Ejemplo n.º 1
0
def test_div():
    acc_data = AccountData(data_path1)
    acc_data_div = acc_data / 2

    assert (sum(acc_data.get_column("amount")) / 2 == sum(
        acc_data_div.get_column("amount")))
    assert (len(acc_data.get_data()) == len(acc_data_div.get_data()))
Ejemplo n.º 2
0
def test_update():
    account_data1 = AccountData("./example_data/data1.csv",
                                tag_file="./example_data/tags_nested.json")
    account_data2 = AccountData("./example_data/data2.csv",
                                account_name="other_data")

    summed_account = account_data1 / 2 + account_data2
    summed_account.update("./example_data/data_new.csv", "data1")
    #Old and new data should be available

    #Old data
    summed_account.filter_data("date", "==", datetime.date(2021, 1, 1))
    assert (summed_account.get_column("text") == [
        "Lorem Ipsum", "Lorem Ipsum"
    ])
    summed_account.reset_filter()

    #New data
    summed_account.filter_data("date", "==", datetime.date(2021, 1, 5))
    assert (summed_account.get_column("text") == ["A1", "SWISH FRÅN Namn"])
    summed_account.reset_filter()

    #Overlapping data should be updated
    summed_account.filter_data("date", "==", datetime.date(2021, 1, 4))
    assert (summed_account.get_column("text") == [
        '201229 A1', '201230 A3 ', '210101 B1', '210102 a4', 'Updated data'
    ])
    #Last one is the new data (not reliable so change if it starts failing)
    #summed_account.filter_data("account" == "other_data")
    assert (summed_account.get_column("amount")[-1] == 333.33 / 2)
    summed_account.reset_filter()
Ejemplo n.º 3
0
def test_save_load(tmp_path):
    acc_data = AccountData(data_path1, tag_file=tag_nested_path)
    acc_data.save(tmp_path / "test_save_load_data.csv")
    acc_data_loaded = AccountData(tmp_path / "test_save_load_data.csv")

    #Saving and loading should not affect data
    acc_data._expenses == acc_data_loaded._expenses
    acc_data._daterange == acc_data_loaded._daterange
Ejemplo n.º 4
0
def test_get_data__is_sorted():
    #Everything should sorted ascending by the first column (date) after initialization
    acc_data1 = AccountData(data_path1)

    all_data = acc_data1.get_data()
    last_date = all_data[0][0]
    for data in all_data[1:]:
        assert (data[0] >= last_date)
        last_date = data[0]
Ejemplo n.º 5
0
def test_filter__type_wrong():
    acc_data1 = AccountData(data_path1, cat_path)
    with pytest.raises(ValueError):
        acc_data1.filter_data("amount", "==", "text")
    with pytest.raises(ValueError):
        acc_data1.filter_data("date", ">", 2)
    with pytest.raises(ValueError):
        acc_data1.filter_data("text", ">", "text")
    with pytest.raises(ValueError):
        acc_data1.filter_data("category", "==", datetime.date(2021, 1, 1))
Ejemplo n.º 6
0
def test_get_total():
    acc_data = AccountData(data_path1, tag_path)
    assert (acc_data.get_total() == -44559.5)
    acc_data.filter_data("tags", "==", "tag2")
    assert (acc_data.get_total() == -24560.0)
    acc_data.filter_data("date", ">", datetime.date(2020, 12, 25))
    assert (acc_data.get_total() == 200.0)
Ejemplo n.º 7
0
def test_add__is_sorted():
    #Everything should still be sorted ascending by the first column (date) after adding two account data
    acc_data1 = AccountData(data_path1)
    acc_data2 = AccountData(data_path2)
    sum_data = acc_data1 + acc_data2

    all_data = sum_data.get_data()
    last_date = all_data[0][0]
    for data in all_data[1:]:
        assert (data[0] >= last_date)
        last_date = data[0]
Ejemplo n.º 8
0
def test_get_timeseries__correct_sum():
    #The total expenses should not change
    acc_data1 = AccountData(data_path2)
    sum1 = 0
    for data in acc_data1.get_data():
        sum1 += data[1]
    sum2 = 0
    for data in acc_data1.get_timeseries().data:
        sum2 += data[1]

    assert (sum1 == sum2)
Ejemplo n.º 9
0
def test_get_timeseries():
    acc_data2 = AccountData(data_path2)
    ts = acc_data2.get_timeseries().data

