 10, 20])

Only the first occurence of 10 is removed.

You can also use the pop() method, and specify the position of the element to be removed:

import array as arr 

#original array
numbers = arr.array('i',[10,20,30,10,20])

#remove the first instance of 10
numbers.pop(0)

print(numbers)

#output

#array('i', [20, 30, 10, 20])

Conclusion

And there you have it - you now know the basics of how to create arrays in Python using the array module. Hopefully you found this guide helpful.

Thanks for reading and happy coding!

#python #programming 

Chloe  Butler

Chloe Butler

1667425440

Pdf2gerb: Perl Script Converts PDF Files to Gerber format

pdf2gerb

Perl script converts PDF files to Gerber format

Pdf2Gerb generates Gerber 274X photoplotting and Excellon drill files from PDFs of a PCB. Up to three PDFs are used: the top copper layer, the bottom copper layer (for 2-sided PCBs), and an optional silk screen layer. The PDFs can be created directly from any PDF drawing software, or a PDF print driver can be used to capture the Print output if the drawing software does not directly support output to PDF.

The general workflow is as follows:

  1. Design the PCB using your favorite CAD or drawing software.
  2. Print the top and bottom copper and top silk screen layers to a PDF file.
  3. Run Pdf2Gerb on the PDFs to create Gerber and Excellon files.
  4. Use a Gerber viewer to double-check the output against the original PCB design.
  5. Make adjustments as needed.
  6. Submit the files to a PCB manufacturer.

Please note that Pdf2Gerb does NOT perform DRC (Design Rule Checks), as these will vary according to individual PCB manufacturer conventions and capabilities. Also note that Pdf2Gerb is not perfect, so the output files must always be checked before submitting them. As of version 1.6, Pdf2Gerb supports most PCB elements, such as round and square pads, round holes, traces, SMD pads, ground planes, no-fill areas, and panelization. However, because it interprets the graphical output of a Print function, there are limitations in what it can recognize (or there may be bugs).

See docs/Pdf2Gerb.pdf for install/setup, config, usage, and other info.


pdf2gerb_cfg.pm

#Pdf2Gerb config settings:
#Put this file in same folder/directory as pdf2gerb.pl itself (global settings),
#or copy to another folder/directory with PDFs if you want PCB-specific settings.
#There is only one user of this file, so we don't need a custom package or namespace.
#NOTE: all constants defined in here will be added to main namespace.
#package pdf2gerb_cfg;

use strict; #trap undef vars (easier debug)
use warnings; #other useful info (easier debug)


##############################################################################################
#configurable settings:
#change values here instead of in main pfg2gerb.pl file

use constant WANT_COLORS => ($^O !~ m/Win/); #ANSI colors no worky on Windows? this must be set < first DebugPrint() call

#just a little warning; set realistic expectations:
#DebugPrint("${\(CYAN)}Pdf2Gerb.pl ${\(VERSION)}, $^O O/S\n${\(YELLOW)}${\(BOLD)}${\(ITALIC)}This is EXPERIMENTAL software.  \nGerber files MAY CONTAIN ERRORS.  Please CHECK them before fabrication!${\(RESET)}", 0); #if WANT_DEBUG

use constant METRIC => FALSE; #set to TRUE for metric units (only affect final numbers in output files, not internal arithmetic)
use constant APERTURE_LIMIT => 0; #34; #max #apertures to use; generate warnings if too many apertures are used (0 to not check)
use constant DRILL_FMT => '2.4'; #'2.3'; #'2.4' is the default for PCB fab; change to '2.3' for CNC

use constant WANT_DEBUG => 0; #10; #level of debug wanted; higher == more, lower == less, 0 == none
use constant GERBER_DEBUG => 0; #level of debug to include in Gerber file; DON'T USE FOR FABRICATION
use constant WANT_STREAMS => FALSE; #TRUE; #save decompressed streams to files (for debug)
use constant WANT_ALLINPUT => FALSE; #TRUE; #save entire input stream (for debug ONLY)

