Metadata-Version: 2.1
Name: epflldap
Version: 0.4.1
Summary: Ce module permet de d'analyser les données d'LDAP à l'EPFL
Home-page: UNKNOWN
Author: Raphaël Rey
Author-email: raphael.rey@epfl.ch
License: MIT
Description: # epflldap
        
        ## Installation
        `pip install dist/epflldap-<version>-py3-none-any.whl`
        
        ## Build new version
        * Makes changes
        * Change the version in `_version.py`
        * `python setup.py bdist_wheel`
        
        ## Basic usages
        
        ### 1. Get and save locally the data of EPFL Ldap
        ```python
        import epflldap
        data = epflldap.db()
        data.to_pickle()
        ```
        This will create locally a `ldap_epfl.pickle` file.
        
        To load the local data:
        ```python
        import epflldap
        data = epflldap.db(read_from_pickle=True)
        ```
        
        ### 2. Get users data only
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        ```
        You will get a `Users` object.
        
        ### 3. Filter users data
        
        #### Filter by group
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        users_filtered = users.filter_by_group('webmasters')
        ```
        You will get an other `Users` object with only the filtered data. Available
        groups are here: https://groups.epfl.ch/
        
        #### Filter by status
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        users_filtered = users.filter_by_status(['Personnel'])
        ```
        Possible status are:
        * `Personnel`
        * `Etudiant`
        * `HÃ´te`
        * `Hors EPFL`
        
        Several entries don't have a status.
        
        #### Filter by unit
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        users_filtered = users.filter_by_unit('SISB')
        ```
        You will get all the users from the SISB team.
        
        #### Filter by school
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        users_filtered = users.filter_by_school('CDH')
        ```
        You will get all the users from the CDH school.
        
        #### Filter by sciper
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        users_filtered = users.filter_by_sciper(['sciper1', 'sciper2'])
        ```
        Filter the list of users with the given list of sciper id.
        
        In order to get information about a specific user you can:
        ```python
        import epflldap
        epflldap.db(read_from_pickle=True)
            .get_users()
            .filter_by_sciper(['sciper1'])
            .data[0]
            .get_info()
        ```
        You will get a Pandas Series with information about the person with the
        given sciper.
        
        #### Keep only first accred
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        users_filtered = users.filter_by_first_accred()
        ```
        You will get only the main accreditation of each user.
        
        
        ### 4. Get all the email addresses of a `Users` object
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        users_filtered = users.filter_by_group('webmasters')
        users_filtered.get_emails()
        ```
        You will get all the email addresses of the group 'webmaster'. If you want a txt
        file, you can add an argument:
        ```python
        users.get_emails(output='addresses.txt')
        ```
        
        ### 5. Get Excel file with personal information data
        ```python
        import epflldap
        users = epflldap.db(read_from_pickle=True).get_users()
        users_filtered = users.filter_by_group('webmasters')
        users_filtered.to_excel(webmasters.xlsx)
        ```
        This will create a xlsx file with personal information about the users.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Description-Content-Type: text/markdown
