The pythonic way to code in Java.
xpresso is a Java library inspired by Python. It allows a (near) line-into-line rewrite of a Python code into Java. It's also a great way to prototype your algorithms directly in Java.
xpresso implements in Java familiar pythonic methods (e.g., len, enumerate, split/join, slicing) and coding paradigms (e.g., everything is iterable, list comprehensions, generators, lambda expressions, filtering iterables using predicates and modifying them using functions).
xpresso also offers multiple useful tools, usually one-liners, that save developer's time and make the code more readable: x.String, x.Object, x.Function, x.memo, x.WebService, x.MapReduce, x.go, x.timer, x.Json, x.mysql, x.csv and others.
xpresso: less boilerplate, more fun, more work done.
License: [MIT] (https://en.wikipedia.org/wikei/MIT_License).
import com.wantedtech.common.xpresso.x;
x.print("Hello World!");
import com.wantedtech.common.xpresso.types.*;
Imports: set, dict, list, tuple, DefaultDict, OrderedDict, Bag, HappyFile, HappySQL
str city = x.str("New York City");
x.print(city.slice(4,8));
Console: York
for (String character : city)
x.print(character);
Console: N
e
w
Y
o
r
k
Python:
with open("name.txt","r","utf-8") as f:
#do stuff
xpresso:
try (HappyFile f = x.open("name.txt","r","utf-8")) {
//do stuff
}
Works for write/read/append in both text and binary mode.
As in Python, a file opened for reading in text mode is an Iterable of strings:
Python:
for line in f:
print line
xpresso:
for (String line : f)
x.print(line);
Python:
my_car = ("Honda", "red", 2010, True)
xpresso:
tuple myCar = x.tuple("Honda", "red", 2010, true);
Dynamic name assignment to tuple elements:
myCar.name("make","color","year","good");
x.print(myCar.get("good"),myCar.get("make"),myCar.get("year"));
Console: true Honda 2010
If name method has not yet been called, but get(someName) is called for the first time, then the returned value will be get(i), where i is the smallest index of a remaining unnamed element in the tuple. All the subsequent calls for the same value someName, the same element i will be returned by get(someName).
You can also define and use a typed version of tuple. For example:
tuple3<String,String,Integer> myCar = x.tuple3("Honda", "red", 2010);
String myCarMake = myCar.left;
String myCarColor = myCar.middle;
Integer myCarYear = myCar.right;
tuple2<String,tuple3<String,String,Integer>> item = x.tuple2("car",myCar);
String type = item.key; //or, alternatively String type = item.left;
tuple3<String,String,Integer> car = item.value; //or, alternatively tuple3<String,String,Integer> car = item.right;
Python:
trips = ["Dubai","New York","London","Paris","Moscow","London","Saint-Petersburg","New York"]
russian_cities = set(["Moscow","Saint-Petersburg"])
rank = dict(("Moscow":30),("Saint-Petersburg":15),("New York":20),("London":10),("Paris":5),("Dubai":32))
xpresso:
list<String> trips = x.list("Dubai","New York","London","Paris","Moscow","London","Saint-Petersburg","New York");
set<String> russianCities = x.set("Moscow","Saint-Petersburg");
dict<Integer> rank = x.dict(x.tuple("Moscow",30),x.tuple("Saint-Petersburg",15),x.tuple("New York",20),x.tuple("London",10),x.tuple("Paris",5),x.tuple("Dubai",32));
import com.wantedtech.common.functional.*
Function<Object, String> toUpperCaseFun = new Function<Object, String>() {
public String apply(Object value) {
return value.toString().toUpperCase();
}
};
list<String> tripsUp = x.map(toUpperCaseFun, trips);
x.print(tripsUp);
Console: [DUBAI, NEW YORK, LONDON, PARIS, MOSCOW, LONDON, SAINT-PETERSBURG, NEW YORK]
Predicate<Object> containsO = new Predicate<Object>() {
public Boolean apply(Object value) {
return x.String("o").in(value.toString()) ? true : false;
}
};
list<String> tripsO = x.filter(containsO, trips);
x.print(tripsO);
Console: [New York, London, Moscow, London, New York]
You don't need to define a new Function class every time you want to transform an iterable in a certain way. You can use the x.Function that automagically wraps any static method of any Java class into a Function:
Function<String,String> myUpper = x.Function(String.class, "toUpperCase");
iterable = x.map(myUpper, iterable);
The x.Function method can also wrap static methods that take several arguments:
Function<tuple3<String,Integer,Boolean>,Double> mySomeFunc = x.Function(Some.class, "someStaticMethod");
