some testing, some pandas to polars in tasks.py

rowers/dataprep.py

@@ -89,10 +89,9 @@ from rowers.dataroutines import *
 
 from rowers.tasks import (
     handle_sendemail_newftp,
-    handle_sendemail_unrecognized, handle_setcp,
+    handle_sendemail_unrecognized, 
     handle_getagegrouprecords, handle_update_wps,
     handle_request_post, handle_calctrimp,
-    handle_updatecp, handle_updateergcp,
     handle_sendemail_breakthrough,
     handle_sendemail_hard,
 )

rowers/dataroutines.py

@@ -2705,7 +2705,7 @@ def create_c2_stroke_data_db(
     else:
         power = 0
 
-    df = pd.DataFrame({
+    df = pl.DataFrame({
         'TimeStamp (sec)': unixtime,
         ' Horizontal (meters)': d,
         ' Cadence (stokes/min)': spm,
@@ -2726,9 +2726,10 @@ def create_c2_stroke_data_db(
         'cum_dist': d
     })
 
-    df[' ElapsedTime (sec)'] = df['TimeStamp (sec)']
+    df = df.with_columns((pl.col("TimeStamp (sec)")).alias(" ElapsedTime (sec)"))
 
-    _ = df.to_csv(csvfilename, index_label='index', compression='gzip')
+    row = rrdata_pl(df=df)
+    row.writecsv(csvfilename, compression=True)
 
     data = dataplep(df, id=workoutid, bands=False, debug=debug)
 

rowers/integrations/c2.py

@@ -2,7 +2,7 @@ from .integrations import SyncIntegration, NoTokenError, create_or_update_syncre
 from rowers.models import User, Rower, Workout, TombStone
 from django.db.utils import IntegrityError
 
-from rowingdata import rowingdata
+from rowingdata import rowingdata, rowingdata_pl
 import numpy as np
 import datetime
 import json

rowers/interactiveplots.py

@@ -61,7 +61,7 @@ from rowers.models import (
     Workout, User, Rower, WorkoutForm, RowerForm,
     GraphImage, GeoPolygon, GeoCourse, GeoPoint,
 )
-from rowers.tasks import handle_setcp
+
 from rowingdata import rower as rrower
 from rowingdata import main as rmain
 from rowingdata import cumcpdata, histodata
@@ -1380,7 +1380,7 @@ def interactive_chart(id=0, promember=0, intervaldata={}):
 
     columns = ['time', 'pace', 'hr', 'fpace', 'ftime', 'spm']
     datadf = dataprep.getsmallrowdata_pl(columns, ids=[id])
-    if datadf.is_empty():
+    if datadf.is_eompty():
         return "", "No Valid Data Available"
 
     datadf = datadf.fill_nan(None).drop_nulls()
@@ -2372,223 +2372,6 @@ def get_zones_report_pl(rower, startdate, enddate, trainingzones='hr', date_agg=
 
     return chart_data
 
-            
-
-def get_zones_report(rower, startdate, enddate, trainingzones='hr', date_agg='week',
-                     yaxis='time'):
-
-    dates = []
-    dates_sorting = []
-    minutes = []
-    hours = []
-    zones = []
-
-    enddate = enddate + datetime.timedelta(days=1)
-
-    workouts = Workout.objects.filter(
-        user=rower,
-        startdatetime__gte=startdate,
-        startdatetime__lte=enddate,
-        duplicate=False,
-    ).order_by("-startdatetime")
-
-    ids = [w.id for w in workouts]
-
-    columns = ['workoutid', 'hr', 'power', 'time']
-
-    df = dataprep.getsmallrowdata_db(columns, ids=ids)
-    try:
-        df['deltat'] = df['time'].diff().clip(lower=0).clip(upper=20*1e3)
-    except KeyError:  # pragma: no cover
-        pass
-
-    df = dataprep.clean_df_stats(df, workstrokesonly=False,
-                                 ignoreadvanced=True, ignorehr=False)
-
-    hrzones = rower.hrzones
-    powerzones = rower.powerzones
-
-    for w in workouts:
-        dd3 = w.date.strftime('%Y/%m')
-        dd4 = '{year}/{week:02d}'.format(
-            week=arrow.get(w.date).isocalendar()[1],
-            year=w.date.strftime('%y')
-        )
-        dd4 = (w.date - datetime.timedelta(days=w.date.weekday())
-               ).strftime('%y/%m/%d')
-
-        # print(w.date,arrow.get(w.date),arrow.get(w.date).isocalendar())
-        iswater = w.workouttype in mytypes.otwtypes
-        qryw = 'workoutid == {workoutid}'.format(workoutid=w.id)
-
-        qry = 'hr < {ut2}'.format(ut2=rower.ut2)
-        if trainingzones == 'power':
-            qry = 'power < {ut2}'.format(ut2=rower.pw_ut2)
-        timeinzone = df.query(qry).query(qryw)['deltat'].sum()/(60*1e3)
-        if date_agg == 'week':
-            dates.append(dd4)
-            dates_sorting.append(dd4)
-        else:  # pragma: no cover
-            dates.append(dd3)
-            dates_sorting.append(dd3)
-        minutes.append(timeinzone)
-        hours.append(timeinzone/60.)
-        if trainingzones == 'hr':
-            zones.append('<{ut2}'.format(ut2=hrzones[1]))
-        else:
-            zones.append('<{ut2}'.format(ut2=powerzones[1]))
-        # print(w,dd,timeinzone,'<UT2')
-
-        qry = '{ut2} <= hr < {ut1}'.format(ut1=rower.ut1, ut2=rower.ut2)
-        if trainingzones == 'power':
-            qry = '{ut2} <= power < {ut1}'.format(
-                ut1=rower.pw_ut1, ut2=rower.pw_ut2)
-            if iswater:
-                qry = '{ut2} <= power < {ut1}'.format(
-                    ut1=rower.pw_ut1*rower.otwslack/100., ut2=rower.pw_ut2*rower.otwslack/100.)
-        timeinzone = df.query(qry).query(qryw)['deltat'].sum()/(60*1e3)
-        if date_agg == 'week':
-            dates.append(dd4)
-            dates_sorting.append(dd4)
-        else:  # pragma: no cover
-            dates.append(dd3)
-            dates_sorting.append(dd3)
-        minutes.append(timeinzone)
-        hours.append(timeinzone/60.)
-        if trainingzones == 'hr':
-            zones.append(hrzones[1])
-        else:
-            zones.append(powerzones[1])
-        # print(w,dd,timeinzone,'UT2')
-
-        qry = '{ut1} <= hr < {at}'.format(ut1=rower.ut1, at=rower.at)
-        if trainingzones == 'power':
-            qry = '{ut1} <= power < {at}'.format(
-                ut1=rower.pw_ut1, at=rower.pw_at)
-            if iswater:
-                qry = '{ut1} <= power < {at}'.format(
-                    ut1=rower.pw_ut1*rower.otwslack/100., at=rower.pw_at*rower.otwslack/100.)
-        timeinzone = df.query(qry).query(qryw)['deltat'].sum()/(60*1e3)
-        if date_agg == 'week':
-            dates.append(dd4)
-            dates_sorting.append(dd4)
-        else:  # pragma: no cover
-            dates.append(dd3)
-            dates_sorting.append(dd3)
-        minutes.append(timeinzone)
-        hours.append(timeinzone/60.)
-        if trainingzones == 'hr':
