Tutorial
This tutorial is intended to describe the ways of working, and the most important features of mockneat.
It’s not a long read, and it should take less than a few hours. I would also suggest running the examples as you go.
For a comprehensive description of the various APIs and their usage, it’s recommended to check the official docs.
Table of contents:
- The MockNeat class
- MockNeat as an enhanced Random for:
- Everything is a
MockUnit<T> - The
MockUnitString - More than an enhanced Random
- Composing Objects
- More Formatted Data
The MockNeat class
The MockNeat.class is the “entry-point” of the library. Think of this as a fat factory class, responsible for the instantiation of all the existing data generators. It’s the most important and, in most of the cases, the most “invisible” component from the library.
By default, three reusable MockNeat “factory objects” are created, each wrapping a different type of java Random generators (ThreadLocalRandom, SecureRandom or the good Old Random):
MockNeat mock1 = MockNeat.threadLocal(); // recommended !
MockNeat mock2 = MockNeat.secure();
MockNeat mock3 = MockNeat.old();
Calling threadLocal(), secure() or old() will always return the same instances of MockNeat, so in a way the class is a “three”-ngleton (I made up the term).
In most of the use-cases, it’s recommended to (re)use the MockNeat.threadLocal() object. After the instance is referenced, the library can be used like this:
import net.andreinc.mockneat.MockNeat;
...
MockNeat mock = MockNeat.threadLocal();
// Gets a random int, long and string
int x = mock.ints().get();
long y = mock.longs().get();
String s = mock.strings().get();
Since version 0.2.6 “shortcut static methods” were introduced pointing to MockNeat.threadLocal().
This is syntactic sugar, and as long as you stick with the MockNeat.threadLocal() implementation this should be the preferred way of doing things:
import static net.andreinc.mockneat.unit.text.Strings.strings;
import static net.andreinc.mockneat.unit.types.Ints.ints;
import static net.andreinc.mockneat.unit.types.Longs.longs;
...
// Gets a random int, long and string
int x = ints().get();
long y = longs().get();
String s = strings().get();
Where:
MockNeat mock = MockNeat.threadLocal();
int x = mock.ints().get();
Is equivalent with:
int x = ints().get();
In this tutorial most of the examples will use the shortcut static methods “mirroring” the ones in MockNeat.threadLocal(), so there will be little interaction with MockNeat.class.
Note:
For particular use-cases, new MockNeat instances can be created by invoking the directly the public constructor. For example, if we want to create a secure MockNeat object with 123l as the seed:
Long seed = 123l;
MockNeat mock = new MockNeat(RandomType.SECURE, seed);
It’s highly recommended to avoid creating multiple MockNeat instances. It’s better to stick with one instance per-project.
Also, it should be taken in consideration that none of the data generators is thread-safe.
Note:
RandomType.OLD can be used to to generate data considered to be “stable”.
Example:
long hashBasis = 99823981L;
System.out.println(new MockNeat(RandomType.OLD, hashBasis).countries().names().get());
System.out.println(new MockNeat(RandomType.OLD, hashBasis).countries().names().get());
System.out.println(new MockNeat(RandomType.OLD, hashBasis).countries().names().get());
System.out.println(new MockNeat(RandomType.OLD, hashBasis).countries().names().get());
// Prints out
// Iceland
// Iceland
// Iceland
// Iceland
MockNeat as an enhanced Random
Internally the MockNeat.class wraps a java Random implementation and offers a powerful API for generating arbitrary values for primitive (boolean, chars, ints, doubles, etc.), String, LocalDate, Day and Month types.
After creating any of the data generators (also called a MockUnit<Type>) you always have to call get() to obtain the actual value. mockneat works lazily; no value will be generated until explicitly calling the “closing” method get() (or val()).
Note: Older examples you can find on the Internet might be using val() instead of get(). get() is just an alias which was introduced later, starting with version 0.2.5. The reason for this addition is simple, val is a restricted keyword in some other JVM languages (eg.: Scala).
Booleans
Boolean (or boolean) values can be generated using the bools() (or mockNeat.bools()) method.
As an additional feature true values can be generated with a given probability like in the example below.
import static net.andreinc.mockneat.unit.types.Bools.bools;
...
// Generating boolean values
boolean bool = bools().get();
boolean almostTrue = bools().probability(99.00)
.get();
Chars
char (or Character) values can be generated using the chars() (or mockNeat.chars()) method.
import static net.andreinc.mockneat.types.enums.CharsType.*;
import static net.andreinc.mockneat.unit.types.Chars.chars;
...
// Example for generating a single char value
char c1 = chars().get();
// Example for generating a digit char
// (Eg.: '0', '1', etc.)
char digit1 = chars().digits().get();
char digit2 = chars().type(DIGITS).get();
// Example for generating a lower letter
// (Eg.: 'a', 'z', etc.)
char lowerLetter1 = chars().lowerLetters().get();
char lowerLetter2 = chars().type(LOWER_LETTERS).get();
// Example for generating an upper letter
// (Eg.: 'A', 'J', etc.)
char upperLetter1 = chars().upperLetters().get();
char upperLetter2 = chars().type(UPPER_LETTERS).get();
// Example for generating a letter which is either
// lowercase or uppercase
char letter1 = chars().letters().get();
char letter2 = chars().type(LETTERS).get();
// Example for generating an arbitrary HEX character
// Hex characters are considered to be:
// [ "0", "1", "2", "3", "4", "5", "6", "7", "8", "9",
// "a", "b", "c", "d", "e", "f" ]
Character hex1 = chars().hex().get();
Character hex2 = chars().type(HEX).get();
// Example for generating an arbitrary alphanumeric character
char an1 = chars().alphaNumeric().get();
char an2 = chars().type(ALPHA_NUMERIC).get();
All of the methods digits(), letters(), hex() etc. are shortcuts for the type(CharsType) method. In case you want to combine different types but in the same time exclude others, you can use the types(CharTypes...) method.
For example, the following code will be generating either a lower letter or digit (but not an upper letter):
char lowerLetterOrDigit = chars().types(LOWER_LETTERS, DIGITS).get();
Note: The type()/types()/shortcut methods “pattern” will be found “across” the library in different areas.
Ints
int (or Integer) values can be generated using the ints() (or mockNeat.ints()) method.
import static net.andreinc.mockneat.unit.types.Ints.ints;
...
// Generates a arbitrary integer in the interval
// [Integer.MIN_VALUE, Integer.MAX_VALUE]
int x = ints().get();
// Generates an arbitrary integer in the interval
// [0, 10)
int y = ints().range(0, 10).get();
// Generates an arbitrary integer in the interval
// [0, 100)
int z = ints().bound(100).get();
The ints() data generator has an additional helper method that allows the developer to “extract” a random value from an array int[]:
// Generates a integer value from the given array
int[] array = new int[] {1,10,100,1000};
int fromArray = ints().from(array).get();
For example, we can use the from(int[]) method to arbitrary generate a 10x10 matrix of integers containing only 0 and 1:
// Create a "matrix" of zeroes and ones
int[][] zeroesAndOnes = new int[10][10];
// Populate the matrix with values
for(int i = 0; i < 10; i++)
for(int j = 0; j < 10; j++)
zeroesAndOnes[i][j] = ints()
.from(new int[]{0, 1})
.get();
// Printing the matrix
for (int i = 0; i < 10; i++) {
for(int j = 0; j < 10; j++) {
System.out.print(zeroesAndOnes[i][j] + " ");
}
System.out.println();
}
// (Possible) Output:
/**
1 0 1 1 1 1 1 1 0 1
0 0 1 0 1 1 1 0 0 0
1 0 0 1 0 1 1 1 1 1
1 1 1 1 1 1 0 1 0 0
1 1 1 1 0 1 0 1 1 1
0 0 0 0 1 0 0 1 1 0
0 1 0 1 0 1 1 1 0 0
0 0 1 1 1 1 1 1 1 0
1 0 1 0 0 1 1 0 1 0
0 0 0 1 0 0 0 0 1 1
*/
The above can be re-written using a more mockneat-ish approach:
final int rows = 5;
final int cols = 8;
Integer[] possibleValues = {0, 1};
Consumer<Integer[][]> prettyPrint = (ints) -> {
for (int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
System.out.print(ints[i][j] + " ");
}
System.out.println();
}
};
fromInts(possibleValues)
.array(() -> new Integer[cols])
.array(() -> new Integer[rows][])
.consume(prettyPrint);
It’s normal if you are not familiar with the above syntax. Think of this as a “sneak-peek” into the libraries’ features that are going to be presented later.