Function<tuple3<String,Integer,Boolean>,Double> myOtherFunc = x.Function(Other.class, "someOtherMethod");
Function<tuple3<String,Integer,Boolean>,Double> funcToUse;
if (someCondition) {
funcToUse = mySomeFunc;
} else {
funcToUse = myOtherFunc;
}
double sum;
for (element : iterable) {
sum += funcToUse.apply(x.tuple3(element,intParam,boolParam));
}
If in a certain class there're more than one static method with the same name, you need to specify which one of them you want to wrap by providing parameter types:
Function<tuple3<String,Integer,Boolean>,Double> mySomeFunc = x.Function(Some.class, "someStaticMethod", String.class, Integer.class, Boolean.class);
Python:
best_cities = reversed(sorted(item for item in rank.items(),lambda x: x[0]))
xpresso:
list<String> bestCities = x.reverse(x.sort(yield().forEach(rank.items()),x.lambdaF("x: x[0]")));
More complex lambda expressions:
Predicate<Object> pr = x.lambdaP("x : f0(f1(x[1])) == '''new york'''",x.lower,x.strip);
Function<Object,Integer> squareFun = x.lambdaF("x : x * x");
Function<Object,Integer> fun = x.lambdaF("x : x[0] * 10 * (x[1] - f0(x[2])))",squareFun);
Function chains:
Function<Object,Integer> incrementFun = x.lambdaF("x : x + 1");
Function<Object,Integer> squareFun = x.lambdaF("x : x * x");
Function<Object,Integer> chainFun = x.chain(incrementFun,squareFun);
chainFun will first increment, then square its input. x.chain(...) can take more than two functions as argument. The last function in the chain has to return the value of the desired output type.
Python:
foreign_trips_lower = [city.lower() for city in trips if city not in russian_cities]
xpresso:
list<String> foreignTripsLower = x.list(x.<String>yield().apply(x.lower).forEach(trips).unless(x.in(russianCities)));
Python:
cool_cities = dict([(city.upper(),true) for (city, score) in rank.items() if score > 5])
xpresso:
dict<Integer> coolCities = x.dict(x.yield("city","_").apply(x.upper).replace(true).where("city","score").in(rank.items()).when(x.lambdaP("city, score : score > 20")));
Python:
evals = [True if value == "good" else False for value in some_list]
xpresso:
list<Boolean> evals = x.list(x.<Boolean>yield().replace(true).when(x.lambdaP("x : x == '''good'''")).replaceOtherwise(false).forEach(someList));
You can use list comprehensions to extract properties from element objects:
class PlannedTrip {
int year;
String city;
public PlannedTrip(int year, String city) {
this.year = year;
this.city = city;
}
public int getYear() { return year; }
public String getCity() { return city; }
}
list<PlannedTrip> plans = x.list(new PlannedTrip(2015, "Moscow"), new PlannedTrip(2016, "Paris"));
list<tuple> plansData = x.list(x.yield("year", "city").where("year", "city").in(plans));
x.print(plansData);
Console: [(2015, Moscow), (2016, Paris)]
You can also filter the extracted values in the same expression:
list<tuple> plansData = x.list(x.yield("year", "city").where("year", "city").in(plans).when(x.lambdaP("year, city : year > 2015)));
x.print(plansData);
Console: [(2016, Paris)]
Let's suppose we have an object of a class SomeMath which has two methods we would like to publish on the network as RESTful web services, getSum and getProduct:
public class SomeMath() {
public Double getSum(Double[] values) { //we want to publish this one
return x.sum(values);
}
public Double getProduct(Double x, Double y) {//and this one
return x * y;
}
public Double anotherMethod(Double somethingElse) {//but not this one
return somethingElse;
}
}
In order to convert our SomeMath class into a web service, we simply need to first annotate our two methods we want to call from the network with the @ExposeAs annotation, and then start our web service:
public class SomeMath() {
public Double getSum(@ExposeAs("values") Double[] values) {
return x.sum(values);
}
public Double getProduct(@ExposeAs("x") Double x, @ExposeAs("y") Double y) {
return x * y;
}
public Double anotherMethod(Double somethingElse) {
return somethingElse;
}
}
WebService ws = x.WebService(new SomeMath(), 8080).start();
That's all! Our web service is up and running. Let's test it. Open the following url in your browser:
http://localhost:8080/SomeMath/getSum?values=5&values=6&values=7
The output:
18.0
Now open the following url:
http://localhost:8080/SomeMath/getProduct?x=5&y=10
The output:
50.0
If a method returns an output type of more complex classes such as Java's standard Map and List, or xpresso's own list and dict, the output will be a corresponding JSON string.
