Performance implementing large JSON parsing in Python 2.7 using simplejson
I'm working through a tutorial and I'm confused about I'm sure I'm missing something obvious here, but I'm experiencing important performance degradation when trying to parse large JSON files (over 100 MB) using the `simplejson` library in Python 2.7... My implementation looks like this: ```python import simplejson as json with open('large_file.json', 'r') as f: data = json.load(f) ``` While this works for smaller files, the parsing time for the larger JSON file exceeds 60 seconds, which is unacceptable for my application. I've tried using the `json` module from the standard library as well, but the performance was similarly poor. I considered using `json.load()` in a streaming fashion to reduce memory usage, but I am unsure how to implement it correctly. Additionally, I'm running this within a Flask app and have noticed that the application becomes unresponsive during parsing. I also attempted to increase the buffer size when reading the file, but it didn’t seem to make a difference. I've checked whether the JSON structure could be causing these delays; it is a large array of objects with many nested fields, but the structure seems valid according to JSON validators. Is there a more efficient way to handle large JSON files in Python 2.7 without running into these performance optimization? Should I consider alternative libraries or methods for parsing? Any insights or suggestions would be greatly appreciated. This is part of a larger service I'm building. I'm on CentOS using the latest version of Python 2.7. Any pointers in the right direction?