Doubles
double (or Double) values can be generated using the doubles() (or mockNeat.doubles()) method.
import static net.andreinc.mockneat.unit.types.Doubles.doubles;
...
// Generates an arbitrary double in the interval [0.0, 1.0)
double d1 = doubles().get();
// Generates an arbitrary double in the interval [0,0, 10.0)
double d2 = doubles().range(0, 10.0).get();
Just like the ints() data generator, the doubles() generator has a helper method to select values randomly from an already existing array (double[] array).
// Generates an arbitrary double that is either 1.1, 1.2 or 1.3
double d3 = doubles().from(new double[]{1.1, 1.2, 1.3}).get();
Longs and floats
The API for longs() is identical with the one for ints().
The API for floats() is identical with one for doubles().
For brevity we won’t add additional code examples, please check the docs.
Strings
mockneat has a few String generators, but for the moment we will describe the behaviour of the most common one, strings() (or mockUnit.strings()).
This generates text without any inherent meaning (let’s call it “giberish”).
Even so, it’s possible to specify the type of the characters used (eg.: NUMBERS, ALPHA_NUMERIC, LETTERS, HEX or SPECIAL_CHARACTERS) and the size of the resulting String. The size can be fixed (int) or arbitrary (defined with ints()).
If no type is specified, the default characters are letters (both upper case and lower case) and numbers, but no special characters will be used.
If no size is specified, the default is 64 (don’t ask me why).
Examples:
// Generates a String of size 64 (default value)
// containing letters (upper case and lowercase) and numbers
String theFirstString = strings().get();
System.out.println("theFirstString= " + theFirstString);
// Generates a String of size 10 (custom value)
// containing only NUMBERS
String someNumbers = strings()
.size(10)
.type(NUMBERS)
.get();
System.out.println("someNumbers= " + someNumbers);
// Generates a String with a random size from 1 to 99
String randomSized = strings()
.size(ints().range(1, 100))
.get();
// Output:
/**
theFirstString= r6dficsvQlkj7j75bDrRN8GktU0PejNXRGfDmK8F5HlM69lNZBZ6Tz3MX9S9mRiU
someNumbers= 9098810282
*/
Dates
An easy-to-use mechanism was implemented to generate LocalDate values, using the localDate() (or mockUnit.localDates()) method.
By default, dates are generated from [1970, now()]:
LocalDate localDate = localDates().get();
//Output:
/**
1984-05-10
*/
But it’s also possible to generate dates only in the current year:
LocalDate thisYear = localDates().thisYear().get();
//Output:
/**
2018-12-28
*/
// The tutorial was written in 2018 sic!
Or in the current month:
LocalDate thisMonth = localDates()
.thisMonth()
.get();
Future or past:
LocalDate maxDateInTheFuture = LocalDate.of(2050, 12, 12);
LocalDate inTheFuture = localDates()
.future(maxDateInTheFuture)
.get();
// OR
LocalDate minDateInThePast = LocalDate.of(1987, 1, 30);
LocalDate inThePast = localDates(minDateInThePast)
.past(min)
.get();
If the application uses the java.util.Date type instead of the newer java.time.LocalDate there’s a convenient way to do it by adding into the mix toUtilDate(), just before calling the closing get():
Date thisMonth = localDates()
.thisMonth()
.toUtilDate() // THIS!
.get();
PS: After reading the next chapter, the “magic” behind toUtilDate() will more obvious.
“Everything” is a MockUnit<T>
The rule of thumbs is that every data generator from MockNeat is a MockUnit<T>, where <T> represents the type of the data being generated and MockUnit is a @FunctionalInterface that comes with a few handy default methods.
For example, calling chars() without the closing method (get() or val()) returns a MockUnit<Character>.
MockUnit<Character> asAMockUnit = chars();
…and so on
For specific data types, more specialised interfaces exist. For example ints() returns an Ints data generator, which is an implementation of MockUnitInt, which is an extension for MockUnit<Integer> that adds additional benefits (read more methods).
The same goes for MockUnitString which is an extension of MockUnit<String> or MockUnitLocalDate which is an extension for MockUnit<LocalDate>.
MockUnit<String> genericStringGenerator = strings();
// OR
MockUnitString smarterStringGenerator = strings();
In short, MockUnits are powerful mechanisms that allow developers to generate data incrementally, by defining broader behaviours that can be reused/transformed later, under different circumstances.
For example, we define an ints() generator (MockUnitInt) that generates numbers between [0, 100).
MockUnitInt generator = ints().range(0, 100);
Now the same generator can be re-used in different scenarios by adding new behaviours or additional constraints.
We can create arrays of int or Integer.
Integer[] ints1 = generator.array(10).get();
int[] ints2 = generator.arrayPrimitive(10).get();
Or an infinite stream of arbitrary integers in that range:
Stream<Integer> infiniteStream = generator.stream().get();
Or a List<String> where each String is actually a integer from the given range [0, 100):
MockUnitInt generator = ints().range(0, 100);
// MockUnitString stringGenerator = generator.map(i -> i.toString());
MockUnitString stringGenerator = generator.mapToString();
MockUnit<List<String>> listGenerator = stringGenerator.list(LinkedList::new, 10);
List<String> list1 = listGenerator.get();
List<String> list2 = listGenerator.get();
System.out.println(list1);
System.out.println(list2);
// Output:
/**
[43, 8, 11, 83, 97, 67, 62, 97, 46, 55]
[62, 4, 23, 97, 79, 4, 81, 62, 37, 12]
*/
mapToString(), map() and list(...) are what we call “transformers”, default generic methods defined in the MockUnit<T> interface.
More precisely mapToString() is transforming the MockUnitInt generator into a new generator MockUnitString, which will generate String values obtained from integers in the range yes, exactly[0, 100).
list(Supplier<List<String>>, int size) is another transformer that will transform the previous MockUnitString into a new MockUnit<List<String>>, where each element from the resulting List is a String representing an Integer in the range yes, exactly[0, 100).
