build Python desktop application
Budget: $750 – $1,500 USD
I have a need to build a desktop application that automates the process of downloading PDF files from a website, after a site lookup the lists of documents and the documents populate everyday, we need to extract specific data from at least one of the documents after downloading them and storing them into specific individual files, data will be extracted and stored it in an EXL or similar file, using python and several libraries that will make the process easier. Here is an outline of the steps and libraries I think we would need to use.
once the data is in the excel file we will need to make sure that the info can be pulled to go back out to the internet and search the web for the same associated info or ? we can search a Local Database. once built for this information.
Schedule the task: Use a scheduler like schedule (https://schedule.readthedocs.io/en/stable/) to run your script at a specific time daily.
Access the website: Use the requests library (https://docs.python-requests.org/en/latest/) to access the website and download the HTML content.
Parse the HTML: Use BeautifulSoup from the bs4 library (https://www.crummy.com/software/BeautifulSoup/bs4/doc/) to parse the HTML and find the links to the PDF files.
Download PDFs: Use the requests library again to download the PDF files and save them to your local storage.
Read PDFs: Use the PyPDF2 (https://github.com/mstamy2/PyPDF2) or pdfplumber (https://github.com/jsvine/pdfplumber) library to read and extract the text from the PDF files.
Extract specific data: Use regular expressions or natural language processing libraries like re (https://docs.python.org/3/library/re.html) or spaCy (https://spacy.io/) to identify and extract the required information.
Write to Excel: Use the pandas (https://pandas.pydata.org/) and openpyxl (https://openpyxl.readthedocs.io/en/stable/) libraries to create and manipulate Excel sheets and store the extracted data.
next part is pulling info from excel sheet and then getting it too a data base or web search to find more relative information about the search.
once the data is in the excel file we will need to make sure that the info can be pulled to go back out to the internet and search the web for the same associated info or ? we can search a Local Database. once built for this information.
Schedule the task: Use a scheduler like schedule (https://schedule.readthedocs.io/en/stable/) to run your script at a specific time daily.
Access the website: Use the requests library (https://docs.python-requests.org/en/latest/) to access the website and download the HTML content.
Parse the HTML: Use BeautifulSoup from the bs4 library (https://www.crummy.com/software/BeautifulSoup/bs4/doc/) to parse the HTML and find the links to the PDF files.
Download PDFs: Use the requests library again to download the PDF files and save them to your local storage.
Read PDFs: Use the PyPDF2 (https://github.com/mstamy2/PyPDF2) or pdfplumber (https://github.com/jsvine/pdfplumber) library to read and extract the text from the PDF files.
Extract specific data: Use regular expressions or natural language processing libraries like re (https://docs.python.org/3/library/re.html) or spaCy (https://spacy.io/) to identify and extract the required information.
Write to Excel: Use the pandas (https://pandas.pydata.org/) and openpyxl (https://openpyxl.readthedocs.io/en/stable/) libraries to create and manipulate Excel sheets and store the extracted data.
next part is pulling info from excel sheet and then getting it too a data base or web search to find more relative information about the search.
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