-            zones.append(hrzones[2])
-        else:
-            zones.append(powerzones[2])
-        # print(w,dd,timeinzone,'UT1')
-
-        qry = '{at} <= hr < {tr}'.format(at=rower.at, tr=rower.tr)
-        if trainingzones == 'power':
-            qry = '{at} <= power < {tr}'.format(at=rower.pw_at, tr=rower.pw_tr)
-            if iswater:
-                qry = '{at} <= power < {tr}'.format(at=rower.pw_at*rower.otwslack/100.,
-                                                    tr=rower.pw_tr*rower.otwslack/100.)
-        timeinzone = df.query(qry).query(qryw)['deltat'].sum()/(60*1e3)
-        if date_agg == 'week':
-            dates.append(dd4)
-            dates_sorting.append(dd4)
-        else:  # pragma: no cover
-            dates.append(dd3)
-            dates_sorting.append(dd3)
-        minutes.append(timeinzone)
-        hours.append(timeinzone/60.)
-        if trainingzones == 'hr':
-            zones.append(hrzones[3])
-        else:
-            zones.append(powerzones[3])
-        # print(w,dd,timeinzone,'AT')
-
-        qry = '{tr} <= hr < {an}'.format(tr=rower.tr, an=rower.an)
-        if trainingzones == 'power':
-            qry = '{tr} <= power < {an}'.format(tr=rower.pw_tr, an=rower.pw_an)
-            if iswater:
-                qry = '{tr} <= power < {an}'.format(tr=rower.pw_tr*rower.otwslack/100.,
-                                                    an=rower.pw_an*rower.otwslack/100.)
-        timeinzone = df.query(qry).query(qryw)['deltat'].sum()/(60*1e3)
-        if date_agg == 'week':
-            dates.append(dd4)
-            dates_sorting.append(dd4)
-        else:  # pragma: no cover
-            dates.append(dd3)
-            dates_sorting.append(dd3)
-        minutes.append(timeinzone)
-        hours.append(timeinzone/60.)
-        if trainingzones == 'hr':
-            zones.append(hrzones[4])
-        else:
-            zones.append(powerzones[4])
-        # print(w,dd,timeinzone,'TR')
-
-        qry = 'hr >= {an}'.format(an=rower.an)
-        if trainingzones == 'power':
-            qry = 'power >= {an}'.format(an=rower.pw_an)
-            if iswater:
-                qry = 'power >= {an}'.format(an=rower.pw_an*rower.otwslack/100.)
-        timeinzone = df.query(qry).query(qryw)['deltat'].sum()/(60*1e3)
-        if date_agg == 'week':
-            dates.append(dd4)
-            dates_sorting.append(dd4)
-        else:  # pragma: no cover
-            dates.append(dd3)
-            dates_sorting.append(dd3)
-        minutes.append(timeinzone)
-        hours.append(timeinzone/60.)
-        if trainingzones == 'hr':
-            zones.append(hrzones[5])
-        else:
-            zones.append(powerzones[5])
-        # print(w,dd,timeinzone,'AN')
-
-    try:
-        d = utc.localize(startdate)
-    except (ValueError, AttributeError):  # pragma: no cover
-        d = startdate
-
-    try:
-        enddate = utc.localize(enddate)
-    except (ValueError, AttributeError):  # pragma: no cover
-        pass
-
-    while d <= enddate:
-        if date_agg == 'week':
-            dd4 = '{year}/{week:02d}'.format(
-                week=arrow.get(d).isocalendar()[1],
-                year=d.strftime('%y')
-            )
-            dd4 = (d - datetime.timedelta(days=d.weekday())).strftime('%y/%m/%d')
-
-            dates.append(dd4)
-            dates_sorting.append(dd4)
-        else:  # pragma: no cover
-            dates.append(d.strftime('%Y/%m'))
-            dates_sorting.append(d.strftime('%Y/%m'))
-
-        minutes.append(0)
-        hours.append(0)
-        if trainingzones == 'hr':
-            zones.append(hrzones[1])
-        else:
-            zones.append(powerzones[1])
-
-        d += datetime.timedelta(days=1)
-
-    # this should be renamed with rower zones
-    data = {
-        'date': dates,
-        'date_sorting': dates_sorting,
-        'minutes': minutes,
-        'zones': zones,
-        'hours': hours,
-    }
-
-
-    return data
 
