Hiển thị các bài đăng có nhãn pdf. Hiển thị tất cả bài đăng
Hiển thị các bài đăng có nhãn pdf. Hiển thị tất cả bài đăng

Thứ Sáu, 16 tháng 12, 2016

[xtopdf] Publish DSV data (Delimiter-Separated Values) to PDF

By Vasudev Ram



Here is another in my series of posts about xtopdf, my Python toolkit for PDF creation from other data/file formats. This one is for conversion of DSV data to PDF.

DSV stands for Delimiter-Separated Values, and is a superset or generalization of formats like CSV (Comma-Separated Values) and TSV (Tab-Separated Values). These formats are commonly used in general computing (business, scientific, etc.) and also in data science.

This program, DSVToPDF.py, builds upon the code in the read_dsv.py program in this recent post:

Processing DSV data (Delimiter-Separated Values) with Python

It reads DSV content either from filenames given as command-line arguments, or from standard input, and converts each such input into a PDF file with the same name as the DSV file, but with added extension ".pdf". In the case of standard input, since there is no DSV filename to use as the base, the PDF file is named dsv_output.pdf.

Here is the code for DSVToPDF.py:
from __future__ import print_function

"""
DSVToPDF.py
Author: Vasudev Ram
Web site: https://vasudevram.github.io
Blog: https://jugad2.blogspot.com
Product store: https://gumroad.com/vasudevram
Twitter: https://mobile.twitter.com/vasudevram
Purpose: Show how to publish DSV data (Delimiter-Separated Values)
to PDF, using the xtopdf toolkit.
Requires:
- ReportLab: https://www.reportlab.com/ftp/reportlab-1.21.1.tar.gz
- xtopdf: https://bitbucket.org/vasudevram/xtopdf
First install ReportLab, then install xtopdf, using instructions here:
http://jugad2.blogspot.in/2012/07/guide-to-installing-and-using-xtopdf.html
The DSV data can be read from either files or standard input.
The delimiter character is configurable by the user and can
be specified as either a character or its ASCII code.
References:
DSV format: https://en.wikipedia.org/wiki/Delimiter-separated_values
TAOUP (The Art Of Unix Programming): Data File Metaformats:
http://www.catb.org/esr/writings/taoup/html/ch05s02.html
ASCII table: http://www.asciitable.com/
"""

import sys
import string
from PDFWriter import PDFWriter

def err_write(message):
sys.stderr.write(message)

def error_exit(message):
err_write(message)
sys.exit(1)

def usage(argv, verbose=False):
usage1 = \
"{}: publish DSV (Delimiter-Separated-Values) data to PDF.\n".format(argv[0])
usage2 = "Usage: python" + \
" {} [ -c delim_char | -n delim_code ] [ dsv_file ] ...\n".format(argv[0])
usage3 = [
"where one of either the -c or -n option must be given,\n",
"delim_char is a single ASCII delimiter character, and\n",
"delim_code is a delimiter character's ASCII code.\n",
"Text lines will be read from specified DSV file(s) or\n",
"from standard input, split on the specified delimiter\n",
"specified by either the -c or -n option, processed, and\n",
"written, formatted, to PDF files with the name dsv_file.pdf.\n",
]
usage4 = "Use the -h or --help option for a more detailed help message.\n"
err_write(usage1)
err_write(usage2)
if verbose:
'''
for line in usage3:
err_write(line)
'''
err_write(''.join(usage3))
if not verbose:
err_write(usage4)

def str_to_int(s):
try:
return int(s)
except ValueError as ve:
error_exit(repr(ve))

def valid_delimiter(delim_code):
return not invalid_delimiter(delim_code)

def invalid_delimiter(delim_code):
# Non-ASCII codes not allowed, i.e. codes outside
# the range 0 to 255.
if delim_code < 0 or delim_code > 255:
return True
# Also, don't allow some specific ASCII codes;
# add more, if it turns out they are needed.
if delim_code in (10, 13):
return True
return False

