Scala2
Scala2是一款code方向的AI技能,核心价值是Scala 2,可用于解决开发者在code领域的实际问题,帮助用户提升效率、自动化重复任务或优化工作流。
Scala 2.12/2.13 programming language coding conventions and best practices following Databricks style guide for functional programming, type safety, and production code quality.
mkdir -p ./skills/scala2 && curl -sfL https://raw.githubusercontent.com/github/awesome-copilot/main/skills/scala2/SKILL.md -o ./skills/scala2/SKILL.md Run in terminal / PowerShell. Requires curl (Unix) or PowerShell 5+ (Windows).
Skill Content
# Scala Best Practices
Based on the [Databricks Scala Style Guide](https://github.com/databricks/scala-style-guide)
Core Principles
Write Simple Code
Code is written once but read and modified multiple times. Optimize for long-term readability and maintainability by writing simple code.
Immutability by Default
- Always prefer `val` over `var`
- Use immutable collections from `scala.collection.immutable`
- Case class constructor parameters should NOT be mutable
- Use copy constructor to create modified instances
// Good - Immutable case class
case class Person(name: String, age: Int)
// Bad - Mutable case class
case class Person(name: String, var age: Int)
// To change values, use copy constructor
val p1 = Person("Peter", 15)
val p2 = p1.copy(age = 16)
// Good - Immutable collections
val users = List(User("Alice", 30), User("Bob", 25))
val updatedUsers = users.map(u => u.copy(age = u.age + 1))Pure Functions
- Functions should be deterministic and side-effect free
- Separate pure logic from effects
- Use explicit types for methods with effects
// Good - Pure function
def calculateTotal(items: List[Item]): BigDecimal =
items.map(_.price).sum
// Bad - Impure function with side effects
def calculateTotal(items: List[Item]): BigDecimal = {
println(s"Calculating total for ${items.size} items") // Side effect
val total = items.map(_.price).sum
saveToDatabase(total) // Side effect
total
}Naming Conventions
Classes and Objects
// Classes, traits, objects - PascalCase
class ClusterManager
trait Expression
object Configuration
// Packages - all lowercase ASCII
package com.databricks.resourcemanager
// Methods/functions - camelCase
def getUserById(id: Long): Option[User]
def processData(input: String): Result
// Constants - uppercase in companion object
object Configuration {
val DEFAULT_PORT = 10000
val MAX_RETRIES = 3
val TIMEOUT_MS = 5000L
}Variables and Parameters
// Variables - camelCase, self-evident names
val serverPort = 1000
val clientPort = 2000
val maxRetryAttempts = 3
// One-character names OK in small, localized scope
for (i <- 0 until 10) {
// ...
}
// Do NOT use "l" (Larry) - looks like "1", "|", "I"Enumerations
// Enumeration object - PascalCase
// Values - UPPER_CASE with underscores
private object ParseState extends Enumeration {
type ParseState = Value
val PREFIX,
TRIM_BEFORE_SIGN,
SIGN,
VALUE,
UNIT_BEGIN,
UNIT_END = Value
}Syntactic Style
Line Length and Spacing
// Limit lines to 100 characters
// One space before and after operators
def add(int1: Int, int2: Int): Int = int1 + int2
// One space after commas
val list = List("a", "b", "c")
// One space after colons
def getConf(key: String, defaultValue: String): String = {
// code
}
// Use 2-space indentation
if (true) {
println("Wow!")
}
// 4-space indentation for long parameter lists
def newAPIHadoopFile[K, V, F <: NewInputFormat[K, V]](
path: String,
fClass: Class[F],
kClass: Class[K],
vClass: Class[V],
conf: Configuration = hadoopConfiguration): RDD[(K, V)] = {
// method body
}
// Class with long parameters
class Foo(
val param1: String, // 4 space indent
val param2: String,
val param3: Array[Byte])
extends FooInterface // 2 space indent
with Logging {
def firstMethod(): Unit = { ... } // blank line above
}Rule of 30
- A method should contain less than 30 lines of code
- A class should contain less than 30 methods
Curly Braces
// Always use curly braces for multi-line blocks
if (true) {
println("Wow!")
}
// Exception: one-line ternary (side-effect free)
val result = if (condition) value1 else value2
// Always use braces for try-catch
try {
foo()
} catch {
case e: Exception => handle(e)
}Long Literals
// Use uppercase L for long literals
val longValue = 5432L // Do this🎯 Best For
- UI designers
- Product designers
- Claude users
- GitHub Copilot users
- Software engineers
💡 Use Cases
- Generating component mockups
- Creating design system tokens
- Code quality improvement
- Best practice enforcement
📖 How to Use This Skill
- 1
Install the Skill
Copy the install command from the Terminal tab and run it. The SKILL.md file downloads to your local skills directory.
- 2
Load into Your AI Assistant
Open Claude or GitHub Copilot and reference the skill. Paste the SKILL.md content or use the system prompt tab.
- 3
Apply Scala2 to Your Work
Open your project in the AI assistant and ask it to apply the skill. Start with a small module to verify the output quality.
- 4
Review and Refine
Review AI suggestions before committing. Run tests, check for regressions, and iterate on the skill output.
❓ Frequently Asked Questions
Does this work with Figma?
Some design skills integrate with Figma plugins. Check the Works With section for supported tools.
Is Scala2 compatible with Cursor and VS Code?
Yes — this skill works with any AI coding assistant including Cursor, VS Code with Copilot, and JetBrains IDEs.
Do I need specific dependencies for Scala2?
Check the install command and Works With section. Most code skills only require the AI assistant and your codebase.
How do I install Scala2?
Copy the install command from the Terminal tab and run it. The skill downloads to ./skills/scala2/SKILL.md, ready to use.
Can I customize this skill for my team?
Absolutely. Edit the SKILL.md file to add team-specific instructions, examples, or workflows.
⚠️ Common Mistakes to Avoid
Skipping usability testing
AI-generated designs should be validated with real users before development.
Skipping validation
Always test AI-generated code changes, even for simple refactors.
Missing dependency updates
Check if the skill requires updated dependencies or new packages.