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| 1 | +# Language Selection for Automation Tooling |
| 2 | + |
| 3 | +## Key Requirements |
| 4 | + |
| 5 | +The primary requirements for the selected language are: |
| 6 | + |
| 7 | +1. **Cross-Platform Compatibility**: Must run seamlessly on Linux, macOS, and |
| 8 | + Windows. |
| 9 | +2. **Performance**: Should be fast enough for tasks like file I/O, data |
| 10 | + processing, and network requests. |
| 11 | +3. **Ecosystem and Libraries**: A rich ecosystem with libraries for common |
| 12 | + automation tasks is crucial. |
| 13 | +4. **Ease of Use and Learning Curve**: Should be accessible to a wide range of |
| 14 | + contributors. |
| 15 | +5. **Tooling and IDE Support**: Excellent tooling and IDE support are essential |
| 16 | + for developer productivity. |
| 17 | +6. **Developer Experience**: The language should be productive and easy for |
| 18 | + contributors to learn and use, enabling rapid development and maintenance. |
| 19 | +7. **Public Codebase Availability**: The volume of publicly available code is a |
| 20 | + key factor for AI-assisted development. A larger and more diverse codebase |
| 21 | + allows for better training of AI models, leading to more accurate and |
| 22 | + relevant code generation, faster prototyping, and more effective |
| 23 | + problem-solving. |
| 24 | +8. **Community and Contributor Pool**: A large, active community and a readily |
| 25 | + available pool of potential contributors are vital for the long-term health |
| 26 | + and sustainability of the project. This ensures better support, more |
| 27 | + third-party libraries, and a higher likelihood of attracting developers. |
| 28 | + |
| 29 | +## Language Candidates |
| 30 | + |
| 31 | +The following languages have been identified as strong candidates: |
| 32 | + |
| 33 | +1. **Python**: A high-level, dynamically-typed language renowned for its |
| 34 | + simplicity, readability, and extensive ecosystem in the automation and |
| 35 | + DevOps space. |
| 36 | +2. **Go (Golang)**: A statically-typed, compiled language developed by Google, |
| 37 | + designed for building simple, reliable, and efficient software. It is the |
| 38 | + de-facto language of the cloud-native ecosystem (Kubernetes, Docker, |
| 39 | + Prometheus, OpenTofu). |
| 40 | +3. **Rust**: A statically-typed, compiled language focused on performance, |
| 41 | + safety, and concurrency. While the Torrust project itself uses Rust, its |
| 42 | + suitability for high-level orchestration scripts needs to be evaluated. |
| 43 | +4. **Perl**: A high-level, general-purpose, interpreted, dynamic programming |
| 44 | + language. It has a long history of being used for system administration |
| 45 | + and automation tasks. |
| 46 | +5. **Shell Scripting (Baseline)**: The current approach. It serves as a |
| 47 | + baseline for comparison. |
| 48 | + |
| 49 | +## Comparison |
| 50 | + |
| 51 | +### Evaluation Criteria |
| 52 | + |
| 53 | +| Criterion | Python | Go | Rust | Perl | Shell Script | |
| 54 | +| :--------------------------------- | :--------------------- | :--------------------- | :------------------- | :----------------- | :----------------------------- | |
| 55 | +| **Ease of Testing** | ⭐⭐⭐⭐⭐ (Excellent) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐ (Good) | ⭐⭐⭐ (Good) | ⭐ (Poor) | |
| 56 | +| **Ecosystem & Libraries** | ⭐⭐⭐⭐⭐ (Excellent) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐ (Good) | ⭐⭐ (Fair) | ⭐⭐ (Fair) | |
| 57 | +| **Plugin Architecture** | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐ (Good) | ⭐ (Poor) | |
| 58 | +| **Standard Library** | ⭐⭐⭐⭐⭐ (Excellent) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐ (Good) | ⭐⭐ (Fair) | ⭐⭐ (Fair) | |
| 59 | +| **Infrastructure Adoption** | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐⭐⭐ (Excellent) | ⭐⭐⭐ (Growing) | ⭐⭐⭐ (Growing) | ⭐⭐⭐⭐ (Widespread) | |
