moving to upload_tasks, stopped just before c2
This commit is contained in:
@@ -1,10 +1,15 @@
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import os
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import time
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from uuid import uuid4
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import shutil
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import requests
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from rowingdata import FITParser as FP
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from rowingdata.otherparsers import FitSummaryData
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import rowingdata
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import pandas as pd
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import iso8601
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import arrow
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import numpy as np
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os.environ["DJANGO_ALLOW_ASYNC_UNSAFE"] = "true"
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from YamJam import yamjam
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@@ -32,10 +37,13 @@ from rowers.mytypes import intervalsmappinginv
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from rowers.dataroutines import (
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totaltime_sec_to_string,
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)
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from rowers.utils import ewmovingaverage, dologging
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from rowers.celery import app
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from celery import shared_task
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from django.utils import timezone
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SITE_URL = CFG['site_url']
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SITE_URL_DEV = CFG['site_url']
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PROGRESS_CACHE_SECRET = CFG['progress_cache_secret']
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@@ -229,3 +237,295 @@ def handle_intervals_getworkout(rower, intervalstoken, workoutid, debug=False, *
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return w.id
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def splitstdata(lijst): # pragma: no cover
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t = []
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latlong = []
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while len(lijst) >= 2:
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t.append(lijst[0])
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latlong.append(lijst[1])
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lijst = lijst[2:]
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return [np.array(t), np.array(latlong)]
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@app.task
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def handle_sporttracks_workout_from_data(user, importid, source,
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workoutsource, debug=False, **kwargs): # pragma: no cover
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r = user.rower
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authorizationstring = str('Bearer ' + r.sporttrackstoken)
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headers = {'Authorization': authorizationstring,
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'user-agent': 'sanderroosendaal',
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'Content-Type': 'application/json'}
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url = "https://api.sporttracks.mobi/api/v2/fitnessActivities/" + \
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str(importid)
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s = requests.get(url, headers=headers)
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data = s.json()
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strokedata = pd.DataFrame.from_dict({
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key: pd.Series(value, dtype='object') for key, value in data.items()
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})
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try:
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workouttype = data['type']
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except KeyError: # pragma: no cover
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workouttype = 'other'
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if workouttype not in [x[0] for x in Workout.workouttypes]:
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workouttype = 'other'
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try:
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comments = data['comments']
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except:
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comments = ''
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r = Rower.objects.get(user=user)
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rowdatetime = iso8601.parse_date(data['start_time'])
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starttimeunix = arrow.get(rowdatetime).timestamp()
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try:
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title = data['name']
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except: # pragma: no cover
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title = "Imported data"
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try:
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res = splitstdata(data['distance'])
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distance = res[1]
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times_distance = res[0]
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except KeyError: # pragma: no cover
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try:
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res = splitstdata(data['heartrate'])
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times_distance = res[0]
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distance = 0*times_distance
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except KeyError:
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return (0, "No distance or heart rate data in the workout")
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try:
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locs = data['location']
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res = splitstdata(locs)
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times_location = res[0]
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latlong = res[1]
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latcoord = []
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loncoord = []
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for coord in latlong:
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lat = coord[0]
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lon = coord[1]
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latcoord.append(lat)
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loncoord.append(lon)
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except:
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times_location = times_distance
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latcoord = np.zeros(len(times_distance))
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loncoord = np.zeros(len(times_distance))
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if workouttype in mytypes.otwtypes: # pragma: no cover
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workouttype = 'rower'
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try:
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res = splitstdata(data['cadence'])
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times_spm = res[0]
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spm = res[1]
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except KeyError: # pragma: no cover
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times_spm = times_distance
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spm = 0*times_distance
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try:
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res = splitstdata(data['heartrate'])
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hr = res[1]
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times_hr = res[0]
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except KeyError:
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times_hr = times_distance
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hr = 0*times_distance
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# create data series and remove duplicates
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distseries = pd.Series(distance, index=times_distance)
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distseries = distseries.groupby(distseries.index).first()
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latseries = pd.Series(latcoord, index=times_location)
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latseries = latseries.groupby(latseries.index).first()
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lonseries = pd.Series(loncoord, index=times_location)
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lonseries = lonseries.groupby(lonseries.index).first()
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spmseries = pd.Series(spm, index=times_spm)
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spmseries = spmseries.groupby(spmseries.index).first()
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hrseries = pd.Series(hr, index=times_hr)
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hrseries = hrseries.groupby(hrseries.index).first()
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# Create dicts and big dataframe
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d = {
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' Horizontal (meters)': distseries,
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' latitude': latseries,
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' longitude': lonseries,
