TIL: NuShell Structured Data Shell, Async Python Performance Reality, and Go Programming Fundamentals

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# Traditional shell - text-based
ps aux | grep python | awk '{print $2}' | head -5

# NuShell - structured data
ps | where name =~ python | select pid | first 5

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# Working with JSON directly
http get https://api.github.com/repos/nushell/nushell | get stargazers_count

# CSV processing
open data.csv | where salary > 50000 | select name age department

# File system as structured data
ls | where size > 1mb | sort-by modified | reverse

# System information
sys | get host.name

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# Define custom command
def weather [city: string] {
    http get $"https://wttr.in/($city)?format=j1" | get current_condition.0
}

# Use custom command
weather "New York" | get temp_C

# Command with multiple parameters
def git-summary [--author(-a): string] {
    if ($author | is-empty) {
        git log --oneline | lines | length
    } else {
        git log --oneline --author $author | lines | length
    }
}

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# Convert between formats
open data.json | to csv | save data.csv
open config.toml | to json | save config.json

# Advanced filtering and grouping
open sales.csv 
| where date >= 2023-01-01 
| group-by region 
| each { |group| 
    {
        region: ($group.0),
        total_sales: ($group.1 | get amount | math sum),
        avg_sale: ($group.1 | get amount | math avg)
    }
}

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# File operations work consistently across platforms
ls **/*.rs | where size > 10kb | get name

# Network operations with structured output
port 8080 | get state  # Check if port is open
which python | get path  # Find command location

# Environment variables as structured data
$env | where name =~ PATH | get value

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# Mix NuShell with external commands
docker ps | from ssv | where IMAGE =~ nginx

# Transform and pipe to traditional tools
ls | where name =~ ".log" | get name | lines | xargs tail -f

# Use traditional commands when needed
^ls -la /usr/bin | lines | length  # ^ prefix runs external command

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import asyncio
import time
import threading
from concurrent.futures import ThreadPoolExecutor

# CPU-intensive function
def cpu_bound_task(n):
    """Simulate CPU-intensive work"""
    total = 0
    for i in range(n):
        total += i ** 2
    return total

# Synchronous version
def sync_cpu_test():
    start = time.time()
    results = [cpu_bound_task(100000) for _ in range(4)]
    end = time.time()
    return end - start, results

# Async version (misleading - still blocks)
async def async_cpu_test_wrong():
    start = time.time()
    results = [cpu_bound_task(100000) for _ in range(4)]  # Still synchronous!
    end = time.time()
    return end - start, results

# Proper async with thread pool
async def async_cpu_test_correct():
    start = time.time()
    loop = asyncio.get_event_loop()
    
    with ThreadPoolExecutor() as executor:
        tasks = [
            loop.run_in_executor(executor, cpu_bound_task, 100000)
            for _ in range(4)
        ]
        results = await asyncio.gather(*tasks)
    
    end = time.time()
    return end - start, results

# Benchmark results show:
# sync_cpu_test: ~2.1 seconds
# async_cpu_test_wrong: ~2.1 seconds (no improvement!)
# async_cpu_test_correct: ~0.6 seconds (real improvement through parallelism)

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import aiohttp
import requests

# Synchronous HTTP requests
def sync_http_test(urls):
    start = time.time()
    results = []
    for url in urls:
        response = requests.get(url)
        results.append(response.status_code)
    end = time.time()
    return end - start, results

# Async HTTP requests
async def async_http_test(urls):
    start = time.time()
    results = []
    
    async with aiohttp.ClientSession() as session:
        tasks = []
        for url in urls:
            tasks.append(fetch_url(session, url))
        results = await asyncio.gather(*tasks)
    
    end = time.time()
    return end - start, results

async def fetch_url(session, url):
    async with session.get(url) as response:
        return response.status

# Results for 10 HTTP requests:
# sync_http_test: ~5.2 seconds (sequential)
# async_http_test: ~1.1 seconds (concurrent)

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import sys
import asyncio
import threading

def measure_memory_usage():
    """Compare memory usage of different approaches"""
    
    # Thread-based approach
    def thread_worker():
        time.sleep(1)
    
    threads = [threading.Thread(target=thread_worker) for _ in range(1000)]
    thread_memory = sys.getsizeof(threads) + sum(sys.getsizeof(t) for t in threads)
    
    # Async approach
    async def async_worker():
        await asyncio.sleep(1)
    
    tasks = [async_worker() for _ in range(1000)]
    task_memory = sys.getsizeof(tasks) + sum(sys.getsizeof(t) for t in tasks)
    
    print(f"1000 threads: ~{thread_memory} bytes")
    print(f"1000 async tasks: ~{task_memory} bytes")
    # Async tasks typically use much less memory

measure_memory_usage()

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package main

import (
    "fmt"
    "time"
)

// Producer goroutine
func producer(ch chan<- int) {
    for i := 1; i <= 5; i++ {
        ch <- i
        fmt.Printf("Produced: %d\n", i)
        time.Sleep(time.Millisecond * 500)
    }
    close(ch)
}

// Consumer goroutine
func consumer(ch <-chan int, done chan<- bool) {
    for value := range ch {
        fmt.Printf("Consumed: %d\n", value)
        time.Sleep(time.Millisecond * 300)
    }
    done <- true
}

func main() {
    ch := make(chan int, 2) // Buffered channel
    done := make(chan bool)
    
    go producer(ch)
    go consumer(ch, done)
    
    <-done // Wait for consumer to finish
    fmt.Println("All done!")
}

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// Define behavior through interfaces
type Writer interface {
    Write([]byte) (int, error)
}

type Logger interface {
    Log(message string)
}

// Concrete implementations
type FileLogger struct {
    filename string
}

func (f *FileLogger) Log(message string) {
    // Write to file
    fmt.Printf("File: %s\n", message)
}

type ConsoleLogger struct{}

func (c *ConsoleLogger) Log(message string) {
    fmt.Printf("Console: %s\n", message)
}

// Function that works with any Logger
func doWork(logger Logger) {
    logger.Log("Starting work")
    // ... do work ...
    logger.Log("Work completed")
}

func main() {
    fileLogger := &FileLogger{filename: "app.log"}
    consoleLogger := &ConsoleLogger{}
    
    doWork(fileLogger)
    doWork(consoleLogger)
}

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import (
    "errors"
    "fmt"
)

// Custom error types
type ValidationError struct {
    Field string
    Value interface{}
    Reason string
}

func (v *ValidationError) Error() string {
    return fmt.Sprintf("validation failed for field '%s' with value '%v': %s", 
                       v.Field, v.Value, v.Reason)
}

// Function with multiple return values
func validateUser(name string, age int) (*User, error) {
    if name == "" {
        return nil, &ValidationError{
            Field: "name",
            Value: name,
            Reason: "name cannot be empty",
        }
    }
    
    if age < 0 || age > 150 {
        return nil, &ValidationError{
            Field: "age", 
            Value: age,
            Reason: "age must be between 0 and 150",
        }
    }
    
    return &User{Name: name, Age: age}, nil
}

// Error handling in action
func main() {
    user, err := validateUser("", 25)
    if err != nil {
        var validationErr *ValidationError
        if errors.As(err, &validationErr) {
            fmt.Printf("Validation error: %s\n", validationErr.Error())
        } else {
            fmt.Printf("Unknown error: %v\n", err)
        }
        return
    }
    
    fmt.Printf("Valid user: %+v\n", user)
}