[英]Creating a Data Pipeline to BigQuery Using Cloud Functions and Cloud Scheduler
I am trying to build a Data Pipeline that will download the data from this website and push it to a BigQuery Table.我正在尝试构建一个数据管道,该管道将从该网站下载数据并将其推送到 BigQuery 表。
def OH_Data_Pipeline(trigger='Yes'):
if trigger=='Yes':
import pandas as pd
import pandas_gbq
import datetime
schema=[{'name': 'SOS_VOTERID', 'type': 'STRING'},{'name': 'COUNTY_NUMBER', 'type': 'STRING'}, {'name': 'COUNTY_ID', 'type': 'INT64'}, {'name': 'LAST_NAME', 'type': 'STRING'}, {'name': 'FIRST_NAME', 'type': 'STRING'}, {'name': 'MIDDLE_NAME', 'type': 'STRING'}, {'name': 'SUFFIX', 'type': 'STRING'}, {'name': 'DATE_OF_BIRTH', 'type': 'DATE'},
{'name': 'REGISTRATION_DATE', 'type': 'DATE'}, {'name': 'VOTER_STATUS', 'type': 'STRING'},
{'name': 'PARTY_AFFILIATION', 'type': 'STRING'}, {'name': 'RESIDENTIAL_ADDRESS1', 'type': 'STRING'},
{'name': 'RESIDENTIAL_SECONDARY_ADDR', 'type': 'STRING'}, {'name': 'RESIDENTIAL_CITY', 'type': 'STRING'},
{'name': 'RESIDENTIAL_STATE', 'type': 'STRING'}, {'name': 'RESIDENTIAL_ZIP', 'type': 'STRING'},
{'name': 'RESIDENTIAL_ZIP_PLUS4', 'type': 'STRING'}, {'name': 'RESIDENTIAL_COUNTRY', 'type': 'STRING'},
{'name': 'RESIDENTIAL_POSTALCODE', 'type': 'STRING'}, {'name': 'MAILING_ADDRESS1', 'type': 'STRING'},
{'name': 'MAILING_SECONDARY_ADDRESS', 'type': 'STRING'}, {'name': 'MAILING_CITY', 'type': 'STRING'},
{'name': 'MAILING_STATE', 'type': 'STRING'}, {'name': 'MAILING_ZIP', 'type': 'STRING'},
{'name': 'MAILING_ZIP_PLUS4', 'type': 'STRING'}, {'name': 'MAILING_COUNTRY', 'type': 'STRING'},
{'name': 'MAILING_POSTAL_CODE', 'type': 'STRING'}, {'name': 'CAREER_CENTER', 'type': 'STRING'},
{'name': 'CITY', 'type': 'STRING'}, {'name': 'CITY_SCHOOL_DISTRICT', 'type': 'STRING'},
{'name': 'COUNTY_COURT_DISTRICT', 'type': 'STRING'}, {'name': 'CONGRESSIONAL_DISTRICT', 'type': 'STRING'},
{'name': 'COURT_OF_APPEALS', 'type': 'STRING'}, {'name': 'EDU_SERVICE_CENTER_DISTRICT', 'type': 'STRING'},
{'name': 'EXEMPTED_VILL_SCHOOL_DISTRICT', 'type': 'STRING'}, {'name': 'LIBRARY', 'type': 'STRING'},
{'name': 'LOCAL_SCHOOL_DISTRICT', 'type': 'STRING'}, {'name': 'MUNICIPAL_COURT_DISTRICT', 'type': 'STRING'},
{'name': 'PRECINCT_NAME', 'type': 'STRING'}, {'name': 'PRECINCT_CODE', 'type': 'STRING'},
{'name': 'STATE_BOARD_OF_EDUCATION', 'type': 'STRING'}, {'name': 'STATE_REPRESENTATIVE_DISTRICT', 'type': 'STRING'},
{'name': 'STATE_SENATE_DISTRICT', 'type': 'STRING'}, {'name': 'TOWNSHIP', 'type': 'STRING'},
{'name': 'VILLAGE', 'type': 'STRING'}, {'name': 'WARD', 'type': 'STRING'},
{'name': 'PRIMARY_03_07_2000', 'type': 'STRING'}, {'name': 'GENERAL_11_07_2000', 'type': 'INT64'},
{'name': 'SPECIAL_05_08_2001', 'type': 'STRING'}, {'name': 'GENERAL_11_06_2001', 'type': 'INT64'},
{'name': 'PRIMARY_05_07_2002', 'type': 'STRING'}, {'name': 'GENERAL_11_05_2002', 'type': 'INT64'},
{'name': 'SPECIAL_05_06_2003', 'type': 'STRING'}, {'name': 'GENERAL_11_04_2003', 'type': 'INT64'},
{'name': 'PRIMARY_03_02_2004', 'type': 'STRING'}, {'name': 'GENERAL_11_02_2004', 'type': 'INT64'},
{'name': 'SPECIAL_02_08_2005', 'type': 'STRING'}, {'name': 'PRIMARY_05_03_2005', 'type': 'STRING'},
{'name': 'PRIMARY_09_13_2005', 'type': 'STRING'}, {'name': 'GENERAL_11_08_2005', 'type': 'INT64'},
{'name': 'SPECIAL_02_07_2006', 'type': 'STRING'}, {'name': 'PRIMARY_05_02_2006', 'type': 'STRING'},
{'name': 'GENERAL_11_07_2006', 'type': 'INT64'}, {'name': 'PRIMARY_05_08_2007', 'type': 'STRING'},
{'name': 'PRIMARY_09_11_2007', 'type': 'STRING'}, {'name': 'GENERAL_11_06_2007', 'type': 'INT64'},
{'name': 'PRIMARY_11_06_2007', 'type': 'STRING'}, {'name': 'GENERAL_12_11_2007', 'type': 'INT64'},
{'name': 'PRIMARY_03_04_2008', 'type': 'STRING'}, {'name': 'PRIMARY_10_14_2008', 'type': 'STRING'},
{'name': 'GENERAL_11_04_2008', 'type': 'INT64'}, {'name': 'GENERAL_11_18_2008', 'type': 'INT64'},
{'name': 'PRIMARY_05_05_2009', 'type': 'STRING'}, {'name': 'PRIMARY_09_08_2009', 'type': 'STRING'},
{'name': 'PRIMARY_09_15_2009', 'type': 'STRING'}, {'name': 'PRIMARY_09_29_2009', 'type': 'STRING'},
