Awesome

CSVImporter

Import CSV files line by line with ease.

Rationale

"Why yet another CSVImporter" you may ask. "There is already SwiftCSV and CSwiftV" you may say. The truth is that these frameworks work well for smaller CSV files. But once you have a really large CSV file (or could have one, because you let the user import whatever CSV file he desires to) then those solutions will probably cause delays and memory issues for some of your users.

CSVImporter on the other hand works both asynchronously (prevents delays) and reads your CSV file line by line instead of loading the entire String into memory (prevents memory issues). On top of that it is easy to use and provides beautiful callbacks for indicating failure, progress, completion and even data mapping if you desire to.

Installation

Currently the recommended way of installing this library is via Carthage on macOS or Swift Package Manager on Linux. Cocoapods might work, too, but is not tested.

You can of course also just include this framework manually into your project by downloading it or by using git submodules.

Usage

Please have a look at the UsageExamples.playground and the Tests/CSVImporterTests/CSVImporterSpec.swift files for a complete list of features provided. Open the Playground from within the .xcworkspace in order for it to work.

Basic CSV Import

First create an instance of CSVImporter and specify the type the data within a line from the CSV should have. The default data type is an array of String objects which would look like this:

let path = "path/to/your/CSV/file"
let importer = CSVImporter<[String]>(path: path)
importer.startImportingRecords { $0 }.onFinish { importedRecords in
    for record in importedRecords {
        // record is of type [String] and contains all data in a line
    }
}

Note that you can specify an alternative delimiter when creating a CSVImporter object alongside the path. The delimiter defaults to , if you don't specify any.

Asynchronous with Callbacks

CSVImporter works asynchronously by default and therefore doesn't block the main thread. As you can see the onFinish method is called once it finishes for using the results. There is also onFail for failure cases (for example when the given path doesn't contain a CSV file), onProgress which is regularly called and provides the number of lines already processed (e.g. for progress indicators). You can chain them as follows:

importer.startImportingRecords { $0 }.onFail {

    print("The CSV file couldn't be read.")

}.onProgress { importedDataLinesCount in

    print("\(importedDataLinesCount) lines were already imported.")

}.onFinish { importedRecords in

    print("Did finish import with \(importedRecords.count) records.")

}

By default the real importing work is done in the .utility global background queue and callbacks are called on the main queue. This way the hard work is done asynchronously but the callbacks allow you to update your UI. If you need a different behavior, you can customize the queues when creating a CSVImporter object like so:

let path = "path/to/your/CSV/file"
let importer = CSVImporter<[String]>(path: path, workQosClass: .background, callbacksQosClass: .utility)

Import Synchronously

If you know your file is small enough or blocking the UI is not a problem, you can also use the synchronous import methods to import your data. Simply call importRecords instead of startImportingRecords and you will receive the end result (the same content as in the onFinish closure when using startImportingRecords) directly:

let importedRecords = importer.importRecords { $0 }

Note that this method doesn't have any option to get notified about progress or failure – you just get the result. Check if the resulting array is empty to recognize potential failures.

Easy data mapping

As stated above the default type is a [String] but you can provide whatever type you like. For example, let's say you have a class like this

class Student {
  let firstName: String, lastName: String
  init(firstName: String, lastName: String) {
    self.firstName = firstName
    self.lastName = lastName
  }
}

and your CSV file looks something like the following

Harry,Potter
Hermione,Granger
Ron,Weasley

then you can specify a mapper as the closure instead of the { $0 } from the examples above like this:

let path = "path/to/Hogwarts/students"
let importer = CSVImporter<Student>(path: path)
importer.startImportingRecords { recordValues -> Student in

    return Student(firstName: recordValues[0], lastName: recordValues[1])

}.onFinish { importedRecords in

    for student in importedRecords {
        // Now importedRecords is an array of Students
    }

}

Header Structure Support

Last but not least some CSV files have the structure of the data specified within the first line like this:

firstName,lastName
Harry,Potter
Hermione,Granger
Ron,Weasley

In that case CSVImporter can automatically provide each record as a dictionary like this:

let path = "path/to/Hogwarts/students"
let importer = CSVImporter<[String: String]>(path: path)
importer.startImportingRecords(structure: { (headerValues) -> Void in

    print(headerValues) // => ["firstName", "lastName"]

}) { $0 }.onFinish { importedRecords in

    for record in importedRecords {
        print(record) // => e.g. ["firstName": "Harry", "lastName": "Potter"]
        print(record["firstName"]) // prints "Harry" on first, "Hermione" on second run
        print(record["lastName"]) // prints "Potter" on first, "Granger" on second run
    }

}

Note: If a records values count doesn't match that of the first lines values count then the record will be ignored.

Donation

BartyCrouch was brought to you by Cihat Gündüz in his free time. If you want to thank me and support the development of this project, please make a small donation on PayPal. In case you also like my other open source contributions and articles, please consider motivating me by becoming a sponsor on GitHub or a patron on Patreon.

Thank you very much for any donation, it really helps out a lot! 💯

Contributing

See the file CONTRIBUTING.md.

License

This library is released under the MIT License. See LICENSE for details.