parsing people and groups

parsing people and groups#

Licence CC BY-NC-ND, Thierry Parmentelat

grab the zip for starters

you will need the zipfile that you can find here

This activity is about parsing text files, and building structures using builtin types.

read a file#

  • works on: list file tuple

  • the input: file contains lines like

    first_name last_name email phone

    fields are separated by any number (but at least one) of spaces/tabs, like e.g. in file people-simple-03

    Mathilde Martin mathilde.martin@example.com 0987654321
Jean Dupont jean.dupont@example.com 0123456789
Alice de-la-Borderie alice.de-la-borderie@mystartup.io 0478362410

  • todo: write a function for parsing this format; it should return a list of 4-tuples

    def parse(filename) -> list[tuple[str, str, str, str]]:
    ...

discussion

in the whole TP we will model a person as a 4-tuple
however we could just as well have decided to use instead a dictionary with 4 keys
discuss the pros and cons of each approach

indexing#

  • works on: hash-based types, comprehensions

  • what we need: a fast way to

    • check whether an email is in the file

    • quickly retrieve the details that go with a given email

  • question: what is the right data structure to implement that ?

  • todo:

    • write a function

      def index(list_of_tuples):

      that builds and returns that data structure

    • write a function

      def initial(list_of_tuples):

      that indexes the data on the initial of the first name (what changes do we need to do on the resulting data structure ?)

dataframe (optional)#

  • works on: dataframes

  • todo: build a pandas dataframe to hold all the data

  • tip: see the documentation of pd.DataFrame() and observe that there are multiple interfaces to build a dataframe

groups#

  • works on: set

  • a more elaborate input
    the file now contains optional fields

    first_name last_name email phone [group1 .. groupn]

    where the part between [] is optional, i.e there can be 0 or more groupnames mentioned on each student line; like e.g. from people-groups-10:

    Laurine Bodin Laurine.Bodin@green.org 0400419660 maths french
Tom Côté Tom.Côté@green.org 0373230810 french
Pauline Adrien Pauline.Adrien@traditional.com 0488588126 maths
Franck Dupont Franck.Dupont@green.org 0393821035 french
Julia Castillon Julia.Castillon@mystartup.io 0627047562 maths french
Rémi Archambeau Rémi.Archambeau@mystartup.io 0223515785 maths french
Adam Beaufort Adam.Beaufort@mystartup.io 0196433784
Agathe Alarie Agathe.Alarie@mystartup.io 0632393074
Matthieu Bois Matthieu.Bois@green.org 0675802411 maths french
Emma Lavigne Emma.Lavigne@mystartup.io 0349239656 maths

  • todo duplicate and tweak the parse function, so as to write

    def group_parse(filename):

    so it now returns a 2-tuple with

    • the list of tuples as before

    • a dictionary of sets

      • the keys here will be the group names,

      • and the corresponding value is a set of tuples corresponding to the students in that group

regexps (optional)#

  • works on: regexps

  • what we need: be able to check the format for the input file:

    • first_name and last_name may contain letters and - and _

    • email may contain letters, numbers, dots (.), hyphens (-) and must contain exactly one @

    • phone numbers may contain 10 digits, or +33 followed by 9 digits

  • todo: write a function

    def check_values(L: list[tuple]) -> None:

    that expects as an input the output of parse, and that outlines ill-formed input

  • note on ASCII vs Unicode input:

    • in a first approximation, use patterns like a-z to check for letters;

    • how does this behave with respect to names with accents and cedillas

    • then play with \w to see if you can overcome this problem

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