def dsv_to_pdf(dsv_fil, delim_char, pdf_filename):
with PDFWriter(pdf_filename) as pw:
pw.setFont("Courier", 12)
pw.setHeader(pdf_filename[:-4] + " => " + pdf_filename)
pw.setFooter("Generated by xtopdf: https://google.com/search?q=xtopdf")
for idx, lin in enumerate(dsv_fil):
fields = lin.split(delim_char)
assert len(fields) > 0
# Knock off the newline at the end of the last field,
# since it is the line terminator, not part of the field.
if fields[-1][-1] == '\n':
fields[-1] = fields[-1][:-1]
# Treat a blank line as a line with one field,
# an empty string (that is what split returns).
pw.writeLine(' - '.join(fields))

def main():
# Get and check validity of arguments.
sa = sys.argv
lsa = len(sa)
if lsa == 1:
usage(sa)
sys.exit(0)
elif lsa == 2:
# Allow the help option with any letter case.
if sa[1].lower() in ("-h", "--help"):
usage(sa, verbose=True)
sys.exit(0)
else:
usage(sa)
sys.exit(0)

# If we reach here, lsa is >= 3.
# Check for valid mandatory options (sic).
if not sa[1] in ("-c", "-n"):
usage(sa, verbose=True)
sys.exit(0)

# If -c option given ...
if sa[1] == "-c":
# If next token is not a single character ...
if len(sa[2]) != 1:
error_exit(
"{}: Error: -c option needs a single character after it.".format(sa[0]))
if not sa[2] in string.printable:
error_exit(
"{}: Error: -c option needs a printable ASCII character after it.".format(\
sa[0]))
delim_char = sa[2]
# else if -n option given ...
elif sa[1] == "-n":
delim_code = str_to_int(sa[2])
if invalid_delimiter(delim_code):
error_exit(
"{}: Error: invalid delimiter code {} given for -n option.".format(\
sa[0], delim_code))
delim_char = chr(delim_code)
else:
# Checking for what should not happen ... a bit of defensive programming here.
error_exit("{}: Program error: neither -c nor -n option given.".format(sa[0]))

try:
# If no filenames given, do sys.stdin to PDF ...
if lsa == 3:
print("Converting content of standard input to PDF.")
dsv_fil = sys.stdin
dsv_to_pdf(dsv_fil, delim_char, "dsv_output.pdf")
dsv_fil.close()
print("Output is in dsv_output.pdf")
# else (filenames given), convert them to PDFs ...
else:
for dsv_filename in sa[3:]:
pdf_filename = dsv_filename + ".pdf"
print("Converting file {} to PDF.", dsv_filename)
dsv_fil = open(dsv_filename, 'r')
dsv_to_pdf(dsv_fil, delim_char, pdf_filename)
dsv_fil.close()
print("Output is in {}".format(pdf_filename))
except IOError as ioe:
error_exit("{}: Error: {}".format(sa[0], repr(ioe)))

if __name__ == '__main__':
main()
Note the commented and uncommented lines in the "if verbose:" clause in the usage() function. The latter is shorter, and, methinks, a tad more Pythonic.
I did a sample run with the data shown in the image at the top of this post, which uses the pipe character (|) as the delimiter between fields (124 is the ASCII code for the pipe character):
$ python DSVToPDF.py -n 124 file4.dsv
And here is a cropped screenshot of the PDF output as viewed in Foxit PDF Reader:


- Enjoy.

- Vasudev Ram - Online Python training and consulting

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Thứ Hai, 5 tháng 12, 2016

[xtopdf] Wildcard text files to PDF with xtopdf and glob

By Vasudev Ram



First joker card image attribution

This is another in my series of applications that use xtopdf (source), my Python toolkit for PDF creation from other formats.

[ Here's a good overview of xtopdf, its uses, supported platforms and formats, etc. ]

I called this app WildcardTextToPDFpy.. It lets you specify a wildcard for text files, and then converts each of the text files matching the wildcard (like grades*2016.txt or monthly*sales.txt) [1], into corresponding PDF files - with the same names but with '.pdf' appended.

[1] For example, the wildcard grades*2016.txt could match grades-math-2016.txt and grades-bio-2016.txt (think a school or college), while monthly*sales.txt might match monthly-car-sales.txt and monthly-bike-sales.txt (think a vehicle dealership), so a PDF file will be generated for each text file matching the given wildcard.

