Created
October 13, 2014 16:20
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Flask isn't releasing memory used for large dictionaries
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import random | |
import optparse | |
from flask import redirect, Flask | |
from memory_profiler import memory_usage | |
# Create flask app | |
app = Flask(__name__) | |
app.debug = True | |
@app.route('/') | |
def hello_world(): | |
### | |
# The test: | |
# Generate a ~2440 mb dictionary and return a blank page. | |
### | |
large_dict = {} | |
for x in xrange(125000): | |
large_row = {} | |
for y in xrange(125): | |
large_row[random.randint(1, 10000000000)] = random.randint(1, 10000000000) | |
large_dict[random.randint(1, 10000000000)] = large_row | |
print memory_usage(-1, interval=.2, timeout=1), "end" | |
return '' | |
### | |
# The result: | |
# large_dict stays in memory, and memory usage never goes below ~2440 mb | |
### | |
def main(): | |
app.config['SECRET_KEY'] = "BLAH" | |
parser = optparse.OptionParser() | |
parser.add_option("--host", default="0.0.0.0") # can't use -h, it's already taken by help | |
parser.add_option("-p", "--port", default="5123") | |
options, args = parser.parse_args() | |
if len(args) > 0: | |
parser.error("Unexpected arguments: %s" % args) | |
app.run(host=options.host, port=int(options.port)) | |
if __name__ == '__main__': | |
# Start app | |
main() |
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There's still a reference to the memory,
large_dict
, when you run the profiler. Even if there wasn't you can't guarantee that the interpreter will have released the memory.Try running the profiler in the
after_request
handler, or on a subsequent request. (Provided that the garbage collection has run.)