{'name': 'GENERAL_11_03_2009', 'type': 'INT64'}, {'name': 'PRIMARY_05_04_2010', 'type': 'STRING'},
{'name': 'PRIMARY_07_13_2010', 'type': 'STRING'}, {'name': 'PRIMARY_09_07_2010', 'type': 'STRING'},
{'name': 'GENERAL_11_02_2010', 'type': 'INT64'}, {'name': 'PRIMARY_05_03_2011', 'type': 'STRING'},
{'name': 'PRIMARY_09_13_2011', 'type': 'STRING'}, {'name': 'GENERAL_11_08_2011', 'type': 'INT64'},
{'name': 'PRIMARY_03_06_2012', 'type': 'STRING'}, {'name': 'GENERAL_11_06_2012', 'type': 'INT64'},
{'name': 'PRIMARY_05_07_2013', 'type': 'STRING'}, {'name': 'PRIMARY_09_10_2013', 'type': 'STRING'},
{'name': 'PRIMARY_10_01_2013', 'type': 'STRING'}, {'name': 'GENERAL_11_05_2013', 'type': 'INT64'},
{'name': 'PRIMARY_05_06_2014', 'type': 'STRING'}, {'name': 'GENERAL_11_04_2014', 'type': 'INT64'},
{'name': 'PRIMARY_05_05_2015', 'type': 'STRING'}, {'name': 'PRIMARY_09_15_2015', 'type': 'STRING'},
{'name': 'GENERAL_11_03_2015', 'type': 'INT64'}, {'name': 'PRIMARY_03_15_2016', 'type': 'STRING'},
{'name': 'GENERAL_06_07_2016', 'type': 'INT64'}, {'name': 'PRIMARY_09_13_2016', 'type': 'STRING'},
{'name': 'GENERAL_11_08_2016', 'type': 'INT64'}, {'name': 'PRIMARY_05_02_2017', 'type': 'STRING'},
{'name': 'PRIMARY_09_12_2017', 'type': 'STRING'}, {'name': 'GENERAL_11_07_2017', 'type': 'INT64'},
{'name': 'PRIMARY_05_08_2018', 'type': 'STRING'}, {'name': 'GENERAL_08_07_2018', 'type': 'INT64'},
{'name': 'GENERAL_11_06_2018', 'type': 'INT64'}, {'name': 'PRIMARY_05_07_2019', 'type': 'STRING'},
{'name': 'PRIMARY_09_10_2019', 'type': 'STRING'}, {'name': 'GENERAL_11_05_2019', 'type': 'INT64'}]
prim_list = ['PRIMARY-03/07/2000', 'SPECIAL-05/08/2001', 'PRIMARY-05/07/2002', 'SPECIAL-05/06/2003', 'PRIMARY-03/02/2004',
'SPECIAL-02/08/2005', 'PRIMARY-05/03/2005', 'PRIMARY-09/13/2005', 'SPECIAL-02/07/2006', 'PRIMARY-05/02/2006',
'PRIMARY-05/08/2007', 'PRIMARY-09/11/2007', 'PRIMARY-11/06/2007', 'PRIMARY-03/04/2008', 'PRIMARY-10/14/2008',
'PRIMARY-05/05/2009', 'PRIMARY-09/08/2009', 'PRIMARY-09/15/2009', 'PRIMARY-09/29/2009', 'PRIMARY-05/04/2010',
'PRIMARY-07/13/2010', 'PRIMARY-09/07/2010', 'PRIMARY-05/03/2011', 'PRIMARY-09/13/2011', 'PRIMARY-03/06/2012',
'PRIMARY-05/07/2013', 'PRIMARY-09/10/2013', 'PRIMARY-10/01/2013', 'PRIMARY-05/06/2014', 'PRIMARY-05/05/2015',
'PRIMARY-09/15/2015', 'PRIMARY-03/15/2016', 'PRIMARY-09/13/2016', 'PRIMARY-05/02/2017', 'PRIMARY-09/12/2017',
'PRIMARY-05/08/2018', 'PRIMARY-05/07/2019', 'PRIMARY-09/10/2019']
prim_list = [f.replace('-', '_').replace('/', '_') for f in prim_list]
gen_list = ['GENERAL-11/07/2000', 'GENERAL-11/06/2001', 'GENERAL-11/05/2002', 'GENERAL-11/04/2003', 'GENERAL-11/02/2004',
'GENERAL-11/08/2005', 'GENERAL-11/07/2006', 'GENERAL-11/06/2007', 'GENERAL-12/11/2007', 'GENERAL-11/04/2008',
'GENERAL-11/18/2008', 'GENERAL-11/03/2009', 'GENERAL-11/02/2010', 'GENERAL-11/08/2011', 'GENERAL-11/06/2012',
'GENERAL-11/05/2013', 'GENERAL-11/04/2014', 'GENERAL-11/03/2015', 'GENERAL-06/07/2016', 'GENERAL-11/08/2016',
'GENERAL-11/07/2017', 'GENERAL-08/07/2018', 'GENERAL-11/06/2018', 'GENERAL-11/05/2019']
gen_list = [f.replace('-', '_').replace('/', '_') for f in gen_list]
party_list = ['PARTY_AFFILIATION']
df=[pd.read_csv('https://www6.sos.state.oh.us/ords/f?p=VOTERFTP:DOWNLOAD::FILE:NO:2:P2_PRODUCT_NUMBER:{}'.format(88+f), encoding='Latin1', low_memory=False) for f in range(1, 17)]
df=pd.concat(df)
df.columns = [f.replace('-', '_').replace('/', '_') for f in df.columns]
df['birth_year'] = df['DATE_OF_BIRTH'].map(lambda x: str(x)[:-6]).astype(int)
df['Age'] = now.year - df['birth_year']
for f in prim_list:
df.loc[df[f]=='D', f]='Democrat'
df.loc[df[f]=='R', f]='Republican'
df.loc[df[f]=='G', f]='Green'
df.loc[df[f]=='E', f]='Reform'
df.loc[df[f]=='L', f]='Libertarian'
df.loc[df[f]=='C', f]='Constitution'
df.loc[df[f]=='N', f]='Natural Law'
df.loc[df[f]=='S', f]='Socialist'
df.loc[df[f]=='X', f]='Without Affiliation'
df.loc[(df[f]=='') | (df[f].isnull()==True) | (df[f]==0), f]='Not Voted'
for f in party_list:
df.loc[df[f]=='D', f]='Democrat'
df.loc[df[f]=='R', f]='Republican'
df.loc[df[f]=='G', f]='Green'
df.loc[df[f]=='E', f]='Reform'
df.loc[df[f]=='L', f]='Libertarian'
df.loc[df[f]=='C', f]='Constitution'
df.loc[df[f]=='N', f]='Natural Law'
df.loc[df[f]=='S', f]='Socialist'
df.loc[df[f]=='X', f]='Unaffiliated'
df.loc[(df[f]=='') | (df[f].isnull()==True) | (df[f]==0), f]='Unaffiliated'
for g in gen_list:
df.loc[(df[g]!='') & (df[g].isnull()!=True) & (df[g]!=0) & (df[g]!='NaN'), g]=1
df.loc[(df[g]=='') | (df[g].isnull()==True) | (df[g]==0) | (df[g]=='NaN'), g]=0
df[gen_list]=df[gen_list].astype(int)
df[prim_list]=df[prim_list].astype(str)
df[party_list]=df[party_list].astype(str)
df.to_gbq(destination_table='Voterfile.OH_Voterfile', project_id='oh-data-pipeline', if_exists='replace', table_schema=schema, reauth=False)
else:
pass
The problem is after defining the function in cloud functions, I will run the script in cloud scheduler, it will say the function ran, but no data will show up in BigQuery.问题是在云函数中定义函数后,我将在云调度程序中运行脚本,它会说该函数已运行,但在 BigQuery 中不会显示任何数据。
Here are the logs as well: [ { "insertId": "1idtfdbg5drzu63", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "project_id": "oh-data-pipeline", "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader" } }, "timestamp": "2020-01-01T21:12:39.949108697Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T21:12:39.949108697Z" }, { "insertId": "k9f9cjg5ds4bft", "jsonPayload": { "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-06T05:00:00.271618Z" }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T21:12:39.823311702Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T21:12:39.823311702Z" }, { "insertId": "1xnnrrug5g0c2qj", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T21:12:37.290359769Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T21:12:37.290359769Z" }, { "insertId": "sv8ssdg5e3blni", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-06T05:00:00.183767Z", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T21:12:36.916739031Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T21:12:36.916739031Z" }, { "insertId": "7i1kgtfutdv2s", "jsonPayload": { "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "project_id": "oh-data-pipeline", "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader" } }, "timestamp": "2020-01-01T19:37:07.201347795Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T19:37:07.201347795Z" }, { "insertId": "19io9oog5fvqy42", "jsonPayload": { "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-06T05:00:00Z", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline" }, "resource": { "type": "cloud_scheduler_job", "labels": { "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline" } }, "timestamp": "2020-01-01T19:37:07.092810676Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T19:37:07.092810676Z" }, { "insertId": "1t7pz9vg5e70eo5", "jsonPayload": { "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T17:30:00.396767720Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:30:00.396767720Z" }, { "insertId": "1p23vr0g59sba7d", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-01T17:30:00.250018Z", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "resource": { "type": "cloud_scheduler_job", "labels": { "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline" } }, "timestamp": "2020-01-01T17:30:00.267802278Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:30:00.267802278Z" }, { "insertId": "1yi5eng4p1lgiq", "jsonPayload": { "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T17:26:15.268636308Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:26:15.268636308Z" }, { "insertId": "1u1dz02g41np17v", "jsonPayload": { "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-01T17:30:00.369545Z" }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T17:26:15.133041426Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:26:15.133041426Z" }, { "insertId": "1gzxg1lg4qi1i28", "jsonPayload": { "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T17:22:41.388248918Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:22:41.388248918Z" }, { "insertId": "1es7ag9g5bdguh5", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-01T17:30:00.257483Z", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "resource": { "type": "cloud_scheduler_job", "labels": { "project_id": "oh-data-pipeline", "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader" } }, "timestamp": "2020-01-01T17:22:41.268121872Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:22:41.268121872Z" } ]