For brevity, it’s not recommended keeping all the intermediary references, so you can chain all the methods (in the most fluent mode possible):
List<String> list3 = ints()
.range(0, 100)
.mapToString()
.list(LinkedList::new, 10)
.get();
System.out.println(list3);
//Output
/**
[57, 80, 26, 99, 31, 40, 98, 4, 77, 58]
*/
Data generators are lazy by nature. That’s why we can split the methods associated with them into two main categories:
- Closers: methods that are asking the
MockUnit<T>to generate data on the spot. After calling a closer method, theMockUnit<?>“chain ends”. (Eg.:get()). - Transformers: methods that are incrementally changing the behaviour of the
MockUnit<T>without actually computing any data. (Eg.:map(...),list(...), etc.);
For a comprehensive list of transformer or closing methods please check the docs for:
MockUnit<T>;MockUnitDays;MockUnitDouble;MockUnitInt;MockUnitLocalDate;MockUnitLong;MockUnitMonth;MockUnitString
Closing Methods
get()
The most obvious closing method is get(). All the examples have used it, so there’s need to (re)explain what it does.
consume()
Another important method is consume(). Compared to get() this computes the arbitrary value, but it doesn’t return it, instead it consumes it through a Consumer<T> consumer (or BiConsumer<Integer, T>). For example, if we just want to print a List<Integer> a on System.out we can write something like:
ints().list(10).consume((list) -> System.out.println(list));
// OR
ints().list(10).consume(System.out::println); // Using the :: notation
The (Bi)Consumer<T> consumer can be called multiple times, and with each call the MockUnit will return a different value. For example, we can write a program that rolls a dice 10 times and prints the results on System.out like this:
BiConsumer<Integer, Integer> dicePrinter =
(i, dice) -> System.out.printf("Roll = %d, Dice = %d\n", i+1, dice);
ints()
.range(1, 7)
.consume(10, dicePrinter);
// output
/**
Roll = 1, Dice = 1
Roll = 2, Dice = 6
Roll = 3, Dice = 2
Roll = 4, Dice = 3
Roll = 5, Dice = 3
Roll = 6, Dice = 3
Roll = 7, Dice = 4
Roll = 8, Dice = 6
Roll = 9, Dice = 2
Roll = 10, Dice = 4
*/
Transformer Methods
map(Function<T1, T2>)
This is one of the most useful transformation method: it takes a MockUnit<T1> and transforms it into a MockUnit<T2>, through a Function<T1, T2>.
For example, if we run the FizzBuzz solution over a 100 Integers and print the results we can do something like:
// Solution for FizzBuzz exercise.
Function<Integer, String> fizzBuzz = (i) -> {
if (i % (5*3) == 0) return i + "=>FizzBuzz";
else if (i % 3 == 0) return i + "=>Fizz";
else if (i % 5 == 0) return i + "=>Buzz";
return String.valueOf(i);
};
ints()
.range(1, 100)
.map(fizzBuzz) // MockUnitInt becomes MockUnit<String>
.list(100) // MockUnitString becomes MockUnit<List<String>>
.consume(System.out::println);
//output:
/**
[27=>Fizz, 37, 55=>Buzz, 19, 7, 65=>Buzz, 77, 5=>Buzz, 17, 20=>Buzz, 64, 85=>Buzz, 2, 79, 81=>Fizz, 92, 87=>Fizz,
...]
*/
After calling map(fizzBuzz) the initial MockUnitInt is transformed into a MockUnit<String>, this can be ok for most use-cases, but to enable the usage of more advanced String processing methods it’s probably recommended to “upgrade” directly to MockUnitString (a smarter extension for MockUnit<String>):
ints()
.range(1, 100)
.mapToString(fizzBuzz) // MockUnit becomes MockUnitString (not MockUnit<String>)
.format(UPPER_CASE) // Uppercase the Strings (available only on MockUnitString)
.replace("F", "X") // Replaces "F" with "X" (available only on MockUnitString)
.list(100) // MockUnitString becomes MockUnit<List<String>>
.consume(System.out::println);
Equivalent methods exist for all the other enhanced MockUnits:
mapToDouble(...)to transform an existingMockUnit<T>into aMockUnitDouble;mapToInt(...)to transform an existingMockUnit<T>into aMockUnitInt;mapToLong(...)to transform an existingMockUnit<T>into aMockUnitLong;mapToLocalDate(...)to transform an existingMockUnit<T>into aMockUnitLocalDate;
The map(Function<T1, T2>) doesn’t impose any restriction over the types. T1 can be similar with T2. In this case the MockUnit will not be translated into something else (from the type perspective).
For example, if we want to generate an arbitrary multiple of 10, we can simply apply map() and return the same type:
int multipleOf10 = ints().map(i -> i * 10).get();
array(), collection(), list() and set()
Those methods are used to transform an existing MockUnit<T> into a MockUnit<T[], MockUnit<Collection<T>>, MockUnit<List<T>> and MockUnit<Set<T>>.
Multiple values will be generated and collected into arrays, collections, lists and sets.
Generating a uni-dimensional array of Integer values from the interval [0,5) can be written in a very concise way:
Integer[] ints = ints()
.range(0, 5)
.array(10)
.get();
MockUnits can be chained to obtain powerful constructs. For example, generating a List<List<Integer>> can be obtained just by calling list() twice:
List<List<Integer>> listOfLists = ints()
.list(2) // MockUnitInt becomes MockUnit<List<Integer>>
.list(2) // MockUnit<List<Integer>> becomes MockUnit<List<List<Integer>>>
.get(); // Evaluate the value
System.out.println(listOfLists);
//Output
/**
[[1082381729, 1097865582], [1952501993, 221886267]]
*/
By default, the internal implementation used for List<T> is ArrayList<T>. But what if we want to change the implementation of the “wrapping” List<T> from ArrayList<T> to LinkedList<T>.
Additionally, what if we want the list to have an arbitrary length itself:
MockUnitInt sizeGen = ints().range(0, 5); // size will be randomly generated
List<List<Integer>> listOfLists = ints()
.list(sizeGen)
.list(LinkedList::new, sizeGen)
.get();
//Output
/**
[[-1086447222, 364023211], [-1712221397, -1973762881], [-1502802628, 1863612508]]
*/
set() works similarly as list(), the API is the same except one big difference: size is not guaranteed. This is a normal consequence of the fact that a Set<T> can only contain unique elements.
Set<Integer> set = ints()
.from(new int[]{1,2,3})
.set(1000) // There only 3 possible distinct values,
// mockneat will try 1000 times to add new data
// but in the end the Set<Integer> will probably
// contain
// only 3 elements.
// This is normal behaviour.
.get();
System.out.println("set.size() =" + set.size());
//Output
/**
set.sizie() =3
*/
mapKeys() and mapVals()
The mapKeys() method is used to create Map<K, V>s and fill them up with arbitrary data.
Basically it transforms an existing MockUnit<T> into a new MockUnit<R, T> where the <R> keys are generated from:
- A
Supplier<R>(this can be obtained from aMockUnitwithmockUnit.supplier()); - An
Iterable<R>(eg.: aList<R>); - A generic array
R[]; - Primitive arrays of type:
int[],double[],long[]. In this case<R>is not generic so correspondingMockUnit<Integer, T>,MockUnit<Double, T>orMockUnit<Long, T>will be created.
Map<Integer, List<Double>> map =
doubles()
// MockUnitDouble
.gaussians()
// Is transformed into a MockUnit<List<Double>>
.list(2)
// Is transformed into a MockUnit<Map<Integer, List<Double>>
.mapKeys(3, ints().bound(10000).supplier())
// The resulting object is computed
.get();
System.out.println(map);
// Output:
/**
{5680=[0.3378495069224774, -0.333557489486435], 5386=[0.9789656246200228, 0.3684941698377526], 5822=[1.2328661504292975, 0.5981217534882592]}
*/
Note: Just like in the Set<T>’s case the keys in the Map are unique so the actual size of the Map<K,V> is not guaranteed to be the input value.
mapVals() works similarly, but instead of mapping keys, we are mapping values. The transformation works the other way around, MockUnit<T> becomes MockUnit<T,R> where <R> keys are generated from the same sources as for mapKeys().