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' Cadence (stokes/min)': spmseries,
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' HRCur (bpm)': hrseries,
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}
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df = pd.DataFrame(d)
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df = df.groupby(level=0).last()
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cum_time = df.index.values
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df[' ElapsedTime (sec)'] = cum_time
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velo = df[' Horizontal (meters)'].diff()/df[' ElapsedTime (sec)'].diff()
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df[' Power (watts)'] = 0.0*velo
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nr_rows = len(velo.values)
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df[' DriveLength (meters)'] = np.zeros(nr_rows)
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df[' StrokeDistance (meters)'] = np.zeros(nr_rows)
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df[' DriveTime (ms)'] = np.zeros(nr_rows)
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df[' StrokeRecoveryTime (ms)'] = np.zeros(nr_rows)
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df[' AverageDriveForce (lbs)'] = np.zeros(nr_rows)
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df[' PeakDriveForce (lbs)'] = np.zeros(nr_rows)
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df[' lapIdx'] = np.zeros(nr_rows)
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unixtime = cum_time+starttimeunix
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unixtime[0] = starttimeunix
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df['TimeStamp (sec)'] = unixtime
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dt = np.diff(cum_time).mean()
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wsize = round(5./dt)
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velo2 = ewmovingaverage(velo, wsize)
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df[' Stroke500mPace (sec/500m)'] = 500./velo2
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df = df.fillna(0)
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df.sort_values(by='TimeStamp (sec)', ascending=True)
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csvfilename = 'media/{code}_{importid}.csv'.format(
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importid=importid,
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code=uuid4().hex[:16]
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)
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res = df.to_csv(csvfilename+'.gz', index_label='index',
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compression='gzip')
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w = Workout(
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user=r,
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duration=totaltime_sec_to_string(cum_time[-1]),
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uploadedtosporttracks=importid,
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)
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w.save()
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uploadoptions = {
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'user': user.id,
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'file': csvfilename+'.gz',
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'title': '',
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'workouttype': workouttype,
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'boattype': '1x',
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'sporttracksid': importid,
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'id': w.id,
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'title':title,
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}
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response = upload_handler(uploadoptions, csvfilename+'.gz')
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if response['status'] != 'processing':
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return 0
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return 1
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@app.task
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def handle_rp3_async_workout(userid, rp3token, rp3id, startdatetime, max_attempts, debug=False, **kwargs):
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timezone = kwargs.get('timezone', 'UTC')
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headers = {'Authorization': 'Bearer ' + rp3token}
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get_download_link = """{
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download(workout_id: """ + str(rp3id) + """, type:csv){
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id
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status
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link
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}
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}"""
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have_link = False
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download_url = ''
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counter = 0
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waittime = 3
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while not have_link:
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try:
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response = requests.post(
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url=graphql_url,
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headers=headers,
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json={'query': get_download_link}
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)
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dologging('rp3_import.log',response.status_code)
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if response.status_code != 200: # pragma: no cover
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have_link = True
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workout_download_details = pd.json_normalize(
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response.json()['data']['download'])
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dologging('rp3_import.log', response.json())
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except: # pragma: no cover
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return 0
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if workout_download_details.iat[0, 1] == 'ready':
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download_url = workout_download_details.iat[0, 2]
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have_link = True
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dologging('rp3_import.log', download_url)
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counter += 1
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dologging('rp3_import.log', counter)
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if counter > max_attempts: # pragma: no cover
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have_link = True
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time.sleep(waittime)
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if download_url == '': # pragma: no cover
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return 0
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filename = 'media/RP3Import_'+str(rp3id)+'.csv'
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res = requests.get(download_url, headers=headers)
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dologging('rp3_import.log','tasks.py '+str(rp3id))
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dologging('rp3_import.log',startdatetime)
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if not startdatetime: # pragma: no cover
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startdatetime = str(timezone.now())
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try:
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startdatetime = str(startdatetime)
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except: # pragma: no cover
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pass
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if res.status_code != 200: # pragma: no cover
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return 0
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with open(filename, 'wb') as f:
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# dologging('rp3_import.log',res.text)
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dologging('rp3_import.log', 'Rp3 ID = {id}'.format(id=rp3id))
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f.write(res.content)
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w = Workout(
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user=User.objects.get(id=userid),
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duration=totaltime_sec_to_string(cum_time[-1]),
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uploadedtosporttracks=importid,
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)
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w.save()
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uploadoptions = {
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'secret': UPLOAD_SERVICE_SECRET,
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'user': userid,
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'file': filename,
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'workouttype': 'rower',
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'boattype': 'rp3',
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'rp3id': int(rp3id),
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'startdatetime': startdatetime,
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'timezone': timezone,
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}
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response = upload_handler(uploadoptions, filename)
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if response['status'] != 'processing':
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return 0
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return 1
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