Skip to main content
  1. Posts/

uWSGI Install and Use Issues

··627 words·3 mins·
Python UWSGI
Table of Contents

My notes on several issues when installing and running uWSGI.

pip install uwsgi error
#

When I try to install uwsgi using pip, there are compilation errors. After some search, based on discussions here, I find the cause of this issue is that the version of gcc is too high. I am using Ubuntu 18.04, and the default gcc version is 7.4.0.

Based on this post, the minimum gcc we can install from the default Ubuntu 18.04 remote repo is gcc-4.8. There is no gcc-4.7 available for install. It turns out that gcc-4.8 works fine:

apt-get update && apt-get install gcc-4.8 g++-4.8

Then we need to change the gcc command to point to gcc-4.8:

rm /usr/bin/gcc && ln -s /usr/bin/gcc-4.8 /usr/bin/gcc

After that, I can install uwsgi successfully using pip. Finally, let’s revert the gcc version to its old state:

rm /usr/bin/gcc && ln -s /usr/bin/gcc-7 /usr/bin/gcc

uwsgi can not find shared object
#

I use the following command to install uwsgi with conda:

conda create -n py36 -c conda-forge python==3.6.5 uwsgi

When I run uwsgi --version, I see the following error message:

error while loading shared libraries: libicui18n.so.58: cannot open shared object file: No such file or directory

The solution is to run conda install icu=58, ref here.

uwsgi segmentation fault
#

I am using uwsgi 2.0.18 (installed via conda install -c conda-forge uwsgi) with python 3.7.7 from Miniconda. When I use uwsgi to server a simple Flask application, I see segmentation errors below:

uwsgi(uwsgi_backtrace+0x2c) [0x5638f8685bbc]
uwsgi(uwsgi_segfault+0x32) [0x5638f8685ff2]
/lib/x86_64-linux-gnu/libc.so.6(+0x3ef20) [0x7f8c09c22f20]
/opt/miniconda/lib/python3.7/lib-dynload/_queue.cpython-37m-x86_64-linux-gnu.so(+0x2932) [0x7f8c07fe9932]
uwsgi(_PyDict_DelItem_KnownHash+0x36b) [0x5638f860ec1b]
uwsgi(_PyEval_EvalFrameDefault+0x2510) [0x5638f85a1680]
uwsgi(_PyEval_EvalCodeWithName+0x2f9) [0x5638f862abc9]
uwsgi(_PyFunction_FastCallDict+0x1d7) [0x5638f86045a7]
uwsgi(+0x1ed7a3) [0x5638f86057a3]
uwsgi(PyObject_CallFunctionObjArgs+0x99) [0x5638f8605a09]
uwsgi(PyObject_ClearWeakRefs+0x33c) [0x5638f86010fc]
uwsgi(+0x1a638c) [0x5638f85be38c]
uwsgi(+0x1b9a27) [0x5638f85d1a27]
uwsgi(+0x1f70b8) [0x5638f860f0b8]
uwsgi(+0x1a6435) [0x5638f85be435]
uwsgi(_PyFunction_FastCallKeywords+0x290) [0x5638f8604020]
uwsgi(_PyEval_EvalFrameDefault+0x40a) [0x5638f859f57a]
uwsgi(_PyFunction_FastCallDict+0x10b) [0x5638f86044db]
uwsgi(_PyEval_EvalFrameDefault+0x1e1d) [0x5638f85a0f8d]
uwsgi(_PyFunction_FastCallKeywords+0xfb) [0x5638f8603e8b]
uwsgi(_PyEval_EvalFrameDefault+0x6d4) [0x5638f859f844]
uwsgi(_PyFunction_FastCallKeywords+0xfb) [0x5638f8603e8b]
uwsgi(_PyEval_EvalFrameDefault+0x6d4) [0x5638f859f844]
uwsgi(_PyFunction_FastCallKeywords+0xfb) [0x5638f8603e8b]
uwsgi(_PyEval_EvalFrameDefault+0x6d4) [0x5638f859f844]
uwsgi(_PyFunction_FastCallDict+0x10b) [0x5638f86044db]
uwsgi(_PyObject_Call_Prepend+0x63) [0x5638f86054b3]
uwsgi(+0x1b56fa) [0x5638f85cd6fa]
uwsgi(PyObject_Call+0x6b) [0x5638f8604bdb]
uwsgi(python_call+0x12) [0x5638f869ffa2]
uwsgi(uwsgi_request_wsgi+0x266) [0x5638f86a2556]
uwsgi(wsgi_req_recv+0xa7) [0x5638f8633557]
uwsgi(simple_loop_run+0xd1) [0x5638f8681521]
uwsgi(simple_loop+0x11) [0x5638f8681301]
uwsgi(uwsgi_ignition+0x315) [0x5638f8686395]
uwsgi(uwsgi_worker_run+0x2b4) [0x5638f868aef4]
uwsgi(uwsgi_run+0x525) [0x5638f868b575]
/lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xe7) [0x7f8c09c05b97]
uwsgi(+0x21abed) [0x5638f8632bed]
*** end of backtrace ***

