Develop Reference

Python convert.txt to .csv without having a specific file name

I am currently working on an application that will convert a messy text file full of data into an organized CSV. It currently works well but when I convert the text file to csv I want to be able to select a text file with any name. The way my code is currently written, I have to name the file "file.txt". How do I go about this?
Here is my code. I can send the whole script if necessary. Just to note this is a function that is linked to a tkinter button. Thanks in advance.
def convert():
df = pd.read_csv("file.txt",delimiter=';')
df.to_csv('Cognex_Data.csv')

Try defining your function as follow:
def convert(input_filename, output_filename='Cognex_Data.csv'):
df = pd.read_csv(input_filename, delimiter=';')
df.to_csv(output_filename)
And for instance use it as follow:
filename = input("Enter filename: ")
convert(filename, "Cognex_Data.csv")
You can also put "Cognex_Data.csv" as a default value for the output_filename argument in the convert function definition (as done above).
And finally you can use any way you like to get the filename (for instance tkinter.filedialog as suggested by matszwecja).

I haven't worked with tkinter, but PySimplyGUI, which to my knowledge is built on tkinter so you should have the possibility to extract the variables that correspond to the name of the file selected by the user. That's what I'm doing using PySimpleGUIon a similar problem.
Then, extract the file name selected by the user through the prompt and pass it as an argument to your function:
def convert(file):
df = pd.read_csv("{}.txt".format(file), delimiter=';')
df.to_csv('Cognex_Data.csv')

When I import an array from another file, do I take just the data from it or need to "build" the array with how the original file build it?

Sorry if the question is not well formulated, will reformulated if necessary.
I have a file with an array that I filled with data from an online json db, I imported this array to another file to use its data.
#file1
response = urlopen(url1)
a=[]
data = json.loads(response.read())
for i in range(len(data)):
a.append(data[i]['name'])
i+=1
#file2
from file1 import a
'''do something with "a"'''
Does importing the array means I'm filling the array each time I call it in file2?
If that is the case, what can I do to just keep the data from the array without "building" it each time I call it?

If you saved a to a file, then read a -- you will not need to rebuild a -- you can just open it. For example, here's one way to open a text file and get the text from the file:
# set a variable to be the open file
OpenFile = open(file_path, "r")
# set a variable to be everything read from the file, then you can act on that variable
file_guts = OpenFile.read()

From the Python docs on the Modules section - link - you can read:
When you run a Python module with
python fibo.py <arguments>
the code in the module will be executed, just as if you imported it
This means that importing a module has the same behavior as running it as a regular Python script, unless you use the __name__ as mentioned right after this quotation.
Also, if you think about it, you are opening something, reading from it, and then doing some operations. How can you be sure that the content you are now reading from is the same as the one you had read the first time?