 def interactive_zoneschart2(rower, data, startdate, enddate, trainingzones='hr', date_agg='week',
                            yaxis='time'):
@@ -2621,133 +2404,3 @@ def interactive_zoneschart2(rower, data, startdate, enddate, trainingzones='hr',
     return script, div
 
 
-def interactive_zoneschart(rower, data, startdate, enddate, trainingzones='hr', date_agg='week',
-                           yaxis='time'):
-    if startdate >= enddate:  # pragma: no cover
-        st = startdate
-        startdate = enddate
-        enddate = st
-
-    hrzones = rower.hrzones
-    powerzones = rower.powerzones
-
-    color_map = {
-        '<{ut2}'.format(ut2=hrzones[1]): 'green',
-        hrzones[1]: 'lime',
-        hrzones[2]: 'yellow',
-        hrzones[3]: 'blue',
-        hrzones[4]: 'purple',
-        hrzones[5]: 'red',
-    }
-    if trainingzones == 'power':
-        color_map = {
-            '<{ut2}'.format(ut2=powerzones[1]): 'green',
-            powerzones[1]: 'lime',
-            powerzones[2]: 'yellow',
-            powerzones[3]: 'blue',
-            powerzones[4]: 'purple',
-            powerzones[5]: 'red',
-        }
-
-    zones_order = [
-        '<{ut2}'.format(ut2=hrzones[1]),
-        hrzones[1],
-        hrzones[2],
-        hrzones[3],
-        hrzones[4],
-        hrzones[5]
-    ]
-
-    if trainingzones == 'power':
-        zones_order = [
-            '<{ut2}'.format(ut2=powerzones[1]),
-            powerzones[1],
-            powerzones[2],
-            powerzones[3],
-            powerzones[4],
-            powerzones[5]
-        ]
-
-    df = pd.DataFrame(data)
-    df2 = pd.DataFrame(data)
-
-    df.drop('minutes', inplace=True, axis='columns')
-
-    df.sort_values('date_sorting', inplace=True)
-    df.drop('date_sorting', inplace=True, axis='columns')
-    df['totaltime'] = 0
-    if df.empty:  # pragma: no cover
-        return '', 'No Data Found'
-
-    if yaxis == 'percentage':
-        dates = list(set(df['date'].values))
-        for date in dates:
-            qry = 'date == "{d}"'.format(d=date)
-
-            totaltime = df.query(qry)['hours'].sum()
-
-            mask = df['date'] == date
-            df.loc[mask, 'totaltime'] = totaltime
-
-        df['percentage'] = 100.*df['hours']/df['totaltime']
-        df.drop('hours', inplace=True, axis='columns')
-        df.drop('totaltime', inplace=True, axis='columns')
-
-    hv.extension('bokeh')
-
-    xrotation = 0
-    nrdates = len(list(set(df['date'].values)))
-    if nrdates > 10:
-        xrotation = 45
-
-    bars = hv.Bars(df, kdims=['date', 'zones']).aggregate(
-        function=np.sum).redim.values(zones=zones_order)
-
-    bars.opts(
-        opts.Bars(cmap=color_map, show_legend=True, stacked=True,
-                  tools=['tap', 'hover'], width=550, padding=(0, (0, .1)),
-                  legend_position='bottom',
-                  xrotation=xrotation,
-                  show_frame=False)
-    )
-
-    p = hv.render(bars)
-
-    p.title.text = 'Activity {d1} to {d2} for {r}'.format(
-        d1=startdate.strftime("%Y-%m-%d"),
-        d2=enddate.strftime("%Y-%m-%d"),
-        r=str(rower),
-    )
-
-    if date_agg == 'week':
-        p.xaxis.axis_label = 'Week'
-    else:  # pragma: no cover
-        p.xaxis.axis_label = 'Month'
-
-    if yaxis == 'percentage':
-        p.yaxis.axis_label = 'Percentage'
-
-    p.width = 550
-    p.height = 350
-    p.toolbar_location = 'right'
-    p.y_range.start = 0
-    #p.sizing_mode = 'stretch_both'
-
-    if yaxis == 'percentage':
-        tidy_df = df2.groupby(['date']).sum()
-
-        source2 = ColumnDataSource(tidy_df)
-        y2rangemax = tidy_df.loc[:, 'hours'].max()*1.1
-        p.extra_y_ranges["yax2"] = Range1d(start=0, end=y2rangemax)
-        p.line('date', 'hours', source=source2,
-               y_range_name="yax2", color="black", width=5)
-        p.circle('date', 'hours', source=source2, y_range_name="yax2", color="black", size=10)
-        
-#        p.circle('date', 'hours', source=source2, y_range_name="yax2", color="black", size=10,
-#                 legend_label='Hours')
-        p.add_layout(LinearAxis(y_range_name="yax2",
-                                axis_label='Hours'), 'right')
-
-    script, div = components(p)
-
-    return script, div

