def process_ccc_or_credit_request(lookup_type, lookup_value):
"""
Fetches course data table in HTML, extracts sections, and generates list of courses.
:param lookup_type: Type of data being requested (CCC requirement or credit level)
:param lookup_value: Value of data requested (W1, EGSS, half credit, etc.)
:return: List of parsed course data
"""
# return cached data, if it exists
cache_data = course_data_get(lookup_value)
if cache_data is not None:
return cache_data["set_time"], cache_data["data"]
# fetch the HTML
lookup_type_enum = LookupType[lookup_type.upper()]
html = fetch_course_html(lookup_value, lookup_type_enum)
# extract section data from html
sections = extract_sections(html)
# ignore elements that don't contain course data
filtered_sections = filter(lambda x: len(x) > 5, sections)
# generate a list of dictionaries to organize data for each section
all_courses = map(CreditOrCCC.handle_ccc_or_credit_section,
filtered_sections)
# store in cache and return data
cache_time = course_data_set(lookup_value, all_courses)
return cache_time, all_courses
def fetch_section_details(crn, department):
"""
Fetches description and other data for an individual section.
:param crn: CRN of the section
:param department: Department the section belongs to
:return: Section details
"""
# return cached data, if it exists
key = crn + "details"
details = course_data_get(key)
if details is not None:
return details["set_time"], details["data"]
# Create and execute server request
payload = {
'formopt': 'VIEWSECT',
'term': TERM,
'updsubj': department,
'crn': crn,
'viewterm': TERM,
'viewlookopt': 'DPT',
'viewparam1': department,
'viewopenopt': 'ALL',
}
r = requests.get(BUCKNELL_SECTION_DETAILS_URL, params=payload)
# Create object that will allow parsing of HTML
soup = BeautifulSoup(r.text)
# Extract section details
details = str(soup.find_all(class_='datadisplaytable')[0])
# store details in cache
cache_time = course_data_set(key, details, timeout=259200)
return cache_time, details
def process_department_request(department_name):
"""
Fetches course data table in HTML, extracts sections, and generates list of courses.
:param department_name: The department being requested (CSCI, ECON, etc)
:return: List of parsed course data
"""
# return cached data, if it exists
cache_data = course_data_get(department_name)
if cache_data is not None:
return cache_data["set_time"], cache_data["data"]
# fetch the HTML
html = fetch_course_html(department_name, LookupType.DEPARTMENT)
# extract sections from HTML
sections = extract_sections(html)
# ignore first row of section data if it is a department message
sections = sections[1:] if len(
sections[0].find_all("td")) == 1 else sections
# divide a row of section data into its individual columns
section_split = map(
lambda current_section: current_section.find_all("td"), sections)
# group sections by course
grouped_sections = Department.group_sections_by_course(section_split)
# parse courses to group sections with their labs, recitations, etc.
parsed_courses = map(Course, grouped_sections)
# create format that can be stored in cache or returned to user
formatted_results = [course.export() for course in parsed_courses]
cache_time = course_data_set(department_name, formatted_results)
return cache_time, formatted_results