def extract_data(export=False):
df = get_books()
df_todo = get_todo()
out = {
"dashboard": get_dashboard(df),
"year_by_category": get_year_data(df),
"month_by_category": get_month_data(df),
"colors": {name: get_colors(data)
for name, data in c.COLORS.items()},
}
# Add percents
data = out["year_by_category"]
out["year_percent"] = get_year_percent(data, cumsum=False)
out["year_percent_cumsum"] = get_year_percent(data, cumsum=True)
# Extract totals
out["year"] = out["year_by_category"].pop("Total")
out["month"] = out["month_by_category"].pop("Total")
# Top Authors
out["top_authors"] = get_top(df, groupby=c.COL_AUTHOR)
# TO DO section
out["todo_by_author"] = get_top(df_todo, c.COL_AUTHOR)
out["todo_by_source"] = get_top(df_todo, c.COL_SOURCE)
out["todo_by_ownership"] = get_top(df_todo, c.COL_OWNED)
if export:
u.get_vdropbox().write_yaml(out, f"{c.PATH_VBOOKS}/report_data.yaml")
return out
def merge_flights_history(mdate):
vdp = get_vdropbox()
# Check for monthly folders and get all parquets inside
for folder in vdp.ls(c.PATH_HISTORY):
is_date_folder = re.search(r"\d{4}_\d{2}", folder)
if is_date_folder and ("."
not in folder) and (folder < f"{mdate:%Y_%m}"):
log.info(f"Merging '{folder}' vflights history")
sub_folder = f"{c.PATH_HISTORY}/{folder}"
# Read all daily parquets
dfs = []
for file in vdp.ls(sub_folder):
if file.endswith(".parquet"):
dfs.append(vdp.read_parquet(f"{sub_folder}/{file}"))
# Export it as only one parquet file
df = pd.concat(dfs)
vdp.write_parquet(df, f"{sub_folder}.parquet")
log.success(f"Successfuly merged '{folder}' vflights history")
# Delete original folder
vdp.delete(sub_folder)
def main(mdate=datetime.now(), data=None):
"""Creates the report"""
mdate = mdate.replace(day=1)
vdp = u.get_vdropbox()
# Read data
if data is None:
log.debug("Reading report_data from dropbox")
data = vdp.read_yaml(f"{c.PATH_EXPENSOR}/report_data/{mdate.year}/{mdate:%Y_%m}.yaml")
# Add title
data["mdate"] = f"{mdate:%Y_%m}"
data["title"] = f"{mdate:%Y_%m} Expensor"
data["sections"] = {
"evolution": "fa-chart-line",
"comparison": "fa-poll",
"pies": "fa-chart-pie",
"liquid": "fa-tint",
"investments": "fa-wallet",
"fire": "fa-fire-alt",
"sankey": "fa-stream",
}
# Create report
report = u.render_jinja_template("expensor.html", data)
vdp.write_file(report, f"{c.PATH_EXPENSOR}/reports/{mdate.year}/{mdate:%Y_%m}.html")
def vbooks():
"""Creates the report"""
data = extract_data()
# Add title
data["title"] = "VBooks"
data["sections"] = {
"evolution": "fa-chart-line",
"percent": "fa-percent",
"authors": "fa-user",
"todo": "fa-list",
}
# Create report
report = u.render_jinja_template("vbooks.html", data)
u.get_vdropbox().write_file(report, f"{c.PATH_VBOOKS}/vbooks.html")
def backup_files():
"""Back up all files from URIS"""
vdp = get_vdropbox()
for kwargs in files_regexs:
log.info("Scanning '{path}/{regex}'".format(**kwargs))
one_backup(vdp, **kwargs)
def clean_backups():
"""Delete backups so that only one per month remain (except if newer than 30d)"""
vdp = get_vdropbox()
df = get_all_backups(vdp)
df = tag_duplicates(df)
# Delete files tagged as 'delete'
for uri in df[df["delete"]].index:
vdp.delete(uri)
def send_summary(mdate, channel):
"""Send gcalendar report"""
vdp = get_vdropbox()
df = get_daily_data(vdp, mdate)
# Prepare slack message
data = get_n_week(df)
block = create_slack_block(data)
# Send slack
send_slack(channel=channel, blocks=[block])
def money_lover():
"""Retrives all dataframes and update DFS global var"""
vdp = get_vdropbox()
# Read
df = get_money_lover_df(vdp)
# Transform
df = transform_transactions(df)
# Export
vdp.write_excel(df, c.FILE_TRANSACTIONS)
def flights(mdate):
filename = c.FILE_FLIGHTS_DAY.format(date=mdate)
vdp = get_vdropbox()