这里还有日志:
[ { "insertId": "1idtfdbg5drzu63", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "project_id": "oh-data-pipeline", "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader" } }, "timestamp": "2020-01-01T21:12:39.949108697Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T21:12:39.949108697Z" }, { "insertId": "k9f9cjg5ds4bft", "jsonPayload": { "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-06T05:00:00.271618Z" }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T21:12:39.823311702Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T21:12:39.823311702Z" }, { "insertId": "1xnnrrug5g0c2qj", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } 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"logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:22:41.388248918Z" }, { "insertId": "1es7ag9g5bdguh5", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-01T17:30:00.257483Z", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "resource": { "type": "cloud_scheduler_job", "labels": { "project_id": "oh-data-pipeline", "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader" } }, "timestamp": "2020-01-01T17:22:41.268121872Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:22:41.268121872Z" } ]
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"2020-01-01T17:30:00.396767720Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:30:00.396767720Z" }, { "insertId": "1p23vr0g59sba7d", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-01T17:30:00.250018Z", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "resource": { "type": "cloud_scheduler_job", "labels": { "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline" } }, "timestamp": "2020-01-01T17:30:00.267802278Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:30:00.267802278Z" }, { "insertId": "1yi5eng4p1lgiq", "jsonPayload": { "@type": 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"scheduledTime": "2020-01-01T17:30:00.369545Z" }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T17:26:15.133041426Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:26:15.133041426Z" }, { "insertId": "1gzxg1lg4qi1i28", "jsonPayload": { "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptFinished", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader", "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline" }, "httpRequest": { "status": 200 }, "resource": { "type": "cloud_scheduler_job", "labels": { "job_id": "OH_Voterfile_Data_Loader", "project_id": "oh-data-pipeline", "location": "us-east4" } }, "timestamp": "2020-01-01T17:22:41.388248918Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:22:41.388248918Z" }, { "insertId": "1es7ag9g5bdguh5", "jsonPayload": { "targetType": "HTTP", "url": "https://us-central1-oh-data-pipeline.cloudfunctions.net/OH_Data_Pipeline", "@type": "type.googleapis.com/google.cloud.scheduler.logging.AttemptStarted", "scheduledTime": "2020-01-01T17:30:00.257483Z", "jobName": "projects/oh-data-pipeline/locations/us-east4/jobs/OH_Voterfile_Data_Loader" }, "resource": { "type": "cloud_scheduler_job", "labels": { "project_id": "oh-data-pipeline", "location": "us-east4", "job_id": "OH_Voterfile_Data_Loader" } }, "timestamp": "2020-01-01T17:22:41.268121872Z", "severity": "INFO", "logName": "projects/oh-data-pipeline/logs/cloudscheduler.googleapis.com%2Fexecutions", "receiveTimestamp": "2020-01-01T17:22:41.268121872Z" } ]
Can you please help me figure out why this is not working?你能帮我弄清楚为什么这不起作用吗?
