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Collection values#

Code Example

Runnable Example in Jac and JacLib

"""Collection values: Lists, tuples, dicts, sets, and comprehensions."""

with entry {
    # Literals
    lst = [1, 2, 3];
    tpl = (1, 2, 3);
    dct = {"a": 1, "b": 2};
    st = {1, 2, 3};

    # Empty collections
    empty_lst = [];
    empty_dct = {};
    empty_tpl = ();

    # List comprehension
    squares = [x ** 2 for x in range(5)];
    filtered = [x for x in range(10) if x % 2 == 0];

    # Dict comprehension
    dict_comp = {x: x ** 2 for x in range(5)};

    # Set comprehension
    set_comp = {x ** 2 for x in range(5)};

    # Generator comprehension
    gen_comp = (x ** 2 for x in range(5));

    # Multiple loops/filters
    multi = [x * y for x in [1, 2] for y in [3, 4]];
    multi_if = [x for x in range(20) if x % 2 == 0 if x % 3 == 0];

    # Nested comprehensions
    matrix = [[i * j for j in range(3)] for i in range(3)];

    # Dictionary unpacking
    merged = {**dct, "c": 3};

    print(lst, tpl, dct, st, squares, dict_comp, set_comp, list(gen_comp), multi, multi_if, matrix, merged);
}

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"""Collection values: Lists, tuples, dicts, sets, and comprehensions."""

with entry {
    # Literals
    lst = [1, 2, 3];
    tpl = (1, 2, 3);
    dct = {"a": 1, "b": 2};
    st = {1, 2, 3};

    # Empty collections
    empty_lst = [];
    empty_dct = {};
    empty_tpl = ();

    # List comprehension
    squares = [x ** 2 for x in range(5)];
    filtered = [x for x in range(10) if x % 2 == 0];

    # Dict comprehension
    dict_comp = {x: x ** 2 for x in range(5)};

    # Set comprehension
    set_comp = {x ** 2 for x in range(5)};

    # Generator comprehension
    gen_comp = (x ** 2 for x in range(5));

    # Multiple loops/filters
    multi = [x * y for x in [1, 2] for y in [3, 4]];
    multi_if = [x for x in range(20) if x % 2 == 0 if x % 3 == 0];

    # Nested comprehensions
    matrix = [[i * j for j in range(3)] for i in range(3)];

    # Dictionary unpacking
    merged = {**dct, "c": 3};

    print(lst, tpl, dct, st, squares, dict_comp, set_comp, list(gen_comp), multi, multi_if, matrix, merged);
}

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"""Collection values: Lists, tuples, dicts, sets, and comprehensions."""
from __future__ import annotations
from jaclang.runtimelib.builtin import *
lst = [1, 2, 3]
tpl = (1, 2, 3)
dct = {'a': 1, 'b': 2}
st = {1, 2, 3}
empty_lst = []
empty_dct = {}
empty_tpl = ()
squares = [x ** 2 for x in range(5)]
filtered = [x for x in range(10) if x % 2 == 0]
dict_comp = {x: x ** 2 for x in range(5)}
set_comp = {x ** 2 for x in range(5)}
gen_comp = (x ** 2 for x in range(5))
multi = [x * y for x in [1, 2] for y in [3, 4]]
multi_if = [x for x in range(20) if x % 2 == 0 if x % 3 == 0]
matrix = [[i * j for j in range(3)] for i in range(3)]
merged = {**dct, 'c': 3}
print(lst, tpl, dct, st, squares, dict_comp, set_comp, list(gen_comp), multi, multi_if, matrix, merged)
Jac Grammar Snippet 
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atom_collection: dict_compr
               | set_compr
               | gen_compr
               | list_compr
               | dict_val
               | set_val
               | tuple_val
               | list_val

list_compr: LSQUARE expression inner_compr+ RSQUARE
gen_compr: LPAREN expression inner_compr+ RPAREN
set_compr: LBRACE expression inner_compr+ RBRACE
dict_compr: LBRACE kv_pair inner_compr+ RBRACE
inner_compr: KW_ASYNC? KW_FOR atomic_chain KW_IN pipe_call (KW_IF walrus_assign)*

dict_val: LBRACE ((kv_pair COMMA)* kv_pair COMMA?)? RBRACE
list_val: LSQUARE (expr_list COMMA?)? RSQUARE
tuple_val: LPAREN tuple_list? RPAREN
set_val: LBRACE expr_list COMMA? RBRACE

kv_pair: expression COLON expression | STAR_POW expression
expr_list: (expr_list COMMA)? expression

tuple_list: expression COMMA expr_list COMMA kw_expr_list COMMA?
          | expression COMMA kw_expr_list COMMA?
          | expression COMMA expr_list COMMA?
          | expression COMMA
          | kw_expr_list COMMA?

kw_expr_list: (kw_expr_list COMMA)? kw_expr
kw_expr: named_ref EQ expression | STAR_POW expression

Description

Collection Values in Jac

Jac provides powerful syntax for creating and manipulating collections including lists, tuples, dictionaries, sets, and comprehensions. This example demonstrates literal notation and comprehension expressions.

