Understanding async, await, and Concurrency#
Understanding async, await, and Concurrency in Python — A Simple Tutorial
If you’re learning Python and find terms like async, await, and concurrent tasks confusing — you’re not alone! This tutorial explains how to write Python code that runs multiple tasks simultaneously, such as reading data from the internet, analyzing logs, and fetching records from a remote server.
Let’s walk through a real-world example.
Problem Scenario#
Imagine you work at a company that:
- Reads content from its company website
- Analyzes yesterday’s webserver logs
- Retrieves client information from a remote SAP server
- Then sends a report email to the clients
All these actions involve waiting — for internet access, file I/O, or server responses. If we run them one-by-one (synchronously), it could take over 40 minutes.
Instead, we’ll use Python’s asynchronous capabilities to do these tasks concurrently and finish everything in just 23 minutes.
🧠 What You’ll Learn#
- What
asyncandawaitmean in Python - How to run multiple tasks at once with
asyncio.create_task() - How
asyncio.gather()helps you wait for multiple tasks - Why this pattern saves time in I/O-heavy operations
🔧 Step-by-Step Async Python Example#
import asyncio
# 🕸️ 1. Async function to read from company website
async def read_some_content_from_internet():
print("🔵 Reading content from website...")
await asyncio.sleep(15 * 60) # simulate 15 minutes delay
content = "Company news and updates"
print("✅ Finished reading website content.")
return content
# 🧾 2. Async function to analyze yesterday’s logs
async def analyse_log_of_events_of_last_day():
print("🔵 Analyzing yesterday's logs...")
await asyncio.sleep(5 * 60) # simulate 5 minutes delay
log_content = "Errors and warnings found in logs"
print("✅ Finished analyzing logs.")
return log_content
# 📡 3. Async function to fetch client data from SAP server
async def read_client_data_from_sap_server():
print("🔵 Fetching client data from SAP...")
await asyncio.sleep(12 * 60) # simulate 12 minutes delay
client_data = {
"clients": [
{"name": "Alice", "email": "alice@example.com"},
{"name": "Bob", "email": "bob@example.com"}
]
}
print("✅ Finished fetching SAP client data.")
return client_data
# 📬 4. Async function to merge all data and send email
async def merge_infomation_a_b_c__and_send_email_to_client(a, b, c):
print("🟡 Merging information and sending emails...")
await asyncio.sleep(8 * 60) # simulate 8 minutes processing
print(f"📧 Email sent to {len(c['clients'])} clients.")
return "Email task complete"
🚀 Running All Tasks Concurrently#
Here’s the main function that does the magic:
async def main():
# 🟢 Fire all 3 tasks concurrently
task_a = asyncio.create_task(read_some_content_from_internet()) # 15 mins
task_b = asyncio.create_task(analyse_log_of_events_of_last_day()) # 5 mins
task_c = asyncio.create_task(read_client_data_from_sap_server()) # 12 mins
# 🔄 Wait for all 3 tasks to complete (runs in parallel)
a, b, c = await asyncio.gather(task_a, task_b, task_c)
# 🟢 Now safely do the final step
result = await merge_infomation_a_b_c__and_send_email_to_client(a, b, c)
print("🎉 All tasks completed:", result)
Finally, run this:
asyncio.run(main())
🕒 Total Time Breakdown#
| Task | Time Taken |
|---|---|
| Website Content (task_a) | 15 min |
| Log Analysis (task_b) | 5 min |
| SAP Client Data (task_c) | 12 min |
| Merge + Email | 8 min |
| Total Time with Async | 23 min |
| (vs 40+ min if run sequentially) |
✅ Final Thoughts#
async defis used to define asynchronous functionsawaitis used inside async functions to pause until an async task completesasyncio.create_task()lets you start multiple async functions at onceasyncio.gather()waits for multiple tasks concurrently and collects their results
This pattern is ideal for any program that deals with networking, file I/O, or waiting.
🎁 Bonus Tip#
You can extend this idea for:
- Calling multiple APIs at once
- Running 100s of slow web scrapers in parallel
- Simultaneously checking system logs and health metrics
Would you like a visual diagram (timeline or flowchart) of this process for your article?
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