rowers/tasks.py

@@ -56,7 +56,7 @@ from scipy.signal import savgol_filter
 from scipy.interpolate import griddata
 
 import rowingdata
-from rowingdata import make_cumvalues
+from rowingdata import make_cumvalues, make_cumvalues_array
 from uuid import uuid4
 from rowingdata import rowingdata as rdata
 
@@ -115,6 +115,9 @@ tpapilocation = TP_API_LOCATION
 from requests_oauthlib import OAuth1, OAuth1Session
 
 import pandas as pd
+import polars as pl
+from polars.exceptions import ColumnNotFoundError
+
 
 from django_rq import job
 from django.utils import timezone
@@ -2583,53 +2586,6 @@ def handle_otwsetpower(self, f1, boattype, boatclass, coastalbrand, weightvalue,
     return 1
 
 
-@app.task
-def handle_updateergcp(rower_id, workoutfilenames, debug=False, **kwargs):
-    therows = []
-    for f1 in workoutfilenames:
-        try:
-            rowdata = rdata(csvfile=f1)
-        except IOError:  # pragma: no cover
-            try:
-                rowdata = rdata(csvfile=f1 + '.csv')
-            except IOError:
-                try:
-                    rowdata = rdata(csvfile=f1 + '.gz')
-                except IOError:
-                    rowdata = 0
-        if rowdata != 0:
-            therows.append(rowdata)
-
-    cpdata = rowingdata.cumcpdata(therows)
-    cpdata.columns = cpdata.columns.str.lower()
-
-    updatecpdata_sql(rower_id, cpdata['delta'], cpdata['cp'],
-                     table='ergcpdata', distance=cpdata['distance'],
-                     debug=debug)
-
-    return 1
-
-
-@app.task
-def handle_updatecp(rower_id, workoutids, debug=False, table='cpdata', **kwargs):
-    columns = ['power', 'workoutid', 'time']
-    df = getsmallrowdata_db(columns, ids=workoutids, debug=debug)
-
-    if df.empty:  # pragma: no cover
-        return 0
-
-    maxt = 1.05*df['time'].max()/1000.
-
-    logarr = datautils.getlogarr(maxt)
-
-    dfgrouped = df.groupby(['workoutid'])
-
-    delta, cpvalue, avgpower = datautils.getcp(dfgrouped, logarr)
-
-    updatecpdata_sql(rower_id, delta, cpvalue, debug=debug, table=table)
-
-    return 1
-
 
 @app.task
 def handle_makeplot(f1, f2, t, hrdata, plotnr, imagename,
@@ -3179,43 +3135,6 @@ def handle_sendemail_invite_reject(email, name, teamname, managername,
     return 1
 
 
-@app.task
-def handle_setcp(strokesdf, filename, workoutid, debug=False, **kwargs):
-    try:
-        os.remove(filename)
-    except FileNotFoundError:
-        pass
-    if not strokesdf.empty:
-
-        try:
-            totaltime = strokesdf['time'].max()
-        except KeyError:  # pragma: no cover
-            return 0
-        try:
-            powermean = strokesdf['power'].mean()
-        except KeyError:  # pragma: no cover
-            powermean = 0
-
-        if powermean != 0:
-            thesecs = totaltime
-            maxt = 1.05 * thesecs
-
-            if maxt > 0:
-                logarr = datautils.getlogarr(maxt)
-                dfgrouped = strokesdf.groupby(['workoutid'])
-                delta, cpvalues, avgpower = datautils.getcp(dfgrouped, logarr)
-
-                df = pd.DataFrame({
-                    'delta': delta,
-                    'cp': cpvalues,
-                    'id': workoutid,
-                })
-                df.to_parquet(filename, engine='fastparquet',
-                              compression='GZIP')
-                return 1
-
-    return 1  # pragma: no cover
-
 
