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How I automate my python script or get multiple entries in one run?

I am running the following python script:
import random
result_str = ''.join((random.choice('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!##$%^&*()') for i in range(8)))
with open('file_output.txt','a') as out:
out.write(f'{result_str}\n')
Is there a way I could automate this script to run automatically? or If I can get multiple outputs instantly?
Ex. Right now the output stores itself in the file one by one
kmfd5s6s
But if somehow I can get 1,000,000 entries in the file on one click and there is no duplication.

Same logic as given by PangolinPaws,but since you require it for a 1,000,000 entries, which is quite large, using numpy could be more effecient. Also, replacing random.choice() with random.choices() with k=8, inorder to avoid the for loop to generate the string.
import random
import numpy as np
a = np.array([])
for i in range(1000000):
str = ''.join((random.choices('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!##$%^&*()', k = 8)))
if str not in a:
a = np.append(a,str)
np.savetxt("generate_strings.csv", a, fmt='%s')

You need to nest your out.write() in a loop, something like this, to make it happen multiple times:
import random
with open('file_output.txt','a') as out:
for x in range(1000): # the number of lines you want in the output file
result_str = ''.join((random.choice('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!##$%^&*()') for i in range(8)))
out.write(f'{result_str}\n')
However, while unlikely, it is possible that you could end up with duplicate rows. To avoid this, you can generate and store your random strings in a loop and check for duplicates as you go. Once you have enough, write them all to the file outside the loop:
import random
results = []
while len(results) < 1000: # the number of lines you want in the output file
result_str = ''.join((random.choice('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!##$%^&*()') for i in range(8)))
if result_str not in results: # check if the generated result_str is a duplicate
results.append(result_str)
with open('file_output.txt','a') as out:
out.write( '\n'.join(results) )

How to read in multiple documents with same code?

So I have a couple of documents, of which each has a x and y coordinate (among other stuff). I wrote some code which is able to filter out said x and y coordinates and store them into float variables.
Now Ideally I'd want to find a way to run the same code on all documents I have (number not fixed, but let's say 3 for now), extract x and y coordinates of each document and calculate an average of these 3 x-values and 3 y-values.
How would I approach this? Never done before.
I successfully created the code to extract the relevant data from 1 file.
Also note: In reality each file has more than just 1 set of x and y coordinates but this does not matter for the problem discussed at hand.
I'm just saying that so that the code does not confuse you.
with open('TestData.txt', 'r' ) as f:
full_array = f.readlines()
del full_array[1:31]
del full_array[len(full_array)-4:len(full_array)]
single_line = full_array[1].split(", ")
x_coord = float(single_line[0].replace("1 Location: ",""))
y_coord = float(single_line[1])
size = float(single_line[3].replace("Size: ",""))
#Remove unecessary stuff
category= single_line[6].replace(" Type: Class: 1D Descr: None","")
In the end I'd like to not have to write the same code for each file another time, especially since the amount of files may vary. Now I have 3 files which equals to 3 sets of coordinates. But on another day I might have 5 for example.

Use os.walk to find the files that you want. Then for each file do you calculation.
https://docs.python.org/2/library/os.html#os.walk

First of all create a method to read a file via it's file name and do the parsing in your way. Now iterate through the directory,I guess files are in the same directory.
Here is the basic code:
import os
def readFile(filename):
try:
with open(filename, 'r') as file:
data = file.read()
return data
except:
return ""
for filename in os.listdir('C:\\Users\\UserName\\Documents'):
#print(filename)
data=readFile( filename)
print(data)
#parse here
#do the calculation here