When I tested your code, I received the following error message: OH_Data_Pipeline() takes from 0 to 1 positional arguments but 2 were given
当我测试您的代码时,我收到以下错误消息:
OH_Data_Pipeline() takes from 0 to 1 positional arguments but 2 were given
You should modify your function definition to follow the sample code (I'm not sure what trigger
is used for, so for now I'm just hardcoding it to 'Yes'
):您应该修改函数定义以遵循示例代码(我不确定
trigger
的用途,所以现在我只是将其硬编码为'Yes'
):
def OH_Data_Pipeline(event, context):
trigger='Yes'
...
Also, make sure you have a requirements.txt
file and it has the correct libraries specified:另外,请确保您有一个
requirements.txt
文件并且它指定了正确的库:
pandas
pandas_gbq
datetime
After all of these changes, I then receive this error:在所有这些更改之后,我收到此错误:
Error: function terminated. Recommended action: inspect logs for termination reason. Details:
<urlopen error [SSL: CERTIFICATE_VERIFY_FAILED] certificate verify failed: unable to get local issuer certificate (_ssl.c:1051)>
There seems to be an issue with the SSL certificate for the domain you are trying to access.您尝试访问的域的 SSL 证书似乎存在问题。 You will need to play around with
read_csv()
to allow working with the domain despite the concerns with its certificates.尽管担心其证书,您仍需要使用
read_csv()
来允许使用域。
I changed your code a little to run on my machine and also in Cloud Functions.我稍微更改了您的代码,以便在我的机器和 Cloud Functions 中运行。
def main(arg):
import pandas as pd
import pandas_gbq
import datetime, io, requests
from google.oauth2 import service_account
schema=[{'name': 'SOS_VOTERID', 'type': 'STRING'},{'name': 'COUNTY_NUMBER', 'type': 'STRING'}, {'name': 'COUNTY_ID', 'type': 'INT64'}, {'name': 'LAST_NAME', 'type': 'STRING'}, {'name': 'FIRST_NAME', 'type': 'STRING'}, {'name': 'MIDDLE_NAME', 'type': 'STRING'}, {'name': 'SUFFIX', 'type': 'STRING'}, {'name': 'DATE_OF_BIRTH', 'type': 'DATE'},
{'name': 'REGISTRATION_DATE', 'type': 'DATE'}, {'name': 'VOTER_STATUS', 'type': 'STRING'},
{'name': 'PARTY_AFFILIATION', 'type': 'STRING'}, {'name': 'RESIDENTIAL_ADDRESS1', 'type': 'STRING'},
{'name': 'RESIDENTIAL_SECONDARY_ADDR', 'type': 'STRING'}, {'name': 'RESIDENTIAL_CITY', 'type': 'STRING'},
{'name': 'RESIDENTIAL_STATE', 'type': 'STRING'}, {'name': 'RESIDENTIAL_ZIP', 'type': 'STRING'},
{'name': 'RESIDENTIAL_ZIP_PLUS4', 'type': 'STRING'}, {'name': 'RESIDENTIAL_COUNTRY', 'type': 'STRING'},
{'name': 'RESIDENTIAL_POSTALCODE', 'type': 'STRING'}, {'name': 'MAILING_ADDRESS1', 'type': 'STRING'},
{'name': 'MAILING_SECONDARY_ADDRESS', 'type': 'STRING'}, {'name': 'MAILING_CITY', 'type': 'STRING'},
{'name': 'MAILING_STATE', 'type': 'STRING'}, {'name': 'MAILING_ZIP', 'type': 'STRING'},
{'name': 'MAILING_ZIP_PLUS4', 'type': 'STRING'}, {'name': 'MAILING_COUNTRY', 'type': 'STRING'},
{'name': 'MAILING_POSTAL_CODE', 'type': 'STRING'}, {'name': 'CAREER_CENTER', 'type': 'STRING'},
{'name': 'CITY', 'type': 'STRING'}, {'name': 'CITY_SCHOOL_DISTRICT', 'type': 'STRING'},
{'name': 'COUNTY_COURT_DISTRICT', 'type': 'STRING'}, {'name': 'CONGRESSIONAL_DISTRICT', 'type': 'STRING'},