#DebugPrint(sprintf("${\(CYAN)}DEBUG: stdout %d, gerber %d, want streams? %d, all input? %d, O/S: $^O, Perl: $]${\(RESET)}\n", WANT_DEBUG, GERBER_DEBUG, WANT_STREAMS, WANT_ALLINPUT), 1);
#DebugPrint(sprintf("max int = %d, min int = %d\n", MAXINT, MININT), 1); 

#define standard trace and pad sizes to reduce scaling or PDF rendering errors:
#This avoids weird aperture settings and replaces them with more standardized values.
#(I'm not sure how photoplotters handle strange sizes).
#Fewer choices here gives more accurate mapping in the final Gerber files.
#units are in inches
use constant TOOL_SIZES => #add more as desired
(
#round or square pads (> 0) and drills (< 0):
    .010, -.001,  #tiny pads for SMD; dummy drill size (too small for practical use, but needed so StandardTool will use this entry)
    .031, -.014,  #used for vias
    .041, -.020,  #smallest non-filled plated hole
    .051, -.025,
    .056, -.029,  #useful for IC pins
    .070, -.033,
    .075, -.040,  #heavier leads
#    .090, -.043,  #NOTE: 600 dpi is not high enough resolution to reliably distinguish between .043" and .046", so choose 1 of the 2 here
    .100, -.046,
    .115, -.052,
    .130, -.061,
    .140, -.067,
    .150, -.079,
    .175, -.088,
    .190, -.093,
    .200, -.100,
    .220, -.110,
    .160, -.125,  #useful for mounting holes
#some additional pad sizes without holes (repeat a previous hole size if you just want the pad size):
    .090, -.040,  #want a .090 pad option, but use dummy hole size
    .065, -.040, #.065 x .065 rect pad
    .035, -.040, #.035 x .065 rect pad
#traces:
    .001,  #too thin for real traces; use only for board outlines
    .006,  #minimum real trace width; mainly used for text
    .008,  #mainly used for mid-sized text, not traces
    .010,  #minimum recommended trace width for low-current signals
    .012,
    .015,  #moderate low-voltage current
    .020,  #heavier trace for power, ground (even if a lighter one is adequate)
    .025,
    .030,  #heavy-current traces; be careful with these ones!
    .040,
    .050,
    .060,
    .080,
    .100,
    .120,
);
#Areas larger than the values below will be filled with parallel lines:
#This cuts down on the number of aperture sizes used.
#Set to 0 to always use an aperture or drill, regardless of size.
use constant { MAX_APERTURE => max((TOOL_SIZES)) + .004, MAX_DRILL => -min((TOOL_SIZES)) + .004 }; #max aperture and drill sizes (plus a little tolerance)
#DebugPrint(sprintf("using %d standard tool sizes: %s, max aper %.3f, max drill %.3f\n", scalar((TOOL_SIZES)), join(", ", (TOOL_SIZES)), MAX_APERTURE, MAX_DRILL), 1);

#NOTE: Compare the PDF to the original CAD file to check the accuracy of the PDF rendering and parsing!
#for example, the CAD software I used generated the following circles for holes:
#CAD hole size:   parsed PDF diameter:      error:
#  .014                .016                +.002
#  .020                .02267              +.00267
#  .025                .026                +.001
#  .029                .03167              +.00267
#  .033                .036                +.003
#  .040                .04267              +.00267
#This was usually ~ .002" - .003" too big compared to the hole as displayed in the CAD software.
#To compensate for PDF rendering errors (either during CAD Print function or PDF parsing logic), adjust the values below as needed.
#units are pixels; for example, a value of 2.4 at 600 dpi = .0004 inch, 2 at 600 dpi = .0033"
use constant
{
    HOLE_ADJUST => -0.004 * 600, #-2.6, #holes seemed to be slightly oversized (by .002" - .004"), so shrink them a little
    RNDPAD_ADJUST => -0.003 * 600, #-2, #-2.4, #round pads seemed to be slightly oversized, so shrink them a little
    SQRPAD_ADJUST => +0.001 * 600, #+.5, #square pads are sometimes too small by .00067, so bump them up a little
    RECTPAD_ADJUST => 0, #(pixels) rectangular pads seem to be okay? (not tested much)
    TRACE_ADJUST => 0, #(pixels) traces seemed to be okay?
    REDUCE_TOLERANCE => .001, #(inches) allow this much variation when reducing circles and rects
};