The program uses the iglob function from the glob module in Python's standard library, similar to how this recent other post:

Simple directory lister with multiple wildcard arguments

used the glob function. The difference is that glob returns a list, while iglob returns a generator, so it will return the matching filenames lazily, on demand, as shown here:
$ python
>>> g1 = glob.glob('text*.txt')
>>> g1
['text1.txt', 'text2.txt', 'text3.txt']
>>>>>> g2 = glob.iglob('text*.txt')
>>> g2
<generator object iglob at 0x027C2850>
>>> next(g2)
'text1.txt'
>>> for f in g2:
... print f
...
text2.txt
text3.txt

Here is the code for WildcardTextToPDF.py:
from __future__ import print_function

# WildcardTextToPDF.py
# Convert the text files specified by a filename wildcard,
# like '*.txt' or 'foo*bar*baz.txt', to PDF files.
# Each text file's content goes to a separate PDF file, with the
# PDF file name being the full text file name (including the
# '.txt' part), with '.pdf' appended.
# Requires:
# - xtopdf: https://bitbucket.org/vasudevram/xtopdf
# - ReportLab: https://www.reportlab.com/ftp/reportlab-1.21.1.tar.gz
# Author: Vasudev Ram
# Copyright 2016 Vasudev Ram
# Product store: https://gumroad.com/vasudevram
# Web site: https://vasudevram.github.io
# Blog: http://jugad2.blogspot.com

import sys
import os
import glob
from PDFWriter import PDFWriter

def usage(argv):
sys.stderr.write("Usage: python {} txt_filename_pattern\n".format(argv[0]))
sys.stderr.write("E.g. python {} foo*.txt\n".format(argv[0]))

def text_to_pdf(txt_filename):
pw = PDFWriter(txt_filename + '.pdf')
pw.setFont('Courier', 12)
pw.setHeader('{} converted to PDF'.format(txt_filename))
pw.setFooter('PDF conversion by xtopdf: https://google.com/search?q=xtopdf')

with open(txt_filename) as txt_fil:
for line in txt_fil:
pw.writeLine(line.strip('\n'))
pw.savePage()

def main():
if len(sys.argv) != 2:
usage(sys.argv)
sys.exit(0)

try:
for filename in glob.glob(sys.argv[1]):
print("Converting {} to {}".format(filename, filename + '.pdf'))
text_to_pdf(filename)
except Exception as e:
print("Caught Exception: type: {}, message: {}".format(\
e.__class__, str(e)))

if __name__ == '__main__':
main()
And here are the relevant files before and after running the program, with the program's output in between:
$ dir text*.txt/b
text1.txt
text2.txt
text3.txt

$ python WildcardTextToPDF2.py text*.txt
Converting text1.txt to text1.txt.pdf
Converting text2.txt to text2.txt.pdf
Converting text3.txt to text3.txt.pdf

$ dir text?.txt*/od/b
text1.txt
text2.txt
text3.txt
text1.txt.pdf
text2.txt.pdf
text3.txt.pdf
Finally, here's a cropped screenshot of the third output file, text3.txt.pdf, in Foxit PDF Reader (a lightweight PDF reader that I use):


Also look up:

[xtopdf] Batch convert text files to PDF (with xtopdf and fileinput)

for another variation on the approach to converting text files to PDF.

Speaking of generators, also check out this other post about them:

Python generators are pluggable

The image at the top of the post is of the earliest Joker card by Samuel Hart c. 1863, according to Wikipedia:

Joker (playing card)

Enjoy.

- Vasudev Ram - Online Python training and consulting

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Thứ Ba, 25 tháng 10, 2016

Read from CSV with D, write to PDF with Python

By Vasudev Ram


CSV => PDF

Here is another in my series of applications of xtopdf, my PDF creation toolkit for Python (xtopdf source here).

This xtopdf application is actually a pipeline (nothing Unix-specific though, will work on both *nix and Windows) - a D program reading CSV data and sending it to a Python program, which writes the data to PDF.

The D program, read_csv.d, reads CSV data from a .csv file, and writes it to standard output.

The Python program, StdinToPDF.py (which is part of the xtopdf toolkit), reads its standard input (which is redirected by the pipeline to come from the D program's standard output) and writes the data it reads, to PDF.

