Python Group.find_by_scoutid_without_senior_duplicates方法代码示例

# 需要导入模块: from group import Group [as 别名]
# 或者: from group.Group import find_by_scoutid_without_senior_duplicates [as 别名]
def group_payments(osm, auth, outfile):
    important_fields = ['first_name',
                        'last_name',
                        'joined',
                        'started',
                        'date_of_birth']

    # Define payment schedules that we are interested in.
    payment_schedules_list = [
        ('2016 - Spring Term - Part 1', datetime.date(2016, 1, 4)),
        ('2016 - Spring Term - Part 2', datetime.date(2016, 2, 22)),
        ('2016 - Summer Term - Part 1', datetime.date(2016, 4, 11)),
        ('2016 - Summer Term - Part 2', datetime.date(2016, 6, 6)),
        ('2016 - Autumn Term - Part 1', datetime.date(2016, 9, 5)),
        ('2016 - Autumn Term - Part 2', datetime.date(2016, 10, 31)),
        ('2017 - Spring Term - Part 1', datetime.date(2017, 1, 9)),
        ('2017 - Spring Term - Part 2', datetime.date(2017, 2, 20))
    ]

    payment_dates = collections.OrderedDict(payment_schedules_list)

    schedules = [_[0] for _ in payment_schedules_list]
    first_date = min([_[1] for _ in payment_schedules_list])
    last_date = max([_[1] for _ in payment_schedules_list])

    # Payment amounts. Assumes all schedules use the same quantity.
    general_amount = 17.95
    discount_amount = 12.13

    # Fetch all of the available data for each term on which a payment is due.
    group_by_date = {}
    for name, date in payment_dates.items():
        group_by_date[name] = Group(osm, auth, important_fields, on_date=date)

    # Get a list of all members in all terms across the whole group.
    all_yp_members = []
    for group in group_by_date.values():
        all_yp_members.extend(group.all_yp_members_without_leaders())

    all_yp_by_scout_id = {member['member_id']: member for member in all_yp_members}

    # Get the current group data for the current term.
    current = Group(osm, auth, important_fields)

    res = []
    for scoutid, member in all_yp_by_scout_id.items():
        current_member = current.find_by_scoutid_without_senior_duplicates(str(scoutid))
        section = current_member[0]._section['sectionname'] if len(current_member) else 'Unknown'
        d = collections.OrderedDict((('scoutid', scoutid), ('First name', member['first_name']),
                                     ('Last name', member['last_name']), ('joined', member['started']),
                                     ('left', member['end_date']),
                                     ('section', section)))

        joined = datetime.datetime.strptime(member['started'], "%Y-%m-%d").date()
        ended = datetime.datetime.strptime(member['end_date'], "%Y-%m-%d").date() if member['end_date'] else False

        amount = discount_amount if member['customisable_data.cf_subs_type_n_g_d_'] == 'D' else general_amount

        for schedule, date_ in payment_dates.items():
            d[schedule] = amount if ((joined < date_ and not ended) or
                                     (joined < date_ and ended > date_)) else 0
        res.append(d)

    tbl = pd.DataFrame(res)
    tbl.set_index(["Last name", "First name"], inplace=True)

    all_sections = list(Group.SECTIONIDS.keys())

    def fetch_section(section_name):
        section = group._sections.sections[Group.SECTIONIDS[section_name]]
        payments = section.get_payments(first_date.strftime('%Y-%m-%d'),
                                        last_date.strftime('%Y-%m-%d'))
        return pd.read_csv(StringIO(payments.content.decode())) if payments is not None else pd.DataFrame()

    all = pd.concat([fetch_section(name) for name in all_sections], ignore_index=True)

    all['Schedule'] = all['Schedule'].str.replace('^General Subscriptions.*$', 'General Subscriptions')
    all['Schedule'] = all['Schedule'].str.replace('^Discounted Subscriptions.*$', 'Discounted Subscriptions')
    subs = all[(all['Schedule'] == 'General Subscriptions') | (all['Schedule'] == 'Discounted Subscriptions')]

    pv = pd.pivot_table(subs, values='Net', index=['Last name', 'First name'], columns=['Schedule', 'Payment'])
    for schedule in schedules:
        pv['General Subscriptions'][schedule].fillna(
            pv['Discounted Subscriptions'][schedule], inplace=True)
    del pv['Discounted Subscriptions']
    pv.columns = pv.columns.droplevel()
    del pv['2015/Q3']

    combined = tbl.join(pv, lsuffix='_est', rsuffix='_act', how='outer')

    for schedule in schedules:
        for suffix in ['_est', '_act']:
            combined[schedule + suffix].fillna(0, inplace=True)

    for schedule in schedules:
        combined[schedule + '_var'] = combined.apply(lambda row: row[schedule + '_est'] - row[schedule + '_act'],
                                                     axis=1)

    combined.to_excel(outfile, sheet_name="Data", merge_cells=False)