mapKeys() and mapVals() can achieve the same results. For example, we can create the exact Map<Integer, List<Double>> as in the previous example:
Map<Integer, List<Double>> sameMapAsAbove =
ints()
// MockUnitInt
.bound(10000)
// Is transformed into a MockUnit<Map<Integer, List<Double>>
.mapVals(3, doubles().gaussians().list(2).supplier())
// The resulting object is computed
.get();
System.out.println(sameMapAsAbove);
// Output:
/**
{8195=[-0.8483899838848824, 0.42267892251968014], 7051=[-0.9665327769342633, 0.4030082004963111], 2991=[-1.0825503179214298, -0.9325765134899544]}
*/
The MockUnitString
MockUnitString is an extension for MockUnit<String>. Out of all the specialised MockUnits it contains the most (useful) methods for customising output (both closers and transformers).
accumulate()
This is a method that concatenates multiple values into one “big String”. You can specify how many Strings to be concatenated and what separator to use (Eg.: “,”, “\n”, etc.):
Example for creating an “HTML List” of random characters:
StringBuilder buff = new StringBuilder();
buff.append("<ul>\n")
.append(
chars()
.upperLetters()
.mapToString((c) -> String.format("\t<li>%s</li>", c.toString()))
.accumulate(5, "\n")
.get()
)
.append("\n</ul>");
System.out.println(buff.toString());
//Output:
/**
<ul>
<li>Q</li>
<li>F</li>
<li>F</li>
<li>H</li>
<li>S</li>
</ul
*/
format()
format(type) is used to format the String values generated by a MockUnitString.
The possible formatting types are kept in the StringFormatType.enum and the possible values are:
UPPER_CASELOWER_CASECAPITALIZED
Example:
import static java.lang.System.out;
import static net.andreinc.mockneat.types.enums.StringFormatType.UPPER_CASE;
//....
strings()
.size(10)
.format(UPPER_CASE)
.accumulate(10, "\n")
.consume(out::println);
// Output:
/**
L6K8FUGNXL
PLUJTTTAOG
AN09ZKVEQB
EHZPAEJFPR
FAMYLHXUOT
GXDSOJWSJB
KZR8JYNZEE
2DU7WTHOJA
IIVRYJIMIW
Q9GOFLQERB
*/
append() and prepend()
append(String) and prepend(String) are modifying the arbitrary generated String from the MockUnitString by appending and prepending additional text.
For example, we pretty print a random matrix of integers like this:
int size = 10;
// Hack-ish way of repeating a char 'n=10' times
String horizontalLine =
String.format("\n " + new String(new char[size]).replace("\0", "- ") + " \n");
ints()
.range(0, 10)
.mapToString()
.accumulate(size, " ") // We create the "row"
.prepend("|") // Every row will be prefixed with "|"
.append("|") // Every row will be suffixed with "|"
.accumulate(size, "\n") // We accumulate 10 strings
.append(horizontalLine)
.prepend(horizontalLine)
.consume(out::println);
// Output:
/**
- - - - - - - - - -
|3 0 5 0 4 0 7 4 5 8|
|5 5 3 2 2 6 0 6 9 8|
|8 1 0 4 1 5 9 3 2 1|
|9 3 3 7 0 6 3 2 2 9|
|2 3 1 4 6 3 7 7 9 9|
|8 7 9 8 0 2 9 0 3 2|
|7 2 1 8 6 2 9 2 7 3|
|0 6 6 0 4 4 7 4 3 1|
|2 2 6 8 5 8 2 2 4 1|
|6 1 5 6 7 8 0 4 2 3|
- - - - - - - - - -
*/
More than an enhanced Random
It’s nice to be able to generate Integer, Double or Character values, but mockneat can do much more…
The main reason the library was created was to enable developers to generate (big) data be it json, xml, csv or sql (inserts) format.
That’s why multiple and more complex generators were created:
Address Generators
The following generators are useful to generate user information related to addresses.
| Data Generator | MockUnit | Description |
|---|---|---|
cities() |
MockUnitString |
Generates arbitrary city names from US or World Capitals. |
countries() |
MockUnitString |
Generates arbitrary country names (or their ISO2 code). |
usStates() |
MockUnitString |
Generates US states names (or their ISO2 code). |
Examples:
import static java.lang.System.out;
//****
cities().us().consume(out::println);
cities().capitals().consume(out::println);
countries().names().consume(out::println);
countries().iso2().consume(out::println);
usStates().consume(out::println);
usStates().iso2().consume(out::println);
//Output:
/**
Kellner
Helsinki
Liberia
BG
Massachusetts
MN
*/
Financial Generators
The following generators are useful to generate “financial” information.
| Data Generator | MockUnit | Description |
|---|---|---|
creditCards() |
MockUnitString |
Generates valid credit card numbers of different types (eg: VISA, MASTERCARD or AMEX) |
currencies() |
MockUnitString |
Generates valid Forex Pairs (eg.: “EUR/USD”), currencies codes or currency names (eg.: “Dollar”). |
cvvs() |
MockUnitString |
Generates valid CVV numbers for credit cards. |
ibans() |
MockUnitString |
Generates valid IBAN numbers. |
money() |
MockUnitString |
Generate money amounts as String (Money Symbol + Sum of Money). |
Example for generating valid credit card numbers (either VISA or MASTERCARD):
import static java.lang.System.out;
import static net.andreinc.mockneat.types.enums.CreditCardType.MASTERCARD;
import static net.andreinc.mockneat.types.enums.CreditCardType.VISA_16;
import static net.andreinc.mockneat.unit.financial.CreditCards.creditCards;
//...
creditCards()
.types(VISA_16, MASTERCARD)
.accumulate(10, "\n")
.prepend("Valid Credit Card Numbers (VISA or Mastercard):\n")
.consume(out::println);
// Output:
/**
Valid Credit Card Numbers (VISA or Mastercard):
5595283075583783
5392788967714978
2720852738101152
2720445808982955
5408438861860897
2720609587283287
5118860666122093
5161222900516349
5438740188862769
5162746414517780
*/
Internet Data Generators
The following generators are useful to generate information related to the networking and the Internet.
| Data Generator | MockUnit | Description |
|---|---|---|
domains() |
MockUnitString |
Generates domains suffixes for URLs. |
ipv4s() |
MockUnitString |
Generates arbitrary (valid) IPv4 addresses. |
ipv6s() |
MockUnitString |
Generates an arbitrary (valid) IPv6 address. |
macs() |
MockUnitString |
Generates arbitrary (valid) MAC addresses. |
urls() |
MockUnitString |
This method can be used to generate random URLs. |
Example for generating a Map<String, String> association where the key is an IPv4 address, and the value is a MAC Address:
import static net.andreinc.mockneat.types.enums.IPv4Type.CLASS_A_NONPRIVATE;
import static net.andreinc.mockneat.types.enums.MACAddressFormatType.COLON_EVERY_2_DIGITS;
import static net.andreinc.mockneat.unit.networking.IPv4s.ipv4s;
import static net.andreinc.mockneat.unit.networking.Macs.macs;
//....
// Map<String, String>
// K = IPV4 Address, V = MAC
Map<String, String> networkStuff =
ipv4s()
.type(CLASS_A_NONPRIVATE)
.mapVals(20,
macs()
.type(COLON_EVERY_2_DIGITS)
.supplier()
)
.get();
System.out.println(networkStuff);
// Output:
/**
{83.107.137.237=bf:95:ab:de:f3:cf,
39.175.116.211=01:42:62:10:e6:a1,
120.117.0.254=f7:cb:87:39:de:6e,
57.61.73.171=df:4a:76:bf:1e:35,
4.14.181.9=43:20:96:b4:66:00,
..... etc
}
*/
Sequence Generators
Those methods are useful for generating sequences of numbers or to cycle through an already existing collection.
The resulting data is not arbitrary, but the generators can prove useful for generating SQL table ids or “unique objects” for Maps and Sets.
intSeq() and longSeq()
The simplest usage to define a sequence of numbers is with intSeq() for Integer or longSeq() for Long.