Here is the D program, read_csv.d:
/**************************************************
File: read_csv.d
Purpose: A program to read CSV data from a file and
write it to standard output.
Author: Vasudev Ram
Date created: 2016-10-25
Copyright 2016 Vasudev Ram
Web site: https://vasudevram.github.io
Blog: http://jugad2.blogspot.com
Product store: https://gumroad.com/vasudevram
**************************************************/

import std.algorithm;
import std.array;
import std.csv;
import std.stdio;
import std.file;
import std.typecons;

int main()
{
try {
stderr.writeln("Reading CSV data from file.");
auto file = File("input.csv", "r");
foreach (record;
file.byLine.joiner("\n").csvReader!(Tuple!(string, string, int)))
{
writefln("%s works as a %s and earns $%d per year",
record[0], record[1], record[2]);
}
} catch (CSVException csve) {
stderr.writeln("Caught CSVException: msg = ", csve.msg,
" at row, col = ", csve.row, ", ", csve.col);
} catch (FileException fe) {
stderr.writeln("Caught FileException: msg = ", fe.msg);
} catch (Exception e) {
stderr.writeln("Caught Exception: msg = ", e.msg);
}
return 0;
}
The D program is compiled as usual with:
dmd read_csv.d
I ran it first (only the D program) with an invalid CSV file (it has an extra comma at the start on line 3, which invalidates the data by making "Driver" be in the salary column position), and got the expected error message, which includes the row and column number of the place in the CSV file where the program encountered the error - this is useful for fixing the input data:
$ type input.csv
Jack,Carpenter,40000
Tom,Blacksmith,50000
,Jill,Driver,60000
$ read_csv
Reading CSV data from file.
Jack works as a Carpenter and earns $40000 per year
Tom works as a Blacksmith and earns $50000 per year
Caught CSVException: msg = Unexpected 'D' when converting from type string to type int
at row, col = 3, 3
Then I ran it again, in the regular way, this time with a valid CSV file, and as part of a pipeline, the other pipeline component being StdinToPDF:
$ read_csv | python StdinToPDF.py csv_output.pdf
Reading CSV data from file.
And here is a cropped view of the output as seen in Foxit PDF Reader:


- Enjoy.

- Vasudev Ram - Online Python training and consulting

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Thứ Tư, 28 tháng 9, 2016

Publish Peewee ORM data to PDF with xtopdf

By Vasudev Ram

Peewee => PDF

Peewee is a small, expressive ORM for Python, created by Charles Leifer.

After trying out Peewee a bit, I thought of writing another application of xtopdf (my Python toolkit for PDF creation), to publish Peewee data to PDF. I used an SQLite database underlying the Peewee ORM, but it also supports MySQL and PostgreSQL, per the docs. Here is the program, in file PeeweeToPDF.py:
# PeeweeToPDF.py
# Purpose: To show basics of publishing Peewee ORM data to PDF.
# Requires: Peewee ORM and xtopdf.
# Author: Vasudev Ram
# Copyright 2016 Vasudev Ram
# Web site: https://vasudevram.github.io
# Blog: http://jugad2.blogspot.com
# Product store: https://gumroad.com/vasudevram

from peewee import *
from PDFWriter import PDFWriter

def print_and_write(pw, s):
print s
pw.writeLine(s)

# Define the database.
db = SqliteDatabase('contacts.db')

# Define the model for contacts.
class Contact(Model):
name = CharField()
age = IntegerField()
skills = CharField()
title = CharField()

class Meta:
database = db

# Connect to the database.
db.connect()

# Drop the Contact table if it exists.
db.drop_tables([Contact])

# Create the Contact table.
db.create_tables([Contact])

# Define some contact rows.
contacts = (
('Albert Einstein', 22, 'Science', 'Physicist'),
('Benjamin Franklin', 32, 'Many', 'Polymath'),
('Samuel Johnson', 42, 'Writing', 'Writer')
)

# Save the contact rows to the contacts table.
for contact in contacts:
c = Contact(name=contact[0], age=contact[1], \
skills=contact[2], title=contact[3])
c.save()

sep = '-' * (20 + 5 + 10 + 15)

# Publish the contact rows to PDF.
with PDFWriter('contacts.pdf') as pw:
pw.setFont('Courier', 12)
pw.setHeader('Demo of publishing Peewee ORM data to PDF')
pw.setFooter('Generated by xtopdf: slides.com/vasudevram/xtopdf')
print_and_write(pw, sep)
print_and_write(pw,
"Name".ljust(20) + "Age".center(5) +
"Skills".ljust(10) + "Title".ljust(15))
print_and_write(pw, sep)

# Loop over all rows queried from the contacts table.
for contact in Contact.select():
print_and_write(pw,
contact.name.ljust(20) +
str(contact.age).center(5) +
contact.skills.ljust(10) +
contact.title.ljust(15))
print_and_write(pw, sep)

# Close the database connection.
db.close()
I could have used Python's namedtuple feature instead of tuples, but did not do it for this small program.

