1 | |
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2 | from datetime import datetime, timedelta, timezone |
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3 | from decimal import Decimal |
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4 | |
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5 | import pytz |
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6 | import gpxpy |
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7 | from repoze.folder import Folder |
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8 | from pyramid.security import Allow, Everyone |
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9 | |
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10 | from ow.utilities import ( |
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11 | GPXMinidomParser, |
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12 | copy_blob, |
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13 | create_blob, |
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14 | mps_to_kmph |
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15 | ) |
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16 | |
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17 | from ow.fit import Fit |
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18 | |
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19 | |
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20 | class Workout(Folder): |
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21 | |
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22 | __parent__ = __name__ = None |
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23 | |
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24 | def __acl__(self): |
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25 | """ |
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26 | If the workout is owned by a given user, only that user have access to |
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27 | it (for now). If not, everybody can view it, only admins can edit it. |
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28 | """ |
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29 | # Default permissions |
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30 | permissions = [ |
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31 | (Allow, Everyone, 'view'), |
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32 | (Allow, 'group:admins', 'edit') |
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33 | ] |
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34 | |
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35 | uid = getattr(self.__parent__, 'uid', None) |
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36 | if uid is not None: |
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37 | # Change permissions in case this workout has an owner |
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38 | permissions = [ |
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39 | (Allow, str(uid), 'view'), |
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40 | (Allow, str(uid), 'edit'), |
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41 | ] |
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42 | return permissions |
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43 | |
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44 | def __init__(self, **kw): |
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45 | super(Workout, self).__init__() |
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46 | # we do store datetime objects with UTC timezone |
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47 | self.start = kw.get('start', datetime.now(timezone.utc)) |
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48 | self.sport = kw.get('sport', 'unknown') # string |
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49 | self.title = kw.get('title', '') # unicode string |
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50 | self.notes = kw.get('notes', '') # unicode string |
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51 | self.duration = kw.get('duration', None) # a timedelta object |
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52 | self.distance = kw.get('distance', None) # kilometers, Decimal |
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53 | self.speed = kw.get('speed', {}) |
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54 | self.hr_min = kw.get('hr_min', None) # bpm, Decimal |
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55 | self.hr_max = kw.get('hr_max', None) # bpm, Decimal |
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56 | self.hr_avg = kw.get('hr_avg', None) # bpm, Decimal |
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57 | self.uphill = kw.get('uphill', None) |
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58 | self.downhill = kw.get('downhill', None) |
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59 | self.cad_min = kw.get('cad_min', None) |
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60 | self.cad_max = kw.get('cad_max', None) |
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61 | self.cad_avg = kw.get('cad_avg', None) |
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62 | self.atemp_min = kw.get('atemp_min', None) |
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63 | self.atemp_max = kw.get('atemp_max', None) |
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64 | self.atemp_avg = kw.get('atemp_avg', None) |
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65 | self.tracking_file = kw.get('tracking_file', None) # Blob |
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66 | self.tracking_filetype = '' # unicode string |
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67 | # attr to store ANT fit files. For now this file is used to |
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68 | # generate a gpx-encoded tracking file we then use through |
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69 | # the whole app |
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70 | self.fit_file = kw.get('fit_file', None) # Blob |
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71 | |
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72 | @property |
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73 | def workout_id(self): |
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74 | return self.__name__ |
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75 | |
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76 | @property |
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77 | def owner(self): |
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78 | return self.__parent__ |
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79 | |
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80 | @property |
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81 | def end(self): |
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82 | if not self.duration: |
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83 | return None |
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84 | return self.start + self.duration |
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85 | |
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86 | @property |
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87 | def start_date(self): |
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88 | return self.start.strftime('%d/%m/%Y') |
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89 | |
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90 | @property |
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91 | def start_time(self): |
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92 | return self.start.strftime('%H:%M') |
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93 | |
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94 | def start_in_timezone(self, timezone): |
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95 | """ |
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96 | Return a string representation of the start date and time, |
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97 | localized into the given timezone |
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98 | """ |
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99 | _start = self.start.astimezone(pytz.timezone(timezone)) |
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100 | return _start.strftime('%d/%m/%Y %H:%M (%Z)') |
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101 | |
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102 | def end_in_timezone(self, timezone): |
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103 | """ |
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104 | Return a string representation of the end date and time, |
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105 | localized into the given timezone |
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106 | """ |
