layout: documentation title: Starlark Language

Starlark Language

The page is an overview of Starlark (formerly known as Skylark), the language used in Bazel. This should be enough to get you started. Please refer to the Starlark repository on GitHub for more information about the language. For a complete list of functions and types, please check the API reference.

Syntax

Starlark is designed to be small, simple, and thread-safe. Although it is inspired from Python, it is not a general-purpose language and most Python features are not included.

The following constructs have been added to the Core Build Language: if statements, for loops, and function definitions. They behave like in Python. Here is an example to show the syntax:

def fizz_buzz(n):
  """Print Fizz Buzz numbers from 1 to n."""
  for i in range(1, n + 1):
    s = ""
    if i % 3 == 0:
      s += "Fizz"
    if i % 5 == 0:
      s += "Buzz"
    print(s if s else i)

fizz_buzz(20)

The following basic types are supported: None, bool, dict, function, int, list, string. On top of that, two new types are specific to Bazel: depset and struct.

Starlark is syntactically a subset of both Python 2 and Python 3, and will remain so through at least the 1.x release lifecycle. This ensures that Python-based tooling can at least parse Starlark code. Although Starlark is not semantically a subset of Python, behavioral differences are rare (excluding cases where Starlark raises an error).

Mutability

Because evaluation of BUILD and .bzl files is performed in parallel, there are some restrictions in order to guarantee thread-safety and determinism. Two mutable data structures are available: lists and dicts.

In a build, there are many “evaluation contexts”: each .bzl file and each BUILD file is loaded in a different context. Each rule is also analyzed in a separate context. We allow side-effects (e.g. appending a value to a list or deleting an entry in a dictionary) only on objects created during the current evaluation context. Once the code in that context is done executing, all of its values are frozen.

For example, here is the content of the file foo.bzl:

var = []

def fct():
  var.append(5)

fct()

The variable var is created when foo.bzl is loaded. fct() is called during the same context, so it is safe. At the end of the evaluation, the environment contains an entry mapping the identifier var to a list [5]; this list is then frozen.

It is possible for multiple other files to load symbols from foo.bzl at the same time. For this reason, the following code is not legal:

load(":foo.bzl", "var", "fct")

var.append(6)  # runtime error, the list stored in var is frozen

fct()          # runtime error, fct() attempts to modify a frozen list

Evaluation contexts are also created for the analysis of each custom rule. This means that any values that are returned from the rule‘s analysis are frozen. Note that by the time a custom rule’s analysis begins, the .bzl file in which it is defined has already been loaded, and so the global variables are already frozen.

Differences with Python

In addition to the mutability restrictions, there are also differences with Python:

  • Global variables cannot be reassigned.

  • for statements are not allowed at the top-level; factor them into functions instead.

  • Dictionaries have a deterministic order of iteration.

  • Recursion is not allowed.

  • Int type is limited to 32-bit signed integers (an overflow will throw an error).

  • Lists and other mutable types may be stored in dictionary keys once they are frozen.

  • Modifying a collection during iteration is an error. You can avoid the error by iterating over a copy of the collection, e.g. for x in list(my_list): .... You can still modify its deep contents regardless.

  • Global (non-function) variables must be declared before they can be used in a function, even if the function is not called until after the global variable declaration. However, it is fine to define f() before g(), even if f() calls g().

  • The comparison operators (<, <=, >=, >) are not defined across different types of values, e.g., you can't compare 5 < 'foo' (however you still can compare them using == or !=). This is a difference with Python 2, but consistent with Python 3. Note that this means you are unable to sort lists that contain mixed types of values.

  • Tuple syntax is more restrictive. You may use a trailing comma only when the tuple is between parentheses, e.g. write (1,) instead of 1,.

  • Dictionary literals cannot have duplicated keys. For example, this is an error: {"a": 4, "b": 7, "a": 1}.

  • Variable of a comprehension may not be used after the comprehension. This is stricter than Python 2 and Python 3, which have different behavior (shadowing vs reassignment).

  • Strings are represented with double-quotes (e.g. when you call repr).

The following Python features are not supported:

  • implicit string concatenation (use explicit + operator)
  • Chained comparisons (e.g. 1 < x < 5)
  • class (see struct function)
  • import (see load statement)
  • while, yield
  • float and set types
  • generators and generator expressions
  • lambda and nested functions
  • is (use == instead)
  • try, raise, except, finally (see fail for fatal errors)
  • global, nonlocal
  • most builtin functions, most methods