Flask 應用程序未在 AWS elastic beanstalk 上部署

Question

我必須在亞馬遜彈性 beantalk 上部署 flask 應用程序

我正在按照這些步驟在彈性 beantalk 上部署

http://www.alcortech.com/steps-to-deploy-python-flask-mysql-application-on-aws-elastic-beanstalk/

我得到的錯誤代碼

----------------------------------------
/var/log/eb-engine.log
----------------------------------------
2020/08/04 17:54:08.190038 [INFO] Copying file /opt/elasticbeanstalk/config/private/healthd/healthd.conf to /var/proxy/staging/nginx/conf.d/elasticbeanstalk/healthd.conf
2020/08/04 17:54:08.191770 [INFO] Executing instruction: configure log streaming
2020/08/04 17:54:08.191779 [INFO] log streaming is not enabled
2020/08/04 17:54:08.191783 [INFO] disable log stream
2020/08/04 17:54:08.192853 [INFO] Running command /bin/sh -c systemctl show -p PartOf amazon-cloudwatch-agent.service
2020/08/04 17:54:08.298022 [INFO] Running command /bin/sh -c systemctl stop amazon-cloudwatch-agent.service
2020/08/04 17:54:08.303818 [INFO] Executing instruction: GetToggleForceRotate
2020/08/04 17:54:08.303831 [INFO] Checking if logs need forced rotation
2020/08/04 17:54:08.303852 [INFO] Running command /bin/sh -c /opt/aws/bin/cfn-get-metadata -s arn:aws:cloudformation:us-east-1:859160877773:stack/awseb-e-dxcnd8btg7-stack/fd1c0e90-d67a-11ea-895d-0ee443750bc7 -r AWSEBAutoScalingGroup --region us-east-1
2020/08/04 17:54:09.170590 [INFO] Running command /bin/sh -c /opt/aws/bin/cfn-get-metadata -s arn:aws:cloudformation:us-east-1:859160877773:stack/awseb-e-dxcnd8btg7-stack/fd1c0e90-d67a-11ea-895d-0ee443750bc7 -r AWSEBBeanstalkMetadata --region us-east-1
2020/08/04 17:54:09.501785 [INFO] Copying file /opt/elasticbeanstalk/config/private/rsyslog.conf to /etc/rsyslog.d/web.conf
2020/08/04 17:54:09.503412 [INFO] Running command /bin/sh -c systemctl restart rsyslog.service
2020/08/04 17:54:10.455082 [INFO] Executing instruction: PostBuildEbExtension
2020/08/04 17:54:10.455106 [INFO] No plugin in cfn metadata.
2020/08/04 17:54:10.455116 [INFO] Starting executing the config set Infra-EmbeddedPostBuild.
2020/08/04 17:54:10.455138 [INFO] Running command /bin/sh -c /opt/aws/bin/cfn-init -s arn:aws:cloudformation:us-east-1:859160877773:stack/awseb-e-dxcnd8btg7-stack/fd1c0e90-d67a-11ea-895d-0ee443750bc7 -r AWSEBAutoScalingGroup --region us-east-1 --configsets Infra-EmbeddedPostBuild
2020/08/04 17:54:10.827402 [INFO] Finished executing the config set Infra-EmbeddedPostBuild.

2020/08/04 17:54:10.827431 [INFO] Executing instruction: CleanEbExtensions
2020/08/04 17:54:10.827453 [INFO] Cleaned ebextensions subdirectories from app staging directory.
2020/08/04 17:54:10.827457 [INFO] Executing instruction: RunPreDeployHooks
2020/08/04 17:54:10.827478 [INFO] The dir .platform/hooks/predeploy/ does not exist in the application. Skipping this step...
2020/08/04 17:54:10.827482 [INFO] Executing instruction: stop X-Ray
2020/08/04 17:54:10.827486 [INFO] stop X-Ray ...
2020/08/04 17:54:10.827504 [INFO] Running command /bin/sh -c systemctl show -p PartOf xray.service
2020/08/04 17:54:10.834251 [WARN] stopProcess Warning: process xray is not registered 
2020/08/04 17:54:10.834271 [INFO] Running command /bin/sh -c systemctl stop xray.service
2020/08/04 17:54:10.844029 [INFO] Executing instruction: stop proxy
2020/08/04 17:54:10.844061 [INFO] Running command /bin/sh -c systemctl show -p PartOf nginx.service
2020/08/04 17:54:10.929856 [WARN] stopProcess Warning: process nginx is not registered 
2020/08/04 17:54:10.929893 [INFO] Running command /bin/sh -c systemctl stop nginx.service
2020/08/04 17:54:10.935107 [INFO] Executing instruction: FlipApplication
2020/08/04 17:54:10.935119 [INFO] Fetching environment variables...
2020/08/04 17:54:10.935125 [INFO] No plugin in cfn metadata.
2020/08/04 17:54:10.936360 [INFO] Purge old process...
2020/08/04 17:54:10.936404 [INFO] Register application processes...
2020/08/04 17:54:10.936409 [INFO] Registering the proc: web