Python:
def firstn(n):
num = 0
while num < n:
yield num
num += 1
for i in firstn(500000):
print i
xpresso:
public Generator<Integer> firstn (final int n) {
return new Generator<Integer>() {
public void generate() {
int num = 0;
while (num < n) {
yield(num);
num++;
}
}
};
}
for (int i : firstn(500000))
x.print(i);
As a quick example, let xerox be a Function object whose method apply copies the string "hello" the given number count of times:
Function<Integer, String> xerox = new Function<Integer, String>() {
public String apply(Integer count) {
return x.String("hello").times(count);
}
};
It's a long to execute function for large values of count.
In order to avoid the long computation for the same value of count, we first create a cached version of xerox using x.memo:
Function<Integer,String> cachedXerox = x.memo(xerox);
The first call of the function. The computation takes a very long time:
x.timer.start();
String copies = cachedXerox.apply(5000000);
x.print(x.timer.stop());
Console: 18.898s
The second call with the same value of count, the result is instantaneous:
x.timer.start();
String moreCopies = cachedXerox.apply(5000000);
x.print(x.timer.stop());
Console: 0.0s
x.memo can be used to cache methods of object of any Java type, not only Function. Notice the usage of the standard x.timer: no additional timer object needs to be created.
Concurrency in xpresso is inspired by Go and, as a consequence, is extremely simple. First, define a worker as an instance of Predicate:
Predicate<Channel<Integer>> worker = new Predicate<Channel<Integer>>() {
public Boolean apply(Channel<Integer> channel) {
while (some_condition_true) {
Integer value = computeValue(); //compute something in parallel
channel.send(value); //send the computed value to the channel
}
return true; //everything went as expected
}
};
Then, define the channel to where the workers should send the computed values as soon as those values are ready:
Channel<Integer> channel = x.Channel(Integer.class);//this channel only accepts Integer values
Then, start as many concurrent workers as needed:
x.go(worker, channel);
x.go(worker, channel);
x.go(worker, channel);
...
Finally, retrieve from the channel the values concurrently computed by the workers when those values are needed:
for (Integer value : channel) {
x.print(value);
}
Let's assume that we have a list of elements we want to process:
list<String> elements = x.list("Map","aNd","ReDuce","arE","aWEsome");
The processing of each element takes a long time (10 seconds), so we want to parallelize the processing on our multicore machine. Let the processing be as follows: if the element starts with an "a", then put it in uppercase and join it with other uppercase elements using "~" as separator; if the element doesn't start with an "a", then put it to lowercase and join it with other lowercase words.