#Also, my CAD's Print function or the PDF print driver I used was a little off for circles, so define some additional adjustment values here:
#Values are added to X/Y coordinates; units are pixels; for example, a value of 1 at 600 dpi would be ~= .002 inch
use constant
{
    CIRCLE_ADJUST_MINX => 0,
    CIRCLE_ADJUST_MINY => -0.001 * 600, #-1, #circles were a little too high, so nudge them a little lower
    CIRCLE_ADJUST_MAXX => +0.001 * 600, #+1, #circles were a little too far to the left, so nudge them a little to the right
    CIRCLE_ADJUST_MAXY => 0,
    SUBST_CIRCLE_CLIPRECT => FALSE, #generate circle and substitute for clip rects (to compensate for the way some CAD software draws circles)
    WANT_CLIPRECT => TRUE, #FALSE, #AI doesn't need clip rect at all? should be on normally?
    RECT_COMPLETION => FALSE, #TRUE, #fill in 4th side of rect when 3 sides found
};

#allow .012 clearance around pads for solder mask:
#This value effectively adjusts pad sizes in the TOOL_SIZES list above (only for solder mask layers).
use constant SOLDER_MARGIN => +.012; #units are inches

#line join/cap styles:
use constant
{
    CAP_NONE => 0, #butt (none); line is exact length
    CAP_ROUND => 1, #round cap/join; line overhangs by a semi-circle at either end
    CAP_SQUARE => 2, #square cap/join; line overhangs by a half square on either end
    CAP_OVERRIDE => FALSE, #cap style overrides drawing logic
};
    
#number of elements in each shape type:
use constant
{
    RECT_SHAPELEN => 6, #x0, y0, x1, y1, count, "rect" (start, end corners)
    LINE_SHAPELEN => 6, #x0, y0, x1, y1, count, "line" (line seg)
    CURVE_SHAPELEN => 10, #xstart, ystart, x0, y0, x1, y1, xend, yend, count, "curve" (bezier 2 points)
    CIRCLE_SHAPELEN => 5, #x, y, 5, count, "circle" (center + radius)
};
#const my %SHAPELEN =
#Readonly my %SHAPELEN =>
our %SHAPELEN =
(
    rect => RECT_SHAPELEN,
    line => LINE_SHAPELEN,
    curve => CURVE_SHAPELEN,
    circle => CIRCLE_SHAPELEN,
);

#panelization:
#This will repeat the entire body the number of times indicated along the X or Y axes (files grow accordingly).
#Display elements that overhang PCB boundary can be squashed or left as-is (typically text or other silk screen markings).
#Set "overhangs" TRUE to allow overhangs, FALSE to truncate them.
#xpad and ypad allow margins to be added around outer edge of panelized PCB.
use constant PANELIZE => {'x' => 1, 'y' => 1, 'xpad' => 0, 'ypad' => 0, 'overhangs' => TRUE}; #number of times to repeat in X and Y directions

# Set this to 1 if you need TurboCAD support.
#$turboCAD = FALSE; #is this still needed as an option?

#CIRCAD pad generation uses an appropriate aperture, then moves it (stroke) "a little" - we use this to find pads and distinguish them from PCB holes. 
use constant PAD_STROKE => 0.3; #0.0005 * 600; #units are pixels
#convert very short traces to pads or holes:
use constant TRACE_MINLEN => .001; #units are inches
#use constant ALWAYS_XY => TRUE; #FALSE; #force XY even if X or Y doesn't change; NOTE: needs to be TRUE for all pads to show in FlatCAM and ViewPlot
use constant REMOVE_POLARITY => FALSE; #TRUE; #set to remove subtractive (negative) polarity; NOTE: must be FALSE for ground planes

