Pros of Starlark

• More actively maintained with frequent updates and contributions
• Broader community support and adoption within the Bazel ecosystem
• Enhanced documentation and examples for easier implementation

Cons of Starlark

• Potentially more complex due to additional features and integrations
• May have a steeper learning curve for newcomers to the Bazel ecosystem
• Slightly larger codebase, which could impact performance in some cases

Code Comparison

Skylark:

def my_rule_impl(ctx):
    # Implementation details
    return struct(
        files = depset([ctx.outputs.out])
    )

my_rule = rule(
    implementation = my_rule_impl,
    attrs = {"deps": attr.label_list()},
    outputs = {"out": "%{name}.out"},
)

Starlark:

def my_rule_impl(ctx):
    # Implementation details
    return [DefaultInfo(files = depset([ctx.outputs.out]))]

my_rule = rule(
    implementation = my_rule_impl,
    attrs = {"deps": attr.label_list()},
    outputs = {"out": "%{name}.out"},
)

The code examples show minor syntax differences, with Starlark using DefaultInfo instead of struct for returning rule information.

Pros of go-jsonnet

• Native Go implementation, offering better performance and easier integration with Go projects
• Supports advanced Jsonnet features like import callbacks and native extensions
• Actively maintained with regular updates and bug fixes

Cons of go-jsonnet

• Limited to Jsonnet language, while Skylark is more versatile and Python-like
• Steeper learning curve for those unfamiliar with Jsonnet syntax
• Less extensive standard library compared to Skylark

Code Comparison

Skylark:

def greet(name):
    return "Hello, " + name + "!"

result = greet("World")
print(result)

go-jsonnet:

local greet(name) = "Hello, " + name + "!";

{
  result: greet("World")
}

Summary

go-jsonnet is a Go implementation of the Jsonnet language, offering better performance and integration with Go projects. It supports advanced Jsonnet features but has a steeper learning curve compared to Skylark. Skylark, on the other hand, provides a more Python-like syntax and a more extensive standard library, making it more versatile for general-purpose configuration and scripting tasks. The choice between the two depends on the specific project requirements and the team's familiarity with each language.

Pros of cel-spec

• Designed specifically for expression evaluation in configuration and policy scenarios
• Supports gradual typing, allowing for more flexible and dynamic expressions
• Offers built-in support for protocol buffers and common data types

Cons of cel-spec

• Less mature and less widely adopted compared to Skylark
• More limited in scope, focusing primarily on expression evaluation rather than full scripting capabilities
• Smaller community and ecosystem of tools and libraries

Code Comparison

Skylark:

def greet(name):
    return "Hello, " + name + "!"

result = greet("World")
print(result)

cel-spec:

name = "World"
greeting = "Hello, " + name + "!"

Summary

Skylark is a more established and feature-rich language for configuration and scripting, while cel-spec focuses on expression evaluation for specific use cases. Skylark offers a Python-like syntax and broader scripting capabilities, making it suitable for more complex configuration scenarios. cel-spec, on the other hand, provides a simpler and more constrained environment optimized for expression evaluation in configuration and policy contexts. The choice between the two depends on the specific requirements of the project and the desired balance between flexibility and simplicity.

Pros of Dhall

• Strongly typed, providing better safety and error detection
• Supports importing from URLs, allowing for distributed configuration
• Has built-in functions for JSON conversion, making integration easier

Cons of Dhall

• Steeper learning curve due to its more complex type system
• Smaller community and ecosystem compared to Skylark
• Less integration with existing build systems and tools

Code Comparison

Skylark example:

def greet(name):
    return "Hello, " + name + "!"

result = greet("World")
print(result)

Dhall example:

let greet = \(name : Text) -> "Hello, ${name}!"

in  greet "World"

Key Differences

• Syntax: Skylark uses Python-like syntax, while Dhall has a more functional style
• Type System: Dhall has a more advanced type system with features like union types
• Evaluation: Skylark is dynamically evaluated, whereas Dhall is statically evaluated
• Use Cases: Skylark is primarily used for build configurations, while Dhall is more general-purpose for configuration files

Conclusion

Both Skylark and Dhall aim to provide better solutions for configuration management, but they take different approaches. Skylark focuses on build systems and is more familiar to Python developers, while Dhall offers a more robust type system and functional programming paradigm for general configuration needs.

Pros of HCL

• Designed specifically for configuration, with a focus on human-readability
• Native support for JSON-compatible data structures
• Extensive use in HashiCorp's ecosystem, including Terraform

Cons of HCL

• Less flexible for general-purpose programming tasks
• Limited built-in functions compared to Skylark
• Steeper learning curve for users unfamiliar with HashiCorp tools

Code Comparison

HCL:

resource "aws_instance" "example" {
  ami           = "ami-0c55b159cbfafe1f0"
  instance_type = "t2.micro"
  tags = {
    Name = "ExampleInstance"
  }
}

Skylark:

aws_instance(
    name = "example",
    ami = "ami-0c55b159cbfafe1f0",
    instance_type = "t2.micro",
    tags = {"Name": "ExampleInstance"},
)

Summary

HCL is tailored for configuration management, particularly within the HashiCorp ecosystem. It offers a readable syntax and native support for JSON-like structures. However, it may be less versatile for general programming tasks compared to Skylark.

Skylark, being more Python-like, provides greater flexibility for scripting and rule definition. It has a broader range of built-in functions but may require more setup for configuration-specific tasks.

The choice between HCL and Skylark depends on the specific use case and ecosystem integration requirements.

Pros of TOML

• Simple and human-readable configuration format
• Widely adopted across various programming languages
• Supports a variety of data types, including dates and times

Cons of TOML

• Less flexible for complex configurations
• Limited support for nested structures compared to Skylark
• No built-in support for expressions or functions

Code Comparison

TOML example:

[database]
server = "192.168.1.1"
ports = [ 8001, 8001, 8002 ]
connection_max = 5000
enabled = true

Skylark example:

database = struct(
    server = "192.168.1.1",
    ports = [8001, 8001, 8002],
    connection_max = 5000,
    enabled = True,
)

Key Differences

• Syntax: TOML uses a more INI-like syntax, while Skylark is Python-inspired
• Functionality: Skylark offers more programming capabilities, including functions and conditionals
• Use cases: TOML is primarily for configuration files, while Skylark is designed for build systems and more complex scripting

Conclusion

TOML is ideal for simple configuration needs with its easy-to-read format. Skylark, being more powerful and flexible, is better suited for complex build systems and scenarios requiring programmatic logic.