if vdp.file_exists(filename):
log.warning(f"File '{filename}' already exists, skipping flights task")
# Only query if the file does not exist
else:
df = retrive_all_flights()
vdp.write_parquet(df, filename)
def get_airports_pairs():
"""Get a set of all airports combinations"""
vdp = get_vdropbox()
df_airports = vdp.read_excel(c.FILE_AIRPORTS)
out = set()
for _, row in df_airports.iterrows():
out.add((row[c.COL_ORIGIN], row[c.COL_DESTINATION]))
out.add((row[c.COL_DESTINATION], row[c.COL_ORIGIN]))
log.info("Airports retrived from dropbox")
return out
def export_calendar_events(mdate):
"""Export all events as a parquet"""
vdp = get_vdropbox()
download_token(vdp)
# Get events
calendars = read_calendars()
df = get_all_events(calendars, mdate)
# Export events
vdp.write_parquet(df, PATH_GCAL_DATA)
upload_token(vdp)
def get_data():
"""Retrive dataframes"""
# Get dfs
log.debug("Reading excels from gdrive")
dfs = {
x: read_df_gdrive(c.FILE_DATA, x, cols)
for x, cols in c.DFS_ALL_FROM_DATA.items()
}
# Add transactions
log.debug("Reading data from dropbox")
vdp = get_vdropbox()
dfs[c.DF_TRANS] = vdp.read_excel(c.FILE_TRANSACTIONS).set_index(c.COL_DATE)
return dfs
def main(dfs, mdate=datetime.now(), export_data=False):
"""Create the report"""
mdate = mdate.replace(day=1)
# Filter dates
dfs = filter_by_date(dfs, mdate)
# Get config info
vdp = get_vdropbox()
yml = vdp.read_yaml(c.FILE_CONFIG)
out = {}
# Expenses, incomes, result and savings ratio
log.debug("Extracting expenses, incomes, result and savings ratio")
for period in ["month", "year"]:
out[period] = get_basic_traces(dfs, period[0].upper() + "S", mdate)
# Liquid, worth and invested
log.debug("Adding liquid, worth and invested")
data = [(c.DF_LIQUID, c.LIQUID), (c.DF_WORTH, c.INVEST),
(c.DF_INVEST, c.INVEST)]
for name, yml_name in data:
out["month"].update(get_investment_or_liquid(dfs, yml[yml_name], name))
out["month"].update(get_total_investments(out))
out["month"].update(get_salaries(dfs, mdate))
out["comp"] = get_comparison_traces(dfs)
out["pies"] = get_pie_traces(dfs, mdate)
out["dash"] = get_dashboard(out, mdate)
out["ratios"] = get_ratios(out)
out["bubbles"] = get_bubbles(dfs, mdate)
out["sankey"] = extract_sankey(out)
out["colors"] = add_colors(dfs, yml)
if export_data:
vdp.write_yaml(
out,
f"{c.PATH_EXPENSOR}/report_data/{mdate.year}/{mdate:%Y_%m}.yaml")
return out
def run_etl():
"""Run the ETL for today"""
# Get dropbox connector
vdp = u.get_vdropbox()
download_log(vdp)
detect_env()
log.info("Starting vtasks")
result = u.timeit(flow.run)(mdate=date.today())
log.info("End of vtasks")
copy_log(vdp)
if not result.is_successful():
log.error("ETL has failed")
raise ValueError("ETL has failed")
def gcal_report(mdate):
"""Creates the report"""
# Start of last month
mdate = mdate.replace(day=1)
vdp = get_vdropbox()
df = get_daily_data(vdp, mdate)
data = extract_data(vdp, df)
# Add title
data["title"] = "Calendar"
data["sections"] = {
"evolution": "fa-chart-line",
"pies": "fa-chart-pie",
}
# Create report
report = render_jinja_template("gcalendar.html", data)
vdp.write_file(report, f"{PATH_GCAL}/gcalendar.html")
def extract_gcal_confusions(exclude_other=True,
merge_study=True,
min_alpha=0.1):
vdp = get_vdropbox()
dfg = vdp.read_parquet(PATH_GCAL_DATA)
df_aux = clear_potential_confusions(dfg, exclude_other, merge_study)
df_matrix = get_confusion_matrix(df_aux,
col_text="summary",
col_category="calendar")
df_confusions = filter_confusions(df_matrix, min_alpha)
num_confusions = df_confusions.shape[0]
if num_confusions > 0:
log.warning(
f"There are {num_confusions} in google calendar. Exporting them")
vdp.write_excel(df_confusions, PATH_CONFUSIONS)
else:
log.success("There are no confusions in google calendar")