{'name': 'COURT_OF_APPEALS', 'type': 'STRING'}, {'name': 'EDU_SERVICE_CENTER_DISTRICT', 'type': 'STRING'},
{'name': 'EXEMPTED_VILL_SCHOOL_DISTRICT', 'type': 'STRING'}, {'name': 'LIBRARY', 'type': 'STRING'},
{'name': 'LOCAL_SCHOOL_DISTRICT', 'type': 'STRING'}, {'name': 'MUNICIPAL_COURT_DISTRICT', 'type': 'STRING'},
{'name': 'PRECINCT_NAME', 'type': 'STRING'}, {'name': 'PRECINCT_CODE', 'type': 'STRING'},
{'name': 'STATE_BOARD_OF_EDUCATION', 'type': 'STRING'}, {'name': 'STATE_REPRESENTATIVE_DISTRICT', 'type': 'STRING'},
{'name': 'STATE_SENATE_DISTRICT', 'type': 'STRING'}, {'name': 'TOWNSHIP', 'type': 'STRING'},
{'name': 'VILLAGE', 'type': 'STRING'}, {'name': 'WARD', 'type': 'STRING'},
{'name': 'PRIMARY_03_07_2000', 'type': 'STRING'}, {'name': 'GENERAL_11_07_2000', 'type': 'INT64'},
{'name': 'SPECIAL_05_08_2001', 'type': 'STRING'}, {'name': 'GENERAL_11_06_2001', 'type': 'INT64'},
{'name': 'PRIMARY_05_07_2002', 'type': 'STRING'}, {'name': 'GENERAL_11_05_2002', 'type': 'INT64'},
{'name': 'SPECIAL_05_06_2003', 'type': 'STRING'}, {'name': 'GENERAL_11_04_2003', 'type': 'INT64'},
{'name': 'PRIMARY_03_02_2004', 'type': 'STRING'}, {'name': 'GENERAL_11_02_2004', 'type': 'INT64'},
{'name': 'SPECIAL_02_08_2005', 'type': 'STRING'}, {'name': 'PRIMARY_05_03_2005', 'type': 'STRING'},
{'name': 'PRIMARY_09_13_2005', 'type': 'STRING'}, {'name': 'GENERAL_11_08_2005', 'type': 'INT64'},
{'name': 'SPECIAL_02_07_2006', 'type': 'STRING'}, {'name': 'PRIMARY_05_02_2006', 'type': 'STRING'},
{'name': 'GENERAL_11_07_2006', 'type': 'INT64'}, {'name': 'PRIMARY_05_08_2007', 'type': 'STRING'},
{'name': 'PRIMARY_09_11_2007', 'type': 'STRING'}, {'name': 'GENERAL_11_06_2007', 'type': 'INT64'},
{'name': 'PRIMARY_11_06_2007', 'type': 'STRING'}, {'name': 'GENERAL_12_11_2007', 'type': 'INT64'},
{'name': 'PRIMARY_03_04_2008', 'type': 'STRING'}, {'name': 'PRIMARY_10_14_2008', 'type': 'STRING'},
{'name': 'GENERAL_11_04_2008', 'type': 'INT64'}, {'name': 'GENERAL_11_18_2008', 'type': 'INT64'},
{'name': 'PRIMARY_05_05_2009', 'type': 'STRING'}, {'name': 'PRIMARY_09_08_2009', 'type': 'STRING'},
{'name': 'PRIMARY_09_15_2009', 'type': 'STRING'}, {'name': 'PRIMARY_09_29_2009', 'type': 'STRING'},
{'name': 'GENERAL_11_03_2009', 'type': 'INT64'}, {'name': 'PRIMARY_05_04_2010', 'type': 'STRING'},
{'name': 'PRIMARY_07_13_2010', 'type': 'STRING'}, {'name': 'PRIMARY_09_07_2010', 'type': 'STRING'},
{'name': 'GENERAL_11_02_2010', 'type': 'INT64'}, {'name': 'PRIMARY_05_03_2011', 'type': 'STRING'},
{'name': 'PRIMARY_09_13_2011', 'type': 'STRING'}, {'name': 'GENERAL_11_08_2011', 'type': 'INT64'},
{'name': 'PRIMARY_03_06_2012', 'type': 'STRING'}, {'name': 'GENERAL_11_06_2012', 'type': 'INT64'},
{'name': 'PRIMARY_05_07_2013', 'type': 'STRING'}, {'name': 'PRIMARY_09_10_2013', 'type': 'STRING'},
{'name': 'PRIMARY_10_01_2013', 'type': 'STRING'}, {'name': 'GENERAL_11_05_2013', 'type': 'INT64'},
{'name': 'PRIMARY_05_06_2014', 'type': 'STRING'}, {'name': 'GENERAL_11_04_2014', 'type': 'INT64'},
{'name': 'PRIMARY_05_05_2015', 'type': 'STRING'}, {'name': 'PRIMARY_09_15_2015', 'type': 'STRING'},