My MWE flask application:

import concurrent.futures

from flask import Flask

app = Flask(__name__)

@app.route("/toy", methods=["GET"])
def process_request():
    results = do_concurrent()

    if not results:
        return "Fail."

    return "Success"


def simple_task(num):
    return 1


def do_concurrent():
    dummy_list = list(range(100))
    with concurrent.futures.ThreadPoolExecutor(max_workers=10) as executor:
        results = list(executor.map(simple_task, dummy_list))

    return results

The uwsgi command to run flask application:

uwsgi --http 0.0.0.0:6012 --wsgi-file flask_demo.py --callable app --processes 1 --threads 1

The scrip to test this service:

import requests


url = "http://0.0.0.0:6012/toy"

r = requests.get(url, timeout=5)
print(r)

When I request the service, I see the above segmentation errors.

If I create a conda virtual env with python version 3.6:

conda create -n py36 -c conda-forge python==3.6.5 uwsgi icu=58 flask

run the service using uwsgi and request again, the error disappears.

If I do not use concurrent.futures, I see no errors both for python 3.7 and python 3.6. I am not knowledgeable enough to know the exact cause of this issue. It seems there is some compatibility issue with uwsgi, python version and concurrent package.

symbol not found on macOS
#

I am using Python 3.7 installed via Anaconda, and uWSGI is installed via pip. When I run my simple Flask application, I see the following error:

ImportError: dlopen(/Users/jdhao/anaconda3/lib/python3.7/lib-dynload/math.cpython-37m-darwin.so, 2): Symbol not found: _PyExc_MemoryErrorImportError: dlopen(/Users/jdhao/anaconda3/lib/python3.7/lib-dynload/math.cpython-37m-darwin.so, 2): Symbol not found: _PyExc_MemoryError
  Referenced from: /Users/jdhao/anaconda3/lib/python3.7/lib-dynload/math.cpython-37m-darwin.so
  Expected in: flat namespace

This seems to be a compatibility issue between uWSGI and Anaconda python. There are two solutions:

  1. Uninstall uWSGI installed via pip and install it using conda:

    # uWSGI is provided by the conda-forge channel
    conda install -c conda-forge uwsgi
    
  2. Using Python 3.6 with uWSGI. We can create a new virtual env with Python 3.6.5 and intall uWSGI inside.

    conda create -n py36 python==3.6.5 flask
    

    After that, activate the virtual env and install uWSGI inside:

    conda activate py36
    pip install uwsgi
    

Related

Monitoring Service Stat with uwsgitop
·107 words·1 min
Python UWSGI
Serving Flask Applications with uWSGI
··757 words·4 mins
Python Flask UWSGI
Run the Job Immediately after Starting Scheduler in Python APScheduler
·322 words·2 mins
Python APScheduler