For-loop over multiple files in same directory in Python

So I already tried to check other questions here about (almost) the same topic, however I did not find something that solves my problem.
Basically, I have a piece of code in Python that tries to open the file as a data frame and execute some eye tracking functions (PyGaze). I have 1000 files that I need to analyse and wanted to create a for-loop to execute my code on all the files automatically.
The code is the following:
os.chdir("/Users/Documents//Analyse/Eye movements/Python - Eye Analyse")
directory = '/Users/Documents/Analyse/Eye movements/R - Filtering Data/Filtered_data/Filtered_data_test'
for files in glob.glob(os.path.join(directory,"*.csv")):
#Downloas csv, plot
df = pd.read_csv(files, parse_dates = True)
#Plot raw data
plt.plot(df['eye_x'],df['eye_y'], 'ro', c="red")
plt.ylim([0,1080])
plt.xlim([0,1920])
#Fixation analysis
from detectors import fixation_detection
fixations_data = fixation_detection(df['eye_x'],df['eye_y'], df['time'],maxdist=25, mindur=100)
Efix_data = fixations_data[1]
numb_fixations = len(Efix_data) #number of fixations
fixation_start = [i[0] for i in Efix_data]
fixation_stop = [i[1] for i in Efix_data]
fixation = {'start' : fixation_start, 'stop': fixation_stop}
fixation_frame = pd.DataFrame(data=fixation)
fixation_frame['difference'] = fixation_frame['stop'] - fixation_frame['start']
mean_fixation_time = fixation_frame['difference'].mean() #mean fixation time
final = {'number_fixations' : [numb_fixations], 'mean_fixation_time': [mean_fixation_time]}
final_frame = pd.DataFrame(data=final)
#write everything in one document
final_frame.to_csv("/Users/Documents/Analyse/Eye movements/final_data.csv")
The code is running (no errors), however : it only runs for the first file. The code is not ran for the other files present in the folder/directory.
I do not see where my mistake is?

Your output file name is constant, so it gets overwritten with each iteration of the for loop. Try the following instead of your final line, which opens the file in "append" mode instead:
#write everything in one document
with open("/Users/Documents/Analyse/Eye movements/final_data.csv", "a") as f:
final_frame.to_csv(f, header=False)

seek. function without output

tips_file = open('code_tips.txt', 'w+')
tips_file.write('-use simple function and variable names\n-comment code\n-organize code into functions\n')
tips_file.seek(0)
tips_text = tips_file.read()
print (tips_text)
There is no output for the above code.
But for the following codes, there is output
tips_file.seek(13)
tips_text = tips_file.read()
print(tips_text)
I am wondering why there is difference
I just figure out that if I separate the code into 2 cells
tips_file = open('code_tips.txt', 'w+')
tips_file.write('-use simple function and variable names\n-
commentcode\n-organize code into functions\n')
and
tips_file.seek(0)
tips_text = tips_file.read()
print(tips_text)
Then I can deliver output if I run the first cell once and the second cell twice. If only run the second cell for once, it gives no output as the same of the problem. I am really confused.

Having an issue with using median function in numpy

I am having an issue with using the median function in numpy. The code used to work on a previous computer but when I tried to run it on my new machine, I got the error "cannot perform reduce with flexible type". In order to try to fix this, I attempted to use the map() function to make sure my list was a floating point and got this error message: could not convert string to float: .
Do some more attempts at debugging, it seems that my issue is with my splitting of the lines in my input file. The lines are of the form: 2456893.248202,4.490 and I want to split on the ",". However, when I print out the list for the second column of that line, I get
4
.
4
9
0
so it seems to somehow be splitting each character or something though I'm not sure how. The relevant section of code is below, I appreciate any thoughts or ideas and thanks in advance.
def curve_split(fn):
with open(fn) as f:
for line in f:
line = line.strip()
time,lc = line.split(",")
#debugging stuff
g=open('test.txt','w')
l1=map(lambda x:x+'\n',lc)
g.writelines(l1)
g.close()
#end debugging stuff
return time,lc
if __name__ == '__main__':
# place where I keep the lightcurve files from the image subtraction
dirname = '/home/kuehn/m4/kepler/subtraction/detrending'
files = glob.glob(dirname + '/*lc')
print(len(files))
# in order to create our lightcurve array, we need to know
# the length of one of our lightcurve files
lc0 = curve_split(files[0])
lcarr = np.zeros([len(files),len(lc0)])
# loop through every file
for i,fn in enumerate(files):
time,lc = curve_split(fn)
lc = map(float, lc)
# debugging
print(fn[5:58])
print(lc)
print(time)
# end debugging
lcm = lc/np.median(float(lc))
#lcm = ((lc[qual0]-np.median(lc[qual0]))/
# np.median(lc[qual0]))
lcarr[i] = lcm
print(fn,i,len(files))