| 60 | +| **Developer Experience** | ⭐⭐⭐⭐⭐ (Excellent) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐ (Steep Curve) | ⭐⭐ (Steep Curve) | ⭐⭐⭐ (Good for simple tasks) | |
| 61 | +| **Public Codebase Availability** | ⭐⭐⭐⭐⭐ (Excellent) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐ (Good) | ⭐⭐⭐ (Good) | ⭐⭐ (Fair) | |
| 62 | +| **Community and Contributor Pool** | ⭐⭐⭐⭐⭐ (Excellent) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐⭐⭐ (Very Good) | ⭐⭐ (Fair) | ⭐⭐⭐⭐⭐ (Ubiquitous) | |
| 63 | +| **Overall Suitability** | **Excellent** | **Excellent** | **Good** | **Fair** | **Poor** | |
| 64 | + |
| 65 | +--- |
| 66 | + |
| 67 | +## Detailed Analysis |
| 68 | + |
| 69 | +### 1. Python |
| 70 | + |
| 71 | +- **Testing**: Excellent. The `pytest` framework is incredibly powerful and |
| 72 | + flexible, making it easy to write clean, maintainable tests. The |
| 73 | + `unittest` module is built-in. Mocking and patching are straightforward. |
| 74 | +- **Libraries**: Unmatched ecosystem for automation. |
| 75 | + - **Cloud SDKs**: Mature and well-supported libraries for all major cloud |
| 76 | + providers (AWS Boto3, Azure, GCP). |
| 77 | + - **OpenTofu**: The `python-terraform` library provides a wrapper, but |
| 78 | + it's not as integrated as the Go provider SDK. |
| 79 | + - **Parsing**: Native `json`, and robust libraries like `PyYAML` and |
| 80 | + `toml`. |
| 81 | +- **Extensibility**: Very good. Python's dynamic nature and support for entry |
| 82 | + points make plugin systems relatively easy to implement. |
| 83 | +- **Adoption**: Widely used. Ansible, a major configuration management tool, |
| 84 | + is built in Python. Many cloud provider SDKs have first-class Python |
| 85 | + support. |
| 86 | +- **Developer Experience**: Excellent. The syntax is clean and readable, |
| 87 | + leading to high productivity. It's a great language for scripting and |
| 88 | + building high-level logic. |
| 89 | +- **Public Codebase Availability**: Excellent. Python is one of the most popular |
| 90 | + languages on GitHub, with a vast and diverse range of projects. This |
| 91 | + provides an enormous dataset for training AI models, leading to excellent |
| 92 | + AI-assisted development. |
| 93 | +- **Community and Contributor Pool**: Excellent. Python has a massive, active, and welcoming |
| 94 | + community. This makes it easy to find help, libraries, and potential |
| 95 | + contributors. |
| 96 | +- **Downsides**: It's dynamically typed, which can lead to runtime errors. |
| 97 | + Performance is lower than compiled languages, but this is rarely a |
| 98 | + bottleneck for orchestration scripts. |
| 99 | + |
| 100 | +### 2. Go (Golang) |
| 101 | + |
| 102 | +- **Score**: ⭐⭐⭐⭐ (Very Good) |
| 103 | +- **Testing**: Very Good. Testing is a first-class citizen, built into the |
| 104 | + toolchain. It's simple to write unit tests, benchmarks, and examples. |
| 105 | + Table-driven tests are a common and effective pattern. |
| 106 | +- **Libraries**: Very Good. |
| 107 | + - **Cloud SDKs**: Official and well-maintained SDKs for all major cloud |
| 108 | + providers. |
| 109 | + - **OpenTofu**: **Excellent support**. Go is the native language of |
| 110 | + Terraform, OpenTofu, Packer, and most HashiCorp tools. The official |
| 111 | + provider development kits are in Go. |
| 112 | + - **Parsing**: Excellent support for JSON, YAML, and TOML. |
| 113 | +- **Extensibility**: Very good. Interfaces and packages provide a solid |
| 114 | + foundation for building extensible systems. |
| 115 | +- **Adoption**: **The standard for cloud-native tools**. Docker, Kubernetes, |
| 116 | + Prometheus, and Terraform are all written in Go. This is its biggest |
| 117 | + strength. |
| 118 | +- **Developer Experience**: Very good. The language is simple, compilation is |
| 119 | + fast, and it produces a single, statically-linked binary, which simplifies |
| 120 | + deployment immensely. |
| 121 | +- **Public Codebase Availability**: Very Good. Go is prevalent in the cloud-native space, |
