Language Primer

If you know Python, you already know 95% of Seq. The following primer assumes some familiarity with Python or at least one “modern” programming language (QBASIC doesn’t count).


# Seq comments start with "# 'and go till the end of the line

There are no multi-line comments. You can (ab)use docstring operator (''')
if you really need them.


Seq is a strongly typed language like C++, Java or C#. That means each expression must have a type that can be inferred at the compile-time.

# Booleans
True  # type: bool

# Numbers
a = 1  # type: int. It's 64-bit signed integer.
b = 1.12  # type: float. Seq's float is identical to C's double.
c = 5u  # type: int, but unsigned
d = Int[8](12)  # 8-bit signed integer; you can go all the way to Int[2048]
e = Int[8](200)  # 8-bit unsigned integer
f = byte(3)  # a byte is C's char; equivalent to Int[8]

h = 0x12AF  # hexadecimal integers are also welcome
h = 0XAF12
g = 3.11e+9  # scientific notation is also supported
g = .223  # and this is also float
g = .11E-1  # and this as well

# Strings
s = 'hello! "^_^" '  # type: str.
t = "hello there! \t \\ '^_^' "  # \t is a tab character; \\ stands for \
raw = r"hello\n"  # raw strings do not escape slashes; this would print "hello\n"
fstr = f"a is {a + 1}"  # an F-string; prints "a is 2"
fstr = f"hi! {a+1=}"  # an F-string; prints "hi! a+1=2"
t = """
multiline string

# The following escape sequences are supported:
#   \\, \', \", \a, \b, \f, \n, \r, \t, \v,
#   \xHHH (HHH is hex code), \OOO (OOO is octal code)

# Sequence types
dna = s"ACGT"  # type: seq. These are DNA sequences.
prt = p"MYX"  # type: bio.pseq. These are protein sequences.
kmer = k"ACGT"  # type: Kmer[4]. Note that Kmer[5] is different than Kmer[12].


While Seq happily parses None literals, it probably does not stand for what you might expected (it is currently used as C++’s equivalent of nullptr for reference types). The next major release of Seq will unify None with all other types via implicit optional types, making their use much more similar to that in Python.


# Tuples
t = (1, 2.3, 'hi')  # type: tuple[int, float, str].
t[1]  # type: float
u = (1, )  # type: tuple[int]

As all types must be known at the compile time, tuple indexing works only if a tuple is homogenous (all types are the same) or if the value of the index is known at compile-time.

For the same reasons, you can only iterate over a homogenous tuple.

t = (1, 2.3, 'hi')
t[1]  # works because 1 is a constant int

x = 2
t[x]  # compile error: x is not known at the compile time

for i in t:  # compile error: tuple is heterogenous
    print i

# This is a homogenous tuple (all member types are the same)
u = (1, 2, 3)  # type: tuple[int, int, int].
u[x]  # works because tuple members share the same type regardless of x
for i in u:  # works
    print i


Tuples are immutable. a = (1, 2); a[1] = 1 will not compile.


l = [1, 2, 3]  # type: list[int]; a list of integers
s = {1.1, 3.3, 2.2, 3.3}  # type: set[float]; a set of integers
d = {1: 'hi', 2: 'ola', 3: 'zdravo'}  # type: dict[int, str]; a simple dictionary

ln = list[int]()  # an empty list
ln = []  # compiler error; this does not (yet) work due to unknown list type
dn = dict[int, float]()  # an empty dictionary; {} does not (yet) work

Because Seq is strongly typed, these won’t compile:

l = [1, 's']  # is it a list[int] or list[str]? you cannot mix-and-match types
d = {1: 'hi'}
d[2] = 3  # d is a dict[int, str]; 3 is clearly not a string.

t = (1, 2.2)
list[int](t)  # compiler error: t is not heterogenous

lp = [1, 2.1, 3, 5]  # compile error: Seq will not automatically cast an int to a float

This will work, though:

u = (1, 2, 3)
list[int](u)  # works: u is homogenous


Dictionaries and sets are unordered and are based on klib.