#PDF uses "points", each point = 1/72 inch
#combined with a PDF scale factor of .12, this gives 600 dpi resolution (1/72 * .12 = 600 dpi)
use constant INCHES_PER_POINT => 1/72; #0.0138888889; #multiply point-size by this to get inches

# The precision used when computing a bezier curve. Higher numbers are more precise but slower (and generate larger files).
#$bezierPrecision = 100;
use constant BEZIER_PRECISION => 36; #100; #use const; reduced for faster rendering (mainly used for silk screen and thermal pads)

# Ground planes and silk screen or larger copper rectangles or circles are filled line-by-line using this resolution.
use constant FILL_WIDTH => .01; #fill at most 0.01 inch at a time

# The max number of characters to read into memory
use constant MAX_BYTES => 10 * M; #bumped up to 10 MB, use const

use constant DUP_DRILL1 => TRUE; #FALSE; #kludge: ViewPlot doesn't load drill files that are too small so duplicate first tool

my $runtime = time(); #Time::HiRes::gettimeofday(); #measure my execution time

print STDERR "Loaded config settings from '${\(__FILE__)}'.\n";
1; #last value must be truthful to indicate successful load


#############################################################################################
#junk/experiment:

#use Package::Constants;
#use Exporter qw(import); #https://perldoc.perl.org/Exporter.html

#my $caller = "pdf2gerb::";

#sub cfg
#{
#    my $proto = shift;
#    my $class = ref($proto) || $proto;
#    my $settings =
#    {
#        $WANT_DEBUG => 990, #10; #level of debug wanted; higher == more, lower == less, 0 == none
#    };
#    bless($settings, $class);
#    return $settings;
#}

#use constant HELLO => "hi there2"; #"main::HELLO" => "hi there";
#use constant GOODBYE => 14; #"main::GOODBYE" => 12;

#print STDERR "read cfg file\n";

#our @EXPORT_OK = Package::Constants->list(__PACKAGE__); #https://www.perlmonks.org/?node_id=1072691; NOTE: "_OK" skips short/common names

#print STDERR scalar(@EXPORT_OK) . " consts exported:\n";
#foreach(@EXPORT_OK) { print STDERR "$_\n"; }
#my $val = main::thing("xyz");
#print STDERR "caller gave me $val\n";
#foreach my $arg (@ARGV) { print STDERR "arg $arg\n"; }

Download Details:

Author: swannman
Source Code: https://github.com/swannman/pdf2gerb

License: GPL-3.0 license

#perl 

Autumn  Blick

Autumn Blick

1593867420

Top Android Projects with Source Code

Android Projects with Source Code – Your entry pass into the world of Android

Hello Everyone, welcome to this article, which is going to be really important to all those who’re in dilemma for their projects and the project submissions. This article is also going to help you if you’re an enthusiast looking forward to explore and enhance your Android skills. The reason is that we’re here to provide you the best ideas of Android Project with source code that you can choose as per your choice.

These project ideas are simple suggestions to help you deal with the difficulty of choosing the correct projects. In this article, we’ll see the project ideas from beginners level and later we’ll move on to intermediate to advance.

top android projects with source code

Android Projects with Source Code

Before working on real-time projects, it is recommended to create a sample hello world project in android studio and get a flavor of project creation as well as execution: Create your first android project

Android Projects for beginners

1. Calculator

build a simple calculator app in android studio source code

Android Project: A calculator will be an easy application if you have just learned Android and coding for Java. This Application will simply take the input values and the operation to be performed from the users. After taking the input it’ll return the results to them on the screen. This is a really easy application and doesn’t need use of any particular package.

To make a calculator you’d need Android IDE, Kotlin/Java for coding, and for layout of your application, you’d need XML or JSON. For this, coding would be the same as that in any language, but in the form of an application. Not to forget creating a calculator initially will increase your logical thinking.