| 122 | + with many high-profile open-source projects (Docker, Kubernetes, etc.) |
| 123 | + providing a rich source of high-quality code for AI training. |
| 124 | +- **Community and Contributor Pool**: Very Good. Go has a strong and growing community, |
| 125 | + particularly in the infrastructure and backend development space. |
| 126 | +- **Downsides**: Error handling can be verbose (`if err != nil`). The lack of |
| 127 | + generics in older versions was a pain point, but this has been addressed. |
| 128 | + |
| 129 | +### 3. Rust |
| 130 | + |
| 131 | +- **Score**: ⭐⭐⭐ (Good) |
| 132 | +- **Testing**: Good. The testing framework is built-in and supports unit and |
| 133 | + integration tests. However, it's generally more verbose than Python's or |
| 134 | + Go's. |
| 135 | +- **Libraries**: Good, but less mature for high-level orchestration compared |
| 136 | + to Python and Go. |
| 137 | + - **Templates**: `Tera` (a Jinja2-like engine) and `Handlebars` are |
| 138 | + available. |
| 139 | + - **OpenTofu**: No mature libraries. Interacting with OpenTofu would |
| 140 | + likely require wrapping the CLI. |
| 141 | +- **Extensibility**: Excellent. Traits and enums make for a very powerful and |
| 142 | + safe plugin system. |
| 143 | +- **Adoption**: Growing, but not a mainstream choice for DevOps tooling yet. |
| 144 | + The learning curve is steep. |
| 145 | +- **Developer Experience**: Good, but can be challenging. The borrow checker, |
| 146 | + while providing safety, adds complexity that may not be necessary for |
| 147 | + orchestration scripts. |
| 148 | +- **Public Codebase Availability**: Good. The amount of public Rust code is growing |
| 149 | + rapidly, especially in systems programming, web assembly, and CLI tools. |
| 150 | + The quality is generally high. |
| 151 | +- **Community and Contributor Pool**: Very Good. Rust has a passionate, helpful, and rapidly |
| 152 | + growing community. |
| 153 | +- **Downsides**: Steep learning curve. The focus on safety and performance is |
| 154 | + often overkill for high-level automation scripts. |
| 155 | + |
| 156 | +### 4. Perl |
| 157 | + |
| 158 | +- **Score**: ⭐⭐ (Fair) |
| 159 | +- **Suitability**: Perl is a powerful and mature language, often praised for its |
| 160 | + text-processing capabilities. It was a de-facto standard for system |
| 161 | + administration and web development (CGI scripts) for many years. However, its |
| 162 | + popularity has declined, and it's often considered a legacy language. |
| 163 | +- **Ecosystem**: The Comprehensive Perl Archive Network (CPAN) is vast but can |
| 164 | + be difficult to navigate. Many libraries are old and may not be actively |
| 165 | + maintained. |
| 166 | +- **Extensibility**: Good. Perl's module system is powerful, but the syntax |
| 167 | + can be dense and difficult to read, making it less approachable for new |
| 168 | + contributors. |
| 169 | +- **Adoption**: Low for new projects. It's still used in many legacy |
| 170 | + systems, but it's rarely chosen for new toolchains. |
| 171 | +- **Developer Experience**: Fair. Perl's "There's more than one way to do |
| 172 | + it" (TMTOWTDI) philosophy can lead to code that is difficult to read and |
| 173 | + maintain. The syntax is often criticized for being "write-only." |
| 174 | +- **Public Codebase Availability**: Good. The Comprehensive Perl Archive Network (CPAN) |
| 175 | + is one of the oldest and largest code repositories. However, much of the |
| 176 | + code is legacy, which might be less relevant for modern AI training. |
| 177 | +- **Community and Contributor Pool**: Fair. While the core community is dedicated, it is much |
| 178 | + smaller and less active in new projects compared to Python, Go, or Rust. |
| 179 | +- **Downsides**: The syntax is complex and often considered "ugly." The |
| 180 | + community is smaller and less active than for other languages. Finding |
| 181 | + developers with Perl experience can be difficult. |
| 182 | + |
| 183 | +### 5. Shell Scripting (Baseline) |
