def get_expenses(db_exp_data_fpaths: list,
db_inc_data_fpaths: list,
stor_pair_path: str,
stor_exp_data_path: str,
budg_path: str,
exp_path: str,
dont_print_cols=None,
bankconfig=None):
"""
main method for the importing of expense data
"""
bank_json = data_help.read_jsonFile(bankconfig.settings_path)
exp_df = data_help.load_csvs(
db_exp_data_fpaths,
dtype=bankconfig.exp_dtypes,
parse_dates=env.pdates_colname
) # only using on csv db for now. newest will be last? idk verify later.
exp_df = data_help.drop_for_substring(
exp_df, env.BANK_STORENAME, bankconfig.ignorable_transactions,
"\nRemoving the below expense transactions as they are either an internal bank acct transfer, cash advance or credit payment."
)
dates = data_help.extract_months(exp_df[env.DATE], start=False)
# check for any missing budgets either this month or any month in the data
expManager.get_budgets(budg_path, exp_path, dates)
exp_df = expManager.get_expenses_for_rows(exp_df, stor_exp_data_path,
stor_pair_path, budg_path,
bankconfig)
print("\nFinished gathering your expense data: \n")
util.print_fulldf(exp_df, dont_print_cols)
data_help.write_data(exp_df, db_exp_data_fpaths[0])
def notes_editor(db_exp_data_fpaths,
db_inc_data_fpaths,
notes_path,
bankconfig=None):
"""
Main menu for editing notes
"""
done = False
while not done:
exp_df = data_help.load_csvs(db_exp_data_fpaths,
dtype=bankconfig.exp_dtypes,
parse_dates=env.pdates_colname)
inc_df = data_help.load_csvs(db_inc_data_fpaths,
dtype=bankconfig.inc_dtypes,
parse_dates=env.pdates_colname)
notes_dict = data_help.read_jsonFile(notes_path)
exp_months = data_help.extract_months(exp_df[env.DATE], start=False)
inc_months = data_help.extract_months(inc_df[env.DATE], start=False)
months_in_data = util.add_set_to_set(exp_months, inc_months, sort=True)
if notes_dict == {}:
prompt = "You have not entered any notes yet. Which month(s) would you like to add notes for? "
edit_prompt_base = "Please enter your note below for month "
else:
prompt = "Please select a month to edit : "
edit_prompt_base = "Edit your note below for month "
sel_months = util.select_indices_of_list(
prompt,
list_to_compare_to=months_in_data,
return_matches=True,
abortchar='q')
if sel_months is not None:
notes = edit_notes(edit_prompt_base, notes_dict, sel_months,
notes_path)
else:
done = True
def get_income(db_inc_data_fpaths: list,
dont_print_cols=None,
bankconfig=None):
"""
main method for the importing of income data
"""
inc_df = data_help.load_csvs(db_inc_data_fpaths,
dtype=bankconfig.inc_dtypes,
parse_dates=env.pdates_colname)
inc_df = data_help.drop_for_substring(
inc_df, env.BANK_STORENAME, bankconfig.ignorable_transactions,
"\nRemoving the below income transactions as they are either an internal bank acct transfer, cash advance or credit payment."
)
data_help.write_data(inc_df, db_inc_data_fpaths[0])
print("\nFinished gathering your income data: \n")
util.print_fulldf(inc_df, dont_print_cols)
def store_editor(db_exp_data_fpaths,
db_exprec_data_fpath,
stor_pair_path,
exp_stor_data_path,
budg_path,
exp_path,
bankconfig=None):
"""
Edits a store's name across all databases.
