I have data in an excel file that I would like to use to create a case in PSSE. The data is organized as it would appear in a case in PSSE (ie. for bus Bus number, name, base kV, and so on. Of course the data can be entered manually but I'm working with over 500 buses. I have tried copied and pasting, but that seems to works only sometimes. For machine data, it barely works.
Is there a way to import this data to PSSE from an excel file? I have recently started running PSSE with Python, and maybe there is a way to do this?
--
MK.
Yes. You can import data from an excel file into PSSE using the python package xlrt, however, I would reccomend instead converting your excel file to csv before you import and use csv as it is much easier. Importing data using the API is not just a copy and paste job, into the nicely tabulated spreadsheet that PSSE has in its case data.
Refer to the API documentation for PSSE, chapter II. Search this function, BUS_DATA_2. You will see that you can create buses with this function.
So your job should be three fold.
Import the csv file data with each line being a list of each data parameter for your bus. Like voltage, name, baseKV, PU etc. Store it to another list.
Iterate through the new list you just created and call:
ierr = bus_data_2(i, intgar, realar, name)
and pass in your data from the csv file. (see PSSE API documentation on how to do this) This will effectively load data from the csv file to your case ( in the form of nodes or buses).
After you are finished, you will need to call a function called psspy.save("Casename.sav") to save your work in a new PSSE case.
Note: there are functions to load in line data, fix shunt data, generator data etc.
Your other option is to call up the PTI folks as they can give you training.
Good luck
If you have an Excel data file with exactly the same "format" and same "info" as the regular case file (.sav), try this:
Open any small example .sav file from the example sub-folder PSSE's installation folder
Copy the corresponding spreadsheet to the working case (shown in spreadsheet view) with the same "info" (say, bus, branch,etc.) in PSSE GUI
After finishing copying everything, then save the edited working case in GUI as a new working case.
If this doesn't work, I suggest you to ask this question on forum of "Python for Power Systems":
https://psspy.org/psse-help-forum/questions/
Related
Thanks for taking the time to read my question.
I am working on a personal project to learn python scripting for excel, and I want to learn how to move data from one workbook to another.
In this example, I am emulating a company employee ledger that has name, position, address, and more (The organizations is by row so every employee takes up one row). But the project is to have a selected number of people be transferred to a new ledger (another excel file). So I have a list of emails in a .txt file (it could even be another excel file but I thought .txt would be easier), and I would want the script to run through the .txt file, get the emails, and look for any rows that have a matching email address(all emails are in cell 'B'). And if any are found, then copy that entire row to the new excel file.
I tried a lot of ways to make this work, but I could not figure it out. I am really new to python so I am not even sure if this is possible. Would really appreciate some help!
You have essentially two packages that will allow manipulation of Excel files. For reading in data and performing analysis the standard package for use is pandas. You can save the files as .xlsx however you are only really working with base table data and not the file itself (IE, you are extracing data FROM the file, not working WITH the file)
However what you need is really to perform manipulation on Excel files directly which is better done with openpyxl
You can also read files (such as your text file) using with open function that is native to Python and is not a third party import like pandas or openpyxl.
Part of learning to program includes learning how to use documentation.
As such, here is the documentation you require with sufficient examples to learn openpyxl: https://openpyxl.readthedocs.io/en/stable/
And you can learn about pandas here: https://pandas.pydata.org/docs/user_guide/index.html
And you can learn about python with open here: https://docs.python.org/3/tutorial/inputoutput.html
Hope this helps.
EDIT: It's possible I or another person can give you a specific example using your data / code etc, but you would have to provide it fully. Since you're learning, I suggest using the documentation or youtube.
I am developing a web application in which users can upload excel files. I know I can use the OPENROWSET function to read data from excel into a SQL Server but I am refraining from doing so because this function requires a file path.
It seems kind of indirect as I am uploading a file to a directory and then telling SQL Server go look in that directory for the file instead of just giving SQL Server the file.
The other option would be to read the Excel file into a pandas dataframe and then use the to_sql function but pandas read_excel function is quite slow and the other method I am sure would be faster.
Which of these two methods is "correct" when handling file uploads from a web application?
If the first method is not frowned upon or "incorrect", then I am almost certain it is faster and will use that. I just want an experienced developers thoughts or opinions. The webapp's backend is Python and flask.
If I am understanding your question correctly, you are trying to load the contents of an xls(s) file into a SQLServer database. This is actually not trivial to do, as depending on what is in the Excel file you might want to have one table, or more probably multiple tables based on the data. So I would step back for a bit and ask three questions:
What is the data I need to save and how should that data be structured in my SQL tables. Forget about excel at this point -- maybe just examine the first row of data and see how you need to save it.
How do I get the file into my web application? For example, when the user uploads a file you would want to use a POST form and send the file data to your server and your server to save that file (for example, either on S3, or in a /tmp folder, or into memory for temporary processing).
Now that you know what your input is (the xls(x) file and its location) and how you need to save your data (the sql schema), now it's time to decide what the best tool for the job is. Pandas is probably not going to be a good tool, unless you literally just want to load the file and dump it as-is with minimal (if any) changes to a single table. At this point I would suggest using something like xlrd if only xls files, or openpyxl for xls and xlsx files. This way you can shape your data any way you want. For example, if the user enters in malformed dates; empty cells (should they default to something?); mismatched types, etc.
In other words, the task you're describing is not trivial at all. It will take quite a bit of planning and designing, and then quite a good deal of python code once you have your design decided. Feel free to ask more questions here for more specific questions if you need to (for example, how to capture the POST data in a file update or whatever you need help with).