{'name': 'GENERAL_11_03_2015', 'type': 'INT64'}, {'name': 'PRIMARY_03_15_2016', 'type': 'STRING'},
{'name': 'GENERAL_06_07_2016', 'type': 'INT64'}, {'name': 'PRIMARY_09_13_2016', 'type': 'STRING'},
{'name': 'GENERAL_11_08_2016', 'type': 'INT64'}, {'name': 'PRIMARY_05_02_2017', 'type': 'STRING'},
{'name': 'PRIMARY_09_12_2017', 'type': 'STRING'}, {'name': 'GENERAL_11_07_2017', 'type': 'INT64'},
{'name': 'PRIMARY_05_08_2018', 'type': 'STRING'}, {'name': 'GENERAL_08_07_2018', 'type': 'INT64'},
{'name': 'GENERAL_11_06_2018', 'type': 'INT64'}, {'name': 'PRIMARY_05_07_2019', 'type': 'STRING'},
{'name': 'PRIMARY_09_10_2019', 'type': 'STRING'}, {'name': 'GENERAL_11_05_2019', 'type': 'INT64'}]
prim_list = ['PRIMARY-03/07/2000', 'SPECIAL-05/08/2001', 'PRIMARY-05/07/2002', 'SPECIAL-05/06/2003', 'PRIMARY-03/02/2004',
'SPECIAL-02/08/2005', 'PRIMARY-05/03/2005', 'PRIMARY-09/13/2005', 'SPECIAL-02/07/2006', 'PRIMARY-05/02/2006',
'PRIMARY-05/08/2007', 'PRIMARY-09/11/2007', 'PRIMARY-11/06/2007', 'PRIMARY-03/04/2008', 'PRIMARY-10/14/2008',
'PRIMARY-05/05/2009', 'PRIMARY-09/08/2009', 'PRIMARY-09/15/2009', 'PRIMARY-09/29/2009', 'PRIMARY-05/04/2010',
'PRIMARY-07/13/2010', 'PRIMARY-09/07/2010', 'PRIMARY-05/03/2011', 'PRIMARY-09/13/2011', 'PRIMARY-03/06/2012',
'PRIMARY-05/07/2013', 'PRIMARY-09/10/2013', 'PRIMARY-10/01/2013', 'PRIMARY-05/06/2014', 'PRIMARY-05/05/2015',
'PRIMARY-09/15/2015', 'PRIMARY-03/15/2016', 'PRIMARY-09/13/2016', 'PRIMARY-05/02/2017', 'PRIMARY-09/12/2017',
'PRIMARY-05/08/2018', 'PRIMARY-05/07/2019', 'PRIMARY-09/10/2019']
prim_list = [f.replace('-', '_').replace('/', '_') for f in prim_list]
gen_list = ['GENERAL-11/07/2000', 'GENERAL-11/06/2001', 'GENERAL-11/05/2002', 'GENERAL-11/04/2003', 'GENERAL-11/02/2004',
'GENERAL-11/08/2005', 'GENERAL-11/07/2006', 'GENERAL-11/06/2007', 'GENERAL-12/11/2007', 'GENERAL-11/04/2008',
'GENERAL-11/18/2008', 'GENERAL-11/03/2009', 'GENERAL-11/02/2010', 'GENERAL-11/08/2011', 'GENERAL-11/06/2012',
'GENERAL-11/05/2013', 'GENERAL-11/04/2014', 'GENERAL-11/03/2015', 'GENERAL-06/07/2016', 'GENERAL-11/08/2016',
'GENERAL-11/07/2017', 'GENERAL-08/07/2018', 'GENERAL-11/06/2018', 'GENERAL-11/05/2019']
gen_list = [f.replace('-', '_').replace('/', '_') for f in gen_list]
party_list = ['PARTY_AFFILIATION']
df= [pd.read_csv(io.StringIO(str(requests.get('https://www6.sos.state.oh.us/ords/f?p=VOTERFTP:DOWNLOAD::FILE:NO:2:P2_PRODUCT_NUMBER:{}'.format(88+f), verify=False).text)),encoding='Latin1', low_memory=False) for f in range(1, 2) ]
#df=[pd.read_csv('https://www6.sos.state.oh.us/ords/f?p=VOTERFTP:DOWNLOAD::FILE:NO:2:P2_PRODUCT_NUMBER:{}'.format(88+f), encoding='Latin1', low_memory=False) for f in range(1, 17)]
df=pd.concat(df)
df.columns = [f.replace('-', '_').replace('/', '_') for f in df.columns]
df['birth_year'] = df['DATE_OF_BIRTH'].map(lambda x: str(x)[:-6]).astype(int)
df['Age'] = datetime.datetime.now().year - df['birth_year']
for f in prim_list:
df.loc[df[f]=='D', f]='Democrat'
df.loc[df[f]=='R', f]='Republican'