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107 | _end = self.end.astimezone(pytz.timezone(timezone)) |
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108 | return _end.strftime('%d/%m/%Y %H:%M (%Z)') |
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109 | |
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110 | def split_duration(self): |
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111 | hours, remainder = divmod(int(self.duration.total_seconds()), 3600) |
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112 | minutes, seconds = divmod(remainder, 60) |
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113 | return hours, minutes, seconds |
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114 | |
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115 | @property |
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116 | def duration_hours(self): |
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117 | return str(self.split_duration()[0]).zfill(2) |
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118 | |
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119 | @property |
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120 | def duration_minutes(self): |
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121 | return str(self.split_duration()[1]).zfill(2) |
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122 | |
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123 | @property |
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124 | def duration_seconds(self): |
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125 | return str(self.split_duration()[2]).zfill(2) |
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126 | |
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127 | @property |
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128 | def _duration(self): |
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129 | return ':'.join( |
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130 | [self.duration_hours, self.duration_minutes, self.duration_seconds] |
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131 | ) |
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132 | |
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133 | @property |
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134 | def rounded_distance(self): |
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135 | """ |
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136 | Return rounded value for distance, '-' if the workout has no distance |
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137 | data (weight lifting, martial arts, table tennis, etc) |
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138 | """ |
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139 | if self.distance: |
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140 | return round(self.distance, 1) |
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141 | return '-' |
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142 | |
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143 | @property |
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144 | def has_hr(self): |
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145 | """ |
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146 | True if this workout has heart rate data, False otherwise |
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147 | """ |
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148 | data = [self.hr_min, self.hr_max, self.hr_avg] |
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149 | return data.count(None) == 0 |
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150 | |
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151 | @property |
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152 | def hr(self): |
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153 | """ |
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154 | Return a dict with rounded values for hr min, max and average, |
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155 | return None if there is no heart rate data for this workout |
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156 | """ |
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157 | if self.has_hr: |
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158 | return {'min': round(self.hr_min), |
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159 | 'max': round(self.hr_max), |
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160 | 'avg': round(self.hr_avg)} |
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161 | return None |
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162 | |
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163 | @property |
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164 | def has_cad(self): |
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165 | """ |
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166 | True if this workout has cadence data, False otherwise |
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167 | """ |
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168 | data = [self.cad_min, self.cad_max, self.cad_avg] |
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169 | return data.count(None) == 0 |
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170 | |
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171 | @property |
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172 | def cad(self): |
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173 | """ |
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174 | Return a dict with rounded values for cadence min, max and average |
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175 | return None if there is no cadence data for this workout |
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176 | """ |
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177 | if self.has_cad: |
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178 | return {'min': round(self.cad_min), |
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179 | 'max': round(self.cad_max), |
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180 | 'avg': round(self.cad_avg)} |
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181 | return None |
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182 | |
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183 | @property |
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184 | def has_atemp(self): |
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185 | """ |
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186 | True if this workout has temperature data, False otherwise |
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187 | """ |
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188 | data = [self.atemp_min, self.atemp_max, self.atemp_avg] |
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189 | return data.count(None) == 0 |
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190 | |
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191 | @property |
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192 | def atemp(self): |
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193 | """ |
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194 | Return a dict with rounded values for temperature min, max and average |
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195 | return None if there is no temperature data for this workout |
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196 | """ |
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197 | if self.has_atemp: |
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198 | return {'min': round(self.atemp_min), |
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199 | 'max': round(self.atemp_max), |
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200 | 'avg': round(self.atemp_avg)} |
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201 | return None |
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202 | |
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203 | @property |
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204 | def tracking_file_path(self): |
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205 | """ |
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206 | Get the path to the blob file attached as a tracking file. |
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207 | |
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208 | First check if the file was not committed to the db yet (new workout |
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209 | not saved yet) and use the path to the temporary file on the fs. |
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210 | If none is found there, go for the real blob file in the blobs |
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211 | directory |
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212 | """ |
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213 | path = None |
