Add API Caching to API documentation #2738
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Actionable comments posted: 2
🧹 Outside diff range and nitpick comments (5)
apps/www/content/glossary/api-caching.mdx (5)
6-6: Consider adding relevant categoriesThe
categoriesarray is currently empty. Consider adding relevant categories such as "Performance", "Optimization", or "Infrastructure" to improve content discoverability.
63-63: Consider rephrasing for clarityThe sentence could be more concise. Consider: "This decreases latency and alleviates server load, which is essential for improving user experience and efficiently handling high traffic."
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[style] ~63-~63: Opting for a less wordy alternative here can improve the clarity of your writing.
Context: ...lls made to the actual API server. This not only decreases latency but also alleviates server load, which is essential for imp...(NOT_ONLY_ALSO)
75-82: Consider adding rate limiting best practicesThe best practices section is comprehensive, but consider adding information about implementing rate limiting alongside caching to prevent cache stampedes and protect your API from abuse.
83-150: Add cache eviction policy documentationThe code examples would benefit from comments explaining cache eviction policies and memory management strategies. Consider adding documentation about:
- Time-based eviction
- Size-based eviction
- LRU/LFU policies
- Memory limits
152-152: Consider rephrasing for clarityThe sentence could be more concise. Consider: "Implementing these strategies enhances API performance and ensures a better user experience, especially during peak traffic periods."
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[style] ~152-~152: Opting for a less wordy alternative here can improve the clarity of your writing.
Context: ...mes. Implementing these strategies will not only enhance the performance of your APIs but also ensure a better experience for users, especial...(NOT_ONLY_ALSO)
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apps/www/content/glossary/api-caching.mdx(1 hunks)
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apps/www/content/glossary/api-caching.mdx
[style] ~63-~63: Opting for a less wordy alternative here can improve the clarity of your writing.
Context: ...lls made to the actual API server. This not only decreases latency but also alleviates server load, which is essential for imp...
(NOT_ONLY_ALSO)
[style] ~152-~152: Opting for a less wordy alternative here can improve the clarity of your writing.
Context: ...mes. Implementing these strategies will not only enhance the performance of your APIs but also ensure a better experience for users, especial...
(NOT_ONLY_ALSO)
| #include <unordered_map> | ||
| std::unordered_map<std::string, Product> productCache; | ||
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| Product getProductById(const std::string& id) { | ||
| if (productCache.find(id) != productCache.end()) { | ||
| return productCache[id]; // Return cached data | ||
| } else { | ||
| Product product = fetchProductById(id); // Fetch from DB or API | ||
| productCache[id] = product; // Cache it | ||
| return product; | ||
| } | ||
| } | ||
| ``` |
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Add thread safety to C++ example
The current C++ implementation using std::unordered_map is not thread-safe. Consider using a mutex or a thread-safe cache implementation.
Here's a thread-safe version:
#include <unordered_map>
#include <mutex>
class ProductCache {
private:
std::unordered_map<std::string, Product> cache;
mutable std::mutex mutex;
public:
Product getProductById(const std::string& id) {
{
std::lock_guard<std::mutex> lock(mutex);
auto it = cache.find(id);
if (it != cache.end()) {
return it->second;
}
}
Product product = fetchProductById(id);
{
std::lock_guard<std::mutex> lock(mutex);
cache[id] = product;
}
return product;
}
};| @app.route('/product/<id>') | ||
| @cache.cached(timeout=50, key_prefix='product_') | ||
| def get_product(id): | ||
| # Code to fetch product | ||
| return product | ||
| ``` |
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🛠️ Refactor suggestion
Add error handling to Python example
The Python example should include error handling and logging for cache misses or failures.
Here's an improved version:
from flask import Flask, jsonify
from flask_caching import Cache
import logging
app = Flask(__name__)
cache = Cache(app, config={'CACHE_TYPE': 'simple'})
logger = logging.getLogger(__name__)
@app.route('/product/<id>')
@cache.cached(timeout=50, key_prefix='product_')
def get_product(id):
try:
product = fetch_product(id) # Your fetch logic here
return jsonify(product)
except Exception as e:
logger.error(f"Error fetching product {id}: {str(e)}")
return jsonify({"error": "Failed to fetch product"}), 500
This PR adds the API Caching.mdx file to the API documentation.
Summary by CodeRabbit
New Features
Documentation