2020/08/04 17:54:10.936423 [INFO] Running command /bin/sh -c systemctl show -p PartOf web.service
2020/08/04 17:54:10.942911 [INFO] Running command /bin/sh -c systemctl daemon-reload
2020/08/04 17:54:11.190918 [INFO] Running command /bin/sh -c systemctl reset-failed
2020/08/04 17:54:11.195011 [INFO] Running command /bin/sh -c systemctl is-enabled eb-app.target
2020/08/04 17:54:11.198465 [INFO] Copying file /opt/elasticbeanstalk/config/private/aws-eb.target to /etc/systemd/system/eb-app.target
2020/08/04 17:54:11.200382 [INFO] Running command /bin/sh -c systemctl enable eb-app.target
2020/08/04 17:54:11.275179 [ERROR] Created symlink from /etc/systemd/system/multi-user.target.wants/eb-app.target to /etc/systemd/system/eb-app.target.

2020/08/04 17:54:11.275218 [INFO] Running command /bin/sh -c systemctl start eb-app.target
2020/08/04 17:54:11.280436 [INFO] Running command /bin/sh -c systemctl enable web.service
2020/08/04 17:54:11.355233 [ERROR] Created symlink from /etc/systemd/system/multi-user.target.wants/web.service to /etc/systemd/system/web.service.

2020/08/04 17:54:11.355273 [INFO] Running command /bin/sh -c systemctl show -p PartOf web.service
2020/08/04 17:54:11.360364 [INFO] Running command /bin/sh -c systemctl is-active web.service
2020/08/04 17:54:11.363811 [INFO] Running command /bin/sh -c systemctl start web.service
2020/08/04 17:54:11.389333 [INFO] Executing instruction: start X-Ray
2020/08/04 17:54:11.389349 [INFO] X-Ray is not enabled.
2020/08/04 17:54:11.389354 [INFO] Executing instruction: start proxy with new configuration
2020/08/04 17:54:11.389382 [INFO] Running command /bin/sh -c /usr/sbin/nginx -t -c /var/proxy/staging/nginx/nginx.conf
2020/08/04 17:54:11.594594 [ERROR] nginx: the configuration file /var/proxy/staging/nginx/nginx.conf syntax is ok
nginx: configuration file /var/proxy/staging/nginx/nginx.conf test is successful

2020/08/04 17:54:11.595275 [INFO] Running command /bin/sh -c cp -rp /var/proxy/staging/nginx/. /etc/nginx
2020/08/04 17:54:11.603198 [INFO] Running command /bin/sh -c systemctl show -p PartOf nginx.service
2020/08/04 17:54:11.618752 [INFO] Running command /bin/sh -c systemctl daemon-reload
2020/08/04 17:54:11.716763 [INFO] Running command /bin/sh -c systemctl reset-failed
2020/08/04 17:54:11.724234 [INFO] Running command /bin/sh -c systemctl show -p PartOf nginx.service
2020/08/04 17:54:11.735835 [INFO] Running command /bin/sh -c systemctl is-active nginx.service
2020/08/04 17:54:11.743306 [INFO] Running command /bin/sh -c systemctl start nginx.service
2020/08/04 17:54:11.810080 [INFO] Executing instruction: configureSqsd
2020/08/04 17:54:11.810096 [INFO] This is a web server environment instance, skip configure sqsd daemon ...
2020/08/04 17:54:11.810102 [INFO] Executing instruction: startSqsd
2020/08/04 17:54:11.810105 [INFO] This is a web server environment instance, skip start sqsd daemon ...
2020/08/04 17:54:11.810110 [INFO] Executing instruction: Track pids in healthd
2020/08/04 17:54:11.810114 [INFO] This is an enhanced health env...
2020/08/04 17:54:11.810138 [INFO] Running command /bin/sh -c systemctl show -p ConsistsOf aws-eb.target | cut -d= -f2
2020/08/04 17:54:11.819320 [INFO] healthd.service nginx.service cfn-hup.service