 @app.task
 def handle_sendemail_invite_accept(email, name, teamname, managername,
@@ -3647,7 +3566,7 @@ def handle_c2_async_workout(alldata, userid, c2token, c2id, delaysec,
             loncoord = np.zeros(nr_rows)
 
         try:
-            strokelength = strokedata.loc[:, 'strokelength']
+            strokelength = strokedata.loc[:,'strokelength']
         except:  # pragma: no cover
             strokelength = np.zeros(nr_rows)
 
@@ -3901,7 +3820,7 @@ def fetch_strava_workout(stravatoken, oauth_data, stravaid, csvfilename, userid,
     pace[np.isinf(pace)] = 0.0
 
     try:
-        strokedata = pd.DataFrame({'t': 10*t,
+        strokedata = pl.DataFrame({'t': 10*t,
                                    'd': 10*d,
                                    'p': 10*pace,
                                    'spm': spm,
@@ -3947,18 +3866,18 @@ def fetch_strava_workout(stravatoken, oauth_data, stravaid, csvfilename, userid,
 
     starttimeunix = arrow.get(rowdatetime).timestamp()
 
-    res = make_cumvalues(0.1*strokedata['t'])
+    res = make_cumvalues_array(0.1*strokedata['t'].to_numpy())
-    cum_time = res[0]
+    cum_time = pl.Series(res[0])
-    lapidx = res[1]
+    lapidx = pl.Series(res[1])
 
     unixtime = cum_time+starttimeunix
-    seconds = 0.1*strokedata.loc[:, 't']
+    seconds = 0.1*strokedata['t']
 
     nr_rows = len(unixtime)
 
     try:
-        latcoord = strokedata.loc[:, 'lat']
+        latcoord = strokedata['lat']
-        loncoord = strokedata.loc[:, 'lon']
+        loncoord = strokedata['lon']
         if latcoord.std() == 0 and loncoord.std() == 0 and workouttype == 'water':  # pragma: no cover
             workouttype = 'rower'
     except:  # pragma: no cover
@@ -3968,29 +3887,29 @@ def fetch_strava_workout(stravatoken, oauth_data, stravaid, csvfilename, userid,
             workouttype = 'rower'
 
     try:
-        strokelength = strokedata.loc[:, 'strokelength']
+        strokelength = strokedata['strokelength']
     except:  # pragma: no cover
         strokelength = np.zeros(nr_rows)
 
-    dist2 = 0.1*strokedata.loc[:, 'd']
+    dist2 = 0.1*strokedata['d']
 
     try:
-        spm = strokedata.loc[:, 'spm']
+        spm = strokedata['spm']
-    except KeyError:  # pragma: no cover
+    except (KeyError, ColumnNotFoundError):  # pragma: no cover
         spm = 0*dist2
 
     try:
-        hr = strokedata.loc[:, 'hr']
+        hr = strokedata['hr']
-    except KeyError:  # pragma: no cover
+    except (KeyError, ColumnNotFoundError):  # pragma: no cover
         hr = 0*spm
-    pace = strokedata.loc[:, 'p']/10.
+    pace = strokedata['p']/10.
     pace = np.clip(pace, 0, 1e4)
-    pace = pace.replace(0, 300)
+    pace = pl.Series(pace).replace(0, 300)
 
     velo = 500./pace
 
     try:
-        power = strokedata.loc[:, 'power']
+        power = strokedata['power']
     except KeyError:  # pragma: no cover
         power = 2.8*velo**3
 
@@ -3999,7 +3918,7 @@ def fetch_strava_workout(stravatoken, oauth_data, stravaid, csvfilename, userid,
 
     # save csv
     # Create data frame with all necessary data to write to csv
-    df = pd.DataFrame({'TimeStamp (sec)': unixtime,
+    df = pl.DataFrame({'TimeStamp (sec)': unixtime,
                        ' Horizontal (meters)': dist2,
                        ' Cadence (stokes/min)': spm,
                        ' HRCur (bpm)': hr,
@@ -4019,10 +3938,10 @@ def fetch_strava_workout(stravatoken, oauth_data, stravaid, csvfilename, userid,
                        'cum_dist': dist2,
                        })
 