Assignments and operators

a = 1 + 2  # this is 3
a = 1.__add__(2)  # you can use a function call instead of an operator; this is also 3
a = int.__add__(1, 2)  # this is equivalent to the previous line
b = 5 / 2.0  # this is 2.5
c = 5 // 2  # this is 2; // is an integer division
a *= 2  # a is now 6

This is the list of binary operators and their magic methods:


Magic method













float division



integer division









matrix multiplication;

sequence alignment



bitwise and



bitwise or



bitwise xor



left bit shift



right bit shift



less than



less or equal than



greater than



greater or equal than



equal to



not equal to



belongs to



boolean and (short-circuits)



boolean or (short-circuits)

Seq also has the following unary operators:


Magic method




bitwise inversion;

reverse complement; optional[T] unpacking



unary positive



unary negation



boolean negation

Tuple unpacking

Seq supports most of the Python’s tuple unpacking syntax:

x, y = 1, 2  # x is 1, y is 2
(x, (y, z)) = 1, (2, 3)  # x is 1, y is 2, z is 3
[x, (y, z)] = (1, [2, 3])  # x is 1, y is 2, z is 3

l = range(1, 8)  # l is [1, 2, 3, 4, 5, 6, 7]
a, b, *mid, c = l  # a is 1, b is 2, mid is [3, 4, 5, 6], c is 7
a, *end = l  # a is 1, end is [2, 3, 4, 5, 6, 7]
*beg, c = l  # c is 7, beg is [1, 2, 3, 4, 5, 6]
(*x, ) = range(3)  # x is [0, 1, 2]
*x = range(3)  # error: this does not work

*sth, a, b = (1, 2, 3, 4)  # sth is (1, 2), a is 3, b is 4
*sth, a, b = (1.1, 2, 3.3, 4)  # error: this only works on homogenous tuples for now

(x, y), *pff, z = [1, 2], 'this'
print x, y, pff, z # x is 1, y is 2, pff is an empty tuple --- () ---, and z is "this"

s, *q = 'XYZ'  # works on strings as well; s is "X" and q is "YZ"

Control flow


Seq supports the standard Python conditional syntax:

if a or b or some_cond():
    print 1
elif whatever() or 1 < a <= b < c < 4:  # oh yes, we do support chained comparisons
    print 'meh...'
    print 'lo and behold!'

if x: y()

a = b if sth() else c  # ternary conditional operator

But lo and behold! Seq extends the Python conditional syntax with a match statement, which is inspired by Rust’s match statement (and luckily not by C’s switch):

match a + some_heavy_expr():  # assuming that the type of this expression is int
    case 1:  # is it 1?
        print 'hi'
    case 2 ... 10:  # is it 2, 3, 4, 5, 6, 7, 8, 9 or 10?
        print 'wow!'
    case _:  # "default" case
        print 'meh...'

match bool_expr():  # now it's a bool expression
    case True: ...
    case False: ...

match str_expr():  # now it's a str expression
    case 'abc': print "it's ABC time!"
    case 'def' or 'ghi':  # you can chain multiple rules with "or" operator
        print "it's not ABC time!"
    case s if len(s) > 10: print "so looong!"  # conditional match expression
    case _: assert False

match some_tuple:  # assuming typeof(some_tuple) is tuple[int, int]
    case (1, 2): ...
    case (a, _) if a == 42:  # you can do away with useless terms with an underscore
        print 'hitchhiker!"
    case (a, 50 ... 100) or (10 ... 20, b) if b < 10:  # you can nest match expressions
        print 'cooomplex!'

match list_foo():
    case []:  # [] actually works here
    case [1, 2, 3]:  # make sure that list_foo() returns list[int] though!
    case [1, 2, ..., 5]:  # matches any list that starts with 1 and 2 and ends with 5
    case [..., 6] or [6, ...]:  # matches a list that starts or ends with 6
    case [..., w] if w < 0:  # matches a list that ends with a negative integer
    case [...] as l:  # any other list; binds variable l to it
        print l

match sequence:  # of type seq
    case s'ACGT': ...
    case s'AC_T': ...  # _ is a wildcard character and it can be anything
    case s'A_C_T_': ...  # a spaced k-mer AxCxTx
    case s'AC...T': ...  # matches a sequence that starts with AC and ends with T

You can mix, match and chain match rules as long as the match type matches the expression type.


Standard fare:

a = 10
while a > 0:  # prints even numbers from 9 to 1
    a -= 1
    if i % 2 == 1:
    print a

for i in range(10):  # prints numbers from 0 to 7, inclusive
    print i
    if i > 6: break

for construct can iterate over any generator, which means any object that implements the __iter__ magic method. In practice, generators, lists, sets, dictionaries, homogenous tuples, ranges and many more types implement this method, so you don’t need to worry. If you need to implement one yourself, just keep in mind that __iter__ is a generator and not a function.


Seq does not support while ... else and for ... else constructs. We’re pretty confident nobody is going to miss those. Let us know if you do!