2020/08/04 17:54:11.819352 [INFO] Running command /bin/sh -c systemctl show -p ConsistsOf eb-app.target | cut -d= -f2
2020/08/04 17:54:11.826094 [INFO] web.service

2020/08/04 17:54:11.826211 [INFO] Executing instruction: RunPostDeployHooks
2020/08/04 17:54:11.826223 [INFO] The dir .platform/hooks/postdeploy/ does not exist in the application. Skipping this step...
2020/08/04 17:54:11.826228 [INFO] Executing cleanup logic
2020/08/04 17:54:11.826308 [INFO] CommandService Response: {"status":"SUCCESS","api_version":"1.0","results":[{"status":"SUCCESS","msg":"Engine execution has succeeded.","returncode":0,"events":[]}]}

2020/08/04 17:54:11.826448 [INFO] Platform Engine finished execution on command: app-deploy

2020/08/04 17:55:26.814753 [INFO] Starting...
2020/08/04 17:55:26.814816 [INFO] Starting EBPlatform-PlatformEngine
2020/08/04 17:55:26.817259 [INFO] no eb envtier info file found, skip loading env tier info.
2020/08/04 17:55:26.817348 [INFO] Engine received EB command cfn-hup-exec

2020/08/04 17:55:26.939483 [INFO] Running command /bin/sh -c /opt/aws/bin/cfn-get-metadata -s arn:aws:cloudformation:us-east-1:859160877773:stack/awseb-e-dxcnd8btg7-stack/fd1c0e90-d67a-11ea-895d-0ee443750bc7 -r AWSEBAutoScalingGroup --region us-east-1
2020/08/04 17:55:27.277717 [INFO] Running command /bin/sh -c /opt/aws/bin/cfn-get-metadata -s arn:aws:cloudformation:us-east-1:859160877773:stack/awseb-e-dxcnd8btg7-stack/fd1c0e90-d67a-11ea-895d-0ee443750bc7 -r AWSEBBeanstalkMetadata --region us-east-1
2020/08/04 17:55:27.829610 [INFO] checking whether command tail-log is applicable to this instance...
2020/08/04 17:55:27.829630 [INFO] this command is applicable to the instance, thus instance should execute command
2020/08/04 17:55:27.829635 [INFO] Engine command: (tail-log)

2020/08/04 17:55:27.830551 [INFO] Executing instruction: GetTailLogs
2020/08/04 17:55:27.830557 [INFO] Tail Logs...
2020/08/04 17:55:27.834471 [INFO] Running command /bin/sh -c tail -n 100 /var/log/eb-engine.log


----------------------------------------
/var/log/web.stdout.log
----------------------------------------
Aug  4 17:54:11 ip-172-31-20-145 web: [2020-08-04 17:54:11 +0000] [3881] [INFO] Starting gunicorn 20.0.4
Aug  4 17:54:11 ip-172-31-20-145 web: [2020-08-04 17:54:11 +0000] [3881] [INFO] Listening at: http://127.0.0.1:8000 (3881)
Aug  4 17:54:11 ip-172-31-20-145 web: [2020-08-04 17:54:11 +0000] [3881] [INFO] Using worker: threads
Aug  4 17:54:11 ip-172-31-20-145 web: [2020-08-04 17:54:11 +0000] [3918] [INFO] Booting worker with pid: 3918


----------------------------------------
/var/log/nginx/access.log
----------------------------------------


----------------------------------------
/var/log/nginx/error.log
----------------------------------------

我的 application.py 文件在根目錄及其源代碼中

from pprint import pprint
import re
import smtplib
import ssl
import docxpy
import glob
import time
import spacy
import requests
import json
import pickle
import numpy as np
import pandas as pd
import tensorflow as tf
from flask import Flask 
from flask_restful import Api, Resource, reqparse
from tensorflow.keras.preprocessing.sequence import pad_sequences
from tensorflow.keras.preprocessing.text import one_hot
from tensorflow.keras.models import model_from_json
import en_core_web_sm

NLP = en_core_web_sm.load()
df = pd.read_csv('skill_train.csv')
df=df.dropna()
df['skill']=pd.to_numeric(df['skill'])
negitive=df[df['skill']==0]
positive=df[df['skill']==1]

application = Flask(__name__)
api = Api(application)

class Candidate:

    def __init__(self,file_link):

        __text = docxpy.process(file_link).strip()

        self.__resume={
                'Name':self.__extract_name(__text),
                'Phone Number':self.__extract_phone(__text),
                'Email':self.__extract_email(__text),
                'Experience':self.__extract_experience(__text),
                'Skills':list(),
                'Title':'',
                'match':0,
                'file_path':file_link,
            }
    
    def get_resume(self):
        return self.__resume


    def __extract_name(self,text):
        try:
            return text[:text.index('\n')]
        except:
            return None

    def __extract_email(self,text):
        email_pattern = re.compile(r'\S+@\S+\.\S+')
        try:
            return email_pattern.findall(text)[0].upper()
        except:
            try:
                __hyperlinks = text.data['links'][0][0].decode('UTF-8')
                return email_pattern.findall(__hyperlinks)[0].upper()
            except:
                return None
    
    def __extract_phone(self,text):
        phone_pattern = re.compile(r'(\d{3}[-\.\s]??\d{3}[-\.\s]??\d{4}|\(\d{3}\)[-\.\s]*\d{3}[-\.\s]??\d{4}|\d{3}[-\.\s]??\d{4})')
        try:
            return ''.join(phone_pattern.findall(text)[0]) if len(''.join(phone_pattern.findall(text)[0]))>=10 else None
        except:
            return None
    
    def __extract_experience(self,text):
        try:
            __exp_pattern = re.compile(r'\d\+ years|\d years|\d\d\+ years|\d\d years|\d\d \+ Years|\d \+ Years')
            __exp = __exp_pattern.findall(text)    
            return str(max([int(re.findall(re.compile(r'\d+'),i)[0]) for i in __exp])) + '+ years'
        except:
            try:
                __date_patt = re.compile(r"\d{2}[/-]\d+")
                __dates_list = __date_patt.findall(text)
                try:
                    __year_list=[int(date[-4:]) for date in __dates_list]
                except:
                    __year_list=[int(date[-2:]) for date in __dates_list]
                return str(max(__year_list)-min(__year_list))+'+ years'
            except:
                return None


class JobDescription:

    def __init__(self,args):

        self.description=args['job_description'].upper()
        self.__title=self.__get_title(self.description) if 'job_title' not in args else args['job_title'].upper()
        __doc=NLP(self.description)
        __noun_chunks=set([chunk.text.upper() for chunk in __doc.noun_chunks])
        self.__skills=list(self.__get_skills(list(__noun_chunks)))
    
    def title(self):
        return self.__title
    
    def skills(self):
        return self.__skills

    def __clean_data(self,noun_chunks):

        subs=[r'^[\d|\W]*','EXPERIENCE','EXPERT','DEVELOPER','SERVICES','STACK','TECHNOLOGIES',
        'JOBS','JOB',r'\n',' ',r'\t','AND','DEV','SCRIPTS','DBS','DATABASE','DATABASES','SERVER',
        'SERVERS',r'^\d+']
        __clean_chunks=[]
        for chunk in noun_chunks:
            for sub in subs:
                chunk=(re.sub(sub,' ',chunk).strip())
            filtered_chunk=[]
            chunk=chunk.split(' ')
            for word in chunk:
                for sub in subs:
                    word=(re.sub(sub,' ',word).strip())
                if word != '':
                    if not NLP.vocab[word.strip()].is_stop:
                        filtered_chunk.append(word.strip())
            filtered_chunk=' '.join(filtered_chunk)
            if filtered_chunk != '' and filtered_chunk != ' ':
                if ',' in filtered_chunk:
                    __clean_chunks+=filtered_chunk.split(',')
                elif '/' in filtered_chunk:
                    __clean_chunks+=filtered_chunk.split('/')
                else:
                    __clean_chunks.append(filtered_chunk)
        return set([chunk.strip() for chunk in __clean_chunks])
        

    def __get_skills(self,nounChunks):

