Implement scraper for PA register

[MthwRobinson]

The goal of this issue is to implement the code for downloading regulations from the Pennsylvania register and converting the output to XML. For now, you can store the resulting XML files in a local directory. The directory should use the following convention: pa/{volume}/{number}/{regulation_number}.xml.

The Pennsylvania register has the following disclaimer. Since we're not reselling the data or using it for profit, we should be good to go.

No part of the information on this site may be reused for profit or sold for profit.

[kvnkho]

Does a parser really need to be to handle XML or can we do it in JSON then convert?

[MthwRobinson]

The reason for the XML is:

1. A lot of the regulations (like this one) have strike throughs and other markdown formatting that would be useful to maintain.
2. I'd like to enforce use of a common schema, which is a little easier in XML.
3. I find XML to be more human readable;

That said, I am planning on implementing a helper function that converts a dict to XML, so if you can get all the data into a dictionary, you an just call that.

[kvnkho]

Got it that makes sense. Yeah, I was wondering about the VA code was going to be re-written or just converted. If converted, that helper function would be useful across the registers.

[MthwRobinson]

Yeah, I'm planning to make the changes to the VA code today. Can link that in here so people can use it as an example

[MthwRobinson]

The Regulation data model now has a to_xml method now that you can call. If you can turn your output into a Regulation object, you should be good to go. Here's an example of what it looks like for Virginia.

data-ingest/data_ingest/regs/va.py

Lines 59 to 61 in e72c775

	filename = os.path.join(issue_dir, f"{issue_id}.xml")
	regulation = normalize_regulation(get_regulation(issue_id))
	regulation.to_xml(filename)

data-ingest/data_ingest/regs/va.py

Lines 113 to 154 in e72c775

	def normalize_regulation(regulation):
	"""Normalizes the regulation dictionary and converts it to the standardized
	Regulation object.
	Parameters
	----------
	regulation : dict
	A dictionary representing the infromation scraped from the registry site.
	Returns:
	--------
	normalized_regulation : Regulation
	A base Regulation object
	"""
	normalized_reg = dict()
	body = str()
	for subtitle, content in regulation["content"].items():
	body += f"{subtitle}. {content['description']}\n{content['text']}\n"
	normalized_reg["body"] = body if body else None
	contact = regulation.get("contact", None)
	if contact:
	first_name, last_name, email, phone = _parse_contact(contact)
	contact = Contact.from_dict(
	{
	"first_name": first_name,
	"last_name": last_name,
	"email": email,
	"phone": phone,
	}
	)
	normalized_reg["contacts"] = [contact]
	normalized_reg["effective_date"] = extract_date(regulation["effective_date"])
	normalized_reg["register_date"] = extract_date(regulation["register_date"])
	for key in vars(Regulation()):
	if key not in normalized_reg and key in regulation:
	normalized_reg[key] = regulation[key]
	return Regulation.from_dict(normalized_reg)