    #The lenght of the timeseries should be the number of number of days between first and last day of data 1
    assert (len(ts) == 26)

    #All dates should be present between the first and the last, an only occur once
    last_date = ts[0][0]
    for data in ts[1:]:
        assert (last_date + datetime.timedelta(1) == data[0])
        last_date = data[0]
Ejemplo n.º 10
0
def test_reset_filter():
    acc_data1 = AccountData(data_path1, cat_path)
    original_data = acc_data1.get_data()
    acc_data1.filter_data("amount", "==", 1000)
    filtered_data = acc_data1.get_data()
    acc_data1.reset_filter()
    reset_data = acc_data1.get_data()
    assert (original_data == reset_data)
    assert (reset_data != filtered_data)
Ejemplo n.º 11
0
def test_filter__empty():
    #If filtering twice with an inverted filter the result should be empty
    acc_data = AccountData(data_path1, cat_path)
    acc_data.filter_data("amount", ">=", 300)
    acc_data.filter_data("amount", "<", 300)
    assert (len(acc_data.get_data()) == 0)
    #Tags should also be empty
    assert (len(acc_data.get_tags()) == 0)
    #It should be possible to still call get_timeseries()
    assert (type(acc_data.get_timeseries()) == TimeSeries)
Ejemplo n.º 12
0
def test_get_average():
    acc_data = AccountData(data_path1)
    total_expenses = sum([data[1] for data in acc_data.get_data()])
    days = (acc_data.get_data()[-1][0] - acc_data.get_data()[0][0]).days + 1

    assert (acc_data.get_average("Day") == total_expenses / days)
    assert (acc_data.get_average("Week") == sum(
        [data[1] for data in acc_data.get_data()[1:-1]]) / 3)
Ejemplo n.º 13
0
def test_update__daterange():
    account_data1 = AccountData("./example_data/data1.csv",
                                tag_file="./example_data/tags_nested.json")
    account_data2 = AccountData("./example_data/data2.csv",
                                account_name="other_data")

    summed_account = account_data1 + account_data2 / 2
    old_range = summed_account._daterange

    summed_account.update("./example_data/data_new.csv", "other_data")
    new_range = summed_account._daterange

    #Start date is same
    assert (old_range[0] == new_range[0])
    #New date range is longer however
    assert (old_range[1] < new_range[1])
Ejemplo n.º 14
0
def test_filter__amount(fun):
    acc_data1 = AccountData(data_path1, cat_path)
    acc_data1.filter_data("amount", fun, 200)
    for amount in acc_data1.get_column("amount"):
        if fun == ">":
            assert (amount > 200)
        elif fun == ">=":
            assert (amount >= 200)
        elif fun == "==":
            assert (amount == 200)
        elif fun == "!=":
            assert (amount != 200)
        elif fun == "<=":
            assert (amount <= 200)
        elif fun == "<":
            assert (amount < 200)
Ejemplo n.º 15
0
def test_filter__date():
    acc_data1 = AccountData(data_path1, cat_path)
    first_date = acc_data1.get_column("date")[0]
    next_date = acc_data1.get_column("date")[1]
    acc_data1.filter_data("date", ">", first_date)

    assert (acc_data1.get_column("date")[0] == next_date)
Ejemplo n.º 16
0
def test_div__property():
    acc_data1 = AccountData(data_path1, tag_nested_path)
    acc_data2 = AccountData(data_path2,
                            tag_nested_path,
                            account_name="other_data")

    summed_account = acc_data1 + acc_data2 / 2

    #Use the account name to get the scale of the account, either using the file name, or account name if given
    assert (summed_account.get_scale("data1") == 1)
    assert (summed_account.get_scale("other_data") == 1 / 2)