Calling get() on the resulting MockUnitInt (or MockUnitLong) will return incremental values. By default, both generators start at 0, and the increment is 1. (Note: Negative increments are also supported).
MockUnitInt sequence = intSeq();
System.out.println(sequence.get()); // 0 <- default
System.out.println(sequence.get()); // 1 <- 0+1
System.out.println(sequence.get()); // 2 <- 1+1
// Or for a "negative" sequence
MockUnitLong negativeSeq = longSeq().increment(-5l);
System.out.println(negativeSeq.get()); // 0
System.out.println(negativeSeq.get()); // -5
System.out.println(negativeSeq.get()); // -10
For example, the previous “dice rolling exercise” (see consume) can be rewritten like this:
intSeq()
.start(1) // The sequence starts with 1, by default is 0
.mapToString(i -> // The resulting i is an sequence [0, 1, 2...]
format("Roll = %d, Dice = %d", i, ints()
.range(1, 7)
.get()
)
)
.accumulate(10, "\n")
.consume(System.out::println);
// Output
/**
Roll = 0, Dice = 3
Roll = 1, Dice = 1
Roll = 2, Dice = 1
Roll = 3, Dice = 3
Roll = 4, Dice = 5
Roll = 5, Dice = 1
Roll = 6, Dice = 2
Roll = 7, Dice = 5
Roll = 8, Dice = 1
Roll = 9, Dice = 3
*/
Sequences allow cycling through elements by defining a max and/or min.
intSeq()
.max(5)
.cycle(true) // by default is true
.list(10)
.consume(System.out::println);
// Output:
/**
[0, 1, 2, 3, 4, 5, 0, 1, 2, 3]
// ^ cycling starts here
*/
If cycling is turned off (by explicitly calling .cicle(false)) and the max value is reached an exception is thrown:
intSeq()
.max(5)
.cycle(false)
.list(10)
.consume(System.out::println);
// Output
/**
...
Caused by: java.lang.IllegalStateException: IntSeq overflow. Values are generated inside the interval: [-2147483648, 5]. Cannot increment any further.
...
*/
seq()
seq() is MockUnit<T> that allows traversing arrays or Iterable<T>.
Each subsequent call will return the next value. For example, if we want to traverse a String[] containing three values, and create a Map<String, Integer> we can do something like:
String[] keys = new String[] {"A", "B", "C"};
seq(keys)
.mapVals(keys.length, ints().supplier())
.consume(System.out::println);
// Output
/**
{A=-1153871365, B=1543379867, C=221800466}
*/
Text Generators
strings() is the standard text generator that can be used to generate unformatted, gibberish strings witha given format and having a fixed length.
Fortunately more advanced generators were added:
fmt()
fmt(String template).param(namedParam, mockunit) is a data generator that can be used to generate “formatted” text using named params. The format is defined in the template parameter. Internally the fmt() uses the Aleph Formatter library.
Example for generating a list of 10 String values having following format: #{mac} -> #{ip}
fmt("#{mac} -> #{ip}")
.param("mac", macs().type(COLON_EVERY_2_DIGITS))
.param("ip", ipv4s())
.accumulate(10, "\n")
.consume(System.out::println);
// Output
/**
02:9b:48:c3:11:c9 -> 79.197.227.84
a8:3f:62:52:47:89 -> 215.26.43.138
d0:f9:60:ee:a8:12 -> 223.178.99.247
55:6c:ac:1c:af:ab -> 243.36.40.68
71:7f:8e:2b:29:f6 -> 139.33.106.157
...
*/
At each “iteration” the #{mac} and #{ip} named params are replaced with values generated from the associated MockUnits, in our case macs() respectively #{ipv4s}.
If we were to re-write the “dice rolling example” (see consume() and intSeq()) we can start with the format and fill up the data:
fmt("Roll = #{rollNr}, Dice = #{diceValue}")
.param("rollNr", intSeq().start(1))
.param("diceValue", ints().range(1, 7))
.accumulate(10, "\n")
.consume(System.out::println);
// Output:
/**
Roll = 1, Dice = 6
Roll = 2, Dice = 3
...
*/
regex()
This generator acts as a wrapper for generex, a java library that can generate arbitrary strings matching a certain regular expression.
You shouldn’t expect this generator to be a full-featured reverse-regex engine, but most of the simple regex expression will work.
Think of this as an “experimental” feature, heavily reliant on a third party.
Example for generating 5 phone numbers:
regex("\\d{3}-\\d{3}-\\d{4}")
.accumulate(5, "\n")
.consume(System.out::println);
//Output:
/**
869-374-6856
444-775-2444
443-425-7671
526-144-6383
283-454-1700
*/
markovs()
markovs() is an experimental (for now) implementation of text generated from using a Markov Chain. The code is “not yet quite there” in terms of efficiency or flexibility, but it can be used in production without any concerns.
For the moment the library cannot build text from “external sources” (eg.: a .txt file), but you can use the predefined types: MarkovChainType.LOREM_IPSUM and MarkovChainType.KAFKA.
Note: Once the Markov Chain is created in memory (which can be CPU/Memory intensive for more significant texts), the memory never gets released.
Example of generating Lorem Ipsum text. Each call generates a different text:
markovs()
.type(MarkovChainType.KAFKA)
.consume(System.out::println);
//Output
/**
Pulvinar ante. Morbi in dolor lectus. Maecenas et mi vel lorem malesuada hendrerit. Donec id posuere neque. Aliquam pharetra a ex nec congue. Nunc eget bibendum est. Interdum et malesuada fames ac ante ipsum primis in faucibus. Euismod. Massa vivamus nulla. Feugiat. Enim in integer condimentum vel metus dapibus accumsan lobortis vehicula. Enim morbi consequat vestibulum aliquet sit ultrices mi quis. Etiam ligula nulla, sem vel in sed aliquam ligula velit sed porta felis. Quis ante luctus at lorem. Augue sed...
*/
Example of generating text using Frank Kafka - Metamorphosis as the basis. The generated text might be borderline NSFW so I wouldn’t use this in business contexts:
markovs()
.type(MarkovChainType.KAFKA)
.consume(System.out::println);
// Output:
/**
Down the face of her own mother than stay anywhere near gregor. She rushed over to it; it was his mother with the chief clerk had already had in mind, she wanted to bend one of the rest of him, might be near to death; he could judge this for himself. Meanwhile, it had even become very quiet in the living room where grete had put on a lot of weight and become very unpleasant for the other hand, he made it difficult to eat a little too small, lay peacefully between its four familiar walls. A collection of tex...
*/
words()
This is a simple text generator that can be used to retrieve arbitrary English words.
The words are divided by their role in the phrase: NOUN, ADVERB, etc.:
Example for generating words:
String adjective = words().adjectives().get();
String adverb = words().adverbs().get();
String noun = words().nouns().get();
String verb = words().verbs().get();
System.out.printf("adjective=%s\nadverb=%s\nnoun=%s\nverb=%s\n",
adjective, adverb, noun, verb);
// Output
/**
adjective=piled
adverb=creatively
noun=hydrometers
verb=lunge
*/
As a more advanced example, we can create an address generator:
- The address contains the street number in the range
[1, 600), at the end; - The street has a 25% chance of being a
"Lane", 25% chance of being a boulevard ("Blvd.") and 50% chances of being simply"Street"; - The street name has a 25% of being composed of Adjective + Noun, and 75% chances of being only a Noun.
The example will combine ints(), words(), fmt() and probabilities() for generating the desired result:
MockUnitString addressGenerator =
fmt("#{adj}#{noun} #{suffix} #{nr}")
.param("adj", probabilities(String.class)
.add(0.25, words()
.adjectives()
.format(CAPITALIZED)
.append(" ")
)
.add(0.75, "")
.mapToString()
)
.param("noun", words().nouns().format(CAPITALIZED))
.param("suffix", probabilities(String.class)
.add(0.25, "Lane")
.add(0.25, "Blvd.")