Let's define the Mapper and Reducer:
import com.wantedtech.common.xpresso.experimental.concurrency.Mapper;
import com.wantedtech.common.xpresso.experimental.concurrency.Reducer;
static Mapper<String,String> mapper = new Mapper<String,String>() {
public void map(String input) {
x.Time.sleep(10); //the processing of each element takes a long time :-)
if (x.String(input).startsWith("a")) {
yield("upper", input.toUpperCase());
} else {
yield("lower", input.toLowerCase());
}
}
};
static Reducer<String,String> reducer = new Reducer<String,String>() {
public void reduce(tuple2<String,list<String>> input) {
yield(input.key,x.String("~").join(input.value));
}
};
Our mapper does the transformation of the string case as described above, and our reducer joins the resulting values with the "~".
Our MapReduce setup is now ready, so let's start crunching:
x.timer.start();
x.print(x.<String,String,String>MapReduce(elements).map(mapper).reduce(reducer), x.timer.stop());
Console:
{upper:AND~AWESOME~ARE, lower:reduce~map}
10.013s
As you can see, the processing of all 5 elements took only about 10 seconds, while we have defined above that the processing of each single element takes 10 seconds.
Remember the rank dict:
dict<Integer> rank = x.dict(x.tuple("Moscow",30),x.tuple("Saint-Petersburg",15),x.tuple("New York",20),x.tuple("London",10),x.tuple("Paris",5),x.tuple("Dubai",32));
Let's first dump it as a String:
String rankAsString = x.Json(rank).toString();
x.print(rankAsString);
Console: {"New York":20,"London":10,"Saint-Petersburg":15,"Moscow":30,"Dubai":32,"Paris":5}
Now let's create a copy of the rank dict from its JSON string representation:
dict<Integer> rankCopy = x.String(rankAsString).parseJson();
Compare the original rank dict to the copy:
x.print(x.Object(rank).equals(rankCopy));
Console: true
Read from file:
try (HappyFile f = x.open("filename.txt","r","utf-8")) {
for (list<String> row : x.csv(f)) {
//do stuff
}
}
Or, simply:
list<list<String>> data = x.list(x.csv("filename.txt","r","utf-8"));
Write to file:
try (HappyFile f = x.open("filename.txt","w","utf-8")) {
for (list<?> row : data){
x.csv(f).writerow(row);
}
}
Or, simply:
try (HappyFile f = x.open("filename.txt","w","utf-8")) {
f.write(x.csv(data).toString());
}
Write to a StringBuilder:
StringBuilder builder = new StringBuilder();
for (list<?> row : data) {
x.csv(builder).writerow(row);
}
String cs = c.toString();
Or, simply:
String cs = x.csv(data).toString();
String host = "host:port";
String user = "user";
String password = "password";
String db = "db";
try (HappySQL sql = x.mysql(host, user, password, db)) {
try (HappySQL sql2 = x.mysql(sql)){
String query = "SELECT ID FROM " +
"tbl_Employees e " +
"WHERE e.Name LIKE ?";
for (tuple row : sql.execute(query, "John %")) {
query = "UPDATE tbl_Employees " +
"SET Promoted = 1 " +
"WHERE ID = ?";
sql2.execute(query, row.get("ID"));
}
}
}
Python:
if "e" in "Hello World":
#do stuff
xpresso:
if(x.String("e").in("Hello World")) {
//do stuff
}
Python:
colorsPattern = "|".join(["black","green","red","white"]);
print colorsPattern
>>> black|green|red|white
xpresso:
String colorsPattern = x.String("|").join(x.list("black","green","red","white"));
x.print(colorsPattern);
Console: black|green|red|white
Python:
tokens = "Moscow;London;Paris".split(";")
print tokens
>>> ['Moscow', 'London', 'Paris']
xpresso:
list<String> tokens = x.String("Moscow;London;Paris").split(";");
x.print(tokens);
Console: [Moscow, London, Paris]
Transliterate:
String trans = x.String("Чичётка 北亰").translit();
x.print(trans);
Console: Čičëtka bei jing
x.print(trans.stripAccents());
Console: Cicetka bei jing
Convert unicode to ascii:
String unidec = x.String("Чичётка 北亰").unidecode();
x.print(unidec);
Console: Chichiotka bei jing
Approximate string comparison:
x.print(x.String("Hello World").similarity("Hello Wold!"))
Console: 91
The output is 100% compatible with FuzzyWuzzy.
