def earliestScrobbleYear() -> int:
'''Determine the earliest year for the user's scrobbles.'''
lastPage = int(
getReq(param=Param(method='user.getInfo')).get('playcount')
) - 100 # subtract 100 plays, in case some have "unknown" scrobble dates, i.e. 1970
return getReq(
param=Param(method='user.getRecentTracks', lim=1,
page=lastPage)).loc[0, 'date'].year
def exportScrobbles():
'''Fetch and process user scrobbles for the current year and for any year where exported json files are not present.'''
def earliestScrobbleYear() -> int:
'''Determine the earliest year for the user's scrobbles.'''
lastPage = int(
getReq(param=Param(method='user.getInfo')).get('playcount')
) - 100 # subtract 100 plays, in case some have "unknown" scrobble dates, i.e. 1970
return getReq(
param=Param(method='user.getRecentTracks', lim=1,
page=lastPage)).loc[0, 'date'].year
param = Param(method='user.getRecentTracks', period='overall')
currentYear = datetime.datetime.now().year
for year in range(earliestScrobbleYear(), currentYear):
paramYear = Param(method='user.getRecentTracks',
period=year,
fr=f'{year}-01-01 00:00:00',
to=f'{year}-12-31 23:59:59')
response = getReq(param=paramYear, collapse=False, limit=1)
numPages = math.ceil(
int(response.get('recenttracks').get('@attr').get('total')) /
param.lim)
if numPages != len(paramYear.filePath(glob='*json')):
downloadData(paramYear, download=True)
else:
downloadData(paramYear, download=False)
downloadData(
Param(method='user.getRecentTracks',
period=currentYear,
fr=f'{currentYear}-01-01 00:00:00',
to=f'{currentYear}-12-31 23:59:59'))
mergeRecentTracks(param)
def downloadData(param: Param, download: bool = True):
'''Download user data (if {download} is True) to json files, merge them into a flat pandas.DataFrame, and write it to disk.'''
logging.info(f"{param.filePath().name.replace('.','|')}")
if download:
subMethod = param.splitMethod(lower=True)
for f in param.filePath(glob='*json'):
f.unlink()
pbarManager = enlighten.get_manager()
with pbarManager.counter(unit='page', leave=False) as pbar:
while param.page <= param.nPages:
fileName = param.filePath(ext=f'.{param.page:04d}.json')
response = getReq(param=param,
pbarManager=pbarManager,
collapse=False)
param.page = int(
response.get(subMethod).get('@attr').get('page'))
param.nPages = int(
response.get(subMethod).get('@attr').get('totalPages'))
pbar.total = param.nPages # [tqdm: update total without resetting time elapsed](https://stackoverflow.com/a/58961015/13019084)
pbar.update()
param.filePath().parent.mkdir(exist_ok=True)
with open(file=fileName, mode='w') as jsonF:
json.dump(obj=response, fp=jsonF)
param.page += 1
time.sleep(param.sleep)
pbarManager.stop()
DF = loadJSON(param)
df = flattenDF(param=param, DF=DF, writeToDisk=True)
if param.splitMethod() in ['TopArtists', 'TopAlbums', 'TopTracks']:
writeCSV(param=param, df=df)
def weeklyChart(method:str='user.getWeeklyArtistChart', weeksAgo:int=4, nWeeks:int=1, thr:int=6, **kwargs) -> pandas.DataFrame:
'''Fetch data for {user.getWeekly*Chart} methods.'''
(fr,to) = dateRange(weeksAgo=weeksAgo, nWeeks=nWeeks, **kwargs)
param = Param(method=method, fr=fr, to=to)
# ts = getReq(Param(method='user.getWeeklyChartList'))[::-1].reset_index() # [user.getWeeklyChartList](https://www.last.fm/api/show/user.getWeeklyChartList)
# DF = getReq(param=Param(method=method, fr=ts.loc[weeksAgo+nWeeks,'list_from'], to=ts.loc[weeksAgo,'list_to']))
DF = getReq(param=param)
return DF[DF[f'{param.splitMethod(plural=False, strip=True)}_playcount'] >= thr]
def recommFromNeighbor(neighbor:str=None, method:str='user.getTopArtists', neighborThr:int=100, myThr:int=1000, **kwargs) -> pandas.DataFrame:
'''Return neighbor's top artists/albums/songs missing from the user's top listens'''
if not neighbor: return lastfmNeighbors()
else:
myData = loadUserData(Param(method=method)).head(myThr)
param = Param(method=method, user=neighbor, lim=neighborThr)
entity = param.splitMethod(lower=True, plural=False, strip=True)
neighborData = getReq(param)
cols = [f'{entity}_name', f'{entity}_playcount']
if entity != 'artist': cols = [f'artist_name', *cols]
# numpy.setdiff1d(neighborData.get(f'{entity}_name'), myData.get(f'{entity}_name')) # [Compare and find missing strings in pandas Series](https://stackoverflow.com/a/58544291/13019084)
return neighborData[[item not in myData.get(f'{entity}_name').to_list() for item in neighborData.get(f'{entity}_name').to_list()]][cols]
def getTopArtistTags(artist='opeth', **kwargs): return getReq(param=Param(method='artist.getTopTags'), artist=artist, **kwargs) def topArtistsCountry(country:str='spain', **kwargs): return getReq(param=Param(method='geo.getTopArtists', lim=10), country=country, **kwargs)