Collection Types Overview

Type Syntax Mutable Ordered Allows Duplicates
List [1, 2, 3] Yes Yes Yes
Tuple (1, 2, 3) No Yes Yes
Dictionary {"a": 1, "b": 2} Yes Yes (insertion order) Keys: No, Values: Yes
Set {1, 2, 3} Yes No No

Literal Syntax (Lines 4-8)

The example shows basic collection literals: - Line 5: lst = [1, 2, 3] creates a list - Line 6: tpl = (1, 2, 3) creates a tuple - Line 7: dct = {"a": 1, "b": 2} creates a dictionary with string keys - Line 8: st = {1, 2, 3} creates a set

Empty Collections (Lines 10-13)

Empty collections have special syntax considerations: - Line 11: empty_lst = [] creates an empty list - Line 12: empty_dct = {} creates an empty dictionary (note: {} is dict, not set) - Line 13: empty_tpl = () creates an empty tuple - For empty sets, use set() since {} is reserved for dictionaries

List Comprehension (Lines 15-17)

List comprehensions provide concise syntax for creating lists from iterables:

Line 16: squares = [x ** 2 for x in range(5)] - Produces [0, 1, 4, 9, 16] - squares of numbers 0-4 - Syntax: [expression for variable in iterable]

Line 17: filtered = [x for x in range(10) if x % 2 == 0] - Produces [0, 2, 4, 6, 8] - only even numbers - Syntax: [expression for variable in iterable if condition]

Dictionary Comprehension (Line 20)

Line 20: dict_comp = {x: x ** 2 for x in range(5)} - Creates {0: 0, 1: 1, 2: 4, 3: 9, 4: 16} - Syntax: {key_expr: value_expr for variable in iterable} - Keys and values can be different expressions

Set Comprehension (Line 23)

Line 23: set_comp = {x ** 2 for x in range(5)} - Creates {0, 1, 4, 9, 16} - a set of squares - Syntax: {expression for variable in iterable} - Automatically removes duplicates

Generator Comprehension (Line 26)

Line 26: gen_comp = (x ** 2 for x in range(5)) - Uses parentheses instead of brackets - Creates a generator that produces values lazily - Memory efficient for large datasets - values computed on demand - Convert to list with list(gen_comp) (shown in line 38)

Comprehension Flow Diagram

graph TD
    A[Iterable] --> B{For each item}
    B --> C{Filter condition?}
    C -->|if clause| D{Passes?}
    C -->|no filter| E[Apply expression]
    D -->|Yes| E
    D -->|No| B
    E --> F[Add to result]
    F --> B
    B --> G[Return collection]

Multiple Loops (Line 29)

Line 29: multi = [x * y for x in [1, 2] for y in [3, 4]] - Nested iteration producing all combinations - Results: [1*3, 1*4, 2*3, 2*4] = [3, 4, 6, 8] - Outer loop (x) runs first, inner loop (y) runs for each x

Multiple Filters (Line 30)

Line 30: multi_if = [x for x in range(20) if x % 2 == 0 if x % 3 == 0] - Multiple if clauses act as AND conditions - Only includes values divisible by both 2 AND 3 (multiples of 6) - Results: [0, 6, 12, 18]

Nested Comprehensions (Line 33)

Line 33: matrix = [[i * j for j in range(3)] for i in range(3)] - Creates a 2D matrix (list of lists) - Outer comprehension creates rows, inner creates columns - Results:

Dictionary Unpacking (Line 36)

Line 36: merged = {**dct, "c": 3} - Spreads all key-value pairs from dct into a new dictionary - Adds additional key "c": 3 - If dct = {"a": 1, "b": 2}, result is {"a": 1, "b": 2, "c": 3} - Later values override earlier ones for duplicate keys

Comprehension Performance Characteristics

Type Memory Use Case
List [...] Eager (full list in memory) Need all values, multiple iterations
Generator (...) Lazy (values on demand) Large datasets, single iteration
Dict {k:v...} Eager Key-value mappings
Set {...} Eager Unique values, membership testing

Common Patterns

Transform and filter:

Create lookup tables:

Flatten nested structures:

Matrix operations: