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Using a Tkinter button input to pass as argument

I'm using tkinter to create an option menu, where choosing an option will call a function specific to each option. However, I'm unable to figure out exactly how to do that.
This is the code that is currently being used.
import pandas as pd
import os
import matplotlib.pyplot as plt
#below code imports file needed at the moment
import tkinter as tk
from tkinter import *
from tkinter import filedialog
import pandas as pd
import os
import matplotlib.pyplot as plt
root = tk.Tk()
root.withdraw()
file_path = filedialog.askopenfilename() #will open file from any location, does not need to be in the same place as the code script
df = pd.read_csv(file_path)
df.rename(columns={'Unnamed: 0':'Type'}, inplace=True) #renames the first unnamed column to type (drug available (DA) or not available (NA)
df.dropna(how = 'all', axis = 1, inplace = True) #drops the empty column present in each dataset, only drops it if the whole column is empty
##plotting functions for both active and inactive pokes
def ActivePokes(df):
plt.rcParams["figure.figsize"] = (12,7.5)
df.plot()
plt.xticks(range(0,len(df.Type)), df.Type)
plt.ylabel("Number of Active Pokes")
plt.xlabel("Sessions")
plt.title("Number of Active Pokes vs Drug Availability")
plt.show()
def InactivePokes(df):
plt.rcParams["figure.figsize"] = (12,7.5)
df.plot()
plt.xticks(range(0,len(df.Type)), df.Type)
plt.ylabel("Number of Inactive Pokes")
plt.xlabel("Sessions")
plt.title("Number of Inactive Pokes vs Drug Availability")
plt.show()
def show(df):
if variable == options[1]:
button[command] = ActivePokes(df)
elif variable == options[2]:
button[command] = InactivePokes(df)
else:
print("Error!")
options = [ "Choose Option",
"1. Active pokes, Drug Available and No Drug Available sessions",
"2. Inactive pokes, Drug Available and No Drug Available sessions"]
button = Tk()
button.title("Dialog Window")
button.geometry('500x90')
variable = StringVar(button)
variable.set(options[0]) #default value, might change and edit as time passes
option = OptionMenu(button, variable, *options, command = show)
option.pack()
button.mainloop()
I know the show() function is where the issue lies, but I'm not entirely sure how to rectify it.

The other comments and answer address problems with creating two Tk objects and using .get() with a StringVar.
The command = show callback is passed the string value of the item chosen. In your show( df ) when called from the Optionmenu will have df equal to one of the options. It won't be a pandas dataframe. Pure tkinter example below.
import tkinter as tk
root = tk.Tk()
root.geometry( '100x100' )
var = tk.StringVar( value = 'Option A' )
def on_choice( chosen ):
""" The callback function for an Optionmenu choice.
chosen: The text value of the item chosen.
"""
print( chosen, end = " : " )
print( ' or from the StringVar: ', var.get() )
opt_list = [ 'Option A', 'Option B', 'Option C' ]
options = tk.OptionMenu( root, var, *opt_list, command = on_choice )
options.grid()
root.mainloop()

First problem, you have created a tk instance called root, and then another one called button,why? perhaps you want button to be a tk.Button and not a tk instance? Not sure what is the intention here.
second, what is it command variable you want to change for button? (button[command]). if button where a tk.button, then perhaps you wanted to do button['command'] = ..., however, if the intention is to call the pokes functions why not calling them right away?
third problem is here:
def show(df):
if variable == options[1]:
button[command] = lambda: ActivePokes(df)
elif variable == options[2]:
button[command] = lambda: InactivePokes(df)
else:
print("Error!")
change variable for variable.get()

'str' object has no attribute 'plot'

Consistently getting above stated error when I try to call a function using the tkinter button.
So here is the example code used for this particular issue.
import tkinter as tk
from tkinter import *
from tkinter import filedialog
import pandas as pd
import os
import matplotlib.pyplot as plt
root = tk.Tk()
root.withdraw()
file_path = filedialog.askopenfilename() #will open file from any location, does not need to be in the same place as the code script
df = pd.read_csv(file_path)
df.rename(columns={'Unnamed: 0':'Type'}, inplace=True) #renames the first unnamed column to type (drug available (DA) or not available (NA)
df.dropna(how = 'all', axis = 1, inplace = True) #drops the empty column present in each dataset, only drops it if the whole column is empty
##plotting functions for both active and inactive pokes
def ActivePokes(df):
df.plot(figsize = (12,7.5),
xlabel = 'Number of active pokes', ylabel = 'Sessions',
title = 'Number of Active Pokes vs Drug Availability')
plt.xticks(range(0,len(df.Type)), df.Type)
def InactivePokes(df):
plt.rcParams["figure.figsize"] = (12,7.5)
df.plot()
plt.xticks(range(0,len(df.Type)), df.Type)
plt.ylabel("Number of Inactive Pokes")
plt.xlabel("Sessions")
plt.title("Number of Inactive Pokes vs Drug Availability")
plt.show()
def show(df):
if variable.get() == options[1]:
ActivePokes(df)
elif variable.get() == options[2]:
InactivePokes(df)
else:
print("Error!")
options = [ "Choose Option",
"1. Active pokes, Drug Available and No Drug Available sessions",
"2. Inactive pokes, Drug Available and No Drug Available sessions"]
button = Tk()
button.title("Dialog Window")
button.geometry('500x90')
variable = StringVar(button)
variable.set(options[0]) #default value, might change and edit as time passes
option = OptionMenu(button, variable, *options, command = show)
option.pack()
button.mainloop()
However, the error I keep receiving is this:
Is there any way this can be rectified and I can still produce the graphs needed while using the tkinter button?

The option Menu automatically passes the selected option to the command. Since you named the argument df in the function, the logical connection is df = contentained_string_of_optionmenu in the namespace of your function. However, since df origionally is a dataframe, you should just have to rename the argument/parameter of your function like:
def show(opt):
In addition it makes the StringVar useless since you can do:
if opt == options[1]:
ActivePokes(df)
elif opt == options[2]:
InactivePokes(df)
else:
print("Error!")
You might also choose to clear the argument df elsewhere since it's in the global namespace.

How can I save the headers and values in Html <script> as a table in the csv file?

I'm new to writing code. Using slenium and beautifulsoup, I managed to reach the script I want among dozens of scripts on the web page. I am looking for script [17]. When these codes are executed, the script [17] gives a result as follows.
the last part of my codes
html=driver.page_source
soup=BeautifulSoup(html, "html.parser")
scripts=soup.find_all("script")
x=scripts[17]
print(x)
result, output
note: The list of dates is ahead of the script [17]. slide the bar. Dummy Data
Dummy Data
<script language="JavaScript"> var theHlp='/yardim/matris.asp';var theTitle = 'Piyasa Değeri';var theCaption='Cam (TL)';var lastmod = '';var h='<a class=hisselink href=../Hisse/HisseAnaliz.aspx?HNO=';var e='<a class=hisselink href=../endeks/endeksAnaliz.aspx?HNO=';var d='<center><font face=symbol size=1 color=#FF0000><b>ß</b></font></center>';var u='<center><font face=symbol size=1 color=#008000><b>İ</b></font></center>';var n='<center><font face=symbol size=1 color=#00A000><b>=</b></font></center>';var fr='<font color=#FF0000>';var fg='<font color=#008000>';var theFooter=new Array();var theCols = new Array();theCols[0] = new Array('Hisse',4,50);theCols[1] = new Array('2012.12',1,60);theCols[2] = new Array('2013.03',1,60);theCols[3] = new Array('2013.06',1,60);theCols[4] = new Array('2013.09',1,60);theCols[5] = new Array('2013.12',1,60);theCols[6] = new Array('2014.03',1,60);theCols[7] = new Array('2014.06',1,60);theCols[8] = new Array('2014.09',1,60);theCols[9] = new Array('2014.12',1,60);theCols[10] = new Array('2015.03',1,60);theCols[11] = new Array('2015.06',1,60);theCols[12] = new Array('2015.09',1,60);theCols[13] = new Array('2015.12',1,60);theCols[14] = new Array('2016.03',1,60);theCols[15] = new Array('2016.06',1,60);theCols[16] = new Array('2016.09',1,60);theCols[17] = new Array('2016.12',1,60);theCols[18] = new Array('2017.03',1,60);theCols[19] = new Array('2017.06',1,60);theCols[20] = new Array('2017.09',1,60);theCols[21] = new Array('2017.12',1,60);theCols[22] = new Array('2018.03',1,60);theCols[23] = new Array('2018.06',1,60);theCols[24] = new Array('2018.09',1,60);theCols[25] = new Array('2018.12',1,60);theCols[26] = new Array('2019.03',1,60);theCols[27] = new Array('2019.06',1,60);theCols[28] = new Array('2019.09',1,60);theCols[29] = new Array('2019.12',1,60);theCols[30] = new Array('2020.03',1,60);var theRows = new Array();
theRows[0] = new Array ('<b>'+h+'30>ANA</B></a>','1,114,919,783.60','1,142,792,778.19','1,091,028,645.38','991,850,000.48','796,800,000.38','697,200,000.34','751,150,000.36','723,720,000.33','888,000,000.40','790,320,000.36','883,560,000.40','927,960,000.42','737,040,000.33','879,120,000.40','914,640,000.41','927,960,000.42','1,172,160,000.53','1,416,360,000.64','1,589,520,000.72','1,552,500,000.41','1,972,500,000.53','2,520,000,000.67','2,160,000,000.58','2,475,000,000.66','2,010,000,000.54','2,250,000,000.60','2,077,500,000.55','2,332,500,000.62','3,270,000,000.87','2,347,500,000.63');
theRows[1] = new Array ('<b>'+h+'89>DEN</B></a>','55,200,000.00','55,920,000.00','45,960,000.00','42,600,000.00','35,760,000.00','39,600,000.00','40,200,000.00','47,700,000.00','50,460,000.00','45,300,000.00','41,760,000.00','59,340,000.00','66,600,000.00','97,020,000.00','81,060,000.00','69,300,000.00','79,800,000.00','68,400,000.00','66,900,000.00','66,960,000.00','71,220,000.00','71,520,000.00','71,880,000.00','60,600,000.00','69,120,000.00','62,640,000.00','57,180,000.00','89,850,000.00','125,100,000.00','85,350,000.00');
theRows[2] = new Array ('<b>'+h+'269>SIS</B></a>','4,425,000,000.00','4,695,000,000.00','4,050,000,000.00','4,367,380,000.00','4,273,120,000.00','3,644,720,000.00','4,681,580,000.00','4,913,000,000.00','6,188,000,000.00','5,457,000,000.00','6,137,000,000.00','5,453,000,000.00','6,061,000,000.00','6,954,000,000.00','6,745,000,000.00','6,519,000,000.00','7,851,500,000.00','8,548,500,000.00','9,430,000,000.00','9,225,000,000.00','10,575,000,000.00','11,610,000,000.00','9,517,500,000.00','13,140,000,000.00','12,757,500,000.00','13,117,500,000.00','11,677,500,000.00','10,507,500,000.00','11,857,500,000.00','9,315,000,000.00');
theRows[3] = new Array ('<b>'+h+'297>TRK</B></a>','1,692,579,200.00','1,983,924,800.00','1,831,315,200.00','1,704,000,000.00','1,803,400,000.00','1,498,100,000.00','1,803,400,000.00','1,884,450,000.00','2,542,160,000.00','2,180,050,000.00','2,069,200,000.00','1,682,600,000.00','1,619,950,000.00','1,852,650,000.00','2,040,600,000.00','2,315,700,000.00','2,641,200,000.00','2,938,800,000.00','3,599,100,000.00','4,101,900,000.00','5,220,600,000.00','5,808,200,000.00','4,689,500,000.00','5,375,000,000.00','3,787,500,000.00','4,150,000,000.00','3,662,500,000.00','3,712,500,000.00','4,375,000,000.00','3,587,500,000.00');
var thetable=new mytable();thetable.tableWidth=650;thetable.shownum=false;thetable.controlaccess=true;thetable.visCols=new Array(true,true,true,true,true);thetable.initsort=new Array(0,-1);thetable.inittable();thetable.refreshTable();</script>
My purpose is to extract this output into a table and save it as a csv file. How can i extract this script as i want?
all dates should be on top, all names should be on the far right, all values should be between the two.
Hisse 2012.12 2013.3 2013.4 ...
ANA 1,114,919,783.60 1,142,792,778.19 1,091,028,645.38 ...
DEN 55,200,000.00 55,920,000.00 45,960,000.00 ....
.
.
.

