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rtu-schedule-parser

Easy extraction of the MIREA - Russian Technological University schedule from Excel documents.

Why rtu-schedule-parser?

  • Strict formatting: We strive to extract schedules without unexpected totals. If problems are found, an error is raised and displayed.
  • Output: Schedule data is easily converted to pandas DataFrame format. This allows you to quickly export the extracted schedule to CSV, HTML, XML, JSON and other formats, as well as perform various selecting, sorting, etc. operations on the data.
  • Compatibility: Compatible with .xls and .xlsx document formats. Handles a large number of cases when parsing.

Example

An example of how you can download documents with a schedule and extract a schedule for a specific group. You can see more examples here.

from rtu_schedule_parser import ExcelScheduleParser, ScheduleData
from rtu_schedule_parser.constants import Institute, Degree
from rtu_schedule_parser.downloader import ScheduleDownloader


# Initialize downloader with default directory to save files
downloader = ScheduleDownloader()

# Get documents for specified institute and degree
docs = downloader.get_documents(specific_institutes={Institute.IIT}, specific_degrees={Degree.BACHELOR})

# Download only if they are not downloaded yet.
downloaded = downloader.download_all(docs)

# Create schedule with downloaded files
schedules = None  # type: ScheduleData | None
for doc in downloaded:
    parser = ExcelScheduleParser(
        doc[1], doc[0].period, doc[0].institute, doc[0].degree
    )
    
    # The `force` argument is used to ignore exceptions during document parsing. 
    # This lets you to parse all possible groups.
    if schedules is None:
        schedules = parser.parse(force=True)
    else:
        schedules.extend(parser.parse(force=True).get_schedule())

# Get a schedule for the specified group
group_schedule = schedules.get_group_schedule("ИКБО-01-22")

# Initialize pandas dataframe
df = group_schedule.get_dataframe()

# Export dataframe to csv
df.to_csv("schedule.csv")

Installation

From the source code

$ git clone https://github.com/mirea-ninja/rtu-curriculum-parser

and then install using pip:

$ cd rtu-curriculum-parser
$ python -m pip install .