#!/usr/bin/env python
# coding: utf-8

# ## Table of Contents
# 
# 1. [Initial Setup](#chapter1)
#     * [1.1. Install pdf2docx](#section_1_1)
#     * [1.2. Create an S3 bucket in the same region](#section_1_2)
#     * [1.3. Create Amazon Translate Batch Service Policy](#section_1_3)
#     * [1.4. Create Amazon Translate Batch Service Role](#section_1_4)
#     * [1.5. Attach the policy to the Service Role](#section_1_5)
#     
# ----
#     
# 2. [Upload multiple files to S3](#chapter2)
#     * [2.1. Widget to upload multiple files](#section_2_1)
#     * [2.2. Write to S3 bucket](#section_2_2)
# 
# ----
#     
# 3. [Translate Japanese documents to English using Batch Translation](#chapter3)
#     * [3.1. Create and start the batch translation job](#section_3_1)
#     * [3.2. Check the status of the job](#section_3_2)
# 
# ----
#     
# 4. [Verify and clean up](#chapter4)
#     * [4.1. Verify the document created in S3](#section_4_1)
#     * [4.2. Clean Up (optional)](#section_4_2)
#     
# ----

# ### 1. Initial Setup <a class="anchor" id="chapter1"></a>
# Run this section to install any libraries necessary and and IAM policy or roles needed as a pre-requisite

# #### 1.1  Install pdf2docx <a class="anchor" id="section_1_1"></a>
# Install the library [pdf2docx](https://pdf2docx.com/) to convert pdf to docx as [Amazon Translate](https://aws.amazon.com/translate/) do not currently support pdf formats.

# In[ ]:


get_ipython().system('pip3 install pdf2docx')


# #### 1.2 Create an S3 bucket in the same region <a class="anchor" id="section_1_2"></a>
# _For example since this focusses on Japanaese to English Translation we can name the prefixes accordingly.:-_
# 
# _Choose a unique bucket name_
# 
# bucket_name='translate-ja-en-kunal'
# 
# in_prefix_name='Japanese/input'
# 
# **Enter a unique bucket name before running the below cell**

# In[ ]:


import boto3
from pprint import pprint

# Enter the unique S3 bucket name before running
bucket_name='translate-ja-en-kunal'

my_region = boto3.session.Session().region_name
s3_client = boto3.client('s3', region_name=my_region)
location = {'LocationConstraint': my_region}
response=s3_client.create_bucket(Bucket=bucket_name,CreateBucketConfiguration=location)
pprint(response)


# #### 1.3 Create Amazon Translate Batch Service Policy <a class="anchor" id="section_1_3"></a>
# _Enter the bucket name created above, Policy Name_
# _For example:-_
# 
# bucket_name='translate-ja-en-kunal'
# 
# PolicyName='AmazonTranslateServicePolicy-Japanese-English-Document-Translation'
# 
# Description='Amazon Translate service role policy for Batch'

# In[ ]:


import json

client = boto3.client('iam')
# You may use the same Policy Name as long as it is not taken in your account
policy_name='AmazonTranslateServicePolicy-Japanese-English-Document-Translation'
policy_desc='Amazon Translate service role policy for Batch'

policy_document={
    "Version": "2012-10-17",
    "Statement": [
        {
            "Action": [
                "s3:GetObject"
            ],
            "Resource": [
                "arn:aws:s3:::" + bucket_name + "/*",
                "arn:aws:s3:::" + bucket_name + "/*"
            ],
            "Effect": "Allow"
        },
        {
            "Action": [
                "s3:ListBucket"
            ],
            "Resource": [
                "arn:aws:s3:::" + bucket_name,
                "arn:aws:s3:::" + bucket_name
            ],
            "Effect": "Allow"
        },
        {
            "Action": [
                "s3:PutObject"
            ],
            "Resource": [
                "arn:aws:s3:::" + bucket_name + "/*"
            ],
            "Effect": "Allow"
        }
    ]
}

response = client.create_policy(
    PolicyName=policy_name,
    PolicyDocument=json.dumps(policy_document),
    Description=policy_desc
)
policy_response=response
policy_arn=policy_response['Policy']['Arn']

print("Bucket Name",bucket_name)
print("Policy Name:",policy_name)
print("Policy Arn:",policy_arn)


# #### 1.4 Create Amazon Translate Batch Service Role <a class="anchor" id="section_1_4"></a>
# _Enter a role name and description_
# _For example:-_
# 
# RoleName='AmazonTranslateServiceRole-Japanese-English-Document-Translation'
# 
# Description='Amazon Translate service role for Batch.'

# In[ ]:


import boto3
import json

client = boto3.client('iam')
# You may use the same Policy Name as long as it is not taken in your account
role_name='AmazonTranslateServiceRole-Japanese-English-Document-Translation'
role_desc='Amazon Translate service role for Batch.'

trust_relationship_policy={
  "Version": "2012-10-17",
  "Statement": [
    {
      "Effect": "Allow",
      "Principal": {
        "Service": "translate.amazonaws.com"
      },
      "Action": "sts:AssumeRole"
    }
  ]
}


response = client.create_role(
    Path='/service-role/',
    RoleName=role_name,
    AssumeRolePolicyDocument=json.dumps(trust_relationship_policy),
    Description=role_desc
)
role_response=response
role_arn=role_response['Role']['Arn']

print("Role Name:",role_name)
print("Role Arn:",role_arn)


# #### 1.5 Attach the policy to the Service Role <a class="anchor" id="section_1_5"></a>

# In[ ]:


# Attach a role policy
client.attach_role_policy(
    PolicyArn=policy_arn,
    RoleName=role_name
)


# ----

# ### 2. Upload multiple files to S3 <a class="anchor" id="chapter2"></a>
# 
# Upload multiple Japanese documents to be translated from desktop.
# Accepted formats are _docx_, _pdf_

# #### 2.1 Widget to upload multiples <a class="anchor" id="section_2_1"></a>
# 
# Accepted formats are _docx_, _pdf_

# In[ ]:


# Create the upload widget to upload the file from local
# Click to upload files (docx / pdf)
from ipywidgets import FileUpload
from IPython.display import display
upload = FileUpload(accept='.docx,.pdf', multiple=True)
display(upload)


# #### 2.2 Write to S3 bucket <a class="anchor" id="section_2_2"></a>
# 
# * docx will be written to S3
# * pdf will be converted to docx before writing

# In[ ]:


from pdf2docx import parse
import os

# Translation input and out file prefix in S3
in_prefix_name='Japanese/input'
out_prefix_name='Japanese/output'  

s3 = boto3.resource('s3', region_name=my_region)
for name, md in upload.value.items():
# If the file type is pdf, convert to docx 
    if md['metadata']['type'] == 'application/pdf':
        with open (name, 'wb') as file:
            file.write(md['content'])
        filename, file_extension = os.path.splitext(name)
        newfilename = filename + '.docx'
        parse(name, newfilename, start=0, end=None)
        s3.Bucket(bucket_name).upload_file(newfilename,os.path.join(in_prefix_name,newfilename))
        os.remove(name)
        os.remove(newfilename)
            
    else:
        with open (name, 'wb') as file:
            s3.Object(bucket_name, os.path.join(in_prefix_name,name)).put(Body=md['content'])


# ----

# #### 3.1 Create and start the batch translation job <a class="anchor" id="section_3_1"></a>

# In[ ]:


from datetime import datetime

client = boto3.client('translate')

now=datetime.now().strftime("%m%d%Y%H%M%S")
job_name='japanese-to-english-multi-pages' + '-' + now
content_type='application/vnd.openxmlformats-officedocument.wordprocessingml.document'

job_response = client.start_text_translation_job(
    JobName=job_name,
    InputDataConfig={
        'S3Uri': os.path.join('s3://',bucket_name,in_prefix_name),
        'ContentType': content_type
    },
    OutputDataConfig={
        'S3Uri': os.path.join('s3://',bucket_name,out_prefix_name)
    },
    DataAccessRoleArn=role_arn,
    SourceLanguageCode='ja',
    TargetLanguageCodes=[
        'en',
    ]
)
job_id=job_response['JobId']
job_status=job_response['JobStatus']


print("JobId",job_id)
print("JobStatus",job_status)
print("Job Name",job_name)
pprint(job_response)


# #### 3.2 Check the status of the job <a class="anchor" id="section_3_2"></a>
# 
# Keep checking on the JobStatus which will change from **SUBMITTED** --> **IN_PROGRESS** --> **COMPLETED**

# In[ ]:


# Get job status
status_response = client.describe_text_translation_job(
    JobId=job_id
)

job_status=status_response['TextTranslationJobProperties']['JobStatus']
print("Job Name",job_name)
print("Job Status",job_status)
pprint(status_response)


# ----

# ### 4. Verify and clean up <a class="anchor" id="chapter4"></a>
# 
# Verify the translated document created in S3 and then clean up resources (optional).

# #### 4.1 Verify the document created in s3 <a class="anchor" id="section_4_1"></a>
# 
# Verify the translated document created in s3 location

# In[ ]:


print(os.path.join('s3://',bucket_name,out_prefix_name))


# #### 4.2 Clean up (optional) <a class="anchor" id="section_4_2"></a>
# 
# Clean up the resources created after you are done.

# In[ ]:


print("Reminder : Following are the resources which you created in this Notebook which needs to be cleaned up after you are done in region,{}.".format(my_region))
print("Bucket Name",bucket_name)
print("Policy Name:",policy_name)
print("Policy Arn:",policy_arn)
print("Role Name:",role_name)
print("Role Arn:",role_arn)


# ##### All Done!