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Create shape file from polylines for ArcMAP

I have been given an ArcMAP file with hundreds of polylines which unfortunately consist of line segments. I have written a python script which adds connecting line segments together to create polylines. I now want to write these polylines back to a shapefile so that I can load it in ArcMAP again. However, so far I have not been successful in creating a shapefile (it is my first time working with ArcMAP so very unfamiliar with it).
I have written the polylines to a dictionary which now looks as follows:
{'Owner': 'Owner1', 'type': 'Sewage', 'points': [[44228.171875, 361147.6875], [44247.7695313, 361150.125], [44252.3203125, 361109.125], [44278.8789063, 361149.1875], [44262.4882813, 361177.71875], [44244.9609375, 361187.28125], [44229.9882813, 361118.125], [44286.6210938, 361148.90625], [44225.9882813, 361181.25], [44270.4882813, 361182.09375], [44302.0195313, 361208.4375], [44253.421875, 361203.21875], [44305.5390625, 361234.0], [44284.5117188, 361162.59375], [44286.6210938, 361148.90625], [44287.46875, 361099.78125], [44269.359375, 361089.46875], [44278.8789063, 361108.03125], [44249.28125, 361244.5]]}
So far what I have tried is to take the points-list from the dictionary, add it to a separate list and add this to a shapefile. I have not been succesful yet in doing so but the code I have used it shown below.
polyline_list = []
w = shapefile.Writer(shapeType=1)
w.autoBalance = 1
loop which determines points_list as shown above
polyline_list.append(points_list)
w.line(polyline_list)
w.field('Polyline_field')
w.record('Polyline_record')
w.save('Shapefile_KLIC_2022')
If anyone could help me that would be greatly appreciated. I am also new to using stackoverflow so I am not sure if the code which I provided is clear enough. The code to determine points_list consists of 2 nested while loops with a for loop inside as well so it is difficult to present here. If the points_list provided in the dictionary can be written to a shapefile however that would be enough help for me to write the complete shapefile. If there is a better way to ask my question also please let me know I'd like to learn :D

I'm not able to print node evaluation results in python. My results are visible in VISSIM but can't access them through API COM

I'm writing a program and need to get the following Node results:- ["fuel consumption, Emissions CO, NOx, VOC"] as shown in image. I just need to print these results in Python. My results are visible in VISSIM but can't access them through COM.
I couldn't find any help in PTV Vissim\Training Examples\Basic Commands.
I've tried using multiple codes but It's not working. eg.
Vissim.Net.Nodes.Attvalue('FuelConsumption(Avg,Avg))
Vissim.Net.Node.Movements.ItemBykey(1).AttValue(FuelConsumption(Avg,Avg))
Vissim.Net.Movements.ItemByKey(1).AttValue(FuelConsumption(Avg,Avg))
Vissim.Net.Nodes.Attvalue('EmissionsCO(Avg,Avg)) etc.
I have used COM HELP to write the above syntax but it's giving an error.
I don't want user defined emissions. In Vissim, if you go to evaluation\Results List\Node Results: A list opens which gives by default values of Emissions and fuel consumption. I just need to print those values in EXCEL using PYTHON.

How about saving the result after simulation, close Vissim and then read .att file? I do this job with Ling Segment Results and Node Results.
Here is my simple code: (Python3.7, Vissim 2020)
network_filename, _extention = datainfo['vissim_inpx'].split('.')
node_result = f'{network_filename}_Node Results_001.att'
cal.extract_from_node(node_result)
You have to click 'Autosave after simulation' button in advance to successfully get 'Node Results_001.att'.
Hope this helps.

coordinate conversion script isn't giving me an accurate reading SVY21 to WGS84

I would like to convert my dataset of SVY21 coordinates, into WGS84 coordinates.
I am currently using this script from this repo I found but this script this yields inaccurate results with a discrepancy of up to 0.04, so the coordinates that I convert end up being on an entirely different geographical location in the same country.
Was wondering if there is anyone who can assist to help me with a script for converting a large dataset from SVY21 to WGS84?
E.G I want to convert
38816.0396118, 34379.9602051
but instead I get
1.36728713070321, 103.890645888016
when I should be getting
1.327235496598071, 103.93042021823591
I would do it on those online converters but my file sizes are pretty big(can go up to few GB) so it's better to run a script on my local computer instead using either Python or C++ or any other alternatives that will work. Also most online converters have a limit on file size as well.
Here's an accurate converter link: https://dominoc925-pages.appspot.com/webapp/calc_svy21/default.html but it doesnt accept my file size.
Appreciate the help :D Thanks~!

You probably have your coordinates the wrong way around. Consider the following:
import pyproj
xfm = pyproj.Transformer.from_crs('EPSG:3414', 'EPSG:4326')
x, y = 38816.0396118, 34379.9602051
print(xfm.transform(x, y))
# prints: (1.3673123058118237, 103.89064694097199)
print(xfm.transform(y, x))
# prints: (1.3271927478890677, 103.93050656742128)
Still about a ten-thousandth of a degree off, but I don't know how good pyproj's coordinate space definitions are in this case.

How to find objects in floor plan image in Tkinter python through svg file?