        with open('skill_model.json','r') as f:
            model=f.read()
        sq_model = model_from_json(model)
        sq_model.load_weights('skillweights.h5')
        __clean_chunks=list(self.__clean_data(nounChunks))
        __onehot_repr=[one_hot(words,25000)for words in __clean_chunks]
        __test_data=pad_sequences(__onehot_repr,padding='pre',maxlen=6)
        __results = [(x,y[0])for x,y in zip(__clean_chunks,sq_model.predict_classes(np.array(__test_data)))]
        ones=set(positive['chunk'])
        zeros=set(negitive['chunk'])
        for i,result in enumerate(__results):
            if result[0] in ones and result[1] !=1:
                __results[i]=(result[0],1)
            if result[0] in zeros and result[1] !=0:
                __results[i]=(result[0],0)
        return set([x[0] for x in __results if x[1]==1])


    def __get_title(self,text):
        try:
            __role=re.findall(re.compile(r'POSITION[ ]*:[\w .\(\)]+|ROLE[ ]*:[\w .\(\)]+|TITLE[ ]*:[\w .\(\)]+'),text)[0].split(':')[1].strip()
            if '(' in __role:
                __role=re.findall(re.compile(r'\([\w ]+\)'),__role)[0][1:-1].strip()
            return __role.upper()
        except:
            return None

    def __matcher(self,resume):
        __text = docxpy.process(resume['file_path']).upper()
        if self.__title in __text:
            resume['Title']=self.__title
        for skill in self.__skills:
            if skill in __text:
                resume['Skills'].append(skill)
        resume['Skills'] = list(set(resume['Skills']))
        resume['match'] = 0.0 if len(self.__skills)==0 else (len(resume['Skills'])/len(self.__skills))*100
        return resume
    
    def filter_matches(self,candidates):
        if self.__title != None:
            __matches = []
            for user in candidates:
                resume = user.get_resume()
                result = self.__matcher(resume)
                if (result['Title']!='' and result['match']>60) or result['match']>60:
                    __matches.append(result)
            return sorted(__matches, key=lambda match:match['match'], reverse=True)
        else:
            print('Unable to extract Role try writing Role:...... or Position:....')

    def send_mail(self,matches):
        __port = 465  
        __smtp_server = "smtp.gmail.com"
        __sender_email = 'sonai20202015@gmail.com'
        __password = 'Sonai@123'
        context = ssl.create_default_context()
        with smtplib.SMTP_SSL(__smtp_server, __port, context=context) as server:
            server.login(__sender_email, __password)
            for Candidate in matches:
                __reciver_email = Candidate['Email']
                __message=f'''Subject: Job offer
                Hi {Candidate['Name']},
                This is an autogenrated email from an ATS SONAI we found your resume to be a 
                good match for {self.__title} job
                '''
                server.sendmail(__sender_email,__reciver_email, __message)
    
    def get_acess(self):

        auth_url = 'https://secure.dice.com/oauth/token'
        auth_header = {'Authorization': 'Basic dHM0LWhheWRlbnRlY2hub2xvZ3k6Yzk0NWI4YmItMmRmNi00Yjk4LThmNDUtMTg4ZWU5Mjk3ZGEz', 'Content-Type': 'application/x-www-form-urlencoded'}
        auth_data = {'grant_type': 'password', 'username': 'haydentechnology@dice.com', 'password': '635n3E7s'}
        
        try:

            auth_response =  requests.request('POST',auth_url,headers=auth_header,data=auth_data)
            auth_code = auth_response.status_code
            auth_response = json.loads(auth_response.content.decode())
            return (auth_code,auth_response)      
        
        except:

            return(0,'')

    def boolean_skills(self):

        with open('output.pkl','rb') as f:
            data = pickle.load(f)
        if self.__title in data:
            output = []
            for skill in self.__skills:
                if skill in data[self.__title][0] and data[self.__title][0][skill]>(3/4)*data[self.__title][1]:
                    continue
                output.append(skill)
            return output
        return self.__skills

    def search_with_api(self):

        auth_response = self.get_acess()
        if auth_response[0] == 200:
            
            token = auth_response[1]['access_token']
            headers = {'Authorization':f'bearer {token}'}
            url = 'https://talent-api.dice.com/v2/profiles/search?q='
            boolean_skills = self.boolean_skills()
            for skill in boolean_skills:
                url += f'{skill}&'
            url = url + self.__title
            print('\n',url,'\n')
            try:

                output = requests.request('GET',url,headers=headers)
                output = json.loads(output.content.decode())
                return output
            
            except:

                return ('error while finding users')

        else:

            return ('Authentication error with dice')



class Search_Candidates(Resource):
    
    def post(self):