params:
db_exp_data_fpaths - filepaths to expense csv's
stor_pair_path - filepath to store name database
exp_stor_data_path - filepath to store-expense data base
budg_path - filepath to budget database
"""
done = False
while not done:
df = data_help.load_csvs(db_exp_data_fpaths,
dtype=bankconfig.exp_dtypes,
parse_dates=env.pdates_colname)
df_rec = data_help.load_csv(db_exprec_data_fpath,
dtype=bankconfig.exp_dtypes,
parse_dates=env.pdates_colname)
stor_data = data_help.read_jsonFile(stor_pair_path)
exp_stor_data = data_help.read_jsonFile(exp_stor_data_path)
exp_data = data_help.read_jsonFile(exp_path)
budg_db = data_help.read_jsonFile(budg_path)
prompt = "Would you like to: \n(a) - change storenames\n(b) - edit bank to database store relationships\n(q) - quit\ntype here: "
user_in = util.get_user_input_for_chars(prompt, ['a', 'b', 'q'])
if user_in == 'a':
change_storename(db_exp_data_fpaths, df, db_exprec_data_fpath,
df_rec, exp_stor_data, stor_data, stor_pair_path,
exp_stor_data_path)
elif user_in == 'b':
change_storepair(db_exp_data_fpaths, df, db_exprec_data_fpath,
df_rec, exp_stor_data, stor_data, stor_pair_path,
exp_stor_data_path, exp_data, budg_db)
elif user_in == 'q':
done = True
return
def check_for_data(ndata_filepaths, db_exp_data_fpaths, db_inc_data_fpaths,
adata_path, db_exp_data_path, db_inc_data_path,
exp_recbin_path, inc_recbin_path, bankconfig):
"""
Checks db and new folder for any data.
Imports the data into expense and income dataframes
"""
if len(ndata_filepaths) == 0:
return False
if len(ndata_filepaths) != 0 and len(db_exp_data_fpaths) != 0 and len(
db_inc_data_fpaths) != 0:
df_new = data_help.load_and_process_csvs(
file_paths=ndata_filepaths,
strip_cols=bankconfig.strip_cols,
data_type=bankconfig.selection)
util.print_fulldf(df_new)
df_inc_new, df_exp_new = data_help.filter_by_amnt(
df_new,
col_name=env.AMOUNT,
col_name2=env.NULL,
bank_name=bankconfig.selection)
df_inc_new = data_help.add_columns(
df_inc_new, [env.ADJUSTMENT, env.INC_UUID, env.EXP_UUID])
df_exp_new = data_help.add_columns(df_exp_new, [
env.FILT_STORENAME, env.EXPENSE, env.ADJUSTMENT, env.EXP_UUID,
env.INC_UUID
])
df_exp = data_help.load_csvs(file_paths=db_exp_data_fpaths,
strip_cols=bankconfig.strip_cols,
dtype=bankconfig.exp_dtypes)
df_inc = data_help.load_csvs(file_paths=db_inc_data_fpaths,
strip_cols=bankconfig.strip_cols,
dtype=bankconfig.inc_dtypes)
df_exp = pd.concat([df_exp, df_exp_new])
df_inc = pd.concat([df_inc, df_inc_new])
elif len(ndata_filepaths) != 0:
df_new = data_help.load_and_process_csvs(
file_paths=ndata_filepaths,
strip_cols=bankconfig.strip_cols,
data_type=bankconfig.selection)
df_inc, df_exp = data_help.filter_by_amnt(
df_new,
col_name=env.AMOUNT,
col_name2=env.NULL,
bank_name=bankconfig.selection)
df_inc_new = data_help.add_columns(
df_inc, [env.ADJUSTMENT, env.INC_UUID, env.EXP_UUID])
df_exp_new = data_help.add_columns(df_exp, [
env.FILT_STORENAME, env.EXPENSE, env.ADJUSTMENT, env.EXP_UUID,
env.INC_UUID
])
else:
return False
df_exp_recbin = data_help.load_csvs([exp_recbin_path],
dtype=bankconfig.exp_dtypes,
parse_dates=env.pdates_colname)
df_inc_recbin = data_help.load_csvs([inc_recbin_path],
dtype=bankconfig.inc_dtypes,
parse_dates=env.pdates_colname)
print("New data loaded locally.\n\n")
print("INCOME\n\n")
util.print_fulldf(df_inc)
print("IGNORED INCOME\n\n")
util.print_fulldf(df_inc_recbin)
print("EXPENSES\n\n")