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214 | if self.tracking_file: |
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215 | path = self.tracking_file._p_blob_uncommitted |
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216 | if path is None: |
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217 | path = self.tracking_file._p_blob_committed |
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218 | return path |
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219 | |
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220 | @property |
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221 | def fit_file_path(self): |
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222 | """ |
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223 | Get the path to the blob file attached as a fit file. |
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224 | |
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225 | First check if the file was not committed to the db yet (new workout |
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226 | not saved yet) and use the path to the temporary file on the fs. |
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227 | If none is found there, go for the real blob file in the blobs |
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228 | directory |
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229 | """ |
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230 | path = None |
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231 | if self.fit_file: |
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232 | path = self.fit_file._p_blob_uncommitted |
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233 | if path is None: |
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234 | path = self.fit_file._p_blob_committed |
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235 | return path |
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236 | |
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237 | def load_from_file(self): |
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238 | """ |
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239 | Check which kind of tracking file we have for this workout, then call |
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240 | the proper method to load info from the tracking file |
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241 | """ |
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242 | if self.tracking_filetype == 'gpx': |
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243 | self.load_from_gpx() |
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244 | elif self.tracking_filetype == 'fit': |
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245 | self.load_from_fit() |
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246 | |
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247 | def load_from_gpx(self): |
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248 | """ |
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249 | Load some information from an attached gpx file. Return True if data |
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250 | had been succesfully loaded, False otherwise |
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251 | """ |
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252 | with self.tracking_file.open() as gpx_file: |
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253 | gpx_contents = gpx_file.read() |
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254 | gpx_contents = gpx_contents.decode('utf-8') |
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255 | gpx = gpxpy.parse(gpx_contents) |
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256 | if gpx.tracks: |
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257 | track = gpx.tracks[0] |
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258 | # Start time comes in UTC/GMT/ZULU |
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259 | time_bounds = track.get_time_bounds() |
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260 | self.start = time_bounds.start_time |
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261 | # ensure this datetime start object is timezone-aware |
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262 | self.start = self.start.replace(tzinfo=timezone.utc) |
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263 | # get_duration returns seconds |
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264 | self.duration = timedelta(seconds=track.get_duration()) |
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265 | # length_3d returns meters |
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266 | self.distance = Decimal(track.length_3d()) / Decimal(1000.00) |
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267 | ud = track.get_uphill_downhill() |
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268 | self.uphill = Decimal(ud.uphill) |
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269 | self.downhill = Decimal(ud.downhill) |
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270 | # If the user did not provide us with a title, and the gpx has |
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271 | # one, use that |
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272 | if not self.title and track.name: |
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273 | self.title = track.name |
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274 | |
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275 | # Hack to calculate some values from the GPX 1.1 extensions, |
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276 | # using our own parser (gpxpy does not support those yet) |
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277 | tracks = self.parse_gpx() |
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278 | hr = [] |
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279 | cad = [] |
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280 | atemp = [] |
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281 | for t in tracks: |
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282 | hr += [ |
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283 | d['hr'] for d in tracks[t] if d['hr'] is not None] |
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284 | cad += [ |
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285 | d['cad'] for d in tracks[t] if d['cad'] is not None] |
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286 | atemp += [ |
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287 | d['atemp'] for d in tracks[t] |
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288 | if d['atemp'] is not None] |
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289 | |
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290 | if hr: |
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291 | self.hr_min = Decimal(min(hr)) |
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292 | self.hr_avg = Decimal(sum(hr)) / Decimal(len(hr)) |
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293 | self.hr_max = Decimal(max(hr)) |
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294 | |
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295 | if cad: |
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296 | self.cad_min = Decimal(min(cad)) |
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297 | self.cad_avg = Decimal(sum(cad)) / Decimal(len(cad)) |
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298 | self.cad_max = Decimal(max(cad)) |
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299 | |
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300 | if atemp: |
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301 | self.atemp_min = Decimal(min(atemp)) |
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302 | self.atemp_avg = Decimal(sum(atemp)) / Decimal(len(atemp)) |
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303 | self.atemp_max = Decimal(max(atemp)) |
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304 | |
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305 | return True |
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306 | |
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307 | return False |
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308 | |
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309 | def parse_gpx(self): |
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310 | """ |
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311 | Parse the gpx using minidom. |
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312 | |
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313 | This method is needed as a workaround to get HR/CAD/TEMP values from |
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314 | gpx 1.1 extensions (gpxpy does not handle them correctly so far) |
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315 | """ |