    amount_col = summed_account.columns["amount"]
    amount_unscaled = summed_account.columns["amount_unscaled"]
    account_col = summed_account.columns["account"]

    assert (
        summed_account.get_data()[0][amount_col] ==
        summed_account.get_data()[0][amount_unscaled] *
        summed_account.get_scale(summed_account.get_data()[0][account_col]))
Ejemplo n.º 17
0
def test_add():
    acc_data1 = AccountData(data_path1, tag_nested_path)
    acc_data2 = AccountData(data_path2, tag_nested_path)
    sum_data = acc_data1 + acc_data2

    #Categories should not change since both acc_data use the same tag file, though order may change (so sorting it)
    assert (sorted(list(acc_data1.get_tags())) == sorted(
        list(sum_data.get_tags())))
    #Length of get_data should be the sum of both
    assert (len(sum_data.get_data()) == len(acc_data1.get_data()) +
            len(acc_data2.get_data()))
Ejemplo n.º 18
0
def test_get_data():
    acc_data1 = AccountData(data_path1)
    #Check that data corresponds to the first entry
    assert (acc_data1.get_data()[0][acc_data1.columns['amount']] == 100)
    #And that lenght is correct
    assert (len(acc_data1.get_data()) == 19)
Ejemplo n.º 19
0
def test_filter__type_ok():
    acc_data1 = AccountData(data_path1, cat_path)
    acc_data1.filter_data("amount", ">", 100)
    acc_data1.filter_data("amount", ">", 200.5)
    acc_data1.filter_data("text", "!=", "test")
    acc_data1.filter_data("date", ">", datetime.date(2021, 1, 4))
Ejemplo n.º 20
0
def test_filter__tags():
    acc_data = AccountData(data_path1, tag_file=tag_path)
    acc_data.filter_data("tags", "!=", "tag1")
    assert ("tag1" not in acc_data.get_tags())
    acc_data.filter_data("tags", "==", "tag3")
    assert (acc_data.get_tags() == ["tag3"])
Ejemplo n.º 21
0
def test_filter__multi_tags():
    #If a data point has multiple tags, those tags should be preserved
    acc_data = AccountData(data_path1, tag_file=tag_path)
    acc_data.filter_data("tags", "==", "överföring")
    assert (len(acc_data.get_tags()) > 1)
Ejemplo n.º 22
0
def test_get_average__empty():
    #Should return 0 if there is no data
    acc_data = AccountData(data_path1, tag_nested_path)
    acc_data.filter_data("tags", "==", "Non-existing")
    assert (acc_data.get_average("Day") == 0)
Ejemplo n.º 23
0
def test_update__save_load(tmp_path):
    account_data1 = AccountData("./example_data/data1.csv",
                                tag_file="./example_data/tags_nested.json")
    account_data2 = AccountData("./example_data/data2.csv",
                                account_name="other_data")

    summed_account = account_data1 / 2 + account_data2
    summed_account.update("./example_data/data_new.csv", "data1")

    #Save and load should not affect data
    summed_account.save(tmp_path / "account_data.csv")

    summed_account = AccountData(tmp_path / "account_data.csv")

    #Old data
    summed_account.filter_data("date", "==", datetime.date(2021, 1, 1))
    assert (summed_account.get_column("text") == [
        'Lorem Ipsum', 'Lorem Ipsum'
    ])
    summed_account.reset_filter()

    #New data
    summed_account.filter_data("date", "==", datetime.date(2021, 1, 5))
    assert (summed_account.get_column("text") == ['A1', 'SWISH FRÅN Namn'])
    summed_account.reset_filter()

