def __plot(plot_basis, start_date, end_date, plot_type=None, df=None):
# check if we've plotted this same plot in the past before
kwargs = {}
now = datetime.datetime.now().strftime(BankSchema.DATE_FORMAT2)
title = ImageRegistry._make_plot_key_title(plot_basis, plot_type)
plot_cache_result = PlotCache.hit(title, start_date, end_date, now)
if plot_cache_result is None:
logging.info(f'Plot cache miss for plot: {title}, replotting.')
if plot_type and plot_type not in ImageRegistry.get_supported_plots(plot_basis):
raise KeyError(f"Provided plot type {plot_type} is not supported.")
kwargs['plot_type'] = plot_type
kwargs['title'] = title
kwargs['figsize'] = ImageRegistry.get_plot_figsize(plot_basis)
with ImageRegistry.__global_lock:
if df is not None:
fig_or_html = ImageRegistry.get_plot_func(plot_basis)(df, **kwargs)
else:
# heatmap
fig_or_html = ImageRegistry.get_plot_func(plot_basis)(DateRange(start_date, end_date), **kwargs)
# is figure
if fig_or_html is not None and not isinstance(fig_or_html, str):
stream_reader = StringIO()
fig_or_html.savefig(stream_reader, format='svg', bbox_inches='tight')
stream_reader.seek(0)
html = stream_reader.getvalue()
PlotCache.add_cache_miss(title, start_date, end_date, now, html)
elif fig_or_html is None:
logging.warning(f'Ignoring plot for {plot_basis}.')
else:
# heat-map plot
PlotCache.add_cache_miss(title, start_date, end_date, now, fig_or_html)
else:
logging.info(f'Plot cache hit for plot: {title}, ignoring replotting.')
def update_html_df():
DataState.html_df = HTMLHelper.as_html_form_from_sql(
BankSchema.BANK_TB_NAME,
DateRange(State.date_range_start, State.date_range_end),
DataState.order_by_column_name,
DataState.order_by,
table_id=ConstData.BANK_DATA_TABLE_ID)
class InsightState(State):
html_bank_summary = HTMLHelper.as_html_form_from_df(
RawInsights.Dynammic.table_summary_statistics(
BankSchema.BANK_TB_NAME,
DateRange(State.date_range_start, State.date_range_end)),
Insights.BANK_SUMMARY_TABLE_ID,
replace_default_data_frame_class_with=Insights.INSIGHT_TABLE_CLASS)
html_top_inc_cat = HTMLHelper.as_html_form_from_df(
RawInsights.Dynammic.get_top_n_income_categories(
DateRange(State.date_range_start, State.date_range_end),
BankSchema.BANK_TB_NAME),
Insights.TOP_INC_TABLE_ID,
replace_default_data_frame_class_with=Insights.INSIGHT_TABLE_CLASS)
html_top_exp_cat = HTMLHelper.as_html_form_from_df(
RawInsights.Dynammic.get_top_n_expense_categories(
DateRange(State.date_range_start, State.date_range_end),
BankSchema.BANK_TB_NAME),
Insights.TOP_EXP_TABLE_ID,
replace_default_data_frame_class_with=Insights.INSIGHT_TABLE_CLASS)
_static_clock = time.time()
html_inc_and_exp_this_month_vs_last_month_summary = HTMLHelper.as_html_form_from_df(
RawInsights.Static.get_money_gain_and_spent_this_month_vs_last_month(
DateRange(State.date_range_start, State.date_range_end),
BankSchema.BANK_TB_NAME,
as_dataframe=True),
Insights.SPENDING_VS_LAST_MONTH_TABLE_ID,
replace_default_data_frame_class_with=Insights.INSIGHT_TABLE_CLASS)
html_inc_and_exp_this_month_vs_last_month_summary_as_str = RawInsights.Static. \
summarize_this_and_last_months_spending(
DateRange(State.date_range_start, State.date_range_end), BankSchema.BANK_TB_NAME)
spending_vs_last_month_pid = 'spending_vs_last_month_p'
@staticmethod
def as_dict():
return State.as_dict_helper(InsightState, Insights)
@staticmethod
def get_clock():
return InsightState._static_clock
@staticmethod
def set_clock(clock):
InsightState._static_clock = clock
def valid_dr(start, end):
try:
DateRange(start, end)
return True
except KeyError:
flash(Flash.DATE_RANGE_FILTER_KEY_ERROR.msg,
Flash.DATE_RANGE_FILTER_KEY_ERROR.type)
return False
def refresh_static_insights(ignore_clock=False):
now = time.time()
passed_minutes = now - InsightState.get_clock()
# refresh only if a significant time has passed
if ignore_clock or passed_minutes <= Insights.STATIC_TIME_CACHE_REFRESH_MINUTES:
InsightState.html_inc_and_exp_this_month_vs_last_month_summary = HTMLHelper.as_html_form_from_df(
RawInsights.Static.
