def read_unformatted():
home_id_dict = util.get_homeid_dict()
files = glob.glob(
util.get_path('daily_reading', 'raw_data', 'all') +
'xlsx_unformatted/*.xlsx')
for f in files[:1]:
filename = f[f.rfind('/') + 1:]
tokens = util.split_string([' ', '_', '.', '-'], filename)
home_id = 'UNKNOWN'
for x in tokens:
if x in home_id_dict:
home_id = home_id_dict[x]
df = pd.read_excel(f, sheetname=0)
if filename == 'TC_D2_Romer_Manual readings -logs_ - Sail boat_11-1_11-18.xlsx':
df.rename(columns={
'Date': 'date',
'Time': 'time',
'Action: observations and behaviour': 'activity'
},
inplace=True)
df.dropna(axis=0, how='all', inplace=True)
pattern = re.compile('[0-9]{1,2}')
df['date'] = df['date'].ffill()
df['time'] = df['time'].ffill()
df.dropna(subset=['date', 'time'], axis=0, how='any', inplace=True)
df['time'] = df['time'].map(remove_ampm)
df['date'] = df['date'].map(
lambda x: 'Nov' if x == 'Nov' else '2016-11-{0}'.format(
re.match(pattern, x).group()))
df = df[['date', 'time', 'activity']]
if filename == 'DHP Log - DHP-HP-Daily Readings week of Jan 11, 2016.xlsx':
df = df.ix[19:23, [0, 1, 8]]
df.rename(columns={
'Date': 'date',
'Unnamed: 1': 'time',
datetime.datetime(2016, 1, 14, 0, 0): 'activity'
},
inplace=True)
df['time'] = df['time'].map(remove_ampm)
df.info()
print df.head()
lastdate = df['date'].tolist()[-1]
print type(lastdate)
if type(lastdate) == datetime.datetime:
timestr = lastdate.strftime('%m-%d-%Y')
elif type(lastdate) == pd.tslib.Timestamp:
timestr = '{0}-{1}-{2}'.format(lastdate.month, lastdate.day,
lastdate.year)
else:
timestr = lastdate
outfile = 'activity_{0}_{1}.csv'.format(home_id, timestr)
print 'write to {0}'.format(outfile)
df.to_csv(util.get_path('daily_reading', 'activity_stamp', 'all') +
'{0}'.format(outfile),
index=False)
def read_formatted():
# df_lookup = pd.read_csv(os.getcwd() + '/input/log_rename.csv')
# df_lookup.set_index('oldname', inplace=True)
home_id_dict = util.get_homeid_dict()
files = glob.glob(
util.get_path('daily_reading', 'raw_data', 'all') +
'xlsx_formatted/*.xlsx')
lastline_dict = \
{'LCMP Log_Observation-Incident Report_V6.JJN.xlsx': 32,
'Copy of D4-CMU-Daily Readings_RTto24jan2016.xlsx': 16,
'D4-Hartkopf_Loftness-Daily Readings.xlsx': 14}
sheets_dict = {
'D4-Hartkopf_Loftness-Daily Readings.xlsx': [0, 1],
'Copy of D4-CMU-Daily Readings_RTto24jan2016.xlsx': [0]
}
for f in files:
sheetlist = [1]
filename = f[f.rfind('/') + 1:]
tokens = util.split_string([' ', '_', '.', '-'], filename)
if filename in sheets_dict:
sheetlist = sheets_dict[filename]
home_id = 'UNKNOWN'
for x in tokens:
if x in home_id_dict:
home_id = home_id_dict[x]
for s in sheetlist:
idx_lastline = 33
df = pd.read_excel(f, sheetname=s)
if filename in lastline_dict:
idx_lastline = lastline_dict[filename]
df2 = df.transpose().iloc[:, [1, 2, idx_lastline]]
df2.dropna(subset=[idx_lastline], inplace=True)
df2.rename(columns={
1: 'date',
2: 'time',
33: 'activity'
},
inplace=True)
df2.drop(df2.index[0], axis=0, inplace=True)
timestr = df2.ix[-1, 'date'].strftime('%m-%d-%Y')
outfile = 'activity_{0}_{1}.csv'.format(home_id, timestr)
print 'write to {0}'.format(outfile)
df2.to_csv(
util.get_path('daily_reading', 'activity_stamp', 'all') +
'{0}'.format(outfile),
index=False)
return
def read_unformatted():
home_id_dict = util.get_homeid_dict()
files = glob.glob(util.get_path('daily_reading', 'raw_data', 'all') + 'xlsx_unformatted/*.xlsx')
for f in files[:1]:
filename = f[f.rfind('/') + 1:]
tokens = util.split_string([' ', '_', '.', '-'], filename)
home_id = 'UNKNOWN'
for x in tokens:
if x in home_id_dict:
home_id = home_id_dict[x]
df = pd.read_excel(f, sheetname=0)
if filename == 'TC_D2_Romer_Manual readings -logs_ - Sail boat_11-1_11-18.xlsx':
df.rename(columns={'Date': 'date', 'Time': 'time',
'Action: observations and behaviour':
'activity'}, inplace=True)
df.dropna(axis=0, how='all', inplace=True)
pattern = re.compile('[0-9]{1,2}')
df['date'] = df['date'].ffill()
df['time'] = df['time'].ffill()
df.dropna(subset=['date', 'time'], axis=0, how='any',
inplace=True)
df['time'] = df['time'].map(remove_ampm)
