View request_google.py
import google.auth | |
from google.auth.transport.requests import AuthorizedSession | |
# login | |
from google.colab import auth | |
auth.authenticate_user() | |
# use default credentials to create session | |
cred = google.auth.default()[0] # for cred.token | |
s = AuthorizedSession(cred) | |
# s.get or s.post | |
url = 'https://storage.googleapis.com/storage/v1/b/co-lab' |
View to_sec.py
def to_sec(tstr): | |
""" 1:01:01 -> 3661 """ | |
t = 0 | |
for p in tstr.split(':'): | |
t *= 60 | |
t += int(p) | |
return t |
View duration.py
from requests import get | |
!pip install isodate -q | |
import isodate | |
key = 'AZxxxx' # from https://console.cloud.google.com/apis/credentials | |
def get_durations(id_list): | |
url = 'https://www.googleapis.com/youtube/v3/videos' | |
kw = { | |
'id': ','.join(id_list), |
View dict_string.py
d = ''' | |
a 1 | |
b 2 | |
c 3 | |
'''.strip().split('\n') | |
d = dict(row.split() for row in d) | |
# {'a': '1', 'b': '2', 'c': '3'} |
View df_string.py
import pandas as pd | |
from io import StringIO | |
data = StringIO(''' | |
symbol,quan,v0 | |
ONE-UGERMF, 71472.71, 21.9749 | |
ONE-UGG-ASSF, 5593.87, 35.7534 | |
1SG-LTF-T, 11523.57, 31.9562 | |
'''.strip()) |
View fastquant.py
# manually install dependencies, then use no-deps | |
!pip install backtrader croniter cryptography twython yfinance | |
!pip install fastquant ccxt --no-deps |
View plotly.py
!pip install -U plotly | |
import pandas as pd | |
pd.options.plotting.backend = "plotly" | |
df.col.plot() | |
# To get log scale | |
fig = df.col.plot() # can't logy=True | |
fig.update_layout(yaxis_type="log") |
View kenlm.py
!curl -L bit.ly/kenlm-colab | tar xz -C / |
View mfa_align.py
# install | |
import pandas as pd | |
!pip install textgrid -q | |
from textgrid import TextGrid | |
url = 'https://github.com/MontrealCorpusTools/Montreal-Forced-Aligner/releases/download/v1.1.0-beta.2/montreal-forced-aligner_linux.tar.gz' | |
!curl -L $url | tar xz --strip-components=2 | |
!wget https://github.com/MontrealCorpusTools/mfa-models/raw/master/acoustic/thai.zip | |
!mv thai.zip pretrained_models/ | |
!gdown --id 1-61YXBHhuXWmsRsi_QG-3nmCzzD2MlPR | |
!mv mfa_dict_2.txt dict.txt |
View tg_to_df.py
import pandas as pd | |
!pip install textgrid -q | |
from textgrid import TextGrid | |
def read_tg(tg_file): | |
tg = TextGrid.fromFile(tg_file) | |
data = [(w.minTime, w.maxTime, w.mark) for w in tg[0]] | |
left, right, words = zip(*data) | |
index = pd.IntervalIndex.from_arrays(left, right, name='time') | |
df = pd.DataFrame(words, index, ['word']) |
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