Once the user installs the calculator, they’re ready to use it even without the internet. They’ll enter the values, and the application will show them the value after performing the given operations on the entered operands.

Source Code: Simple Calculator Project

2. A Reminder App

Android Project: This is a good project for beginners. A Reminder App can help you set reminders for different events that you have throughout the day. It’ll help you stay updated with all your tasks for the day. It can be useful for all those who are not so good at organizing their plans and forget easily. This would be a simple application just whose task would be just to remind you of something at a particular time.

To make a Reminder App you need to code in Kotlin/Java and design the layout using XML or JSON. For the functionality of the app, you’d need to make use of AlarmManager Class and Notifications in Android.

In this, the user would be able to set reminders and time in the application. Users can schedule reminders that would remind them to drink water again and again throughout the day. Or to remind them of their medications.

3. Quiz Application

Android Project: Another beginner’s level project Idea can be a Quiz Application in android. Here you can provide the users with Quiz on various general knowledge topics. These practices will ensure that you’re able to set the layouts properly and slowly increase your pace of learning the Android application development. In this you’ll learn to use various Layout components at the same time understanding them better.

To make a quiz application you’ll need to code in Java and set layouts using xml or java whichever you prefer. You can also use JSON for the layouts whichever preferable.

In the app, questions would be asked and answers would be shown as multiple choices. The user selects the answer and gets shown on the screen if the answers are correct. In the end the final marks would be shown to the users.

4. Simple Tic-Tac-Toe

android project tic tac toe game app

Android Project: Tic-Tac-Toe is a nice game, I guess most of you all are well aware of it. This will be a game for two players. In this android game, users would be putting X and O in the given 9 parts of a box one by one. The first player to arrange X or O in an adjacent line of three wins.

To build this game, you’d need Java and XML for Android Studio. And simply apply the logic on that. This game will have a set of three matches. So, it’ll also have a scoreboard. This scoreboard will show the final result at the end of one complete set.

Upon entering the game they’ll enter their names. And that’s when the game begins. They’ll touch one of the empty boxes present there and get their turn one by one. At the end of the game, there would be a winner declared.

Source Code: Tic Tac Toe Game Project

5. Stopwatch

Android Project: A stopwatch is another simple android project idea that will work the same as a normal handheld timepiece that measures the time elapsed between its activation and deactivation. This application will have three buttons that are: start, stop, and hold.

This application would need to use Java and XML. For this application, we need to set the timer properly as it is initially set to milliseconds, and that should be converted to minutes and then hours properly. The users can use this application and all they’d need to do is, start the stopwatch and then stop it when they are done. They can also pause the timer and continue it again when they like.

6. To Do App

Android Project: This is another very simple project idea for you as a beginner. This application as the name suggests will be a To-Do list holding app. It’ll store the users schedules and their upcoming meetings or events. In this application, users will be enabled to write their important notes as well. To make it safe, provide a login page before the user can access it.

So, this app will have a login page, sign-up page, logout system, and the area to write their tasks, events, or important notes. You can build it in android studio using Java and XML at ease. Using XML you can build the user interface as user-friendly as you can. And to store the users’ data, you can use SQLite enabling the users to even delete the data permanently.

Now for users, they will sign up and get access to the write section. Here the users can note down the things and store them permanently. Users can also alter the data or delete them. Finally, they can logout and also, login again and again whenever they like.

7. Roman to decimal converter

Android Project: This app is aimed at the conversion of Roman numbers to their significant decimal number. It’ll help to check the meaning of the roman numbers. Moreover, it will be easy to develop and will help you get your hands on coding and Android.

You need to use Android Studio, Java for coding and XML for interface. The application will take input from the users and convert them to decimal. Once it converts the Roman no. into decimal, it will show the results on the screen.

The users are supposed to just enter the Roman Number and they’ll get the decimal values on the screen. This can be a good android project for final year students.

8. Virtual Dice Roller

Android Project: Well, coming to this part that is Virtual Dice or a random no. generator. It is another simple but interesting app for computer science students. The only task that it would need to do would be to generate a number randomly. This can help people who’re often confused between two or more things.