    #Overlapping data should be updated
    summed_account.filter_data("date", "==", datetime.date(2021, 1, 4))
    assert (summed_account.get_column("text") == [
        '201229 A1', '201230 A3 ', '210101 B1', '210102 a4', 'Updated data'
    ])
    summed_account.filter_data("account", "==", "data1")
    assert (summed_account.get_column("amount") == [333.33 / 2])
    summed_account.reset_filter()
Ejemplo n.º 24
0
def test_filter__tag_list_order():
    acc_data = AccountData(data_path1, tag_file=tag_path)
    #If the order of the tags is different, then it should still yield the same result
    acc_data.filter_data("tags", "==", ["överföring", "tag1"])
    #Should only contain the once that contains all the tags.
    assert (sorted(acc_data.get_tags()) == sorted(["tag1", "överföring"]))
Ejemplo n.º 25
0
def test_get_tags_level():
    acc_data = AccountData(data_path1, tag_file=tag_nested_path)
    assert (acc_data.get_tags("==", 0) == ["tag2", "tagABC"])
    assert (acc_data.get_tags(">=", 1) == ["B23", "B", "A", "B1"])
    #Since there are only 2 levels, getting all levels that are less than 3 should give back all tags
    assert (acc_data.get_tags("<", 3) == acc_data.get_tags())
Ejemplo n.º 26
0
def test_get_tags():
    acc_data = AccountData(data_path1, tag_file=tag_path)
    assert (sorted(
        acc_data.get_tags()) == ["tag1", "tag2", "tag3", "överföring"])
Ejemplo n.º 27
0
def test_init():
    acc_data1 = AccountData(data_path1)
    acc_data2 = AccountData(data_path2, tag_nested_path)
Ejemplo n.º 28
0
def test_get_average__filtered():
    acc_data = AccountData(data_path1, tag_path)
    #If we filter by something by other than date, we should still accumulate to the full extent of the data
    acc_data.filter_data("tags", "==", "tag2")
    assert (acc_data.get_average("Day") == sum(acc_data.get_column("amount")) /
            26)
    #If filter by date, accumulate should only be within the filtered dates
    acc_data.reset_filter()
    acc_data.filter_data("date", ">", datetime.date(2020, 12, 13))
    acc_data.filter_data("date", "<=", datetime.date(2020, 12, 20))
    assert (acc_data.get_average("Week") == (1000 + 100 - 25000) / 1)
    #The filter function should detect if the date filter is greater than the data and it should affect the average
    acc_data.reset_filter()
    acc_data.filter_data("date", ">=", datetime.date(2020, 12, 7))
    acc_data.filter_data("date", "<", datetime.date(2020, 12, 23))
    assert (acc_data.get_average("Week") == (1000 + 100 - 25000) / 1)
Ejemplo n.º 29
0
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
import datetime
import math

from homeplotter.accountdata import AccountData

tag_file = "./data/personal_tags.json"
account_data1 = AccountData("./data/old/konto_gemensamt.csv",
                            tag_file=tag_file)
account_data2 = AccountData("./data/old/konto_personligt.csv")
account_data3 = AccountData("./data/old/konto_ica.csv")
summed_account = (account_data1 / 2) + account_data2 + (account_data3 / 2)

start_date = datetime.date(2021, 2, 1)


def create_plot(tag, output_path, acc_delta="Month"):
    summed_account.reset_filter()
    if tag != "Alla" and tag != "Överskott eller Underskottt":
        summed_account.filter_data("tags", "==", tag)
    else:
        summed_account.filter_data("tags", "!=", "Reservation")
        summed_account.filter_data("tags", "!=", "Överföring")
        if tag == "Alla":
            summed_account.filter_data("tags", "!=", "Lön")
    summed_account.filter_data("date", ">=", start_date)
    plt.cla()
    tsdata = summed_account.get_timeseries()
    tsdata.accumulate(1, acc_delta)
    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m/%d/%Y'))
Ejemplo n.º 30
0
def test_filter__tag_list():
    acc_data = AccountData(data_path1, tag_file=tag_path)
    acc_data.filter_data("tags", "==", ["tag1", "överföring"])
    #Should only contain the once that contains all the tags.
    assert (sorted(acc_data.get_tags()) == sorted(["tag1", "överföring"]))