        parser = reqparse.RequestParser()
        parser.add_argument("application_type",required=False)#String
        parser.add_argument("application_name",required=False)#String
        parser.add_argument("application_internal_only",required=False)#Boolean
        parser.add_argument("application_applicant_history",required=False)#Boolean
        parser.add_argument("application_years_of_employement_needed",required=False)#Float
        parser.add_argument("application_number_of_refrences",required=False)#Float
        parser.add_argument("application_flag_voluntarily_resign",required=False)#Boolean
        parser.add_argument("application_flag_past_employer_contracted",required=False)#Boolean
        parser.add_argument("email_template_default_address",required=False)#String
        parser.add_argument("task",required=False)#List
        parser.add_argument("job_title",required=True)#String
        parser.add_argument("employement_status",required=False)#String
        parser.add_argument('job_description', required=True)#String
        parser.add_argument("joinig_date",required=False)#String as ISO STANDARDS
        parser.add_argument("salary",required=False)#Float
        parser.add_argument("average_hours_weekly",required=False)#Float
        parser.add_argument("post_title",required=False)#String
        parser.add_argument("post_details_category",required=False)#String
        parser.add_argument("number_of_open_position",required=False)#Float
        parser.add_argument("general_application",required=False)#Boolean
        args = parser.parse_args()
        
        response = self.find_matches(args)
        response = json.dumps(response)
        return response


    def find_matches(self,args):

        file_paths=glob.glob(r'demo_word_file\*.docx')
        candidates=[Candidate(file_path) for file_path in file_paths]
        job = JobDescription(args)
        start_time=time.time()
        results = job.filter_matches(candidates)
        pprint(f'Found and Sorted {len(results)} results in {time.time()-start_time} secs from {len(candidates)} files')
        matches = [matches for matches in job.filter_matches(candidates)]
        if not len(matches) == 0:
            matches_with_email=[match for match in matches if match['Email'] != None]
            job.send_mail(matches_with_email)
        else:
            results = job.search_with_api()

        return results

def run():
    file_paths=glob.glob(r'demo_word_file\*.docx')
    candidates=[Candidate(file_path) for file_path in file_paths]
    text = docxpy.process('jobtest.docx')
    args= {'job_description': text}
    job = JobDescription(args)
    results = job.filter_matches(candidates)
    return results

if __name__ == "__main__":

    api.add_resource(Search_Candidates,'/findmatches/')
    application.run('localhost',8080,debug=True)

我的 requirement.txt 文件在這里

# Automatically generated by https://github.com/damnever/pigar.

# application.py: 15
Flask == 1.0.4

# application.py: 16
Flask_RESTful == 0.3.8

# application.py: 5
docxpy == 0.8.5

# application.py: 12
numpy == 1.19.1

# application.py: 13
pandas == 1.1.0

# application.py: 9
requests == 2.18.4

spacy>=2.2.0,<3.0.0
https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-2.2.0/en_core_web_sm-2.2.0.tar.gz#egg=en_core_web_sm

# application.py: 14,17,18,19
tensorflow == 1.14.0


Flask-SQLAlchemy==2.4.3
itsdangerous==1.1.0
Jinja2==2.11.2
MarkupSafe==1.1.1
pytz==2020.1
six==1.15.0
SQLAlchemy==1.3.18
Werkzeug==1.0.1

環境健康狀況良好，但在環境 url 中，我不斷收到 404 not found 我的代碼在開發服務器上工作，但在生產服務器上不工作

Answer 1

一個原因可能是不正確的端口。

您正在使用端口 8080：

application.run('localhost',8080,debug=True)

但是您的應用程序在 EB 上的默認端口是 8000。如果您想使用非默認端口，您可以定義EB 環境變量PORT的值為 8080。您可以使用.ebextenations或在 EB 控制台中執行此操作。

此外，可能還有許多其他問題，目前尚不明顯。 例如，鏈接的教程使用的是舊版本的 EB 環境，基於 Amazon Linux 1，但您使用的是 Amazon Linux 2。AL1和 AL2 之間存在許多差異，導致它們不兼容。

Tensorflow是資源匱乏的 package。 盡管您的問題中未指定實例類型， t2.micro可能對它來說太小了，以防您將它用於測試或開發。

Answer 2

將 Django 項目部署到 AWS EBS 時，我遇到了同樣的問題。

在 settings.py 下，port="5432"（作為字符串）。 我更改為 port=5432（作為 int）並解決了錯誤。