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10 npm Typosquatted Packages Deploy Multi-Stage Credential Harvester
Socket researchers found 10 typosquatted npm packages that auto-run on install, show fake CAPTCHAs, fingerprint by IP, and deploy a credential stealer.
Minimalist measurement of python code time
timy comes with a different idea of the built-in module timeit. It adds flexibility and different ways of measuring code time, using simple context managers and function decorators.
pip install timy
Let's say you have a calculate function and you want to keep track of its execution time
import timy
@timy.timer()
def calculate(n, r):
"""
Divide, multiply and sum 'n' to every number in range 'r'
returning the result list
"""
return [i / n * n + n for i in range(r)]
Whenever you call that function, the execution time will be tracked
calculate(5, 10000000)
>> Timy executed (calculate) for 1 time(s) in 1.529540 seconds
>> Timy best time was 1.529540 seconds
Changing the ident and adding loops to the execution
import timy
@timy.timer(ident='My calculation', loops=10)
def calculate(n, r):
return [i / n * n + n for i in range(r)]
calculate(5, 10000000)
>> My calculation executed (calculate) for 10 time(s) in 15.165313 seconds
>> My calculation best time was 1.414186 seconds
The with statement can also be used to measure code time
Named tracking points can be added with the
trackfunction
import timy
with timy.Timer() as timer:
N = 10000000
for i in range(N):
if i == N/2:
timer.track('Half way')
>> Timy (Half way) 0.557577 seconds
>> Timy 0.988087 seconds
Another usage of tracking in a prime factors function
def prime_factors(n):
with timy.Timer('Factors') as timer:
i = 2
factors = []
def add_factor(n):
factors.append(n)
timer.track('Found a factor')
while i * i <= n:
if n % i == 0:
add_factor(i)
n //= i
else:
i += 1
return factors + [n]
factors = prime_factors(600851475143)
print(factors)
>> Factors (Found a factor) 0.000017 seconds
>> Factors (Found a factor) 0.000376 seconds
>> Factors (Found a factor) 0.001547 seconds
>> Factors 0.001754 seconds
>> [71, 839, 1471, 6857]
from timy.settings import timy_config
You can enable or disable timy trackings with the tracking value.
The default value of
trackingisTrue
timy_config.tracking = False
You can choose between print or logging for all timy outputs by setting the
value of tracking_mode.
The default value of
tracking_modeisTrackingMode.PRINTING.
from timy.settings import (
timy_config,
TrackingMode
)
timy_config.tracking_mode = TrackingMode.LOGGING
timy logs at the INFO level, which is not printed or stored by default. To configure the logging system to print all INFO messages do
import logging
logging.basicConfig(level=logging.INFO)
or to configure the logging system to print only timy's INFO messages do
import logging
logging.basicConfig()
logging.getLogger('timy').level=logging.INFO
Contributions are always welcome, but keep it simple and small.
This project is licensed under the MIT License - see the LICENSE file for details
include_sleeptime to count time elapsed including sleep time (include_sleeptime=True) and excluding sleep time (include_sleeptime=False)FAQs
Minimalist measurement of python code time
We found that timy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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