Python Threading Basics

Threading lets your program run tasks “at the same time” (concurrently). It is most useful when tasks are waiting on I/O, like:
- downloading files
- making API requests
- reading/writing files
- waiting for network responses

  Important concept:
  Threads in Python are not best for CPU-heavy tasks due to the GIL. For CPU-heavy workloads, `multiprocessing` is usually better.
  
  ## Basic thread example
  
  ```python
  import threading
  import time
  
  def task(name):
      print(f"{name} starting...")
      time.sleep(2)
      print(f"{name} done!")
  
  t1 = threading.Thread(target=task, args=("Task 1",))
  t2 = threading.Thread(target=task, args=("Task 2",))
  
  t1.start()
  t2.start()
  
  t1.join()
  t2.join()
  
  print("All done!")
  ```
  
  Expected output (order may vary slightly):
  
  ```
  Task 1 starting...
  Task 2 starting...
  Task 1 done!
  Task 2 done!
  All done!
  ```
  
  ## Threading with a list of tasks
  
  ```python
  import threading
  import time
  
  def download_file(file_name):
      print(f"Downloading {file_name}...")
      time.sleep(1)
      print(f"Downloaded {file_name}")
  
  files = ["file1.txt", "file2.txt", "file3.txt"]
  threads = []
  
  for file in files:
      t = threading.Thread(target=download_file, args=(file,))
      t.start()
      threads.append(t)
  
  for t in threads:
      t.join()
  
  print("All downloads finished.")
  ```
  
  ## Shared data problem (race condition)
  
  If multiple threads update the same variable, results can be wrong.
  
  ## Fix with Lock
  
  ```python
  import threading
  
  counter = 0
  lock = threading.Lock()
  
  def increment():
      global counter
      for _ in range(100000):
          with lock:
              counter += 1
  
  threads = [threading.Thread(target=increment) for _ in range(10)]
  
  for t in threads:
      t.start()
  
  for t in threads:
      t.join()
  
  print(counter)
  ```
  
  Expected output:
  
  ```
  1000000
  ```
  
  ## Graph: thread lifecycle
  
  ```mermaid
  flowchart TD
    A[Create Thread] --> B[start()]
    B --> C[Run task]
    C --> D[join()]
    D --> E[Program continues]
  ```
  
  In the next lesson, you will learn how to work with APIs in Python, which is a practical skill for building real applications.