BeautifulSoup for multiple URLs with different templates

You need an iterable in an outer loop. One way would be to generate a tuple list from your existing dataframe columns and loop that. You can then have your conditional logic, simplified, within the loop.

import requests
from bs4 import BeautifulSoup
import pandas as pd

page_url1 = "https://www.vet.upenn.edu/research/centers-laboratories/research-laboratory/research-laboratory/anguera-laboratory"
page_url2 = "https://www.med.upenn.edu/apps/faculty/index.php/g20001100/p8866286"
page_url_lst = {"url": [page_url1, page_url2], "template": [1, 2]}
page_url_df = pd.DataFrame(page_url_lst)

data = []

with requests.Session() as s:
    for template, url in zip(
        page_url_df["template"].to_list(), page_url_df["url"].to_list()
    ):
        r = s.get(url)
        soup = BeautifulSoup(r.text, "lxml")

        if template == 1:
           
            for e in soup.select("#tabs-publications em"):
                data.append(
                    {
                        "author": e.previous.get_text(strip=True)[:-1],
                        "title": e.get_text(strip=True),
                        "journal": e.next_sibling.get_text(strip=True),
                        "source": url,
                    }
                )
        else:

            for a in soup.find_all("span", {"class": "fac_citation"}):
                data.append(
                    {
                        "author": a.find("b").get_text(),
                        "title": a.find("i").get_text(strip=True),
                        "journal": a.find("i").next_sibling.get_text(strip=True),
                        "source": url,
                    }
                )
print(data)

If I understand you right, you want to create new dataframe based on page_url_df:

import requests
import pandas as pd
from bs4 import BeautifulSoup


page_url1 = "https://www.vet.upenn.edu/research/centers-laboratories/research-laboratory/research-laboratory/anguera-laboratory"
page_url2 = (
    "https://www.med.upenn.edu/apps/faculty/index.php/g20001100/p8866286"
)
page_url_lst = {"url": [page_url1, page_url2], "template": [1, 2]}
page_url_df = pd.DataFrame(page_url_lst)


def get_template_1(url):
    data = []
    soup = BeautifulSoup(requests.get(url).content, "lxml")
    for e in soup.select("#tabs-publications em"):
        data.append(
            {
                "author": e.previous.get_text(strip=True)[:-1],
                "title": e.get_text(strip=True),
                "journal": e.next_sibling.get_text(strip=True),
                "source": url,
            }
        )
    return data


def get_template_2(url):
    data = []
    soup = BeautifulSoup(requests.get(url).text, "lxml")
    for a in soup.find_all("span", {"class": "fac_citation"}):
        data.append(
            {
                "author": a.find("b").get_text(),
                "title": a.find("i").get_text(strip=True),
                "journal": a.find("i").next_sibling.get_text(strip=True),
                "source": url,
            }
        )
    return data


all_data = []
for _, row in page_url_df.iterrows():
    print("Getting", row["url"])
    if row["template"] == 1:
        all_data.extend(get_template_1(row["url"]))
    elif row["template"] == 2:
        all_data.extend(get_template_2(row["url"]))


df_out = pd.DataFrame(all_data)

# print sample data
print(df_out.head().to_markdown())

Prints: