Mukei

//Amazonの注文履歴をCSV形式にして出力するスクリプト
//
//以下のスクリプトを参考に作成されました。
//http://moroya.hatenablog.jp/entry/2013/06/03/225935
//
//CSVに成型しているのは14行目から定義されているformatEntryという関数なので、これを書き換えれば自由な書式で出力できます。
(function(){

	// 各注文履歴をCSVフォーマットにして返す
	var datePattern = new RegExp("(\\d{4})年(\\d{1,2})月(\\d{1,2})日");

Mukei

#!
# Using aws s3 cp will require the --recursive parameter to copy multiple files.
aws s3 cp s3://myBucket/dir localdir --recursive

#The aws s3 sync command will, by default, copy a whole directory. It will only copy new/modified files.
aws s3 sync s3://mybucket/dir localdir
#Just experiment to get the result you want.

#You can combine --exclude and --include options to copy only objects that match a pattern, excluding all others.
aws s3 cp s3://mybucket/logs/ s3://mybucket2/logs/ --recursive --exclude "*" --include "*.log"

Mukei

original source: https://medium.com/statuscode/dockercheatsheet-9730ce03630d

Installation

Linux

curl -sSL https://get.docker.com/ | sh

Mukei

# List unique values in a DataFrame column
# h/t @makmanalp for the updated syntax!
df['Column Name'].unique()

# Convert Series datatype to numeric (will error if column has non-numeric values)
# h/t @makmanalp
pd.to_numeric(df['Column Name'])

# Convert Series datatype to numeric, changing non-numeric values to NaN
# h/t @makmanalp for the updated syntax!

Mukei

#
#  Original solution via StackOverflow:
#    http://stackoverflow.com/questions/35802939/install-only-available-packages-using-conda-install-yes-file-requirements-t
#

#
#  Install via `conda` directly.
#  This will fail to install all
#  dependencies. If one fails,
#  all dependencies will fail to install.

Mukei

#One workaround is to create clone environment, and then remove original one:
#(remember about deactivating current environment with deactivate on Windows and source deactivate on macOS/Linux)

conda create --name new_name --clone old_name --offline #use --offline flag to disable the redownload of all your packages
conda remove --name old_name --all # or its alias: `conda env remove --name old_name`

#There are several drawbacks of this method:
# time consumed on copying environment's files,
# temporary double disk usage.

Mukei

# To access kaggle datasets
!pip install kaggle

# Import data from Kaggle
# Colab's file access feature
from google.colab import files

# Retrieve uploaded file
uploaded = files.upload()

Mukei

#source https://www.kaggle.com/general/64962

!pip install kaggle

#Authenticating with Kaggle API
from googleapiclient.discovery import build
import io, os
from googleapiclient.http import MediaIoBaseDownload
from google.colab import auth
auth.authenticateuser() driveservice = build('drive', 'v3')

Mukei

Table of Contents

• References
• Other cheatsheets
• multiple gcloud config configurations
  • switch gcloud context with gcloud config
• auth
• info
• projects
• zones

Mukei

filter result based on images names containing "base" in their names

index = [index for index, im_similar in enumerate(im_similar) if "base" in im_similar]

im_similar = [im_similar[i] for i in index]
distances = [distances[0][i] for i in index]