Скачать или смотреть Overcoming Overhead Costs When Running Python Scripts from C+ + Shell Commands

Discover the overhead costs associated with running Python scripts via C+ + shell commands and learn efficient methods to streamline your workflow.
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Optimizing Python Script Execution from C+ + : Tackling Overhead Costs

Running a Python script from a C+ + program can be a handy way to harness the strengths of both languages; however, it often comes with a cost—specifically, a significant overhead that can slow down your application considerably. In this guide, we will explore what exactly causes this overhead, why it affects your program performance, and how to potentially streamline your C+ + to Python interactions, especially when you're working on a Raspberry Pi or similar hardware.

Understanding the Overhead

When you run a Python script from C+ + using a shell command, it involves several layers of processing, each contributing to the overall overhead. Let's break down the steps involved:

Using popen():

The function popen() starts a new shell process, which can be relatively low cost, but it still incurs some overhead.

Starting a sh process:

After creating a pipe with popen(), a new shell (sh) process is initiated. This step is relatively expensive as it needs to parse the command line.

Launching the python process:

The shell then starts a new Python process, which entails parsing and compiling the Python script. This is an additional layer of cost that can further slow down your script execution.

The second and third steps similar to manually running your Python script from a terminal add cumulative delays. This constant launch of multiple processes during an iterative loop can be particularly detrimental to performance, as observed in your described scenario.

Why Is Your Program Running Slowly?

Given that you are incrementing data from 0 to around 18,000, the program runs slowly mainly due to the repeated overhead of starting new processes repeatedly. The overhead costs stack up, significantly hindering your program’s performance. You suspect, and rightly so, that the method for invoking Python scripts is likely the bottleneck causing your slow performance.

Suggestions to Enhance Performance

To achieve better performance and reduce the overhead, consider the following options:

1. Avoid Spawning Multiple Processes

Launching Python multiple times per loop iteration adds unnecessary delays. Instead, consider the following approaches:

Single Python Process: Launch a single instance of the Python process at the start, then keep it running while communicating with it. Although more complex to implement, this method minimizes startup delays.

2. Establish Bi-directional Communication

While popen() allows for one-directional communication (C+ + to Python), consider using alternatives such as:

Sockets: Set up a server-client model where your C+ + program can send requests to a persistent Python server and get responses without repeatedly initializing a new Python process.

Named Pipes: Utilize named pipes for communication, allowing for a continuous flow of data between C+ + and Python, enabling you to send input and receive results more efficiently.

3. Optimize Python Code

Make sure your Python script is as efficient as possible. Even small improvements in how your script generates and processes data could yield significant performance boosts when combined with the other optimizations.

Conclusion

Running Python scripts from C+ + can introduce performance hurdles due to the overhead associated with process creation and execution. By understanding these challenges and exploring optimized communication strategies, you can significantly improve the responsiveness of your application. Particularly in resource-constrained environments like Raspberry Pi, these adjustments are crucial for ensuring your programs run effectively.

Is your C+ + to Pyt