Solution
The custom-function process_scripts() will produce what you are looking for. I am using the dummy data given below (at the end). First we check that the code does what it is expected and so we create a pandas dataframe to see the output.
You could also open this Colab Jupyter Notebook and run it on Cloud for free. This will allow you to not worry about any installation or setup and simply focus on examining the solution itself.
1. Processing A Single Script
## Define CSV file-output folder-path
OUTPUT_PATH = './output'
## Process scripts
dfs = process_scripts(scripts = [s],
output_path = OUTPUT_PATH,
save_to_csv = False,
verbose = 0)
print(dfs[0].reset_index(drop=True))
Output:
Name 2012.12 ... 2019.12 2020.03
0 ANA 1,114,919,783.60 ... 3,270,000,000.87 2,347,500,000.63
1 DEN 55,200,000.00 ... 125,100,000.00 85,350,000.00
2 SIS 4,425,000,000.00 ... 11,857,500,000.00 9,315,000,000.00
3 TRK 1,692,579,200.00 ... 4,375,000,000.00 3,587,500,000.00
[4 rows x 31 columns]
2. Processing All the Scripts
You can process all your scripts using the custom-define function process_scripts(). The code is given below.
## Define CSV file-output folder-path
OUTPUT_PATH = './output'
## Process scripts
dfs = process_scripts(scripts,
output_path = OUTPUT_PATH,
save_to_csv = True,
verbose = 0)
## To clear the output dir-contents
#!rm -f $OUTPUT_PATH/*
I did this on Google Colab and it worked as expected.
3. Making Paths in OS-agnostic Manner
Making paths for windows or unix based systems could be very different. The following shows you a method to achieve that without having to worry about which OS you will run the code. I have used the os library here. However, I would suggest you to look at the Pathlib library as well.
# Define relative path for output-folder
OUTPUT_PATH = './output'
# Dynamically define absolute path
pwd = os.getcwd() # present-working-directory
OUTPUT_PATH = os.path.join(pwd, os.path.abspath(OUTPUT_PATH))
4. Code: custom function process_scripts()
Here we use the regex (regular expression) library, along with pandas for organizing the data in a tabular format and then writing to csv file. The tqdm library is used to give you a nice progressbar while processing multiple scripts. Please see the comments in the code to know what to do if you are running it not from a jupyter notebook. The os library is used for path manipulation and creation of output-directory.
#pip install -U pandas
#pip install tqdm
import pandas as pd
import re # regex
import os
from tqdm.notebook import tqdm
# Use the following line if not using a jupyter notebook
# from tqdm import tqdm
def process_scripts(scripts,
output_path='./output',
save_to_csv: bool=False,
verbose: int=0):
"""Process all scripts and return a list of dataframes and
optionally write each dataframe to a CSV file.
Parameters
----------
scripts: list of scripts
output_path (str): output-folder-path for csv files
save_to_csv (bool): default is False
verbose (int): prints output for verbose>0
Example
-------
OUTPUT_PATH = './output'
dfs = process_scripts(scripts,
output_path = OUTPUT_PATH,
save_to_csv = True,
verbose = 0)
## To clear the output dir-contents
#!rm -f $OUTPUT_PATH/*
"""
## Define regex patterns and compile for speed
pat_header = re.compile(r"theCols\[\d+\] = new Array\s*\([\'](\d{4}\.\d{1,2})[\'],\d+,\d+\)")
pat_line = re.compile(r"theRows\[\d+\] = new Array\s*\((.*)\).*")
pat_code = re.compile("([A-Z]{3})")
# Calculate zfill-digits
zfill_digits = len(str(len(scripts)))
print(f'Total scripts: {len(scripts)}')
# Create output_path
if not os.path.exists(output_path):
os.makedirs(output_path)
# Define a list of dataframes:
# An accumulator of all scripts
dfs = []
## If you do not have tqdm installed, uncomment the
# next line and comment out the following line.
#for script_num, script in enumerate(scripts):
for script_num, script in enumerate(tqdm(scripts, desc='Scripts Processed')):
## Extract: Headers, Rows
# Rows : code (Name: single column), line-data (multi-column)
headers = script.strip().split('\n', 0)[0]
headers = ['Name'] + re.findall(pat_header, headers)
lines = re.findall(pat_line, script)
codes = [re.findall(pat_code, line)[0] for line in lines]
# Clean data for each row
lines_data = dict()
for line, code in zip(lines, codes):
line_data = line.replace("','", "|").split('|')
line_data[-1] = line_data[-1].replace("'", "")
line_data[0] = code
lines_data.update({code: line_data.copy()})
if verbose>0:
print('{}: {}'.format(script_num, codes))
## Load data into a pandas-dataframe
# and write to csv.
df = pd.DataFrame(lines_data).T
df.columns = headers
dfs.append(df.copy()) # update list
# Write to CSV
if save_to_csv:
num_label = str(script_num).zfill(zfill_digits)