Approximate pattern matching:
x.print(x.String("You are cooding in Java.").search("coding"));
Console: 8
Get similar strings:
list<String> lookAlikes = x.String("apple").lookAlikes(x.list("ape", "apples", "peach", "puppy"),50);
x.print(lookAlikes);
Console: [ape, apples]
Tokenization:
String text = "English is hard. It can be understood through tough thorough thought, though.";
for (Sentence s : x.String.EN.tokenize(text)) {
for (Token t : s) {
x.print(t);
}
}
Console: English
is
hard
.
It
can
...
With xpresso you can easily POS tag any English text with the very fast and accurate (~97%) Stanford CoreNLP english-left3words model:
import com.wantedtech.common.xpresso.sentence.Sentence;
import com.wantedtech.common.xpresso.sentence.PosTagger;
import com.wantedtech.common.xpresso.sentence.pos.en.stanford.MaxentPosTagger;
PosTagger posTagger = new MaxentPosTagger();
String text = "Some English text. Multiple sentences.";
for (Sentence sent : x.String.EN.tokenize(text)) {
posTagger.tag(sent);
x.print(sent.getAnnotations("pos"));
}
Console: [(Some, DT), (English, NNP), (text, NN), (., .)]
[(Multiple, JJ), (sentences, NNS), (., .)]
Python:
trips = ["Dubai","New York","London","Paris","Moscow","London","Saint-Petersburg","New York"]
print trips[2:4]
>>> ['London', 'Paris']
xpresso:
x.print(trips.slice(2,4));
Console: [London, Paris]
Python:
print trips[:5]
>>> ['Dubai','New York','London','Paris','Moscow']
xpresso:
x.print(trips.sliceTo(5));
Console: [Dubai, New York, London, Paris, Moscow]
Negative and non-unit steps are supported:
Python:
print trips[::-1]
>>> ['New York', 'Saint-Petersburg', 'London', 'Moscow', 'Paris', 'London', 'New York', 'Dubai']
xpresso:
x.print(trips.slice(-1));
Console: [New York, Saint-Petersburg, London, Moscow, Paris, London, New York, Dubai]
Python:
print trips[::2]
>>> ['Dubai','London','Moscow','Saint-Petersburg']
xpresso:
x.print(trips.slice(2));
Console: [Dubai, London, Moscow, Saint-Petersburg]
Slicer LAST_THREE = x.sliceFrom(-3);
x.print(x.String("tic tac toe").slice(LAST_THREE));
Console: toe
Python:
for long_word_match in re.finditer("\b\w{10,}\b",text):
print long_word_match.group(0)
xpresso:
for (Match longWordMatch : x.Regex("\\b\\w{10,}\\b").findIter(text))
x.print(longWordMatch.group(0));
Python:
for long_word in re.findall("\b\w{10,}\b",text):
print long_word
xpresso:
for (String longWord : x.Regex("\\b\\w{10,}\\b").findAll(text))
x.print(longWord);
Python:
def toUpperCaseFun(value):
return value.group(0).upper()
text = re.sub("\b\w{10,}\b",toUpperCaseFun,text)
xpresso:
Function<Match,String> toUpperCaseFun = new Function<Match,String>(){
public String apply(Match value) {
return value.group(0).toUpperCase();
}
}
text = x.Regex("\\b\\w{10,}\\b").sub(toUpperCaseFun,text);
dict<String> replacer = x.dict(x.tuple("bad","good"),x.tuple("small","big"),x.tuple("hard","easy"));
text = x.Regex(replacer).sub(text);
list<String> emails = x.list(x.Regex.EMAIL.findAll("Contact me at [email protected] or [email protected]."));
x.print(emails);
Console: [smith@company.com, john@smith.com]
Other patterns include x.Regex.LINK, x.Regex.EMAIL, x.Regex.IPV4, x.Regex IPV6, x.Regex.HEX_COLOR, x.Regex.ACRONYM, x.Regex.CREDIT_CARD, x.Regex.FLOAT, and so on, as well as a number of country-specific ones: x.Regex.US.DATE, x.Regex.US.TIME, x.Regex.US.PHONE, x.Regex.US.PRICE, x.Regex.US.STREET_ADDRESS, etc.
