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Commit 7ffb4b25 authored by William Bell's avatar William Bell
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data/captions.csv
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View file @ 7ffb4b25
file_name,title
test.srt,My title
test1.srt,A test srt file
test2.vtt,A test vtt file
data/test.srt deleted 100644 → 0
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View file @ 2b07caec
1
00:00:04,090 --> 00:00:05,260
Hi.
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So in this video, I'm
going to talk about
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what exactly is a database, so
what do we mean by a database?
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So a database is an
organised collection of data
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that we want to exist
for a period of time.
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We want to have access to it.
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We want to update it.
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We want to be able to
manipulate it in some way.
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So we want to have essentially
persistent storage and access
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to this data.
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So access to a
database is generally
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managed by a database
management system.
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So that allows us to do
various things, like control
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who has access to what parts
of the database, control who
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can update the database, allow
for the database to be updated,
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allow for searches to be
conducted, for information
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to be extracted,
and generally just
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all aspects of how we
interact with the data that
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is stored within the database.
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So what sort of applications
do we use databases for?
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So there are a wide
variety of databases
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in terms of size and scope.
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So you may have
tiny databases that
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operate on your mobile
device, for example, just
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for some of your personal data.
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You may have more medium
size databases that
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live within applications
that we use,
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so things like Skype
or our browsers
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to, again, manage some
of the data that we have.
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And we move up to larger
scale databases, the things
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that you might see in
enterprises, for example.
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So your bank or your insurer
may have larger data sets
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that they want to
interact with and use.
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Then we have even bigger
types of applications.
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So if you imagine a search
engine or a recommender system
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or some sort of internet-based
video browser or service,
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for example, like
YouTube, then you're
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going to have millions or
billions of interactions
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every day, millions
or billions of items
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that you want to maintain,
that you want to log,
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that you want to have
information about.
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And it's at this
point that we may
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need to consider using
different types of technologies
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to traditional
relational database
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to allow us to
manage those volumes
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and rapidly changing
types of data.
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doc/transcript.tex
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View file @ 7ffb4b25
\documentclass[12pt,a4paper]{article}
\usepackage{strath-assignment}
\usepackage{strath-transcript}
\usepackage{amsmath}
\usepackage{listings}
\usepackage[parfill]{parskip}
......
python/transcripts.py
+ 60
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View file @ 7ffb4b25
......@@ -5,36 +5,37 @@ import tkinter
import tkinter.filedialog
import webvtt
def get_input_file_path(initial_dir:str):
def get_input_file_path(initial_dir: str) -> str:
"""
A function to collect the input file name from the user.
"""
root = tkinter.Tk()
root.withdraw()
file_path = tkinter.filedialog.askopenfilename(initialdir=initial_dir,
filetypes=[('CSV', '.csv')],
title='Select input file')
filetypes=[('CSV', '.csv')],
title='Select input file')
return file_path
def write_title_tex(title:str):
def write_title_tex(title: str, title_file: str) -> None:
"""
A function to write a title.tex file.
"""
s = "\setstretch{1.0}" + "\n"
s = "\\setstretch{1.0}" + "\n"
s += "\\title{" + title + "}" + "\n"
s += "\\author{Audio transcript}" + "\n"
s += "\\date{}" + "\n"
s += "\maketitle" + "\n"
s += "\setstretch{1.2}" + "\n"
output_file = open("title.tex", "w")
s += "\\maketitle" + "\n"
s += "\\setstretch{1.2}" + "\n"
output_file = open(title_file, "w")
output_file.write(s)
output_file.close()
def srt_to_txt(srt_file):
def srt_to_txt(srt_file: str) -> list:
"""
A function to remove the numbers and times from an srt file.
A function to remove the numbers and times from an srt captions file.