script_file_csv = f'Script_{num_label}.csv'
script_path = os.path.join(output_path, script_file_csv)
df.to_csv(script_path, index=False)
return dfs
5. Dummy Data
## Dummy Data
s = """
<script language="JavaScript"> var theHlp='/yardim/matris.asp';var theTitle = 'Piyasa Değeri';var theCaption='Cam (TL)';var lastmod = '';var h='<a class=hisselink href=../Hisse/HisseAnaliz.aspx?HNO=';var e='<a class=hisselink href=../endeks/endeksAnaliz.aspx?HNO=';var d='<center><font face=symbol size=1 color=#FF0000><b>ß</b></font></center>';var u='<center><font face=symbol size=1 color=#008000><b>İ</b></font></center>';var n='<center><font face=symbol size=1 color=#00A000><b>=</b></font></center>';var fr='<font color=#FF0000>';var fg='<font color=#008000>';var theFooter=new Array();var theCols = new Array();theCols[0] = new Array('Hisse',4,50);theCols[1] = new Array('2012.12',1,60);theCols[2] = new Array('2013.03',1,60);theCols[3] = new Array('2013.06',1,60);theCols[4] = new Array('2013.09',1,60);theCols[5] = new Array('2013.12',1,60);theCols[6] = new Array('2014.03',1,60);theCols[7] = new Array('2014.06',1,60);theCols[8] = new Array('2014.09',1,60);theCols[9] = new Array('2014.12',1,60);theCols[10] = new Array('2015.03',1,60);theCols[11] = new Array('2015.06',1,60);theCols[12] = new Array('2015.09',1,60);theCols[13] = new Array('2015.12',1,60);theCols[14] = new Array('2016.03',1,60);theCols[15] = new Array('2016.06',1,60);theCols[16] = new Array('2016.09',1,60);theCols[17] = new Array('2016.12',1,60);theCols[18] = new Array('2017.03',1,60);theCols[19] = new Array('2017.06',1,60);theCols[20] = new Array('2017.09',1,60);theCols[21] = new Array('2017.12',1,60);theCols[22] = new Array('2018.03',1,60);theCols[23] = new Array('2018.06',1,60);theCols[24] = new Array('2018.09',1,60);theCols[25] = new Array('2018.12',1,60);theCols[26] = new Array('2019.03',1,60);theCols[27] = new Array('2019.06',1,60);theCols[28] = new Array('2019.09',1,60);theCols[29] = new Array('2019.12',1,60);theCols[30] = new Array('2020.03',1,60);var theRows = new Array();
theRows[0] = new Array ('<b>'+h+'30>ANA</B></a>','1,114,919,783.60','1,142,792,778.19','1,091,028,645.38','991,850,000.48','796,800,000.38','697,200,000.34','751,150,000.36','723,720,000.33','888,000,000.40','790,320,000.36','883,560,000.40','927,960,000.42','737,040,000.33','879,120,000.40','914,640,000.41','927,960,000.42','1,172,160,000.53','1,416,360,000.64','1,589,520,000.72','1,552,500,000.41','1,972,500,000.53','2,520,000,000.67','2,160,000,000.58','2,475,000,000.66','2,010,000,000.54','2,250,000,000.60','2,077,500,000.55','2,332,500,000.62','3,270,000,000.87','2,347,500,000.63');
theRows[1] = new Array ('<b>'+h+'89>DEN</B></a>','55,200,000.00','55,920,000.00','45,960,000.00','42,600,000.00','35,760,000.00','39,600,000.00','40,200,000.00','47,700,000.00','50,460,000.00','45,300,000.00','41,760,000.00','59,340,000.00','66,600,000.00','97,020,000.00','81,060,000.00','69,300,000.00','79,800,000.00','68,400,000.00','66,900,000.00','66,960,000.00','71,220,000.00','71,520,000.00','71,880,000.00','60,600,000.00','69,120,000.00','62,640,000.00','57,180,000.00','89,850,000.00','125,100,000.00','85,350,000.00');
theRows[2] = new Array ('<b>'+h+'269>SIS</B></a>','4,425,000,000.00','4,695,000,000.00','4,050,000,000.00','4,367,380,000.00','4,273,120,000.00','3,644,720,000.00','4,681,580,000.00','4,913,000,000.00','6,188,000,000.00','5,457,000,000.00','6,137,000,000.00','5,453,000,000.00','6,061,000,000.00','6,954,000,000.00','6,745,000,000.00','6,519,000,000.00','7,851,500,000.00','8,548,500,000.00','9,430,000,000.00','9,225,000,000.00','10,575,000,000.00','11,610,000,000.00','9,517,500,000.00','13,140,000,000.00','12,757,500,000.00','13,117,500,000.00','11,677,500,000.00','10,507,500,000.00','11,857,500,000.00','9,315,000,000.00');
theRows[3] = new Array ('<b>'+h+'297>TRK</B></a>','1,692,579,200.00','1,983,924,800.00','1,831,315,200.00','1,704,000,000.00','1,803,400,000.00','1,498,100,000.00','1,803,400,000.00','1,884,450,000.00','2,542,160,000.00','2,180,050,000.00','2,069,200,000.00','1,682,600,000.00','1,619,950,000.00','1,852,650,000.00','2,040,600,000.00','2,315,700,000.00','2,641,200,000.00','2,938,800,000.00','3,599,100,000.00','4,101,900,000.00','5,220,600,000.00','5,808,200,000.00','4,689,500,000.00','5,375,000,000.00','3,787,500,000.00','4,150,000,000.00','3,662,500,000.00','3,712,500,000.00','4,375,000,000.00','3,587,500,000.00');
var thetable=new mytable();thetable.tableWidth=650;thetable.shownum=false;thetable.controlaccess=true;thetable.visCols=new Array(true,true,true,true,true);thetable.initsort=new Array(0,-1);thetable.inittable();thetable.refreshTable();</script>
"""
## Make a dummy list of scripts
scripts = [s for _ in range(10)]