.add(0.50, "Street")
.mapToString())
.param("nr", ints().range(1, 600));
addressGenerator
.accumulate(30, "\n")
.consume(System.out::println);
// Output:
/**
Saprobes Lane 130
Rhenium Street 321
Grained Mainliners Street 466
Tops Beliefs Street 184
Ain Quatrefoil Street 159
Nobbler Lane 190
Screwed Skelf Lane 348
Pomologist Street 127
Squash Lane 398
Inherited Carse Street 448
Garotte Blvd. 46
Cays Lane 364
Raised Numismatics Blvd. 548
*/
PS: Take care of the words generated; some of them might be slightly NSFW.
User Data Generators
The following generators are useful to generate data that is typically associated with a User.
| Data Generator | MockUnit | Description |
|---|---|---|
emails() |
MockUnitString |
Generates valid email addresses. |
genders() |
MockUnitString |
Generates valid information related to genders. |
names() |
MockUnitString |
Generates valid first names, middle names and last names. |
passwords |
MockUnitString |
Generates passwords with different strengths. |
users() |
MockUnitString |
Generates usernames. |
Example for generating a List<String> of 10 email addresses, and their associated passwords:
fmt("{email='#{email}', pass='#{pass}'}")
.param("email", emails())
.param("pass", passwords().types(WEAK, MEDIUM))
.accumulate(10, "\n")
.consume(System.out::println);
//Output:
/**
{email='stalkedharl@msn.com', pass='satchels'}
{email='confusedfilth@comcast.net', pass='C>}~0n[9F34V'}
{email='taughtstreamings@hotmail.co.uk', pass='`5l}+13e?+FW;'}
{email='loathdanielle@mail.com', pass='1r;4++$5Q1724]'}
{email='eathluckner@yahoo.co.uk', pass='plugs9'}
{email='allwade@hotmail.co.uk', pass='probe4'}
{email='jimpmarlo@mac.com', pass='swoosh'}
{email='moldysardi@me.com', pass='pAw+2+/8TYG:73'}
{email='nextwhirl@yahoo.co.uk', pass='fist79'}
{email='piquebore@aol.com', pass='compote'}
*/
Composing Objects
Creating object generators with mockneat can be done in 4 ways:
- Reflection: setting fields directly (
reflect()), calling a constructor (constructor()) or a static factory method (factory()); - Through setters using lambda expressions (
filler()).
filler()
This is the preferred way of creating custom MockUnit<T> generators for any given type <T>. The only limitation is that setters need to be available (declared as public).
Let’s take for example a simple POJO called User:
public class User {
private String id;
private String firstName;
private String lastName;
private String middleName;
private Date birthDate;
private String email;
public User() {
}
public String getId() {
return id;
}
public void setId(String id) {
this.id = id;
}
// ++ Additional Getters And Setters for all the fields
// ++ a nicely implemente toString() method
}
Creating an User generator (MockUnit<User>) with filler() is as simple as:
/**
* This method is used to create an email from a firstName and a lastName.
* All emails generated belong to "@company.com"
*/
BiFunction<String, String, String> emailComposer = (firstName, lastName) -> {
String fName = firstName.toLowerCase();
String lName = lastName.toLowerCase();
return fName +
chars().from(new char[]{'_', '.'}).get() + // the names are separated with "." or "_"
lName +
ints().bound(100).get() + // additional numbers are added after the lastName
"@company.com";
};
/**
* Creating the user generator
*/
MockUnit<User> userGenerator =
filler(User::new)
.setter(User::setFirstName, names().first())
.setter(User::setLastName, names().last())
.setter(User::setMiddleName, names().first())
.setter(User::setId, uuids())
.setter(User::setBirthDate, localDates().toUtilDate())
.map(user -> {
user.setEmail(emailComposer.apply(user.getFirstName(), user.getLastName()));
return user;
});
As you can see this strategy doesn’t involve any “magic”. The filler() method expects a Supplier<User> (we are going to use the No Args constructor of the POJO), then we need to reference each setter and the associated generator (MockUnit<T>).
The userGenerator can then be used to create User objects:
/** Creates a single user */
User someUser = userGenerator.get();
/** Creates a List of 10 user */
List<User> users = userGenerator.list(10).get();
/** Prints 10 users on the console (System.out) */
userGenerator
.mapToString() // Calls the (toString() method on each User - needs to be implemented)
.accumulate(10, "\n")
.consume(System.out::println);
// Output
/**
User{id='936946ef-0407-441c-bd13-56998e934781', firstName='Luana', lastName='Bontempo', middleName='Lincoln', birthDate=Sun Mar 18 00:00:00 EET 1979, email='luana.bontempo48@company.com'}
User{id='c84930a6-a9cf-45da-982c-a76e6f23928d', firstName='Paulina', lastName='Rina', middleName='Norbert', birthDate=Wed Jan 10 00:00:00 EET 1973, email='paulina.rina48@company.com'}
User{id='e9d19b1b-4e3b-4c34-a54f-c8bd880d0e0b', firstName='Rosie', lastName='Staack', middleName='Gilbert', birthDate=Wed Dec 25 00:00:00 EET 1985, email='rosie.staack25@company.com'}
User{id='b0824444-86c6-4984-a820-0adca34ea829', firstName='Eryn', lastName='Burchfiel', middleName='Lanny', birthDate=Thu Sep 21 00:00:00 EET 1972, email='eryn.burchfiel62@company.com'}
User{id='c34631f1-1ea7-4a74-a8ac-276fa5787ba3', firstName='Louise', lastName='Kallus', middleName='Nathan', birthDate=Wed May 31 00:00:00 EEST 1989, email='louise.kallus41@company.com'}
User{id='d3791c93-fe6e-4d12-8109-5b4aece9c25a', firstName='Tressie', lastName='Andrson', middleName='Leroy', birthDate=Wed Nov 09 00:00:00 EET 2016, email='tressie.andrson31@company.com'}
User{id='8c170122-8db3-4fb5-ae29-a42eff2b8a89', firstName='Dixie', lastName='Piggee', middleName='Heriberto', birthDate=Sat Apr 13 00:00:00 EEST 2002, email='dixie.piggee40@company.com'}
User{id='a0f74109-b468-4933-8907-b573de66ba7d', firstName='Adelle', lastName='Pecinousky', middleName='Reuben', birthDate=Fri Apr 12 00:00:00 EEST 2013, email='adelle.pecinousky94@company.com'}
User{id='23e8b4ca-8b83-45ef-a670-8f23c93a25cc', firstName='Ivette', lastName='Rodillas', middleName='Van', birthDate=Tue Nov 29 00:00:00 EET 2005, email='ivette_rodillas36@company.com'}
User{id='16ca3877-636e-4a21-9d12-ada0248e7038', firstName='Corrine', lastName='Eichner', middleName='Sylvester', birthDate=Mon Jan 27 00:00:00 EET 2003, email='corrine_eichner17@company.com'}
*/
Since version 0.3.2 filler supports setting constant values through the constant() method.
E.g.:
filler(User::new)
.constant(User::setFirstName, "Michael") // HERE
.setter(User::setLastName, names().last())
...
In the previous example the first name of the generated User object will always be "Michael".
constructor()
This is an alternative way of creating Object (<T>) generators (MockUnit<T>).
Internally the method uses reflection trying to match the supplied list of MockUnit<T1>, MockUnit<T2>..., MockUnit<Tn> generators with a class constructor that accepts a list of arguments <T1>, <T2>, ..., <Tn>.