"""
lines = []
input_file = open(srt_file, "r")
......@@ -49,8 +50,24 @@ def srt_to_txt(srt_file):
return lines
def process_files(doc_dir, csv_file_path):
# The data files are expected to be in the
def vtt_to_txt(vtt_file: str) -> list:
"""
A function to remove non-text content from a vtt captions file.
"""
vtt = webvtt.read(vtt_file)
lines = []
for line in vtt:
lines.append(line.text + "\n\n")
return lines
def process_files(doc_dir: str, csv_file_path: str) -> None:
"""
A function to process all caption files and produce
PDF files.
"""
# The data files are expected to be in the
# same directory as the input CSV file.
data_dir = os.path.dirname(csv_file_path)
......@@ -58,16 +75,14 @@ def process_files(doc_dir, csv_file_path):
os.chdir(doc_dir)
input_file = open(csv_file_path, "r", newline='')
dict_reader = csv.DictReader(input_file, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
dict_reader = csv.DictReader(input_file, delimiter=',',
quotechar='"', quoting=csv.QUOTE_MINIMAL)
# Require both columns to be present.
if "file_name" not in dict_reader.fieldnames:
print(f"!! The file \"{csv_file_path}\" must contain a column named file_name.")
if "title" not in dict_reader.fieldnames:
print(f"!! The file \"{csv_file_path}\" must contain a column named title.")
csv_lines = sum(1 for row in dict_reader)
print(csv_lines)
# Process each row in the CSV file.
for row_dict in dict_reader:
......@@ -83,29 +98,37 @@ def process_files(doc_dir, csv_file_path):
# Set the output file file name.
file_prefix, file_extension = os.path.splitext(transcript_file_name)
pdf_file_name = file_prefix + ".pdf"
# Attempt to covert the transcript file to text.
lines = []
if file_extension == ".srt":
lines += srt_to_txt(transcript_file_name)
elif file_extension == ".vtt":
lines += vtt_to_txt(transcript_file_name)
# If the transcript file cannot be converted.
if len(lines) == 0:
print(f"!! Warning the file \"{transcript_file_name}\" cannot be convert to text.")
continue
# Write the tex files.
write_title_tex(title)
output_file = open("body.tex", "w")
title_file = "title.tex"
body_file = "body.tex"
write_title_tex(title, title_file)
output_file = open(body_file, "w")
output_file.writelines(lines)
output_file.close()
# Create the PDF file. The number of pages is calculated
# the first time LaTeX is run.
ret_code = subprocess.call(["pdflatex", "transcript.tex"],
ret_code = subprocess.call(["pdflatex",
"-interaction=nonstopmode",
"transcript.tex"],
stdout=subprocess.DEVNULL,
stderr=subprocess.STDOUT)
ret_code = subprocess.call(["pdflatex", "transcript.tex"],
ret_code = subprocess.call(["pdflatex",
"-interaction=nonstopmode",
"transcript.tex"],
stdout=subprocess.DEVNULL,
stderr=subprocess.STDOUT)
if ret_code != 0:
......@@ -119,15 +142,29 @@ def process_files(doc_dir, csv_file_path):
# Rename the output file.
os.rename("transcript.pdf", pdf_file_name)
# Clean up the doc directory.
if os.path.isfile(title_file):
os.unlink(title_file)
if os.path.isfile(body_file):
os.unlink(body_file)
print(f">> Written \"{pdf_file_name}\"")
input_file.close()
if __name__ == "__main__":
"""
A program to convert .srt and .vtt caption files to
PDF transcript files.
"""
parent_dir = os.path.dirname(os.getcwd())
data_dir = os.path.join(parent_dir, "data")
doc_dir = os.path.join(parent_dir, "doc")
transcript_csv = get_input_file_path(data_dir)
if len(transcript_csv) > 0:
process_files(doc_dir, transcript_csv)
\ No newline at end of file
# Normalise the file path for Windows.
transcript_csv = os.path.normpath(transcript_csv)
# Process the files.
process_files(doc_dir, transcript_csv)
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