Technically, comprehensions are not statements (they are expressions). Comprehensions are a nifty, Pythonic way to create collections:

l = [i for i in range(5)]  # type: list[int]; l is [0, 1, 2, 3, 4]
l = [i for i in range(15) if i % 1 == 1 if i > 10]  # type: list[int]; l is [11, 13]
l = [i * j for i in range(5) for j in range(5) if i == j]  # l is [0, 1, 4, 9, 16]

s = {abs(i - j) for i in range(5) for j in range(5)}  # s is {0, 1, 2, 3, 4}
d = {i: f'item {i+1}' for i in range(3)}  # d is {0: "item 1", 1: "item 2", 2: "item 3"}

You can also use collections to create generators (more about them later on):

g = (i for i in range(10))
print list[int](g)  # prints number from 0 to 9, inclusive

for i in g:  # this code right now crashes because g is already exhausted!
    print i


If a generator is exhausted, a segmentation fault can be produced. This behavior will be changed later by raising an exception instead; in the meantime, be sure not to re-use exhausted generators.

Exception handling

Again, if you know how to do this in Python, you know how to do it in Seq:

def throwable():
     raise ValueError("doom and gloom")

except ValueError as e:
    print "we caught the exception"
    print "ouch, we're in a deep trouble"
    print "whatever, it's done"


Right now, Seq cannot catch multiple exceptions in one statement. Thus catch (Exc1, Exc2, Exc3) as var will not compile.

If you have an object that implements __enter__ and __exit__ methods to manage its lifetime (say, a File), you can use a with statement to make your life easy:

with open('foo.txt') as f, open('foo_copy.txt', 'w') as fo:
    for l in f:

Variables and scoping

You have probably noticed by now that blocks in Seq are defined by their indentation level (as in Python). We recommend using 2 or 4 spaces to indent blocks. Do not mix indentation levels, and do not mix tabs and spaces; stick to any consistent way of indenting your code.

One of the major differences between Seq and Python lies in their variable scoping rules. Seq variables cannot leak to outer blocks. Every variable is accessible only within its own block (after the variable is defined, of course), and within any block that is nested within the variable’s own block.

That means that the following Pythonic pattern won’t compile:

if cond():
     x = 1
     x = 2
print x  # x is defined separately in if/else blocks; it is not accessible here!

for i in range(10):
print i  # error: i is only accessible within the for loop block

In Seq, you can rewrite that as:

x = 2
if cond():
     x = 1

# or even better
x = 1 if cond() else 2

print x

Another important difference between Seq and Python is that, in Seq, variables cannot change types. So this won’t compile:

a = 's'
a = 1  # error: expected string, but got int

A note about function scoping: functions cannot modify variables that are not defined within the function block. You need to use global to modify such variables:

g = 5
def foo():
     print g
foo()  # works, prints 5

def foo2():
     g += 2  # error: cannot access g
     print g

def foo3():
     global g
     g += 2
     print g
foo3()  # works, prints 7
foo3()  # works, prints 9

As a rule, use global whenever you are need to access variables that are not defined within the function.


You can import functions and classes from another Seq module by doing:

# Create foo.seq with a bunch of useful methods
import foo

p = foo.Type()

# Create bar.seq with a bunch of useful methods
from bar import x, y

from bar import z as bar_z

import foo looks for foo.seq or foo/__init__.seq in the current directory.


Functions are defined as follows:

def foo(a, b, c):
    return a + b + c
print foo(1, 2, 3)  # prints 5

How about procedures? Well, don’t return anything meaningful:

def proc(a, b):
    print a, 'followed by', b
proc(1, 's')

def proc2(a, b):
    if a == 5:
    print a, 'followed by', b
proc2(1, 's')
proc2(5, 's')  # this prints nothing

Seq is a strongly-typed language, so you can restrict argument and return types:

def fn(a: int, b: float):
    return a + b  # this works because int implements __add__(float)
fn(1, 2.2)  # 3.2
fn(1.1, 2)  # error: 1.1. is not an int

def fn2(a: int, b):
    return a - b
fn2(1, 2)  # -1
fn2(1, 1.1)  # -0.1; works because int implements __sub__(float)
fn2(1, 's')  # error: there is no int.__sub__(str)!

def fn3(a, b) -> int:
    return a + b
fn3(1, 2)  # works, as 1 + 2 is integer
fn3('s', 'u')  # error: 's'+'u' returns 'su' which is str,
               # but the signature indicates that it must return int

Default arguments? Named arguments? You bet:

def foo(a, b: int, c: float = 1.0, d: str = 'hi'):
    print a, b, c, d
foo(1, 2)  # prints "1 2 1.0 hi"
foo(1, d='foo', b=1)  # prints "1 1 1.0 foo"

