web scraping

We are a small poster-printing company looking for a candidate to build a Python web-scraping script to download and collect images and their metadata from [login to view URL] Specifically, we only wish to download Photos (not the vectors, illustrations, videos etc). The script should capture all photos in the search results in the link above, not only those on the first page. The script will need detailed documentation so that we will be able to modify it as needed for future use with different sites. Please include text explanations for what each block of code is performing. We need the script to perform the following: 1) Export the following information, with the data for each image in its own row, into a single CSV file (with headers): - A unique sequentially generated idenfication number for each photo, for instance, PXB0000001, PXB0000002, PXB0000003, etc. - URL where the image is found - URL for direct download of full-size image (usually TIFF format) - URL for direct download of JPEG image shown on the page - Title (as provided) - Author, or all authors if more than one. Each separate author in his/her own column. - Original publisher (if provided) - Original creation year (if provided) - If a photograph, any information about where the scene in the photograph is located (if provided; not necessary if already included in Title) - If the image is a scan of a physical object (i.e. of an old map or painting), then the location of where the original is held (if provided). Museum name and any relevant subdivisions/branches/departments will suffice. - All associated keywords provided on the page - Image category - Copyright status 2) Prompt the user to choose destination folders for saving images. One should hold the full-size image (usually TIFF) and the other a preview JPEG image (usually what's displayed on the page). 3) Download the TIFFs/JPEGs, assigning them each unique sequentially generated identification numbers that match those in the CSV file of step (1). The TIFF and JPEG for each image, being located in separate folders, should have matching identification numbers. Skills needed: proficiency in Python, web-scraping, data exporting, API management.