-    df.sort_values(by='TimeStamp (sec)', ascending=True)
+    df.sort('TimeStamp (sec)')
 
-    row = rowingdata.rowingdata(df=df)
+    row = rowingdata.rowingdata_pl(df=df)
-    row.write_csv(csvfilename, gzip=False)
+    row.write_csv(csvfilename, compressed=False)
 
     # summary = row.allstats()
     # maxdist = df['cum_dist'].max()

rowers/tests/test_async_tasks.py

@@ -484,51 +484,7 @@ class AsyncTaskTests(TestCase):
         res = tasks.handle_c2_import_stroke_data(c2token,c2id,workoutid,starttimeunix,csvfilename)
         self.assertEqual(res,1)
 
-    @patch('rowers.tasks.grpc',side_effect=mocked_grpc)
-    @patch('rowers.tasks.send_template_email',side_effect=mocked_send_template_email)
-    def test_handle_otwsetpower(self,mocked_send_template_email,mocked_grpc):
-        f1 = get_random_file(filename='rowers/tests/testdata/sprintervals.csv')['filename']
-        boattype = '1x'
-        boatclass = 'water'
-        coastalbrand = 'other'
-        weightvalue = 80.
-        first_name = self.u.first_name
-        last_name = self.u.last_name
-        email = self.u.email
-        workoutid = self.wwater.id
-        job = fakerequest()
 
-        res = tasks.handle_otwsetpower(f1,boattype,boatclass,coastalbrand,
-                                       weightvalue,first_name,last_name,email,workoutid,
-                                       jobkey='23')
-
-        self.assertEqual(res,1)
-
-    @patch('rowers.dataprep.create_engine')
-    def test_handle_updateergcp(self,mocked_sqlalchemy):
-        f1 = get_random_file()['filename']
-        res = tasks.handle_updateergcp(1,[f1])
-        self.assertEqual(res,1)
-
-
-    @patch('rowers.dataprep.getsmallrowdata_db')
-    def test_handle_updatecp(self,mocked_getsmallrowdata_db_updatecp):
-        rower_id = 1
-        workoutids = [1]
-        res = tasks.handle_updatecp(rower_id,workoutids)
-        self.assertEqual(res,1)
-
-    @patch('rowers.dataprep.getsmallrowdata_db')
-    def test_handle_setcp(self,mocked_getsmallrowdata_db_setcp):
-        strokesdf = pd.read_csv('rowers/tests/testdata/uhfull.csv')
-        filename = 'rowers/tests/testdata/temp/pq.gz'
-        workoutids = 1
-        res = tasks.handle_setcp(strokesdf,filename,1)
-        self.assertEqual(res,1)
-        try:
-            os.remove(filename)
-        except FileNotFoundError:
-            pass
 
     @patch('rowers.dataprep.getsmallrowdata_db')
     def test_handle_update_wps(self,mocked_getsmallrowdata_db_wps):

rowers/tests/test_unit_tests.py

@@ -703,7 +703,7 @@ class InteractivePlotTests(TestCase):
         self.assertFalse(len(div)==0)
 
     @patch('rowers.dataprep.create_engine')
-    @patch('rowers.dataprep.getsmallrowdata_db', side_effect=mocked_getsmallrowdata_db)
+    @patch('rowers.dataprep.getsmallrowdata_pl', side_effect=mocked_getsmallrowdata_pl)
     def test_interactive_chart(self, mocked_sqlalchemy,
                                mocked_getsmallrowdata_db):
         workout = Workout.objects.filter(user=self.r,workouttype__in=mytypes.rowtypes)[0]

rowers/views/statements.py

@@ -252,7 +252,7 @@ from rowers.tasks import (
     handle_sendemailfile,
     handle_sendemailkml,
     handle_sendemailnewresponse, handle_updatedps,
-    handle_updatecp, long_test_task, long_test_task2,
+    long_test_task, long_test_task2,
     handle_zip_file, handle_getagegrouprecords,
     handle_update_empower,
     handle_sendemailics,