df['date'] = df['date'].map(lambda x: 'Nov' if x == 'Nov' else '2016-11-{0}'.format(re.match(pattern, x).group()))
df = df[['date', 'time', 'activity']]
if filename == 'DHP Log - DHP-HP-Daily Readings week of Jan 11, 2016.xlsx':
df = df.ix[19:23, [0, 1, 8]]
df.rename(columns={'Date': 'date', 'Unnamed: 1': 'time',
datetime.datetime(2016, 1, 14, 0, 0):
'activity'}, inplace=True)
df['time'] = df['time'].map(remove_ampm)
df.info()
print df.head()
lastdate = df['date'].tolist()[-1]
print type(lastdate)
if type(lastdate) == datetime.datetime:
timestr = lastdate.strftime('%m-%d-%Y')
elif type(lastdate) == pd.tslib.Timestamp:
timestr = '{0}-{1}-{2}'.format(lastdate.month, lastdate.day, lastdate.year)
else:
timestr = lastdate
outfile = 'activity_{0}_{1}.csv'.format(home_id, timestr)
print 'write to {0}'.format(outfile)
df.to_csv(util.get_path('daily_reading', 'activity_stamp',
'all') + '{0}'.format(outfile),
index=False)
def send_message(chatId, message, mode = None, markup = None, \
web_page_preview = True, all_monospace = False, header = None):
try:
if all_monospace:
mode = 'markdown'
splitted_text = split_string(message, 3000)
for text in splitted_text:
if all_monospace:
text = '`' + text + '`'
if header is not None:
text = header + text
header = None
success = False
while not success:
try:
Bot.send_message(
chatId,
text,
parse_mode=mode,
reply_markup=markup,
disable_web_page_preview=not web_page_preview)
success = True
except Exception as e:
se = str(e)
if 'Too Many Requests' in se:
time = int(se[se.find('retry_after') +
len('retry_after') + 1:-4]) + 0.5
sleep(time)
else:
raise e
return True
except Exception as e:
e = str(e)
if 'Forbidden: bot was kicked from the group chat' in e or \
'Forbidden: bot was blocked by the user' in e:
with data.create_connection(dbname) as connection:
_clear(chatId, connection)
else:
logger.error('Unknown error: {0}'.format(e))
return False
def read_formatted():
# df_lookup = pd.read_csv(os.getcwd() + '/input/log_rename.csv')
# df_lookup.set_index('oldname', inplace=True)
home_id_dict = util.get_homeid_dict()
files = glob.glob(util.get_path('daily_reading', 'raw_data', 'all') + 'xlsx_formatted/*.xlsx')
lastline_dict = \
{'LCMP Log_Observation-Incident Report_V6.JJN.xlsx': 32,
'Copy of D4-CMU-Daily Readings_RTto24jan2016.xlsx': 16,
'D4-Hartkopf_Loftness-Daily Readings.xlsx': 14}
sheets_dict = {'D4-Hartkopf_Loftness-Daily Readings.xlsx': [0, 1],
'Copy of D4-CMU-Daily Readings_RTto24jan2016.xlsx': [0]}
for f in files:
sheetlist = [1]
filename = f[f.rfind('/') + 1:]
tokens = util.split_string([' ', '_', '.', '-'], filename)
if filename in sheets_dict:
sheetlist = sheets_dict[filename]
home_id = 'UNKNOWN'
for x in tokens:
if x in home_id_dict:
home_id = home_id_dict[x]
for s in sheetlist:
idx_lastline = 33
df = pd.read_excel(f, sheetname=s)
if filename in lastline_dict:
idx_lastline = lastline_dict[filename]
df2 = df.transpose().iloc[:, [1, 2, idx_lastline]]
df2.dropna(subset=[idx_lastline], inplace=True)
df2.rename(columns={1: 'date', 2: 'time', 33: 'activity'}, inplace=True)
df2.drop(df2.index[0], axis=0, inplace=True)
timestr = df2.ix[-1, 'date'].strftime('%m-%d-%Y')
outfile = 'activity_{0}_{1}.csv'.format(home_id, timestr)
print 'write to {0}'.format(outfile)
df2.to_csv(util.get_path('daily_reading', 'activity_stamp',
'all') + '{0}'.format(outfile),
index=False)
return
def extract_string_columns(text, length):
"""Splits input string into n strings of given length, then transposes
them so that each output string consists of the characters found in the
same positions in the input strings.
For example:
string 1: abc
string 2: def
output 1: ad
output 2: be
output 3: cf
"""
columns = []
for index in range(length):
column = ""
for col in split_string(text, length):
try:
column += col[index]
except IndexError:
# This happens if any input string is shorter than the others
pass
columns.append("".join(column))
return columns
def read_ciphertext(filename):
"""Converts text file consisting of zeroes and ones in ASCII to binary
string."""
ciphertext = readfile(filename)
ciphertext = [int(c, 2) for c in split_string(ciphertext, 8)]
return bytearray(ciphertext)