Using a simple random number generator you can actually create something as good as this. All you’d need to do is get you hands-on OnClick listeners. And a good layout would be cherry on the cake.

The user’s task would be to set the range of the numbers and then click on the roll button. And the app will show them a randomly generated number. Isn’t it interesting ? Try soon!

9. A Scientific Calculator App

Android Project: This application is very important for you as a beginner as it will let you use your logical thinking and improve your programming skills. This is a scientific calculator that will help the users to do various calculations at ease.

To make this application you’d need to use Android Studio. Here you’d need to use arithmetic logics for the calculations. The user would need to give input to the application that will be in terms of numbers. After that, the user will give the operator as an input. Then the Application will calculate and generate the result on the user screen.

10. SMS App

Android Project: An SMS app is another easy but effective idea. It will let you send the SMS to various no. just in the same way as you use the default messaging application in your phone. This project will help you with better understanding of SMSManager in Android.

For this application, you would need to implement Java class SMSManager in Android. For the Layout you can use XML or JSON. Implementing SMSManager into the app is an easy task, so you would love this.

The user would be provided with the facility to text to whichever number they wish also, they’d be able to choose the numbers from the contact list. Another thing would be the Textbox, where they’ll enter their message. Once the message is entered they can happily click on the send button.

#android tutorials #android application final year project #android mini projects #android project for beginners #android project ideas #android project ideas for beginners #android projects #android projects for students #android projects with source code #android topics list #intermediate android projects #real-time android projects

Shawn  Durgan

Shawn Durgan

1595547778

10 Writing steps to create a good project brief - Mobile app development

Developing a mobile application can often be more challenging than it seems at first glance. Whether you’re a developer, UI designer, project lead or CEO of a mobile-based startup, writing good project briefs prior to development is pivotal. According to Tech Jury, 87% of smartphone users spend time exclusively on mobile apps, with 18-24-year-olds spending 66% of total digital time on mobile apps. Of that, 89% of the time is spent on just 18 apps depending on individual users’ preferences, making proper app planning crucial for success.

Today’s audiences know what they want and don’t want in their mobile apps, encouraging teams to carefully write their project plans before they approach development. But how do you properly write a mobile app development brief without sacrificing your vision and staying within the initial budget? Why should you do so in the first place? Let’s discuss that and more in greater detail.

Why a Good Mobile App Project Brief Matters?

Why-a-Good-Mobile-App-Project-Brief-Matters

It’s worth discussing the significance of mobile app project briefs before we tackle the writing process itself. In practice, a project brief is used as a reference tool for developers to remain focused on the client’s deliverables. Approaching the development process without written and approved documentation can lead to drastic, last-minute changes, misunderstanding, as well as a loss of resources and brand reputation.

For example, developing a mobile app that filters restaurants based on food type, such as Happy Cow, means that developers should stay focused on it. Knowing that such and such features, UI elements, and API are necessary will help team members collaborate better in order to meet certain expectations. Whether you develop an app under your brand’s banner or outsource coding and design services to would-be clients, briefs can provide you with several benefits:

  • Clarity on what your mobile app project “is” and “isn’t” early in development
  • Point of reference for developers, project leads, and clients throughout the cycle
  • Smart allocation of available time and resources based on objective development criteria
  • Streamlined project data storage for further app updates and iterations

Writing Steps to Create a Good Mobile App Project Brief

Writing-Steps-to-Create-a-Good-Mobile-App-Project-Brief

1. Establish the “You” Behind the App

Depending on how “open” your project is to the public, you will want to write a detailed section about who the developers are. Elements such as company name, address, project lead, project title, as well as contact information, should be included in this introductory segment. Regardless of whether you build an in-house app or outsource developers to a client, this section is used for easy document storage and access.

#android app #ios app #minimum viable product (mvp) #mobile app development #web development #how do you write a project design #how to write a brief #how to write a project summary #how to write project summary #program brief example #project brief #project brief example #project brief template #project proposal brief #simple project brief template