util.print_fulldf(df_exp)
print("YOUR IGNORED EXPENSES\n\n")
util.print_fulldf(df_exp_recbin)
df_exp = data_help.drop_dups(df=df_exp,
col_names=bankconfig.check_for_dups_cols,
ignore_index=True)
df_inc = data_help.drop_dups(df=df_inc,
col_names=bankconfig.check_for_dups_cols,
ignore_index=True)
df_exp = data_help.remove_subframe(
df_to_remove_from=df_exp,
df_to_remove=df_exp_recbin,
col_names=bankconfig.check_for_dups_cols)
df_inc = data_help.remove_subframe(
df_to_remove_from=df_inc,
df_to_remove=df_inc_recbin,
col_names=bankconfig.check_for_dups_cols)
print("INCOME WITHOUT DUPS\n\n")
util.print_fulldf(df_inc)
print("EXPENSES WITHOUT DUPS\n\n")
util.print_fulldf(df_exp)
df_exp = data_help.iterate_df_and_add_uuid_to_col(df_exp, env.EXP_UUID)
df_inc = data_help.iterate_df_and_add_uuid_to_col(df_inc, env.INC_UUID)
data_help.write_data(df_exp,
os.path.join(db_exp_data_path,
env.OUT_EXP_DATA_TEMPL),
sortby=env.DATE,
fillna_col=[env.ADJUSTMENT])
data_help.write_data(df_inc,
os.path.join(db_inc_data_path,
env.OUT_INC_DATA_TEMPL),
sortby=env.DATE,
fillna_col=[env.ADJUSTMENT])
timestamp = datetime.datetime.now().strftime("%m_%d_%Y__%H_%M_%S") + ".csv"
data_help.move_files(files=ndata_filepaths,
dest=os.path.join(adata_path, timestamp))
print(
f"Data imported to {db_inc_data_path} and {db_exp_data_path}. Old files moved to {adata_path}"
)
return True
def view_money_data(db_exp_data_fpaths,
db_inc_data_fpaths,
stor_pair_path,
stor_exp_data_path,
budg_path,
notes_path,
exp_path,
dont_print_cols=None,
bankconfig=None,
settings_path=None):
"""
main method for the viewing of data
params:
exp_path - path to expenses.json
dont_print_cols - ignore columns for output to CLI
"""
df_exp = data_help.load_csvs(db_exp_data_fpaths,
dtype=bankconfig.exp_dtypes,
parse_dates=env.pdates_colname,
index=env.DATE)
df_inc = data_help.load_csvs(
db_inc_data_fpaths,
dtype=bankconfig.inc_dtypes,
parse_dates=env.pdates_colname,
index=env.DATE) # TODO SHOW NET INCOME ON PLOTS
df_exp = data_help.combine_and_drop(df_exp, env.AMOUNT, env.ADJUSTMENT,
'subtract')
df_inc = data_help.combine_and_drop(df_inc, env.AMOUNT, env.ADJUSTMENT,
'subtract')
exp_dict = data_help.read_jsonFile(exp_path)
settings = data_help.read_jsonFile(settings_path)
if df_inc.empty: # set index to datetime if empty.
df_inc.set_index(pd.to_datetime(df_inc.index), inplace=True)
budg_db = data_help.read_jsonFile(budg_path) # load the budget data
df_budg = pd.DataFrame(budg_db)
df_budg = df_budg.T # transpose to make index date str
df_budg.set_index(pd.to_datetime(df_budg.index),
inplace=True) # set index to date time
notes_dict = data_help.read_jsonFile(notes_path)
years = data_help.extract_years(df_exp.index.to_series())
years_to_show = util.select_indices_of_list(
"Which of the above year(s) would you like to take a peak at, 'a' for all: ",
years,
return_matches=True,
abortchar='q',
ret_all_char='a')
if years_to_show is None: # select_indices_of_list returns None if user aborts
return None
dfs = data_help.drop_dt_indices_not_in_selection(years_to_show, years,
[df_exp, df_budg, df_inc])
df_exp = dfs[0]
df_budg = dfs[1]
df_inc = dfs[2]
if df_exp is None: # quit condition
return None
freq, freq_desc = get_plotting_frequency()
if freq == None:
return None
if freq == env.YEAR_FREQ:
plot_for_date(years,
dont_print_cols,
exp_dict,
df_inc,
df_budg,
df_exp,
settings,
notes_dict,
freq=freq,