I ran the program with:
python PeeweeToPDF.py
Here is a screenshot of the output as seen in Foxit PDF Reader (click image to enlarge):


- Enjoy.

- Vasudev Ram - Online Python training and consulting

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Thứ Ba, 13 tháng 9, 2016

Func-y D + Python pipeline to generate PDF

By Vasudev Ram



Hi, readers,

Here is a pipeline that generates some output from a D (language) program and passes it to a Python program that converts that output to PDF. The D program makes use of a bit of (simple) template programming / generics and a bit of functional programming (using the std.functional module from Phobos, D's standard library).


D => Python


I'm showing this as yet another example of the uses of xtopdf, my Python toolkit for PDF creation, as well as for the D part, which is fun (pun intended :), and because those D features are powerful.

The D program is derived, with some modifications, from a program in this post by Gary Willoughby,

More hidden treasure in the D standard library .

That program demonstrates, among other things, the pipe feature of D from the std.functional module.

First, the D program, student_grades.d:
/*
student_grades.d
Author: Vasudev Ram
Web site: https://vasudevram.github.io
Blog: http://jugad2.blogspot.com
Product store: https://gumroad.com/vasudevram
Adapts code from:
http://nomad.so/2015/08/more-hidden-treasure-in-the-d-standard-library/
*/

import std.stdio;
import std.algorithm;
import std.array;
import std.conv;
import std.functional;

// Set up the functional pipeline by composing some functions.
alias sumString = pipe!(split, map!(to!(int)), sum);

void main(string[] args)
{
// Data to be transformed:
// Each string has the student name followed by
// their grade in 5 subjects.
auto student_grades_list =
[
"A 1 2 3 4 5",
"B 2 3 4 5 6",
"C 3 4 5 6 7",
"D 4 5 6 7 8",
"E 5 6 7 8 9",
];

// Transform the data for each student.
foreach(student_grades; student_grades_list) {
auto student = student_grades[0]; // name
auto total = sumString(student_grades[2..$]); // grade total
writeln("Grade total for student ", student, ": ", total);
}
}
The initial data (which the D program transforms) is hard-coded, but that can easily be changed to read it from a text file, for instance. The program uses pipe() to compose [1] the functions split, map (to int), and sum (some of which are generic / template functions).

So, when it is run, each string (student_grades) of the input array student_grades_list is split (into an array of smaller strings, by space as the delimiter); then each string in the array (except for the first, which is the name), is mapped (converted) to integer; then all the integers are summed up to get the student's grade total; finally these names and totals are written to standard output. That becomes the input to the next stage of the pipeline, the Python program, which does the conversion to PDF.

Build the D program with:
dmd -o- student_grades.d
which gives us the executable, student_grades(.exe).

The Python part of the pipeline is StdinToPDF.py, one of the apps in the xtopdf toolkit, which is designed to be used in pipelines such as the above - basically, any Unix, Windows or Mac OS X pipeline, that generates text as its final output, can be further terminated by StdinToPDF, resulting in conversion of that text to PDF. It is a small Python app written using the core class of the xtopdf library, PDFWriter. Here is the original post about StdinToPDF:

[xtopdf] PDFWriter can create PDF from standard input

Here is the pipeline:
$ student_grades | python StdinToPDF.py sg.pdf

Below is a cropped screenshot of the generated output, sg.pdf, as seen in Foxit PDF Reader.

[1] Speaking of functional composition, you may like to check out this earlier post by me:

fmap(), "inverse" of Python map() function

It's about a different way of composing functions (for certain cases). It also has an interesting comment exchange between me and a reader, who showed both how to do it in Scala, and another way to do it in Python. Also, there is another way to compose functions in D, using a function called compose; it works like pipe, but the composed functions are written in the reverse order. It's in the same D module as pipe, std.functional.

Finally (before I pipe down - for today :), check out this HN comment by me (on another topic), in which I mention and link to multiple other ways of doing pipe-like stuff in Python:

Comment on Streem – a new programming language from Matz

- Enjoy.