The safest scenario when this generator can be used is when the POJO has an All Args Constructor defined.
For example for the User class:
public class User {
private String id;
private String firstName;
private String lastName;
private String middleName;
private Date birthDate;
private String email;
// The All Args Constructor <String, String, String, String, Date, Email>
public User(String id, String firstName, String lastName, String middleName, Date birthDate, String email) {
this.id = id;
this.firstName = firstName;
this.lastName = lastName;
this.middleName = middleName;
this.birthDate = birthDate;
this.email = email;
}
// ++ Getters and Setters (they are not really relevant for this example)
// ++ A nice toString() implementation
}
The generator can be created like this:
MockUnit<User> ctrUserGenerator =
constructor(User.class).params(
uuids(), // MockUnitString -> matches String
names().first(), // MockUnitString -> matches String
names().last(), // MockUnitString -> matches String
names().first(), // MockUnitString -> matches String
localDates().toUtilDate(), // MockUnit<Date> -> matches Date
emails().domain("company.com") // MockUnitString -> matches String
);
And then it can be used to generate actual User objects like this:
// Generates a single user
User ctrUser = ctrUserGenerator.get();
// Generates a Set of users
Set<User> ctrUsersSet = ctrUserGenerator.set(10).get();
// Prints 2 Users on the console (System.out)
ctrUserGenerator
.mapToString()
.accumulate(2, "\n")
.consume(System.out::println);
// Output
/**
User{id='9b0a8f06-b74b-4048-a2f9-78379ad9eb06', firstName='Bill', lastName='Mordino', middleName='Milton', birthDate=Tue Feb 08 00:00:00 EET 1972, email='gibbedpouche@company.com'}
User{id='785ab49d-e359-4953-8ac1-dc648e7213a8', firstName='Courtney', lastName='Rieff', middleName='Wilfredo', birthDate=Mon Oct 25 00:00:00 EEST 1999, email='hookedmarc@company.com'}
*/
factory()
Objects are not always created directly through constructors, in this case the easiest way to create an arbitrary Object <T> generator is to use the factory() method.
Let’s say that our User object doesn’t have an accessible constructor outside the package where it was defined:
public class User {
private String id;
private String firstName;
private String lastName;
private String middleName;
private Date birthDate;
private String email;
// The only constructor is not accesible
protected User() {
}
// ++ more code here
}
An UserFactory class exists in the same package as User and it contains a static method to create User objects:
public class UserFactory {
public static User createUser(String id, String firstName, String lastName, String middleName, Date birthDate, String email) {
User user = new User();
user.setId(id);
user.setFirstName(firstName);
user.setLastName(lastName);
user.setMiddleName(middleName);
user.setBirthDate(birthDate);
user.setEmail(email);
return user;
}
}
In this case the solution will be to call the factory(targetClass, factoryClass):
// Print an arbitrary user to console (System.out)
factory(User.class, UserFactory.class)
.method("createUser") // Invoked through reflection
.params(
uuids(),
names().first(),
names().last(),
names().first(),
localDates().toUtilDate(),
emails().domain("company.com")
)
.consume(System.out::println);
//Output
/**
User{id='14a55707-83e2-4b44-9793-5b6bfa6b72ee', firstName='Ramon', lastName='Edeker', middleName='Marcel', birthDate=Sun May 14 00:00:00 EEST 2006, email='trussedmarquis@company.com'}
*/
reflect()
As the name suggest reflect() use reflection at field level to create objects. A No Args constructor should exist on the class, otherwise the object cannot be created.
public class User {
private String id;
private String firstName;
private String lastName;
private String middleName;
private Date birthDate;
private String email;
// Should be available!
public User() {
}
}
The simplest way to create a generator in this case is to:
MockUnit<User> rUserGenerator =
reflect(User.class)
.field("id", uuids())
.field("firstName", names().first())
.field("lastName", names().last())
.field("middleName", names().first())
.field("birthDate", localDates().toUtilDate())
.field("email", emails());
System.out.println(rUserGenerator.get());
Setters are not used in this case; the values are “forced” at field level. It’s important to remember this in case setters contain their own logic.
By default, an unspecified field() remains null. If the actual data is not important, but the field needs to be populated with “something”, default data generators can be enabled with useDefaults(true):
MockUnit<User> rUserGenerator = reflect(User.class)
.useDefaults(true);
System.out.println(rUserGenerator.get());
// Output
/**
User{id='MbA0Ceett9bIxsAcbggNa0LsDyKrOANf', firstName='41U8JJKtklOAYHZJ07tz3BFoePocUpFH', lastName='L8oiM0bPU2PoMMtAPwpzlpbZJB9tWf9n', middleName='YBbMC8ZSROnErZdL6RuxXRja5e657Gz6', birthDate=null, email='UwaYRbPfEfJFjHL5HsJCD2B8EnbAYMTO'}
*/
Default data generators exist for the following types (and their wrappers if that’s the case):
| Type | Data Generator |
|---|---|
boolean or Boolean |
mockNeat.bools() |
char or Character |
mockNeat.chars().letters() |
double or Doubles |
mockNeat.doubles().bound(10) |
float or Float |
mockNeat.floats().bound(10) |
int or Integer |
mockNeat.ints().bound(100) |
long or Long |
mockNeat.longs().bound(100) |
short or Short |
mockNeat.ints().bound(100).map(Integer::shortValue) |
String |
mockNeat.strings().size(32) |
In the previous example, the birthDate=null. This happens because by default there’s no default generator associated with the Date.class.
Adding new default generators or overriding existing ones can be done by calling type(Class<T1> cls, MockUnit<T1> mockUnit).
For example, if we want to populate the Date fields by default with something, we can write something like this:
MockUnit<User> rUserGenerator = reflect(User.class)
.useDefaults(true)
.type(Date.class, localDates().thisYear().toUtilDate());
System.out.println(rUserGenerator.get());
// Output
/**
User{id='eQ2kHfNsB3JUyGZsGzY8G0eD6knmy3CE', firstName='DkBb98qPh4aWxJwFf8DH6TPfuMbOuiUq', lastName='qjWlN7cECvsWdBAse0gHmobxW2lVI8GG', middleName='M3WZmHtHgrNeFV8chxm1z6n9PpHA8YlO', birthDate=Wed Apr 11 00:00:00 EEST 2018, email='DWLqd2tcqXZohIhLRi9SsjUMIoUBw5JW'}
*/
More formatted data
CSV
There is not a single way to generate CSV files. A few alternatives exists.
One may use a combination of fmt() and accumulate(), like in the following example:
fmt("#{id}, #{fullName}, #{someCode}")
.param("id", uuids())
.param("fullName", names().full().escapeCsv())
.param("someCode", fmt("#{prefix}#{num}")
.param("prefix", chars().lowerLetters())
.param("num", ints().range(0, 100))
)
.accumulate(10, "\n")
.consume(str -> { /* write string to disk */ });
And if we cat the resulting file, the content might look like:
ff13215f-da88-45c5-b77d-38ef02c1b13e, Annemarie Paramore, v60
dcfa9478-d36e-436c-ba53-2a89b1ff0fe6, Paul Giacomini, c86
607b462b-f173-4ee6-a569-4a4422698704, Malcolm Adey, k14
e3005ced-47ec-451c-8b5e-d0f0960e2b48, Nichol Hausteen, y34
d7961c05-c58a-4144-afeb-53eb6722c46b, Wesley Blyther, y58
2d101477-307b-48ee-8271-8cbd289755dc, Adalberto Macleod, l71
84269fdf-e0a3-4d4f-9d65-fdeb123da4f2, Jessika Horwitz, e84
7055aff8-3539-4d01-b7cb-247be5cdbab6, Jackson Hibdon, y90
3d79d066-f2eb-4ba8-95de-745d0bdba351, Patrick Carignan, b10
2f2a48c3-724c-4f91-a237-a5462060ae44, Lanette Steidel, u17
A more concise way of achieving the same results is to use directly the csvs() generator.