freq_desc=freq_desc)
elif freq == env.MONTH_FREQ:
df_exp, df_budg, df_inc, months = choose_months_in_dfs(
df_exp, df_budg, df_inc, years_to_show)
if df_exp is None:
return None
plot_for_date(years,
dont_print_cols,
exp_dict,
df_inc,
df_budg,
df_exp,
settings,
notes_dict,
freq=env.MONTH_FREQ,
freq_desc=freq_desc,
months=months)
elif freq == 'b':
df_exp_mnth, df_budg_mnth, df_inc_mnth, months = choose_months_in_dfs(
df_exp, df_budg, df_inc, years_to_show)
if df_exp_mnth is None:
return None
plot_for_date(years,
dont_print_cols,
exp_dict,
df_inc_mnth,
df_budg_mnth,
df_exp_mnth,
settings,
notes_dict,
freq=env.MONTH_FREQ,
freq_desc='month',
override_show=True,
months=months)
plot_for_date(years,
dont_print_cols,
exp_dict,
df_inc,
df_budg,
df_exp,
settings,
notes_dict,
freq=env.YEAR_FREQ,
freq_desc='year')
else:
pass
def expenses_editor(db_exp_data_fpaths,
exp_recbin_path,
stor_pair_path,
exp_stor_data_path,
budg_path,
exp_path,
bankconfig=None):
"""
Edits an expense's name across all databases
"""
done = False
while not done:
exp_data = data_help.read_jsonFile(exp_path)
df_rec = data_help.load_csv(exp_recbin_path,
dtype=bankconfig.exp_dtypes,
parse_dates=env.pdates_colname)
df = data_help.load_csvs(db_exp_data_fpaths,
dtype=bankconfig.exp_dtypes,
parse_dates=env.pdates_colname)
stor_data = data_help.read_jsonFile(stor_pair_path)
exp_stor_data = data_help.read_jsonFile(exp_stor_data_path)
budg_data = data_help.read_jsonFile(budg_path)
prompt = "\n".join(
("Would you like to:", "(a) - add an expense",
"(b) - edit an expenses name", "(c) - pair expenses to stores",
"(d) - delete an expense **CAUTION**",
"(e) - edit an expense within your database",
"(f) - unpair an expense from stores",
"(g) - add expense to be subtracted in plot title",
"(h) - remove expense to be subtracted in plot title",
"(q) - quit editor", "type here: "))
user_in = util.get_user_input_for_chars(
prompt, ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'q', 's'])
if user_in == 'a':
add_expense(exp_data, exp_stor_data, exp_path, exp_stor_data_path)
elif user_in == 'b': # TODO
edit_expense_name(db_exp_data_fpaths[0], df, exp_recbin_path,
df_rec, exp_data, budg_data, exp_stor_data,
exp_path, budg_path, exp_stor_data_path)
elif user_in == 'c':
add_expenses_to_store(exp_stor_data, exp_stor_data_path,
exp_data[env.EXPENSE_DATA_KEY])
elif user_in == 'd':
remove_expense_from_dbs(db_exp_data_fpaths[0], exp_recbin_path,
exp_stor_data, exp_data, budg_data, df,
df_rec, exp_stor_data_path, budg_path,
exp_path)
elif user_in == 'e':
edit_cell_in_dfcol(db_exp_data_fpaths[0],
df,
col_name=env.EXPENSE,
opt_col=env.FILT_STORENAME,
opt_dict=exp_stor_data)
elif user_in == 'f':
remove_exp_from_store(db_exp_data_fpaths[0], df, exp_recbin_path,
df_rec, exp_stor_data, exp_stor_data_path)
elif user_in == 'g':
prompt = "Which expense(s) would you like to be subtracted in the title to your plots? "
util.edit_list_in_dict(prompt,
exp_data[env.EXPENSE_DATA_KEY],
exp_data,
env.EXPENSES_SUBTRACTED_KEY,
exp_path,
add=True)
elif user_in == 'h':
prompt = "Which expense(s) would you like to remove? "
util.edit_list_in_dict(prompt,
exp_data[env.EXPENSES_SUBTRACTED_KEY],
exp_data,
env.EXPENSES_SUBTRACTED_KEY,
exp_path,
add=False)
elif user_in == 'q':
done = True
elif user_in == 's':
print("Ah so youre an alchemist then.")
sync_expenses(exp_data, exp_stor_data, exp_path,
exp_stor_data_path)