get_money_gain_and_spent_this_month_vs_last_month(
DateRange(State.date_range_start, State.date_range_end),
BankSchema.BANK_TB_NAME,
as_dataframe=True),
Insights.SPENDING_VS_LAST_MONTH_TABLE_ID,
replace_default_data_frame_class_with=Insights.INSIGHT_TABLE_CLASS)
InsightState.html_inc_and_exp_this_month_vs_last_month_summary_as_str = RawInsights.Static. \
summarize_this_and_last_months_spending(
DateRange(State.date_range_start, State.date_range_end),
BankSchema.BANK_TB_NAME)
# refresh the clock for next look up period
InsightState.set_clock(time.time())
def refresh_dynamic_insights():
InsightState.html_bank_summary = HTMLHelper.as_html_form_from_df(
RawInsights.Dynammic.table_summary_statistics(
BankSchema.BANK_TB_NAME,
DateRange(State.date_range_start, State.date_range_end)),
Insights.BANK_SUMMARY_TABLE_ID,
replace_default_data_frame_class_with=Insights.INSIGHT_TABLE_CLASS)
InsightState.html_top_inc_cat = HTMLHelper.as_html_form_from_df(
RawInsights.Dynammic.get_top_n_income_categories(
DateRange(State.date_range_start, State.date_range_end),
BankSchema.BANK_TB_NAME),
Insights.TOP_INC_TABLE_ID,
replace_default_data_frame_class_with=Insights.INSIGHT_TABLE_CLASS)
InsightState.html_top_exp_cat = HTMLHelper.as_html_form_from_df(
RawInsights.Dynammic.get_top_n_expense_categories(
DateRange(State.date_range_start, State.date_range_end),
BankSchema.BANK_TB_NAME),
Insights.TOP_EXP_TABLE_ID,
replace_default_data_frame_class_with=Insights.INSIGHT_TABLE_CLASS)
class DataState(State):
order_by_column_name = BankSchema.SCHEMA_BANK_DATE.name
order_by = Defaults.ORDER_BY_DEFAULT
html_df = HTMLHelper.as_html_form_from_sql(
BankSchema.BANK_TB_NAME,
DateRange(State.date_range_start, State.date_range_end),
order_by_column_name,
order_by,
table_id=ConstData.BANK_DATA_TABLE_ID)
@staticmethod
def as_dict():
return State.as_dict_helper(DataState, ConstData)
def visuals_redraw():
if request.method == 'POST':
form = request.form
drs, dre = form['start_query_name'], form['end_query_name']
if not valid_dr(drs, dre):
return _standard_render()
State.date_range_start, State.date_range_end = drs, dre
# update which visuals to draw and redraw them
requested_plots_to_draw = set(ImageRegistry.get_all_plot_ids()) & set(form.keys())
_update_requested_plots_to_draw(set(requested_plots_to_draw))
df = Data.get_table_as_df(DateRange(State.date_range_start, State.date_range_end),
table_name=BankSchema.BANK_TB_NAME)
if df is None or df.shape[0] == 0:
flash(f'No data int table {BankSchema.BANK_TB_NAME} produce diagrams.', 'warning')
else:
ImageRegistry.plot_all(list(requested_plots_to_draw), df, drs, dre)
return _standard_render()
def data_download():
if request.method == 'POST':
logger.info('Downloading bank data as csv file.')
with tempfile.TemporaryDirectory() as tmpdir:
dr = DateRange(State.date_range_start, State.date_range_end)
bank_df = Data.get_table_as_df(dr, BankSchema.BANK_TB_NAME,
DataState.order_by_column_name,
DataState.order_by)
if bank_df is None or bank_df.shape[0] == 0:
flash(
f'{BankSchema.BANK_TB_NAME} table is empty. Nothing to download.',
'warning')
return _standard_render()
bank_df.to_csv(os.path.join(tmpdir, ConstData.FILE_NAME_DOWNLOAD),
index=False)
return send_from_directory(directory=tmpdir,
filename=ConstData.FILE_NAME_DOWNLOAD,
as_attachment=True)
return _standard_render()