| 184 | + |
| 185 | +- **Score**: ⭐ (Poor) |
| 186 | +- **Testing**: Poor. Testing shell scripts is notoriously difficult. Tools |
| 187 | + like `shellcheck` help, but robust testing requires significant effort. |
| 188 | +- **Libraries**: N/A. Relies on system binaries (`curl`, `jq`, `sed`, `awk`). |
| 189 | +- **Extensibility**: Poor. Extending shell scripts is manual and error-prone. |
| 190 | +- **Adoption**: Ubiquitous, but not ideal for complex logic. |
| 191 | +- **Developer Experience**: Poor for anything beyond simple scripts. Lack of |
| 192 | + modern language features makes it hard to maintain. |
| 193 | +- **Public Codebase**: Good. Countless shell scripts are available online, but |
| 194 | + they often lack standardization, documentation, and quality control, making |
| 195 | + reuse difficult. |
| 196 | +- **Community and Contributor Pool**: Excellent. The user base is massive, but it is not a |
| 197 | + formal community. Finding skilled contributors for a structured project can |
| 198 | + be challenging. |
| 199 | +- **Downsides**: Error handling is fragile, and it's easy to write |
| 200 | + unmaintainable code. Not suitable for building a robust, extensible |
| 201 | + toolchain. |
| 202 | + |
| 203 | +## Decision |
| 204 | + |
| 205 | +**Go** is the recommended language for the new Torrust Tracker automation |
| 206 | +toolchain. |
| 207 | + |
| 208 | +## Rationale |
| 209 | + |
| 210 | +While Python is an extremely strong contender and would also be a valid choice, |
| 211 | +**Go's unparalleled alignment with the modern cloud-native and Infrastructure |
| 212 | +as Code ecosystem makes it the superior choice for this specific project.** |
| 213 | + |
| 214 | +1. **Native IaC Ecosystem**: Terraform, OpenTofu, Packer, and nearly all major |
| 215 | + cloud-native tools are written in Go. By using Go, we are aligning with the |
| 216 | + language of the tools we are automating. This provides access to the best |
| 217 | + SDKs, libraries, and community expertise. We can directly use the same |
| 218 | + libraries that OpenTofu providers use. |
| 219 | +2. **Single Binary Deployment**: Go compiles to a single, statically-linked |
| 220 | + binary with no external dependencies. This dramatically simplifies the |
| 221 | + deployment and distribution of our new installer. We can ship a single file |
| 222 | + that runs on any target system, without worrying about Python versions, |
| 223 | + virtual environments, or dependency conflicts. |
| 224 | +3. **Performance and Concurrency**: While performance is not the primary |
| 225 | + concern, Go's efficiency and built-in support for concurrency are |
| 226 | + significant advantages. This will be beneficial for running tasks in |
| 227 | + parallel, such as provisioning multiple resources or checking multiple |
| 228 | + endpoints simultaneously. |
| 229 | +4. **Static Typing and Simplicity**: Go's static typing catches many errors at |
| 230 | + compile time, a significant improvement over shell scripts and Python. Its |
| 231 | + simplicity and small number of language features make it easy to learn and |
| 232 | + maintain, which is crucial for an open-source project with many |
| 233 | + contributors. |
| 234 | +5. **Strong Standard Library**: Go's standard library is excellent for |
| 235 | + building command-line tools and network services, covering most of our needs |
| 236 | + without requiring numerous third-party dependencies. |
| 237 | + |
| 238 | +While Rust is the language of the main Torrust project, it is not the best fit |
| 239 | +for this high-level orchestration tool. The complexity and development |
| 240 | +overhead of Rust are not justified for a tool that primarily glues together |
| 241 | +other processes and APIs. Using Go for tooling and Rust for the core tracker |
| 242 | +application is a common and effective polyglot strategy, playing to the |
| 243 | +strengths of each language. |
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