Parsing YAML out of a Markdown file

I am working with some legacy code that I have inherited (ie, many of these design decisions were not mine).
The code takes a directory organized into subdirectories with markdown files, and compiles them into one large markdown file (using Markdown-PP: https://github.com/jreese/markdown-pp). Then it converts this file into HTML (using pandoc: https://pandoc.org/), and finally into a PDF (using wkhtmltopdf: https://wkhtmltopdf.org/).
The problem that I am running into is that many of the original markdown files have YAML metadata headers. When stitched together by Markdown-PP, the large markdown ends up with numerous YAML metadata blocks interspersed throughout. Most of this metadata is lost when converting into HTML because of the way pandoc processes YAML (many of the headers use the same key names, and pandoc combines the separate YAML headers and only preserves the first value of the corresponding key).
I originally had no YAML appearing in the HTML, but was able to change this by correctly modifying the HTML template for pandoc. But I only get the first value for each corresponding key. It was not clear if there was a way around this in pandoc, so I instead looked into trying to process the YAML into HTML before the pandoc step. I have tried parsing the YAML in the combined markdown using PyYAML (yaml.load_all()) but only get the first YAML block to appear.
An example of a YAML block:
---
author: foo
size_minimum: 100
time_req_minutes: 120
# and so on
---
The issue being that each one of 20+ modules in the final document have this associated metadata.
To try to parse the YAML, I was using code borrowed from this post: Is it possible to use PyYAML to read a text file written with a "YAML front matter" block inside?
with a few modifications.
import yaml
import sys
def get_yaml(f):
pointer = f.tell()
if f.readline() != '---\n':
f.seek(pointer)
return ''
readline = iter(f.readline, '')
readline = iter(readline.__next__, '---\n') #underscores needed for Python3?
return ''.join(readline)
# Remove sys.argv, not sure what it was doing
with open(filepath, encoding='UTF-8') as f:
config = list(yaml.load_all(get_yaml(f), Loader=yaml.SafeLoader)) # Load all to get all the YAML documents, Loader option required for most recent PyYAML, and list because it was originally returning a generator object
text = f.read()
print("TEXT from", f)
#print(text)
print("CONFIG from", f)
print(config)
But even this only resulted in the first YAML block being read and output.
I would like to able to parse the YAML from the large markdown files, and replace it in the correct place with the corresponding HTML. I just am not sure if these (or any) packages have the capability of doing so. It may be that I just need to manually change the YAML to HTML in the original Markdown files (time intensive, but I could probably already be done with it if I had started that way).

What about this library: https://github.com/eyeseast/python-frontmatter
It parses both the front-matter and the Markdown in the file, placing the Markdown part in the content attribute of the resulting object.
Works with both front-matter containing and front-matterless (is there such a word?) files.

How to read and print the contents of a ttf file?

Is there any way that I can open, read and write a ttf file?
Example:
with open('xyz.ttf') as f:
content = f.readline()
print(content)
A bit more:
If I open a .ttf (font) file with windows font viewer we see the following image
From this I like to extract following lines as text, with proper style.

What is exactly inside this file with *.ttf extension. I think you need to add more details of the input and output. If you reffering to a font type database you must first find a module/package to open and read it, since *.ttf isn't a normal text file.
Read the given links and install the required packages first:
https://pypi.python.org/pypi/FontTools
Then, as suggested:
from fontTools.ttLib import TTFont
font = TTFont('/path/to/font.ttf')
print(font)
<fontTools.ttLib.TTFont object at 0x10c34ed50>
If you need help with something else trying putting the input and expected output.
Other links:
http://www.starrhorne.com/2012/01/18/how-to-extract-font-names-from-ttf-files-using-python-and-our-old-friend-the-command-line.html
Here is a another useful python script:
https://gist.github.com/pklaus/dce37521579513c574d0

change keyword value in the header of a FITS file

I am trying to change the value of a keyword in the header of a FITS file.
Quite simple, this is the code:
import pyfits
hdulist = pyfits.open('test.fits') # open a FITS file
prihdr = hdulist[1].header
print prihdr['AREASCAL']
effarea = prihdr['AREASCAL']/5.
print effarea
prihdr['AREASCAL'] = effarea
print prihdr['AREASCAL']
I print the steps many times to check the values are correct. And they are.
The problem is that, when I check the FITS file afterwards, the keyword value in the header is not changed. Why does this happen?

You are opening the file in read-only mode. This won't prevent you from modifying any of the in-memory objects, but closing or flushing to the file (as suggested in other answers to this question) won't make any changes to the file. You need to open the file in update mode:
hdul = pyfits.open(filename, mode='update')
Or better yet use the with statement:
with pyfits.open(filename, mode='update') as hdul:
# Make changes to the file...
# The changes will be saved and the underlying file object closed when exiting
# the 'with' block

You need to close the file, or explicitly flush it, in order to write the changes back:
hdulist.close()
or
hdulist.flush()

Interestingly, there's a tutorial for that in the astropy tutorials github. Here is the ipython notebook viewer version of that tutorial that explains it all.
Basically, you are noticing that the python instance does not interact with disk instance. You have to save a new file or overwrite the old one explicitly.