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316 | if not self.has_gpx: |
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317 | # No gpx, nothing to return |
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318 | return {} |
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319 | |
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320 | # Get the path to the blob file, first check if the file was not |
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321 | # committed to the db yet (new workout not saved yet) and use the |
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322 | # path to the temporary file on the fs. If none is found there, go |
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323 | # for the final blob file |
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324 | gpx_path = self.tracking_file._p_blob_uncommitted |
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325 | if gpx_path is None: |
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326 | gpx_path = self.tracking_file._p_blob_committed |
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327 | |
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328 | # Create a parser, load the gpx and parse the tracks |
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329 | parser = GPXMinidomParser(gpx_path) |
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330 | parser.load_gpx() |
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331 | parser.parse_tracks() |
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332 | return parser.tracks |
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333 | |
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334 | def load_from_fit(self): |
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335 | """ |
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336 | Try to load data from an ANT-compatible .fit file (if any has been |
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337 | added to this workout). |
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338 | |
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339 | "Load data" means: |
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340 | |
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341 | 1. Copy over the uploaded fit file to self.fit_file, so we can keep |
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342 | that copy around for future use |
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343 | |
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344 | 2. generate a gpx object from the fit file |
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345 | |
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346 | 3. save the gpx object as the tracking_file, which then will be used |
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347 | by the current code to display and gather data to be displayed/shown |
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348 | to the user. |
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349 | |
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350 | 4. Grab some basic info from the fit file and store it in the Workout |
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351 | """ |
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352 | # backup the fit file |
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353 | self.fit_file = copy_blob(self.tracking_file) |
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354 | |
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355 | # create an instance of our Fit class |
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356 | fit = Fit(self.fit_file_path) |
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357 | fit.load() |
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358 | |
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359 | # fit -> gpx and store that as the main tracking file |
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360 | self.tracking_file = create_blob(fit.gpx, 'gpx') |
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361 | self.tracking_filetype = 'gpx' |
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362 | |
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363 | # grab the needed data from the fit file, update the workout |
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364 | self.sport = fit.data['sport'] |
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365 | self.start = fit.data['start'] |
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366 | # ensure this datetime start object is timezone-aware |
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367 | self.start = self.start.replace(tzinfo=timezone.utc) |
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368 | # duration comes in seconds, store a timedelta |
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369 | self.duration = timedelta(seconds=fit.data['duration']) |
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370 | if fit.data['distance']: |
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371 | # distance comes in meters |
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372 | self.distance = Decimal(fit.data['distance']) / Decimal(1000.00) |
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373 | if fit.data['uphill']: |
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374 | self.uphill = Decimal(fit.data['uphill']) |
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375 | if fit.data['downhill']: |
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376 | self.downhill = Decimal(fit.data['downhill']) |
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377 | # If the user did not provide us with a title, build one from the |
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378 | # info in the fit file |
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379 | if not self.title: |
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380 | self.title = fit.name |
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381 | |
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382 | if fit.data['max_speed']: |
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383 | self.speed['max'] = mps_to_kmph(fit.data['max_speed']) |
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384 | |
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385 | if fit.data['avg_speed']: |
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386 | self.speed['avg'] = mps_to_kmph(fit.data['avg_speed']) |
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387 | |
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388 | if fit.data['avg_hr']: |
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389 | self.hr_avg = Decimal(fit.data['avg_hr']) |
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390 | self.hr_min = Decimal(fit.data['min_hr']) |
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391 | self.hr_max = Decimal(fit.data['max_hr']) |
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392 | |
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393 | if fit.data['avg_cad']: |
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394 | self.cad_avg = Decimal(fit.data['avg_cad']) |
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395 | self.cad_min = Decimal(fit.data['min_cad']) |
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396 | self.cad_max = Decimal(fit.data['max_cad']) |
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397 | |
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398 | if fit.data['avg_atemp']: |
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399 | self.atemp_avg = Decimal(fit.data['avg_atemp']) |
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400 | self.atemp_min = Decimal(fit.data['min_atemp']) |
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401 | self.atemp_max = Decimal(fit.data['max_atemp']) |
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402 | |
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403 | return True |
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404 | |
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405 | @property |
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406 | def has_tracking_file(self): |
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407 | return self.tracking_file is not None |
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408 | |
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409 | @property |
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410 | def has_gpx(self): |
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411 | return self.has_tracking_file and self.tracking_filetype == 'gpx' |
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412 | |
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413 | @property |
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414 | def has_fit(self): |
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415 | return self.fit_file is not None |
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