df.loc[df[f]=='G', f]='Green'
df.loc[df[f]=='E', f]='Reform'
df.loc[df[f]=='L', f]='Libertarian'
df.loc[df[f]=='C', f]='Constitution'
df.loc[df[f]=='N', f]='Natural Law'
df.loc[df[f]=='S', f]='Socialist'
df.loc[df[f]=='X', f]='Without Affiliation'
df.loc[(df[f]=='') | (df[f].isnull()==True) | (df[f]==0), f]='Not Voted'
for f in party_list:
df.loc[df[f]=='D', f]='Democrat'
df.loc[df[f]=='R', f]='Republican'
df.loc[df[f]=='G', f]='Green'
df.loc[df[f]=='E', f]='Reform'
df.loc[df[f]=='L', f]='Libertarian'
df.loc[df[f]=='C', f]='Constitution'
df.loc[df[f]=='N', f]='Natural Law'
df.loc[df[f]=='S', f]='Socialist'
df.loc[df[f]=='X', f]='Unaffiliated'
df.loc[(df[f]=='') | (df[f].isnull()==True) | (df[f]==0), f]='Unaffiliated'
for g in gen_list:
df.loc[(df[g]!='') & (df[g].isnull()!=True) & (df[g]!=0) & (df[g]!='NaN'), g]=1
df.loc[(df[g]=='') | (df[g].isnull()==True) | (df[g]==0) | (df[g]=='NaN'), g]=0
df[gen_list]=df[gen_list].astype(int)
df[prim_list]=df[prim_list].astype(str)
df[party_list]=df[party_list].astype(str)
df.to_gbq(destination_table='Voterfile.OH_Voterfile', project_id='astute-acolyte-260912', if_exists='replace', table_schema=schema, reauth=False)
Notice that the verify=False
is ONLY for testing proposes.请注意,
verify=False
仅用于测试建议。 It shall not be used in production.不得用于生产。 After running your code in my machine and in
Cloud Functions
, I realized two things:在我的机器和
Cloud Functions
运行您的代码后,我意识到两件事:
Cloud Functions
because Cloud Functions has a maximum timeout of 9 minutes as you can see hereCloud Functions
,因为云功能有9分钟的最大超时,你可以看到 在这里 You could try using a VM in Compute Engine for that.为此,您可以尝试在 Compute Engine 中使用 VM。 In this case you could also use Cloud Schedule to turn on and turn off your VM in the exactly time you want.
在这种情况下,您还可以使用 Cloud Schedule 在您想要的确切时间打开和关闭您的 VM。 You can find the tutorial for that here
你可以在这里找到教程
For creating a VM in Compute Engine, you can follow this tutorial Creating an instance from a public image要在 Compute Engine 中创建 VM,您可以按照本教程从公共映像创建实例
Keep in mind that when using VMs in Compute Engine, you will pay for the processing when the VM is turned on and for the storage of the VM`s disk both when the VM is turned on or off.请记住,在 Compute Engine 中使用 VM 时,您将支付 VM 开启时的处理费用以及 VM 开启或关闭时 VM 磁盘的存储费用。 After creating the VM, you can access it through the console.
创建 VM 后,您可以通过控制台访问它。 You should prepare the enviroment for your code in the VM the same way you did in your local machine.
您应该在 VM 中为您的代码准备环境,就像您在本地机器上所做的那样。
After having your enviroment configured and a deployable code, you can use crontab to schedule the execution of your script by the system.在配置好环境和可部署的代码后,您可以使用crontab来安排系统执行脚本。
Now we have the last step: configure a Cloud Schedule to turn on an turn off your VM in the righ time.现在我们有了最后一步:配置 Cloud Schedule 以在适当的时候打开和关闭 VM。 You can find the tutorial here .
您可以在此处找到教程。 You should schedule your VM to turn on some minutes before the time you define in the crontab.
您应该安排您的 VM 在您在 crontab 中定义的时间之前几分钟打开。
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