How about optional arguments? Currently you have to use this:

def foo(a, b: optional[int] = None):
    # operator ~ "unpacks" the optional value only if the optional is not None
    bx = ~b if b else 0
    # WARNING: unpacking None can lead to a segmentation fault
    print a, bx
foo(1)  # prints "1 0"
foo(1, 2)  # prints "1 2"


As we’ve said several times: Seq is a strongly typed language. As such, it is not as flexible as Python when it comes to types (e.g. you can’t have lists with elements of different types). However, Seq tries to mimic Python’s “I don’t care about types until I do” attitude as much as possible by utilizing a technique known as compile-time generics. If there is a function that has an argument without a type definition, Seq will consider it a generic function, and will generate different functions for each invocation of that generic function:

def foo(x):
    print x  # print relies on typeof(x).__str__(x) method to print the representation of x
x(1)  # Seq automatically generates foo(x: int) and calls int.__str__ when needed
x('s')  # Seq automatically generates foo(x: str) and calls str.__str__ when needed
x([1, 2])  # Seq automatically generates foo(x: list[int]) and calls list[int].__str__ when needed

But what if you need to mix type definitions and generic types? Say, your function can take a list of anything? Well, you can use generic specifiers:

def foo[T](x: list[T]):
    print x
foo([1, 2])  # prints [1, 2]
foo(['s', 'u'])  # prints [s, u]
foo(5)  # error: 5 is not a list!
foo[int](['s', 'u'])  # fails: T is int, so foo expects list[int] but it got list[str]

def foo[R](x) -> R:
    print x
    return 1
foo(4)  # prints 4, returns 1
foo[str](4)  # error: return type is str, but foo returns int!


Coming from C++? foo[T, U](x: T) -> U: ... is the same as template<typename T, typename U> U foo(T x) { ... }.


Seq supports generators, and they are fast! Really, really fast!

def gen(i) -> int:
    while i < 10:
        yield i
        i += 1
print list[int](gen(0))  # prints [0, 1, ..., 9]
print list[int](gen(10))  # prints []

Notice the type of gen(0) is generator[int]; however, you annotate the return type of generator with the type of value that you yield (int in this example).

You can also use yield to implement coroutines: yield suspends the function, while (yield) (yes, parentheses are required) receives a value, as in Python.

def mysum[T](start: T) -> T:
    m = start
    while True:
        a = (yield)  # receives the input of coroutine.send() call
        if a == -1:
            break  # exits the coroutine
        m += a
    yield m
iadder = mysum(0)  # assign a coroutine
next(iadder)  # activate it
for i in range(10):
    iadder.send(i)  # send a value to coroutine
print(iadder.send(-1))  # prints 45


Seq extends the core Python language with a pipe operator, which is similar to bash pipes (or F#’s |> operator). You can chain multiple functions and generators to form a pipeline:

def add1(x):
    return x + 1

2 |> add1  # 3; equivalent to add1(2)

def calc(x, y):
    return x + y ** 2
2 |> calc(3)  # 11; equivalent to calc(2, 3)
2 |> calc(..., 3)  # 11; equivalent to calc(2, 3)
2 |> calc(3, ...)  # 7; equivalent to calc(3, 2)

def echo(s):
    print s
def gen(i):
    for i in range(i):
        yield i
5 |> gen |> echo  # prints 0, 1, 2, 3, 4
range(1, 4) |> gen |> echo  # prints (0), (0, 1), (0, 1, 2), (0, 1, 2, 3) without parentheses
[1, 2, 3] |> echo   # prints 1, 2, 3
range(1000000000) |> echo  # not only prints all those numbers, but it uses almost no memory at all

Seq will chain anything that implements __iter__; however, use generators as much as possible because the compiler will optimize out generators whenever possible. Combinations of pipes and generators can be used to implement efficient streaming pipelines.

Seq can also execute pipelines in parallel via the parallel pipe (||>) operator:

range(100000) ||> echo  # prints all these numbers, probably in random order
range(100000) ||> process ||> clean  # runs process in parallel, and then cleans data in parallel

In the last example, Seq will automatically schedule the process and clean functions to execute as soon as possible. You can control the number of threads via the OMP_NUM_THREADS environment variable.

Foreign function interface (FFI)

Seq can easily call functions from C and Python.

Let’s import some C functions:

cimport pow(float) -> float
pow(2.0)  # 4.0

# Import and rename function
cimport puts(cobj) -> void as print_line  # type cobj is C's pointer (void*, char*, etc.)
print_line("hi!".ptr)  # prints "hi!".
                       # Note .ptr at the end of string--- needed to cast Seq's string to char*.

cimport only works if the symbol is available to the program. If you are running your programs via seqc, you can link dynamic libraries by running seqc -l path/to/dynamic/ .... Otherwise, link your libraries by passing them to the clang.