According to the provided <script> in your question, you can do something like code below to have a list of Dates for each name ANA, DEN ..:
for _ in range(1, len(aaa.split("<b>'"))-1):
s = aaa.split("<b>'")[_].split("'")
print(_)
lst = []
for i in s:
if "</B>" in i:
name = i.split('>')[1].split("<")[0]
print("{} = ".format(name), end="")
if any(j.isdigit() for j in i) and ',' in i:
lst.append(i)
print(lst)
It's just an example code, so it's not that beautiful :)
Hope this will help you.

Python: correct format on input to datagridview

I want to add rows to a datagridview "manually". I tried converting the following code to python: https://learn.microsoft.com/en-us/dotnet/framework/winforms/controls/how-to-manipulate-rows-in-the-windows-forms-datagridview-control
However, I struggle with adding rows. The following doesn't work:
for j in range(len(signals)):
self._dataGridView1.Rows.Add(signals[j])
The following code does work, but is not dynamically enough as I don't know how many elements there will be:
for j in range(len(signals)):
self._dataGridView1.Rows.Add(signals[j][0], signals[j][1], signals[j][2], signals[j][3])
How should I fix this? I tried tuple, but the result were a tuple with all the info shown in the first cell instead of spread over the columns.
I would not like to add packages, as this is to be run within revid dynamo among several users, and I cannot convince everyone to install packages.
full code for context:
import clr
clr.AddReference('System.Windows.Forms')
clr.AddReference('System.Drawing')
clr.AddReference('System.Data')
clr.AddReference('RevitAPIUI')
from Autodesk.Revit.UI import TaskDialog
from System.Windows.Forms import *
from System.Drawing import (
Point, Size,
Font, FontStyle,
GraphicsUnit
)
from System.Data import DataSet
from System.Data.Odbc import OdbcConnection, OdbcDataAdapter
msgBox = TaskDialog
headers = IN[0]
signals = IN[1]
class DataGridViewQueryForm(Form):
def __init__(self):
self.Text = 'Signals'
self.ClientSize = Size(942, 255)
self.MinimumSize = Size(500, 200)
self.setupDataGridView()
def setupDataGridView(self):
self._dataGridView1 = DataGridView()
self._dataGridView1.AllowUserToOrderColumns = True
self._dataGridView1.ColumnHeadersHeightSizeMode = DataGridViewColumnHeadersHeightSizeMode.AutoSize
self._dataGridView1.Dock = DockStyle.Fill
self._dataGridView1.Location = Point(0, 111)
self._dataGridView1.Size = Size(506, 273)
self._dataGridView1.TabIndex = 3
self._dataGridView1.ColumnCount = len(headers)
self._dataGridView1.ColumnHeadersVisible = True
for i in range(len(headers)):
self._dataGridView1.Columns[i].Name = headers[i]
for j in range(len(signals)):
self._dataGridView1.Rows.Add(signals[j][0], signals[j][1], signals[j][2], signals[j][3])
self.Controls.Add(self._dataGridView1)
Application.Run(DataGridViewQueryForm())

