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##### for signor | |
from s3bz.s3bz import S3 | |
def presign (bucket:str, key:str, expiry:int)->dict: | |
return S3.presignUpload(bucket=bucket, key = key, expiry = 1000) | |
``` | |
{'url': 'https://inventory-bucket-dev-manual.s3-accelerate.amazonaws.com/', | |
'fields': {'key': 'test', |
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AWSTemplateFormatVersion: 2010-09-09 | |
Resources: | |
CloudFrontCachePolicy: | |
Type: AWS::CloudFront::CachePolicy | |
Properties: | |
CachePolicyConfig: | |
CachePolicyConfig | |
cloudfrontdistribution: | |
Type: AWS::CloudFront::Distribution | |
Properties: |
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Parameters: | |
BRANCH: | |
Type: String | |
Default: dev-blank |
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AWSTemplateFormatVersion: '2010-09-09' | |
Transform: AWS::Serverless-2016-10-31 | |
Description: > | |
shortenLink | |
Sample SAM Template for shortenLink | |
Globals: | |
Function: | |
Timeout: 3 | |
Runtime: python3.8 |
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ProductS3: | |
Type: AWS::S3::Bucket | |
Properties: | |
AccelerateConfiguration: | |
AccelerationStatus: Enabled | |
BucketName: !Join [ "-" , ["product-bucket", !Ref BRANCH]] | |
CorsConfiguration: | |
CorsRules: | |
- AllowedMethods: | |
- GET |
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import boto3 | |
from botocore.exceptions import ClientError | |
bucket='filtered-df-sagemaker' | |
s3 = boto3.client('s3') | |
try: | |
s3.create_bucket( | |
Bucket=bucket, | |
CreateBucketConfiguration={'LocationConstraint':'ap-southeast-1'}) | |
except ClientError as e: |
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AWSTemplateFormatVersion: '2010-09-09' | |
Description: Cognito Stack | |
Parameters: | |
AuthName: | |
Type: String | |
Description: Unique Auth Name for Cognito Resources | |
Resources: | |
# Creates a role that allows Cognito to send SNS messages | |
SNSRole: |
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https://www.vembu.com/blog/increase-swap-memory-centos-7/ |
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AWSTemplateFormatVersion: '2010-09-09' | |
Transform: AWS::Serverless-2016-10-31 | |
Description: > | |
shortenLink | |
Sample SAM Template for shortenLink | |
Globals: | |
Function: | |
Timeout: 3 | |
Runtime: python3.8 |
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import pandas as pd | |
import json | |
df = pd.DataFrame({'hello':['1','2','2'], 'world':['1','2','3']}) | |
df | |
tableDict = df.to_dict(orient='list') | |
json.dumps(tableDict) |