I developed a software which can be automatically updated, so I need external-placed config file/files. For now I use json file to store user-input variables like user name etc. But I am not sure how the program itself should be controlled. I mean things like checking if program is opened for first time after update to know if update notes should be shown, what functions were already used etc. For now I am doing it with things like:
if os.path.exists(control_file_1):
actions_1
if os.path.exists(control_file_2):
some other actions unrelated to actions_1
it is independent from the files content - so there is no need to read the file content - which is convenient.
What functions should be used to store those information in one file and read them efficiently? Just normal file.read() etc? It seems not very clean-code friendly.
Thanks
UPDATE:
Looks like a ConfigParser is a way to go. Am I right? Or are they any better ways to accomplish what I am going for?
Given that you need to have config information stored in a file. If you choose to have that information in a file that contains a json record then it is the most convenient if the file is used internally and updating and reading the record in the file is easy (treat it as a dict)
However, if you want a more universal config.ini reader then you can go with ConfigParser class which you can use directly or create your own wrapper
class MYConfig_Parser(ConfigParser):
so that you can check stuff in the constructor like if mandatory entries are available etc before processing the entries.
I wrote a tool that extracts data from a large DB and outputs it to an Excel file along with (conditional) formatting to improve readability. For this I use Python with openpyxl on a Linux machine. It works great, but this package is rather slow for writing Excel.
It seems to be a lot quicker to dump the table as (compressed) csv, import that into Excel and apply formatting there using a macro/vba.
To automate the process I'd like to create an empty Excel file pre-loaded with the required VBA to do the formatting; a template. For every data dump, the data is embedded (compressed using deflate) into the Excel file and loaded into the Workbook upon opening the document (or using a "LOAD" button to circumvent macro related security things).
However, just adding some file into the Excel file raises an error when opened:
We found a problem with some content in 'Werkmap1_test_embed.xlsx'. Do you want us to try to recover as much as we can? If you trust the source of this workbook, click Yes.
Clicking Yes opens the file and shows some tracing information as XML:
<?xml version="1.0" encoding="UTF-8" standalone="yes"?>
<recoveryLog xmlns="http://schemas.openxmlformats.org/spreadsheetml/2006/main">
<logFileName>Repair Result to Werkmap1_OLE_Word0.xml</logFileName>
<summary>Errors were detected in file '/Users/joostk/mnt/cluster/Werkmap1_OLE_Word.xlsx'</summary>
<additionalInfo>
<info>Excel completed file level validation and repair. Some parts of this workbook may have been repaired or discarded.</info>
</additionalInfo>
</recoveryLog>
Is it possible to avoid this? How would I embed a file into the Excel ZIP? Do I need to update some file table (which I could not file easily).
When that's done, I'd like to import the data. Can I access files in the Excel ZIP from VBA? I guess not, and I need to extract the data to some temporary path and load it from there.
I have found these helpful answers elsewhere to load ZIP and plain text:
https://stackoverflow.com/a/35781621/4998990
https://stackoverflow.com/a/11267603/4998990
Many thanks for sharing your thoughts!
so my "Answer" here is that this is caused by using Named Ranges, or an underlying table, or an embedded Query/Connection. When you start manipulating this file you will get the error that you are talking about:
There is no harm to the file if you click "yes" and open. Excel will open this in Repaired Mode which will require you to re-save the file.
The way I've worked around this is to re-read the "repaired" file, in python, and save it as another file or replace it. Essentially just do an extra step of re-reading the data into memory, and write it to a new file. The error will go away. As always, test this method before deploying to production to ensure no records are lost. The way I solve it is with two lines of pandas.
import pandas as pd
repair = pd.read_excel('PATH_TO_REPAIR_FILE')
new_file = repair.to_excel('PATH_TO_WHERE_NEW_FILE_GOES')
Problem
I was trying to implement an web API(based on Flask), which would be used to query the database given some specific conditions, reconstruct the data and finally export the result to a .csv file.
Since the amount of data is really really huge, I can not construct the whole dataset and generate the .csv file all at once(e.g. create a DataFrame using pandas and finally call df.to_csv()), because that would cause a slow query and maybe the http connection would end up timeout.
So I create a generator which query the database 500 records per time and yield the result one by one, like:
def __generator(q):
[...] # some code here
while True:
if records == None:
break
records = q[offset:offset+limit] # q means a sqlalchemy query object
[...] # omit some reconstruct code
for record in records:
yield record
and finally construct a Response object, and send .csv to client side:
return Response(__generate(q), mimetype='text/csv') # Flask
The generator works well and all data are encoded by 'uft-8', but when I try to open the .csv file using Microsoft Excel, it appears to be messy code.
Measures Already Tried
add a BOM header to the export file, doesn't work;
using some other encode like 'gb18030', and 'cp936', most of the messy code disappear, some still remained, and some part of the table structure become weird.
My Question Is
How can I make my code compatible to Microsoft Excel? That means at least two conditions should be satisfied:
no messy code, well displayed;
well structured table;
I would be really appreciated for your answer!
How are you importing the csv file to excel? Have you tried importing the csv as a text file?
By reading as text format for each column, it wont modify columns that it reads as different types like dates. Your code may be correct, and excel may just be modifying the data when it parses it as a csv - by importing as text format, it wont modify anything.
I would recommend you look into xlutils. It's been around for quite some time, and our company has used it both for reading configuration files to run automated test and for generating reports of test results.