Token tok = x.Token("MySQL5");
x.print(tok.shape(), tok.isCamel(), tok.hasDigits(), tok.hasRussian());
Console: ULUUUD, true, true, false
tok = x.Token("Thinking");
x.print(tok.stem());
Console: Think
When defining a class:
@Override
int hashCode() {
return x.Object(this).hashCode();
}
In the above code, xpresso first finds the members of this (via reflections) and then dynamically computes the hash code for this based on the values of its members.
@Override
boolean equals(Object obj) {
return x.Object(this).equals(obj);
}
In the above code, xpresso first finds the members of the two objects (this and obj), and then compares the values of those members.
@Override
public int compareTo(Object obj) {
return x.Object(this).compareTo(obj, fieldName0, fieldName1, ...);
}
In the above code, xpresso first finds the members of the two objects (this and obj). It then compares the values of those members between the two objects if those members' names are listed among the input field names fieldName0, fieldName1, etc. The order of comparisons between the member's values is the same as the order of input field names.
x.assertTrue(condition); // throws IllegalArgumentException
x.assertNotNull(parameter); // throws NullPointerException
x.assertNotEmpty(iterable); /* throws NullPointerException if iterable is null,
throws IllegalArgumentException if iterable is empty */
x.assertNotEmpty(string);
x.assertNotEmpty(array);
- cycle
for (String letter : x.cycle(x.str("ABC")))
x.print(letter);
Console: A
B
C
A
B
C
A
B
C
...
for (String letter : x.cycle(x.list("hello","world"),3))
x.print(letter);
Console: hello
world
hello
world
hello
world
- repeat
for (String word : x.repeat("cool"))
x.print(word);
Console: cool
cool
cool
cool
...
for (String word : x.repeat("cool",3))
x.print(word);
Console: cool
cool
cool
- count
for (Integer index : x.countTo(3))
x.print(index);
Console: 0
1
2
for (Integer index : x.countFrom(10))
x.print(index);
Console: 10
11
12
13
...
for (Integer index : x.count(3,10))
x.print(index);
Console: 3
4
5
6
7
8
9
for (Integer index : x.count(3,10,3))
x.print(index);
Console: 3
6
9
x.count(min, max) and x.count(min, max, step) replace Python's range(min, max) and range(min, max, step).
x.print("Hello World", 1, true, x.list(1, 2, 3), null);
Console: Hello World 1 true [1, 2, 3] NullType
str phrase = "If you want something done right, you have to do it yourself.";
list<str> tokens = phrase.split();
list<list<str>> ngrams = tokens.ngrams(3);
x.print(ngrams);
Console: [[If, you, want], [you, want, something], [something, done, right]..., [do, it, yourself.]]
list<String> cities = x.list("Moscow","San Francisco","Saint-Petersbourg","Rome");
x.print(x.smallestN(cities,2));
Console: [Rome, Moscow]
list<String> cities = x.list("Moscow","San Francisco","Saint-Petersbourg","Rome");
x.print(x.largestN(cities,2));
Console: [Saint-Petersbourg, San Francisco]
- Invert dict:
dict.invert();
- Flatten list:
list.flatten();
- Modify list using slicing:
trips.setAt(3, 5).values(x.list(1, 2, 3, 4, 5));
- Case insensitive regex shortcut:
x.RegexNoCase("\\bmama\\b")
- Replace each match by an empty string:
x.Regex("[,.;]").clear(inputString)
- For more see the javadoc for the main class x.
- HTTP client
- Find longest match (in the spirit of Python's [SequenceMatcher] (https://docs.python.org/3.4/library/difflib.html#difflib.SequenceMatcher)):
tuple match = x.String("I like apples.").longestMatch("My girlfriend likes apples too.");
x.print(match);
Console: ("apples", 7, 20)
- Mistyping detection:
x.String("Random").isMistypingOf("Randon","qwerty") --> true