jinsi 0.9.0

JSON/YAML homoiconic templating language

JSON/YAML homoiconic templating language

python3 -m pip install jinsi

Usage via CLI

python3 -m jinsi -  # read from stdin

python3 -m jinsi -j -  # read from stdin, render as json

python3 -m jinsi file1.yaml file2.yaml

Usage via API

from jinsi import render_json, render_yaml, render_file_json, render_file_yaml

print(render_file_yaml("file.yaml"))
# -> prints YAML

print(render_file_json("file.yaml"))
# -> prints minified JSON

print(render_yaml("""
    a: 3
    b:
      ::get: $arg1
    """, arg1="bar"))
# -> prints YAML

print(render_json("""
    a: 3
    b:
      ::get: $arg1
    """, arg1="foo"))
# -> prints JSON

Examples

Cloudformation Template

YAML input:

::let:
  user:
    ::object:
      - ::titlecase:
          ::get: $user.username
      - Type: AWS::IAM::User
        Properties:
          UserName:
            ::get: $user.username
          Groups:
            - Administrators
          LoginProfile:
            Password:
              ::get: $user.password
              ::else: default
            PasswordResetRequired: Yes
  users:
    ::merge:
      ::each $ as $user:
        ::call user:

Resources:
  ::call users:
    - username: jim
      password: one
    - username: jack
      password: two
    - username: johnny

Rendered output:

Resources:
  Jack:
    Properties:
      Groups:
      - Administrators
      LoginProfile:
        Password: two
        PasswordResetRequired: true
      UserName: jack
    Type: AWS::IAM::User
  Jim:
    Properties:
      Groups:
      - Administrators
      LoginProfile:
        Password: one
        PasswordResetRequired: true
      UserName: jim
    Type: AWS::IAM::User
  Johnny:
    Properties:
      Groups:
      - Administrators
      LoginProfile:
        Password: default
        PasswordResetRequired: true
      UserName: johnny
    Type: AWS::IAM::User

Fibonacci

This is just an example to show how complex a template can be. Also note: The fibonacci function is defined recursively. This would blow up and values upto 50 could not be computed. Since Jinsi is purely functional, functions are mappings and can be cached. This is why the computation returns quickly (at all).

python3 -m jinsi max=50 -

YAML input:

::let:
  fib:
    ::when:
      ::get: $n == 0 or $n == 1
    ::then:
      ::get: $n
    ::else:
      ::add:
        - ::call fib:
            $n:
              ::get: $n - 1
        - ::call fib:
            $n:
              ::get: $n - 2
  fibs:
    ::range_exclusive:
      - 0
      - ::get: $max
        ::else: 10

result:
  ::each fibs as $n:
    ::call: fib

Rendered output:

result:
- 0
- 1
- 1
- 2
- 3
- 5
- 8
- 13
- 21
- 34
- 55
- 89
- 144
- 233
- 377
- 610
- 987
- 1597
- 2584
- 4181
- 6765
- 10946
- 17711
- 28657
- 46368
- 75025
- 121393
- 196418
- 317811
- 514229
- 832040
- 1346269
- 2178309
- 3524578
- 5702887
- 9227465
- 14930352
- 24157817
- 39088169
- 63245986
- 102334155
- 165580141
- 267914296
- 433494437
- 701408733
- 1134903170
- 1836311903
- 2971215073
- 4807526976
- 7778742049