fix: table schema (urgh)
This commit is contained in:
parent
9fff0d123e
commit
f9da0f1ce7
63
pipeline.py
63
pipeline.py
|
@ -7,6 +7,7 @@ import os
|
||||||
from multiprocessing import Process, Lock
|
from multiprocessing import Process, Lock
|
||||||
import pandas as pd
|
import pandas as pd
|
||||||
from google.oauth2 import service_account
|
from google.oauth2 import service_account
|
||||||
|
from google.cloud import bigquery as bq
|
||||||
import data.maker
|
import data.maker
|
||||||
|
|
||||||
from data.params import SYS_ARGS
|
from data.params import SYS_ARGS
|
||||||
|
@ -115,10 +116,44 @@ class Components :
|
||||||
data.maker.train(**_args)
|
data.maker.train(**_args)
|
||||||
|
|
||||||
if 'autopilot' in ( list(args.keys())) :
|
if 'autopilot' in ( list(args.keys())) :
|
||||||
print (['drone mode enabled ....'])
|
print (['autopilot mode enabled ....'])
|
||||||
self.generate(args)
|
self.generate(args)
|
||||||
|
|
||||||
pass
|
pass
|
||||||
|
def shuffle(self,args):
|
||||||
|
"""
|
||||||
|
"""
|
||||||
|
df = args['reader']() if 'reader' in args else args['data']
|
||||||
|
|
||||||
|
|
||||||
|
col = args['columns'][0]
|
||||||
|
distrib = df[col].value_counts()
|
||||||
|
values = np.array(distrib.index)
|
||||||
|
counts = np.array(distrib.values)
|
||||||
|
np.random.shuffle(values)
|
||||||
|
np.random.shuffle(counts)
|
||||||
|
N = len (values)
|
||||||
|
theta = np.random.sample()
|
||||||
|
pad = 0
|
||||||
|
# print (values)
|
||||||
|
iovalues = np.zeros(df.shape[0],dtype=df[col].dtype)
|
||||||
|
for i in range(N) :
|
||||||
|
# n = int(counts[i] - counts[i]*theta)
|
||||||
|
n = counts[i]
|
||||||
|
print ([counts[i],theta,n])
|
||||||
|
index = np.where(iovalues == 0)[0]
|
||||||
|
if index.size > 0 and index.size > n:
|
||||||
|
index = index[:n]
|
||||||
|
iovalues[index] = values[i]
|
||||||
|
|
||||||
|
|
||||||
|
np.random.shuffle(iovalues)
|
||||||
|
df[col] = iovalues
|
||||||
|
|
||||||
|
return df
|
||||||
|
def post(self,args):
|
||||||
|
pass
|
||||||
|
|
||||||
|
|
||||||
# @staticmethod
|
# @staticmethod
|
||||||
def generate(self,args):
|
def generate(self,args):
|
||||||
|
@ -181,12 +216,12 @@ class Components :
|
||||||
# let us fix the data types here every _id field will be an np.int64...
|
# let us fix the data types here every _id field will be an np.int64...
|
||||||
#
|
#
|
||||||
|
|
||||||
for name in df.columns.tolist():
|
# for name in df.columns.tolist():
|
||||||
|
|
||||||
if name.endswith('_id') :
|
# if name.endswith('_id') :
|
||||||
if df[name].isnull().sum() > 0 :
|
# if df[name].isnull().sum() > 0 and name not in ['unique_device_id']:
|
||||||
df[name].fillna(np.nan_to_num(np.nan),inplace=True)
|
# df[name].fillna(np.nan_to_num(np.nan),inplace=True)
|
||||||
df[name] = df[name].astype(int)
|
# df[name] = df[name].astype(int)
|
||||||
|
|
||||||
|
|
||||||
_dc = pd.DataFrame()
|
_dc = pd.DataFrame()
|
||||||
|
@ -232,6 +267,11 @@ class Components :
|
||||||
|
|
||||||
_id = 'path'
|
_id = 'path'
|
||||||
else:
|
else:
|
||||||
|
client = bq.Client.from_service_account_json(args["private_key"])
|
||||||
|
full_schema = client.get_table(client.dataset(args['dataset']).table(args['from'])).schema
|
||||||
|
full_schema = [{'name':item.name,'type':item.field_type,'description':item.description} for item in full_schema]
|
||||||
|
io_schema = [{'name':item['name'],'type':item['type'],'description':item['description']} for item in full_schema if item['name'] in args['columns']]
|
||||||
|
|
||||||
credentials = service_account.Credentials.from_service_account_file('/home/steve/dev/aou/accounts/curation-prod.json')
|
credentials = service_account.Credentials.from_service_account_file('/home/steve/dev/aou/accounts/curation-prod.json')
|
||||||
_pname = os.sep.join([folder,table+'.csv'])
|
_pname = os.sep.join([folder,table+'.csv'])
|
||||||
_fname = table.replace('_io','_full_io')
|
_fname = table.replace('_io','_full_io')
|
||||||
|
@ -243,11 +283,11 @@ class Components :
|
||||||
else:
|
else:
|
||||||
Components.lock.acquire()
|
Components.lock.acquire()
|
||||||
|
|
||||||
data_comp.to_gbq(if_exists='append',destination_table=partial,credentials=credentials,chunksize=90000)
|
data_comp.to_gbq(if_exists='append',destination_table=partial,credentials=credentials,chunksize=90000,table_schema=io_schema)
|
||||||
|
|
||||||
INSERT_FLAG = 'replace' if 'partition' not in args or 'segment' not in args else 'append'
|
INSERT_FLAG = 'replace' if 'partition' not in args or 'segment' not in args else 'append'
|
||||||
|
|
||||||
_args['data'].to_gbq(if_exists='append',destination_table=complete,credentials=credentials,chunksize=90000)
|
_args['data'].to_gbq(if_exists='append',destination_table=complete,credentials=credentials,chunksize=90000,table_schema=full_schema)
|
||||||
Components.lock.release()
|
Components.lock.release()
|
||||||
_id = 'dataset'
|
_id = 'dataset'
|
||||||
info = {"full":{_id:_fname,"rows":_args['data'].shape[0]},"partial":{"path":_pname,"rows":data_comp.shape[0]} }
|
info = {"full":{_id:_fname,"rows":_args['data'].shape[0]},"partial":{"path":_pname,"rows":data_comp.shape[0]} }
|
||||||
|
@ -354,7 +394,12 @@ if __name__ == '__main__' :
|
||||||
else:
|
else:
|
||||||
generator.generate(args)
|
generator.generate(args)
|
||||||
# Components.generate(args)
|
# Components.generate(args)
|
||||||
|
elif 'shuffle' in SYS_ARGS:
|
||||||
|
args['data'] = DATA[0]
|
||||||
|
_df = (Components()).shuffle(args)
|
||||||
|
print (DATA[0][args['columns']])
|
||||||
|
print ()
|
||||||
|
print (_df[args['columns']])
|
||||||
else:
|
else:
|
||||||
|
|
||||||
# DATA = np.array_split(DATA,PART_SIZE)
|
# DATA = np.array_split(DATA,PART_SIZE)
|
||||||
|
|
Loading…
Reference in New Issue