Python – Is there a way to help make this Python logic run faster

I’ve been working on a solution to get data from PLC sensors using Python, and I’m able to calculate syntax using cppo, etc. This approach works well in terms of getting data from labels in a loop in a supposed serialization fashion.

To test this new Python cpppo solution, I’ve connected the machine running Python logic to the PLC through a VPN tunnel, and I have it poll a specific label/sensor. This tag also polls with different non-Python solutions connected to the local machine network and logs over Ethernet.

Question

Does anyone know of a way I can rewrite this simple code below where I can force it to poll 3 or even 4 times in a second? Is there anything else that might contribute to this?

• By contributing to “this”, I’m talking about “other” or “non-Python” methods that seem to log poll responses from the same tag 3 times a second and Python cpppo solutions that seem to only em> at a maximum of 2 times per second so when there are 3 weight values in a second, occasionally a weight is lost – sometimes only 2 per second, so it doesn’t always have 3 values a second, but sometimes there are 3 in a second.

Data

The returned sensor data is enclosed in square brackets, but the weight is expressed in grams and has decimal precision, with a small sample of the original data below.

[610.5999755859375]
[607.5]
[623.5999755859375]
[599.7999877929688]
[602.5999755859375]
[610.0]

Python code

Note: Python logic writes the sensor’s polling values to a csv file, but based on the system date and time via datetime.now() but before that, I convert the value to a string and then remove the square brackets str( x).replace('[','').replace(']','') uses the str() function.

from cpppo.server.enip.get_attribute import proxy_simple
from datetime import datetime
import time, csv

CsvFile = "C:\\folder\\Test\\Test.csv"
host = "<IPAddress>"

while True:
    x, = proxy_simple(host).read("<TagName>")

with open(CsvFile,"a",newline='') as file:
        csv_file = csv.writer(file) 
        for val in x:
            y = str(x).replace('[','').replace(']','')
            csv_file.writerow([datetime.now(), y])
#time.sleep(0.05)

Issues and test results

When I compare the csv file records captured by Python

with the records from other non-Python capture methods of the tag, the csv records generated by Python are sometimes lost, and often are.

Notable details (just in case).

• There is a timestamp difference of one second or less between the two systems because they generate timestamps at the time of capture.

• This particular sensor can spit out three values in a second, but not always; Sometimes one a second, or two a second, or none at all.

• I think the other way is to use Java, but this code is not accessible to compare the logic.

• I’m using Python version 3.6.5 (v3.6.5:f59c0932b4, March 28, 2018, 16:07:46) [MSC v.1900 32-bit (Intel)] from Windows 10.

Results

Python Method CSV (missing the correlated 606.6 value)

2018-04-12 13:56:42.249408,610.5999755859375
2018-04-12 13:56:42.909309,607.5
2018-04-12 13:56:43.559472,623.5999755859375
2018-04-12 13:56:44.259771,599.7999877929688
2018-04-12 13:56:44.910270,602.5999755859375
2018-04-12 13:56:45.541044,610.0

Other Method CSV Results (contains the 606.6 value)

12/04/2018 13:56:41,610.6
12/04/2018 13:56:42,607.5
12/04/2018 13:56:42,623.6
12/04/2018 13:56:43,606.6
12/04/2018 13:56:43,599.8
12/04/2018 13:56:44,602.6
12/04/2018 13:56:44,610

Problem description: Python missed capturing 12/04/2018 13:56:43,606.6 record while it was from another system. I suspect this is due to some slight delay following this logic, as I only see it missing values compared to other non-Python captured files.

The key parts of the code are:

while True:
    x, = proxy_simple(host).read("<TagName>")

with open(CsvFile,"a",newline='') as file:
        for val in x:
            # ...

In pseudocode:

forever:
    create proxy
    open output file
    process values from proxy

You mentioned that the sensor may produce about 3 values per second. If you look at the implementation of read(), What it does is set up a new reader object and produce all the values from it.

You might think your code works like this:

1. Create a proxy
2. Open the output file
3. Process value
4. Go to 3

But actually, it’s probably like this:

1. Create a proxy
2. Open the output file
3. Process value
4. Go to 1

Every time you call read(), it produces a value that it knew at that time. It does not wait for any new values to arrive.

Try this refactoring:

source = proxy_simple(host)
with open(CsvFile,"a",newline='') as file:
    while True:
        for message in source.read("<TagName>"):
            for val in message:
                # ...

Another error in the original code is:

x, = proxy_simple(host).read("<TagName>")

If read() returns multiple values, you only need to use the first one. That’s why there are two for loops in the code I suggested above.

Then you will only open the input and output once each time the program runs, not once per message.