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Operations Specialist (Part-time) at Truework

Truework is on a mission to create trust in every financial transaction. This is why we build products that enable businesses and consumers to regain control over how their sensitive financial information is shared online. Our platform empowers lenders to complete employment and income verifications quickly and accurately while enabling organizations to automate the verification process and…

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Truework Guardian improves employee data security

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Reduce memory usage post-fork in Flask/Gunicorn application [duplicate]

This question already has answers here:

Understanding memory usage in python (1 answer)

How can I explicitly free memory in Python? (10 answers)

Closed 2 years ago.

I am using Flask served with gunicorn, my configuration file looks something like:

timeout = 30limit_request_line = 6000max_requests = 500 # restart worker after this many requestsmax_requests_jitter = 100preload_app = Trueworkers = 2

With two sync workers and preforking I expect most of my application code to be loaded in the parent process before forking. However I've noticed after I do the first couple requests, the memory usage of the two worker processes jumps hugely.

two workers using a bunch of ram after first requests come in

I've tried to find anything I can that would be being loaded at "runtime" so to speak rather than at flask application setup time and I haven't been able to find anything. I've tried using memory_profiler extensively and not come up with any useful data yet.I even tried making sure my app and models and views are for sure loaded before forking:

def pre_fork(server, worker): print(f"PRE-FORK {server} {worker}") import myapp.views

While I can see this is called and loading all of my views (which should load basically everything as far as the app is concerned), it makes no difference. What can I do to figure out what is causing the massive memory consumption on the first request in the worker processes? The memory usage is very stable and flat after the first requests, so I don't think there is an ongoing leak. I just want to find out what is not being loaded before the fork and not shared.

My main question is: what extra work is Flask doing when the first request comes in for a worker that could be loading extra bits into memory?

https://codehunter.cc/a/flask/reduce-memory-usage-post-fork-in-flask-gunicorn-application-duplicate

DHL International Address Verification

DHL international address verification is a service that allows customers to track their packages sent by DHL. The service is available for DHL Express and DHL Parcel and it’s free of charge to use.

A tracking number is a unique set of numbers and sometimes letters that uniquely identify a package for domestic and international shipping. The number will appear on the shipment confirmation email or notification.

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Contact DHL Customer Services directly

If you are not able to track your DHL parcel with Ship24, it may be because you entered the wrong tracking code or the number is incorrect or not valid. This issue is typically resolved by contacting the eCommerce merchant or shipper to confirm that the number is correct.

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DHL International Address Verification

DHL international address verification is a vital step in any international shipping process. It can help you to identify potential issues with your shipments and make sure everything goes as planned.

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Api Standardization – ​​​Blogger

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Flask: Background thread sees a non-empty queue as empty

When I run a Flask app in uwsgi, the background thread and the app functions see different values when querying size of the same Queue.

Components

A Flask application with a thread-safe queue.

A GET call returns the queue size.

A POST call adds an element to the Queue.

A background thread prints the Queue size

The problem

When the app is from the shell using python tester.py, I get the expected result:

2014-06-07 14:20:50.677995 Queue size is: 0127.0.0.1 - - [07/Jun/2014 14:20:51] "POST /addMessage/X HTTP/1.1" 200 -2014-06-07 14:20:51.679277 Queue size is: 12014-06-07 14:20:52.680425 Queue size is: 12014-06-07 14:20:53.681566 Queue size is: 12014-06-07 14:20:54.682708 Queue size is: 1127.0.0.1 - - [07/Jun/2014 14:20:55] "POST /addMessage/Y HTTP/1.1" 200 -2014-06-07 14:20:55.687755 Queue size is: 22014-06-07 14:20:56.688867 Queue size is: 2

However, when the app is executed using uwsgi, I get the following in the logs:

2014-06-07 14:17:42.056863 Queue size is: 02014-06-07 14:17:43.057952 Queue size is: 0[pid: 9879|app: 0|req: 6/6] 127.0.0.1 () {24 vars in 280 bytes} [Sat Jun 7 14:17:43 2014] POST /addMessage/X => generated 16 bytes in 0 msecs (HTTP/1.1 200) 2 headers in 71 bytes (1 switches on core 0)2014-06-07 14:17:44.059037 Queue size is: 02014-06-07 14:17:45.060118 Queue size is: 0[pid: 9879|app: 0|req: 7/7] 127.0.0.1 () {24 vars in 280 bytes} [Sat Jun 7 14:17:45 2014] POST /addMessage/X => generated 16 bytes in 0 msecs (HTTP/1.1 200) 2 headers in 71 bytes (1 switches on core 0)2014-06-07 14:17:46.061205 Queue size is: 02014-06-07 14:17:47.062286 Queue size is: 0

When running under uwsgi, the background thread does not see the same queue as the app. Why is that? How can I make these two threads look at the same Queue object?

Updates

I see inconsistent behaviour even when it's executed as a Python script: Sometimes it does not manage to log messages (using app.logger), and I can only see prints. This means that the thread is running, but it can't do anything with app.logger.

uwsgi .ini configuration

[uwsgi]http-socket = :9002plugin = pythonwsgi-file = /home/ubuntu/threadtest-uwsgi.pyenable-threads = trueworkers = 1chdir = /home/ubuntu/thread-tester/thread_tester

Code

from flask import Flask, jsonifyimport Queuefrom threading import Threadimport timeimport datetimeimport loggingimport syslogging.basicConfig(stream=sys.stderr, format='%(asctime)s %(levelname)s - %(message)s')app = Flask(__name__)messages = Queue.Queue()def print_queue_size(): while True: app.logger.debug("%s Queue size is: %d" % (datetime.datetime.now(), messages.qsize())) time.sleep(1)t = Thread(target=print_queue_size, args=())t.setDaemon(True)t.start()@app.route("/queueSize", methods=["GET"])def get_queue_size(): return jsonify({"qsize": messages.qsize()}), [email protected]("/addMessage/<message>", methods=["POST"])def add_message_to_queue(message): messages.put(message) return jsonify({"qsize": messages.qsize()}), 200if __name__ == "__main__": app.run(port=6000)

https://codehunter.cc/a/flask/flask-background-thread-sees-a-non-empty-queue-as-empty

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