- Vasudev Ram - Online Python training and consulting

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Thứ Bảy, 23 tháng 7, 2016

Control break report to PDF with xtopdf

By Vasudev Ram

Hi readers,

Control break reports are very common in data processing, from the earliest days of computing until today. This is because they are a fundamental kind of report, the need for which is ubiquitous across many kinds of organizations.

Here is an example program that generates a control break report and writes it to PDF, using xtopdf, my Python toolkit for PDF creation.

The program is named ControlBreakToPDF.py. It uses xtopdf to generate the PDF output, and the groupby function from the itertools module to handle the control break logic easily.

I've written multiple control-break report generation programs before, including implementing the logic manually, and it can get a little fiddly to get everything just right, particularly when there is more than one level of nesting (i.e. no off-by-one errors, etc.); you have to check for various conditions, set flags, etc.

So it's nice to have Python's itertools.groupby functionality handle it, at least for basic cases. Note that the data needs to be sorted on the grouping key, in order for groupby to work. Here is the code for ControlBreakToPDF.py:
from __future__ import print_function

# ControlBreakToPDF.py
# A program to show how to write simple control break reports
# and send the output to PDF, using itertools.groupby and xtopdf.
# Author: Vasudev Ram
# Copyright 2016 Vasudev Ram
# http://jugad2.blogspot.com
# https://gumroad.com/vasudevram

from itertools import groupby
from PDFWriter import PDFWriter

# I hard-code the data here to make the example shorter.
# More commonly, it would be fetched at run-time from a
# database query or CSV file or similar source.

data = \
[
['North', 'Desktop #1', 1000],
['South', 'Desktop #3', 1100],
['North', 'Laptop #7', 1200],
['South', 'Keyboard #4', 200],
['North', 'Mouse #2', 50],
['East', 'Tablet #5', 200],
['West', 'Hard disk #8', 500],
['West', 'CD-ROM #6', 150],
['South', 'DVD Drive', 150],
['East', 'Offline UPS', 250],
]

pw = PDFWriter('SalesReport.pdf')
pw.setFont('Courier', 12)
pw.setHeader('Sales by Region')
pw.setFooter('Using itertools.groupby and xtopdf')

# Convenience function to both print to screen and write to PDF.
def print_and_write(s, pw):
print(s)
pw.writeLine(s)

# Set column headers.
headers = ['Region', 'Item', 'Sale Value']
# Set column widths.
widths = [ 10, 15, 10 ]
# Build header string for report.
header_str = ''.join([hdr.center(widths[ind]) \
for ind, hdr in enumerate(headers)])
print_and_write(header_str, pw)

# Function to base the sorting and grouping on.
def key_func(rec):
return rec[0]

data.sort(key=key_func)

for region, group in groupby(data, key=key_func):
print_and_write('', pw)
# Write group header, i.e. region name.
print_and_write(region.center(widths[0]), pw)
# Write group's rows, i.e. sales data for the region.
for row in group:
# Build formatted row string.
row_str = ''.join(str(col).rjust(widths[ind + 1]) \
for ind, col in enumerate(row[1:]))
print_and_write(' ' * widths[0] + row_str, pw)
pw.close()
Running it gives this output on the screen:
$ python ControlBreakToPDF.py
Region Item Sale Value

East
Tablet #5 200
Offline UPS 250

North
Desktop #1 1000
Laptop #7 1200
Mouse #2 50

South
Desktop #3 1100
Keyboard #4 200
DVD Drive 150

West
Hard disk #8 500
CD-ROM #6 150

$
And this is a screenshot of the PDF output, viewed in Foxit PDF Reader:


So the itertools.groupby function basically provides roughly the same sort of functionality that SQL's GROUP BY clause provides (of course, when included in a complete SELECT statement). The difference is that with Python's groupby, you do the grouping and related processing in your program code, on data which is in memory, while if using SQL via a client-server RDBMS from your program, the grouping and processing will happen on the database server and only the aggregate results will be sent to your program to process further. Both methods can have pros and cons, depending on the needs of the application.

In my next post about Python, I'll use this program as one vehicle to demonstrate some uses of randomness in testing, continuing the series titled "The many uses of randomness", the earlier two parts of which are here and here.

- Enjoy.

- Vasudev Ram - Online Python training and consulting

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