I have a vectorized floorplan image. I want to identify the objects in the image through the vector data in the SVG file of that image. The SVG code does not have any close points(z) in between them. So I am unable to understand when does the point moves to the other object? Can somebody help me, please?
I have very little knowledge about these SVG files and using them in Tkinter. So please somebody help me or suggest me what can I do?
This is the vector data of the image.
vector data of the image

use in conjunction with SO floorplan question.
Jump to z_final_floorplan.svg for final file.
A
Create 4 files:
w_original_floorplan.svg
x_rough_static_floorplan.svg
y_rough_live_floorplan.svg
z_final_floorplan.svg
w_original_floorplan.svg and x_rough_static_floorplan.svg are identical apart from filename.
y_rough_live_floorplan.svg and z_final_floorplan.svg are empty; to be populated.
Copy x_rough_static_floorplan.svg to y_rough_live_floorplan.svg.
Open y_rough_live_floorplan.svg on browser using server.
x_rough_static_floorplan.svg find all M and replace with two newlines / symbol M (case sensitive). shift + enter shift + enter /M
B
[this section takes the time]
Take away 1st '/' in path in y_rough_live_floorplan.svg [shows blackout_floorplan]
Label x_rough_static_floorplan.svg code section blackout_floorplan where code is.
(this file is used as rough-work, so being xml / svg valid is irrelevant)
In y_rough_live_floorplan.svg find next '/' and delete it [shows floorplan_top_left_whiteout]
Label x_rough_static_floorplan.svg code section floorplan_top_left_whiteout where code is.
Have x_rough_static_floorplan.svg and y_rough_live_floorplan.svg open in 2 windows, will be going back and forth to each of them. Keep repeating until at end.
(hint: find tool seems to be on switching from files in vscode, so you can use find / and next one cmd + g easily) Maybe handy to have a paper printout of original svg as reference and label the names of objects you create e.g.bath, sink, table, as you go along (don’t be fooled by this, one table is 'table'. Is 2nd chair chair2, chair_2, chair_two etc.?) etc..
C
Reorder the whole labels and corresponding code in path x_rough_static_floorplan.svg so the labels are ordered next to each other, but in the order they are found in the path:
e.g.
…
floorplan
bath
sink
table_chairs
sofa
…
Use the 'find' tool here. This process, itself will require a temp file to copy and paste to rather than reorder within the file working on. And rewrite temp to file working on. Might be good idea to create checklist of objects and cross-off as done.
E.g. floorplan, bath, table_chairs, sink…
D
Create path elements from your grouped objects, putting each id as id=“floorplan_main”, id=“bath”, id=“sink” etc.. etc..
Bear in mind, the data of how this is drawn is really, really bad. Really they should be drawn with rect elements for a rectangle when possible and a lot of the path data is very unnecessary, but that’s obviously how the application generates the svg.

Binary file (Labview .DAT file) conversion using Python

I work in a lab where we acquire electrophysiological recordings (across 4 recording channels) using custom Labview VIs, which save the acquired data as a .DAT (binary) file. The analysis of these files can then be continued in more Labview VIs, however I would like to analyse all my recordings in Python. First, I need walk through all of my files and convert them out of binary!
I have tried numpy.fromfile (filename), but the numbers I get out make no sense to me:
array([ 3.44316221e-282, 1.58456331e+029, 1.73060724e-077, ...,
4.15038967e+262, -1.56447362e-090, 1.80454329e+070])
To try and get further I looked up the .DAT header format to understand how to grab the bytes and translate them - how many bytes the data is saved in etc:
http://zone.ni.com/reference/en-XX/help/370859J-01/header/header/headerallghd_allgemein/
But I can't work out what to do. When I type "head filename" into terminal, below is what I see.
e.g. >> head 2014_04_10c1slice2_rest.DAT
DTL?
0???? ##????
empty array
PF?c ƀ????l?N?"1'.+?K13:13:27;0.00010000-08??t?޾??DY
??N?t?x???D?
?uv?tgD?~I??
??N?t?x>?n??
????t?x>?n??
????t?޾??D?
????t?x???D?
????t?x?~I??
????tgD>?n??
??N?tgD???D?
??N?t?x???D?
????t????DY
??N?t?x>?n??
??N?t????DY
?Kn$?t?????DY
??N?t??>?n??
??N?tgD>?n??
????t?x?~I??
????tgD>?n??
??N?tgD>?n??
??N?tgD???DY
????t?x???D?
????t???~I??
??N?tgD???DY
??N?tgD???D?
??N?t?޿~I??
??N?t?x???DY
??N?tF>?n??
??N?t?x??%Y
Any help or suggestions on what to do next would be really appreciated.
Thanks.
P.s. There is an old (broken) matlab file that seems to have been intended to convert these files. I think this could probably be helpful, but having spent a couple of days trying to understand it I am still stuck. http://www.mathworks.co.uk/matlabcentral/fileexchange/27195-load-labview-binary-data

Based on this link it looks like the following should do the trick:
binaryFile = open('Measurement_4.bin', mode='rb')
(data.offset,) = struct.unpack('>d', binaryFile.read(8))
Note that mode is set to 'rb' for binary.
With numpy you can directly do this as
data = numpy.fromfile('Measurement_4.bin', dtype='>d')
Please note that if you are just using Python as an intermediate and want to go back to LabVIEW with the data, you should instead use the function Read from Binary file.vi to read the binary file using native LabVIEW.

DAT is a pretty generic suffix, not necessarily something pointing to a specific format. If I'm understanding correctly, that help section is for DIAdem, which may be completely unrelated to how your data is saved from LV.
What you want is this help section, which tells you how LV flattens data to be stored on disk - http://zone.ni.com/reference/en-XX/help/371361J-01/lvconcepts/flattened_data/
You will need to look at the LV code to see exactly what kind of data you're saving and how the write file function is configured (byte order, size prepending, etc.) and then use that document to translate it to the actual representation.