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Hello friends! |
Welcome to this week’s Sloth Bytes. I hope you had a great week. |
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Message Queues |
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When I first heard about message queues, I thought they were one of those “enterprise things” that only engineers at Google or Amazon cared about. |
And honestly? I wasn’t wrong. |
You rarely need a message queue for a hobby project or a small side app. |
When you’re the only user, you don’t exactly need a system built to handle millions of requests per second. |
So why should I even care then? |
Fair question. |
Even if you’re not building at that level yet, understanding how message queues work prepares you for the moment you are. |
At some point in your career, you’ll either build something that grows faster than expected, or you’ll join a team managing systems that already handle massive scale. |
And when that happens, you’ll know how to keep things running smoothly. |
So let’s break down what message queues actually do, how they work, and why they keep big systems from melting down. |
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What is a Message Queue? |
A message queue is a system that allows different parts of an application to communicate asynchronously. |
Instead of one service waiting for another to finish, a queue acts as a buffer in between. |
It holds messages until another part of the system is ready to process them. |
Think of it like a restaurant: |
Waiter takes your order Order is put in a queue Chefs work on the order Waiters pick them up when ready.
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If something happens to the chefs and there’s a delay or even failure, new orders can still come in. |
The restaurant never stops running because that queue acts as a buffer between the waiter and chef. |
That’s exactly what message queues do for large systems. They keep everything flowing, even when something slows down. |
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Key Components Of A Message Queue |
Component | Role |
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Producer/Publisher | Creates and sends messages | Queue | Holds messages until they’re processed | Consumer/Subscriber | Retrieves and processes messages | Message Broker (optional but common) | Routes, filters, or transforms messages between producers and consumers (e.g., RabbitMQ, Kafka) | Acknowledgement/ACKs (optional but recommended) | Confirm success so the broker can safely delete the message. | The Message! | contains the payload and headers |
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A single queue can have multiple producers and multiple consumers, all working independently. |
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How Message Queues Work |
Here’s the basic flow of a message queue: |
Producer creates a message and sends it to the queue. Queue stores the message safely until someone’s ready to process it. Consumer retrieves the message and processes it when it can. (Optional) Acknowledgment/ACK: Once done, the consumer tells the queue, “I got it.”
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That’s it! Simple but powerful. |
Instead of breaking under heavy load, message queues let every part of your system move at its own pace without losing a single message. |
A Tiny Example |
Here’s a minimal Python example using the built-in queue module. No broker, just showing the flow: |
import queue
import threading
import time
# Create a queue
q = queue.Queue()
# Producer
def producer():
for i in range(5):
message = f"Task {i}"
print(f"🦥 Producing: {message}")
q.put(message)
time.sleep(0.5)
# Consumer
def consumer():
while True:
message = q.get()
print(f"⚙️ Consuming: {message}")
time.sleep(1)
q.task_done()
# Start threads
threading.Thread(target=producer).start()
threading.Thread(target=consumer, daemon=True).start()
q.join()
print("âś… All messages processed!")
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This little demo shows the same pattern big systems use: |
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If you’re curious how it works with a message broker, rabbitmq has a great hello world section! |
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What exactly is the “message?” |
Messages usually have two parts: |
Headers (metadata): unique ID, timestamp, routing info, message type. Body (payload): the actual content (JSON, binary data, or text)
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It’s basically a shared to-do list. |
Is there specific ways to write the “message?” |
Yep! Message queues have communication protocols/standards. |
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You don’t have to memorize them, but it’s good to know how messages are structured, delivered, and acknowledged between systems. |
What happens if the message fails? |
When a consumer picks up a message but something goes wrong, the message doesn’t just disappear (thankfully). |
Here’s what usually happens depending on how your queue and broker are configured: |
⚰️ 1. Dead Letter Queues (DLQs) |
A DLQ is basically a graveyard for problematic messages. |
If a message keeps failing, it gets sent here instead of clogging the main queue.
You can later inspect these failed messages, fix the issue, and requeue them manually. |
Example uses: |
Log bad messages for debugging. Alert the dev team when the DLQ starts filling up. Trigger automated retries or cleanup scripts.
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2. No Acknowledgment (NACK) |
If the consumer doesn’t send an ACK (acknowledgment), the broker assumes the message wasn’t processed successfully, or is a NACK (negative acknowledgement.) |
Depending on the setup, it’ll do one of two things: |
Retry: Put the message back in the queue to try again later. Dead Letter Queue (DLQ): If it’s failed too many times, move it to a special queue just for failed messages.
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RabbitMQ, SQS, and Kafka all support this kind of behavior. |
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Why Big Companies Love Them |
Asynchronous Communication: Systems can keep running without waiting on each other. Decoupling: Each service can be developed and scaled independently. Scalability Reliability: messages are stored, retried, and never lost. Workflow Management: perfect for multi-step pipelines like e-commerce, payments, or streaming data.
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You might not need a message queue today, but understanding them changes how you think about building systems. |
They’re not just for “big companies”, they’re what make big companies possible. |
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Interested in learning more? |
Check out these useful resources: |
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If you want me to go more in-depth for these topics, let me know! |
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Thanks to everyone who submitted! |
TokugawaBonaparte, OneDollarCat, ipaixaol, grcc492, Siddhesh-Ballal, gcavelier, Yeshua235, Mansi090, Vimalmr, AspenTheRoyal, NeoScripter, s4ngyeonpark, Suji-droid, and alfalconetti! |
Phone Number Letter Combinations |
Given a string of digits (from '2' to '9'), return all possible letter combinations that the digits could represent, using the mapping on a telephone keypad: |
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If the input is an empty string, return an empty list. |
You may return the results in any order. |
Examples |
def letterCombinations("23")
output = ["ad","ae","af","bd","be","bf","cd","ce","cf"]
def letterCombinations("")
output = []
def letterCombinations("2")
output = ["a","b","c"]
def letterCombinations("27")
output = ["ap","aq","ar","as","bp","bq","br","bs","cp","cq","cr","cs"]
def letterCombinations("234")
output = [
"adg","adh","adi","aeg","aeh","aei","afg","afh","afi",
"bdg","bdh","bdi","beg","beh","bei","bfg","bfh","bfi",
"cdg","cdh","cdi","ceg","ceh","cei","cfg","cfh","cfi"
]
def letterCombinations("79")
output = [ "pw","px","py","pz","qw","qx","qy","qz", "rw","rx","ry","rz", "sw","sx","sy","sz"]
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How To Submit Answers |
Reply with |
A link to your solution (github, twitter, personal blog, portfolio, replit, etc) or if you’re on the web version leave a comment! If you want to be mentioned here, I’d prefer if you sent a GitHub link or Replit!
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That’s all from me! |
Have a great week, be safe, make good choices, and have fun coding. |
If I made a mistake or you have any questions, feel free to comment below or reply to the email! |
See you all next week. |
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