This is probably the safest and preferred way of generating valid CSVs because each column has its content escaped by default, and there’s no need to call escapeCsv() explicitly:
String csv = csvs()
.column(intSeq())
.column(names().first())
.column(names().last())
.column(emails())
.column(money().locale(Locale.GERMANY).range(1000, 5000))
.separator("|")
.accumulate(20, "\n")
.get();
System.out.println(csv)
// Output
/**
0|Hal|Gannett|grouserefugio@live.com|"2.907,94 €"
1|Ricardo|Kirsch|thankfuldolan@gmail.com|"3.123,97 €"
2|Nolan|Inglis|webbedjustina@yahoo.co.uk|"3.418,80 €"
3|Sonny|Pareja|wrothjuliana@hotmail.com|"1.041,76 €"
....
*/
csv() offers a shortcut write(fileName) method that will allow the user to persist the data directly on the disk.
In case the file cannot be written on the disk, an UncheckedIOException will be thrown:
csvs()
.column(intSeq())
.column(names().first())
.column(names().last())
.column(emails())
.column(money().locale(Locale.GERMANY).range(1000, 5000))
.separator("|")
.write("filename1.csv", 100); // HERE!
> cat filename1.csv
0|Monte|Probasco|thrumutch@hotmail.com|"2.734,62 €"
1|Harrison|Adebisi|densestschipper@yahoo.com|"4.006,14 €"
2|Kristofer|Tavolieri|dreadsporters@yahoo.co.uk|"3.937,35 €"
3|Royce|Magpusao|auldlino@live.com|"1.532,08 €"
4|Reinaldo|Montori|chasmicdecos@gmx.com|"3.523,23 €"
5|Leonel|Waack|eastwardrousts@comcast.net|"3.835,48 €"
6|Rex|Pyo|pinguiddillaman@msn.com|"2.122,81 €"
7|Perry|Panagos|miffedpop@yahoo.co.uk|"3.201,20
...more
JSON and XML
Arbitrary json (or XML) data can be obtained without any specialised generator.
The sole idea is to create an Object through filler(), constructor(), factory or reflect() and the use a third-party JSON/XML library and map(). (My library of choice when it comes to processing JSON is gson; for XML it’s JAXB.)
This comes with an apparent limitation, a set of additional classes should be created (if they don’t exist) to represent the JSON structure.
Example:
private static class User {
String firstName;
String lastName;
String email;
String creditCard;
// Constructors
// Getters and Setters
}
We will start by defining the actual Object (User) generator MockUnit<User>. The preferred way of creating this should be filler().
MockUnit<User> generator = filler(User::new)
.setter(User::setFirstName, names().first())
.setter(User::setLastName, names().last())
.setter(User::setEmail, emails())
.setter(User::setCreditCard, creditCards().type(VISA_16));
Then same generator can be reused for both JSON:
// Create JSON
Gson gson = new GsonBuilder()
.setPrettyPrinting()
.create();
generator
.map(gson::toJson)
.consume(System.out::println);
// Output
/**
{
"firstName": "Frank",
"lastName": "Bambrick",
"email": "renthugh@hotmail.co.uk",
"creditCard": "4857279349007472"
}
*/
And XML:
final Marshaller jaxbMarshaller = newInstance(User.class, User.class)
.createMarshaller();
jaxbMarshaller.setProperty(Marshaller.JAXB_FORMATTED_OUTPUT, true);
Function<User, String> toXML = (users) -> {
StringWriter productsWriter = new StringWriter();
try {
jaxbMarshaller.marshal(users, productsWriter);
} catch (JAXBException e) {
e.printStackTrace();
}
return productsWriter.toString();
};
generator
.map(toXML)
.consume(System.out::println);
// Output
/**
<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<user>
<creditCard>4783503103187272</creditCard>
<email>baccatetew@att.net</email>
<firstName>Geraldo</firstName>
<lastName>Cler</lastName>
</user>
*/
Note: In order to make the above example work, the User class needs to be decorated with the @XMLRootElement annotation (from JAXB).
If no POJO classes representing the model exist in the project objectMap() can be used instead:
Map<String, Object> om =
objectMap()
.put("person", objectMap()
.put("name", names().full())
.put("age", ints().range(18,60))
.put("visits", objectMap()
.put("city", cities().capitalsEurope())
.put("date", localDates().thisYear().display("yyyy-MM-dd"))
.list(ints().range(3,6))))
.get();
Gson gson = new GsonBuilder().setPrettyPrinting().create();
System.out.println(gson.toJson(om));
With the possible output:
{
"person": {
"visits": [
{
"date": "2020-02-21",
"city": "Zagreb"
},
{
"date": "2020-03-27",
"city": "Vilnius"
},
{
"date": "2020-09-28",
"city": "London"
}
],
"name": "Kellye Alsdon",
"age": 59
}
}
SQL Inserts
Provisioning databases with initial sets of data can be done using the sqlInserts() generator and the associated classes.
For example, to generate a single SQLInsert for a table called "empt" (used to store employees data) can be done in the following way:
SQLInsert oneInsert = sqlInserts()
.tableName("emp")
.column("id", intSeq().increment(10))
.column("first_name", names().first(), TEXT_BACKSLASH)
.column("last_name", names().last(), TEXT_BACKSLASH)
.column("username", users(), TEXT_BACKSLASH)
.column("email", emails(), TEXT_BACKSLASH)
.column("description", markovs().size(32).type(LOREM_IPSUM), TEXT_BACKSLASH)
.column("created", localDates().thisYear().display(BASIC_ISO_DATE), TEXT_BACKSLASH)
.get();
// toString() was overriden to return the actual SQL Insert
System.out.println(oneInsert);
// Possible Output:
// INSERT INTO emp (id, first_name, last_name, username, email, description, created) VALUES (0, 'Mohammad', 'Hibbets', 'lushtraci', 'villousslags@gmx.com', 'Ante ipsum primis in faucibus. E', '20180724');
The TEXT_BACKSLASH parameter is used to denote the fact the column is a text column, and the text is escaped.
For convenience, we can generate multiple SQL inserts, that can be stored in a SQLTable object.
int empTableRows = 100;
SQLTable empTable = sqlInserts()
.tableName("emp")
.column("id", intSeq().increment(10))
.column("first_name", names().first(), TEXT_BACKSLASH)
.column("last_name", names().last(), TEXT_BACKSLASH)
.column("username", users(), TEXT_BACKSLASH)
.column("email", emails(), TEXT_BACKSLASH)
.column("description", markovs().size(32).type(LOREM_IPSUM), TEXT_BACKSLASH)
.column("created", localDates().thisYear().display(BASIC_ISO_DATE), TEXT_BACKSLASH)
.table(empTableRows) // Generate a table instead of a single Insert
.get();
The SQLTable class has a few convenience methods that allows us to modify data:
// After the table is generated we can modify the data in it
empTable.updateAll((i, insert) -> {
// Update all the descriptions with 'N/A'
insert.setValue("description", "N/A");
});
System.out.println(empTable);
Or to select it based on certain criteria:
// Select only the inserts from the table where the first_name starts with and print them
empTable
.selectWhere((sqlInsert -> sqlInsert.getValue("first_name").startsWith("A")))
.forEach(System.out::println);
Generating relational data is easy using the SQLTable.fromColumn("columnName") method which returns a MockUnitString.
To see more advanced usages of this powerful functionality please check this repository: neat-sample-databases-generators.