Major Cloud Providers

# مقارنة مزودي السحاب وأداة التوصية — Cloud Provider Recommender
from dataclasses import dataclass, field

@dataclass
class CloudProvider:
    name: str
    short: str
    icon: str
    market_share: float
    strengths: list[str]
    ai_services: list[str]
    free_tier_highlights: list[str]
    keywords: list[str]
    monthly_estimate_usd: float

PROVIDERS = [
    CloudProvider(
        name="Amazon Web Services", short="AWS", icon="🟠",
        market_share=32.0,
        strengths=["200+ خدمة", "أكبر مجتمع", "33+ منطقة", "Free Tier سخي"],
        ai_services=["SageMaker", "Bedrock (Claude/GPT)", "Rekognition", "Comprehend"],
        free_tier_highlights=["EC2 750h", "S3 5GB", "Lambda 1M calls", "SageMaker 250h"],
        keywords=["startup", "عام", "general", "serverless", "e-commerce"],
        monthly_estimate_usd=50.0,
    ),
    CloudProvider(
        name="Microsoft Azure", short="Azure", icon="🔵",
        market_share=23.0,
        strengths=["تكامل Microsoft 365", "Compliance مؤسسي", "Azure OpenAI", "Hybrid Cloud"],
        ai_services=["Azure OpenAI", "Cognitive Services", "Azure ML", "AI Foundry"],
        free_tier_highlights=["VMs 750h", "Storage 5GB", "Azure Functions 1M"],
        keywords=["enterprise", "مؤسسة", "microsoft", ".net", "hybrid"],
        monthly_estimate_usd=65.0,
    ),
    CloudProvider(
        name="Google Cloud Platform", short="GCP", icon="🔴",
        market_share=12.0,
        strengths=["الأقوى في AI Research", "BigQuery رائد", "TPUs", "Kubernetes الأصل"],
        ai_services=["Vertex AI", "Gemini API", "AutoML", "Cloud Vision", "BigQuery ML"],
        free_tier_highlights=["Compute 1 e2-micro", "GCS 5GB", "BigQuery 1TB/mo"],
        keywords=["ai", "ml", "data", "bigquery", "analytics", "gemini", "vertex", "kubernetes"],
        monthly_estimate_usd=55.0,
    ),
]

def print_provider(p: CloudProvider):
    print(f"\n{p.icon} {p.name} ({p.short})")
    print(f"   حصة السوق: {p.market_share}%")
    print(f"   نقاط القوة: {' | '.join(p.strengths[:2])}")
    print(f"   خدمات AI: {', '.join(p.ai_services[:3])}")
    print(f"   Free Tier: {' | '.join(p.free_tier_highlights[:2])}")
    bar = "█" * int(p.market_share / 2)
    print(f"   الحصة:     [{bar:<16}] {p.market_share}%")

def recommend(use_case: str) -> CloudProvider:
    """توصية بأفضل مزود حسب حالة الاستخدام"""
    scores = {p.short: 0.0 for p in PROVIDERS}
    uc = use_case.lower()
    for p in PROVIDERS:
        for kw in p.keywords:
            if kw in uc:
                scores[p.short] += 3
    # AWS افتراضي للحالات العامة
    if max(scores.values()) == 0:
        scores["AWS"] = 1
    best = max(scores, key=lambda k: scores[k])
    return next(p for p in PROVIDERS if p.short == best)

# ─── عرض كل المزودين ─────────────────────────────────────
print("☁️  مزودو السحاب الكبار")
print("="*55)
for p in PROVIDERS:
    print_provider(p)

# ─── مقارنة مباشرة ───────────────────────────────────────
print(f"\n{'='*55}")
print(f"{'المعيار':<22} {'AWS':^10} {'Azure':^10} {'GCP':^10}")
print(f"{'─'*55}")

criteria = [
    ("حصة السوق",    "32%",    "23%",    "12%"),
    ("للـ AI/ML",    "ممتاز", "ممتاز",  "الأقوى"),
    ("للمؤسسات",    "✅",      "✅✅",    "✅"),
    ("Free Tier",    "⭐⭐⭐",   "⭐⭐",    "⭐⭐"),
    ("Kubernetes",   "EKS",    "AKS",    "GKE ✅"),
    ("تكلفة/شهر",   "$50",    "$65",    "$55"),
]
for row in criteria:
    print(f"{row[0]:<22} {row[1]:^10} {row[2]:^10} {row[3]:^10}")

# ─── أداة التوصية ────────────────────────────────────────
print(f"\n{'='*55}")
print("🎯 توصيات حسب حالة الاستخدام:")
print("="*55)

use_cases = [
    "بناء نموذج AI وتحليل بيانات ضخمة مع BigQuery",
    "تطبيق مؤسسي يعتمد على Microsoft 365 والـ Azure",
    "متجر إلكتروني startup مع serverless functions",
]

for uc in use_cases:
    rec = recommend(uc)
    print(f"\n📌 {uc[:50]}")
    print(f"   التوصية: {rec.icon} {rec.name}")
    print(f"   السبب: {rec.strengths[0]}")