Figured it out. Had to use System.Array.
from System import Array
code changes:
array_str = Array.CreateInstance(str, len(headers))
for j in range(len(signals)):
for k in range(len(headers)):
array_str[k] = signals[j][k]
self._dataGridView1.Rows.Add(array_str)

Not able to save .xlsx file on local which I am trying to create/generate using XlsXcessive python

While running following sample code I am getting error as "save is not defined."
That is why I added from xlsxcessive.xlsx import save.
But still it is not able to save on local machine.
Is this error of Python API or am I doing any mistake in Coding?
"""Just a simple example of XlsXcessive API usage."""
from xlsxcessive.xlsx import Workbook
from xlsxcessive.worksheet import Cell
**from xlsxcessive.xlsx import save**
import decimal
wb = Workbook()
sheet = wb.new_sheet('Test Sheet')
# a shared format
bigguy = wb.stylesheet.new_format()
bigguy.font(size=24)
bigguy.align('center')
# add a border
bigguy.border(top="medium", bottom="medium")
# set a builtin number format
bigguy.number_format('0.00')
# another shared format
boldfont = wb.stylesheet.new_format()
boldfont.font(bold=True)
# and another
highprec = wb.stylesheet.new_format()
# set a custom number format on the shared format
highprec.number_format("0.000")
# the API supports adding rows
row1 = sheet.row(1)
# rows support adding cells - cells can currently store strings, numbers
# and formulas.
a1 = row1.cell("A1", "Hello, World!", format=boldfont)
row1.cell("C1", 42.0, format=bigguy)
# cells can be merged with other cells - there is no checking on invalid merges
# though. merge at your own risk!
a1.merge(Cell('B1'))
# adding rows is easy
row2 = sheet.row(2)
row2.cell("B2", "Foo")
row2.cell("C2", 1, format=bigguy)
# formulas are written as strings and can have default values
shared_formula = sheet.formula("SUM(C1, C2)", 43.0, shared=True)
row3 = sheet.row(3)
row3.cell("C3", shared_formula, format=bigguy)
# you can work with cells directly on the sheet
sheet.cell('D1', 12.0005, format=highprec)
sheet.cell('D2', 11.9995, format=highprec)
sheet.cell('D3', shared_formula, format=highprec)
# and directly via row and column indicies
sheet.cell(coords=(0, 4), value=40)
sheet.cell(coords=(1, 4), value=2)
sheet.cell(coords=(2, 4), value=shared_formula)
# you can share a formula in a non-contiguous range of cells
times_two = sheet.formula('PRODUCT(A4, 2)', shared=True)
sheet.cell('A4', 12)
sheet.cell('B4', times_two)
sheet.cell('C4', 50)
sheet.cell('D4', times_two)
# iteratively adding data is easy now
for rowidx in xrange(5,10):
for colidx in xrange(5, 11, 2):
sheet.cell(coords=(rowidx, colidx), value=rowidx*colidx)
# set column widths
sheet.col(2, width=5)
# write unicode value
sheet.cell('G2', value=u"43\u00b0")
if __name__ == '__main__':
import os
import sys
from xlsxcessive.xlsx import save
if len(sys.argv) == 1:
print "USAGE: python sample.py NEWFILEPATH"
print "Writes a sample .xlsx file to NEWFILEPATH"
raise SystemExit(1)
if os.path.exists(sys.argv[1]):
print "Aborted. File %s already exists." % sys.argv[1]
raise SystemExit(1)
stream = None
if sys.argv[1] == '-':
stream = sys.stdout
# wb is the Workbook created above
save(wb, sys.argv[1], stream)
Note: Tried following also
# local file
save(workbook, 'financials.xlsx')
# stream
save(workbook, 'financials.xlsx', stream=sys.stdout)