Hate linking? You can also use dyld library loading as follows:

from LIBRARY cimport mymethod(int, float) -> cobj
from LIBRARY cimport myothermethod(int, float) -> cobj as my2
foo = mymethod(1, 2.2)
foo2 = my2(4, 3.2)


When loading a function via FFI, you must explicitly specify argument and return types.

How about Python? If you have set the SEQ_PYTHON environment variable as described in the first section, you can do:

import python  # needed for Python support

pyimport len(str) -> int
print len("hehe")  # prints 4 by passing "hehe" to python

Often you want to execute more complex Python code within Seq. To that end, you can use Seq’s pydef construct:

import python
pydef scipy_here_i_come(i: list[list[float]]) -> list[float]:
    # Code within this block is executed by the Python interpreter,
    # and as such it must be valid Python code
    import scipy.linalg
    import numpy as np
    data = np.array(i)
    eigenvalues, _ = scipy.linalg.eig(data)
    return list(eigenvalues)
print scipy_here_i_come([[1, 2], [3, 4]])  # [-0.372281, 5.37228] with some warnings...

Seq will automatically bridge any object that implements the __to_py__ and __from_py__ magic methods. All standard Seq types already implement these methods.

Classes and types

Of course, Seq supports classes! However, you must declare class members and their types in the preamble of each class (like you would do with Python’s dataclasses).

class Foo:
    x: int
    y: float

    def __init__(self: Foo, x: int, y: int):  # constructor
        self.x, self.y = x, y

    def method(self: Foo):
        print self.x, self.y

f = Foo(1, 2)
f.method()  # prints "1 2"


Right now, you must annotate the type of self.


Seq does not (yet!) support inheritance and polymorphism.

Unlike Python, Seq supports method overloading only for magic methods:

class Foo:
    x: int
    y: float

    def __init__(self: Foo, x: int, y: int):  # constructor
        self.x, self.y = 0, 0
    def __init__(self: Foo, x: int, y: int):  # another constructor
        self.x, self.y = x, y
    def __init__(self: Foo, x: int, y: float):  # another constructor
        self.x, self.y = x, int(y)

    def method(self: Foo):
        print self.x, self.y

Foo().method()  # prints "0 0"
Foo(1, 2).method()  # prints "1 2"
Foo(1, 2.3).method()  # prints "1 2"
Foo(1.1, 2.3).method()  # error: there is no Foo.__init__(float, float)


You cannot overload non-magic methods!

Classes can also be generic:

class Container[T]:
    l: list[T]
    def __init__(self: Container[T], l: list[T]):
        self.l = l

Classes create objects that are passed by reference:

class Point:
    x: int
    y: int

p = Point(1, 2)
q = p  # this is a reference!
p.x = 2
(p.x, p.y), (q.x, q.y)  # (2, 2), (2, 2)

If you need to copy an object’s contents, implement the __copy__ magic method and use p = copy(q) instead.

Seq also supports pass-by-value types via the type construct:

type Point(x: int, y: int)
p = Point(1, 2)
q = p  # this is a copy!
(p.x, p.y), (q.x, q.y)  # (1, 2), (1, 2)

However, by-value objects are immutable!. The following code will fail:

type Point(x: int, y: int)
p = Point(1, 2)
p.x = 2  # error! immutable type

Under the hood, types are basically named tuples (equivalent to Python’s collections.namedtuple).

You can also add methods to types:

type Point(x: int, y: int):
    def __new__(self: Point) -> Point:  # types are constructed via __new__, not __init__
        return (0, 1)  # and __new__ returns a tuple representation of type's members
    def some_method(self: Point) -> int:
        return self.x + self.y
p = Point()  # p is (0, 1)
p.some_method()  # 1

Type extensions

Suppose you have a class that lacks a method or an operator that might be really useful. You can extend that class and add the method at the compile time:

class Foo:

f = Foo(...)
# we need but it does not exist... not a problem for Seq
extend Foo:
    def cool(self: Foo):
        ...  # works!

# how about we add a support for adding integers and strings?
extend int:
    def __add__(self: int, other: str) -> int:
        return self + int(other)
5 + '4'  # 9

Magic methods

Here is a list of useful magic methods that you might want to add and overload:

Magic method



overload unary and binary operators (see Assignments and operators)


copy-constructor for copy method


for len method


for bool method and condition checking


overload obj[key]


overload obj[key] = value


overload del obj[key]


support iterating over the object


support printing and str method

Issues, feedback or comments regarding this tutorial? Let us know on GitHub.