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<!-- markdownlint-disable MD003 --> | ||
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# Changelog | ||
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All notable changes to this project will be documented in this file. | ||
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), | ||
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html). | ||
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## [Unreleased] | ||
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## [1.0.1] - 2024-01-17 | ||
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### Changed | ||
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- Updated ECR repository name | ||
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## [1.0.0] - 2023-09-12 | ||
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### Added | ||
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- initial implementation of lambda function for extracting JML data on a schedule |
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FROM public.ecr.aws/lambda/python:3.11 | ||
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ARG VERSION | ||
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ENV BASE_VERSION="${VERSION}" | ||
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COPY src/var/task ${LAMDA_TASK_ROOT} | ||
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RUN python -m pip install --no-cache-dir --upgrade pip==23.3.2 \ | ||
&& python -m pip install --no-cache-dir --requirement requirements.txt | ||
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CMD ["handler.handler"] |
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{ | ||
"name": "jml-extract-lambda", | ||
"version": "1.0.1", | ||
"registry": "ecr", | ||
"ecr": { | ||
"role": "arn:aws:iam::013433889002:role/modernisation-platform-oidc-cicd", | ||
"account": "374269020027", | ||
"region": "eu-west-2", | ||
"repository": "data-platform-jml-extract-lambda-ecr-repo" | ||
} | ||
} |
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import os | ||
from datetime import datetime as dt | ||
from urllib.error import HTTPError | ||
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import awswrangler as wr | ||
import boto3 | ||
import pandas as pd | ||
from notifications_python_client import prepare_upload | ||
from notifications_python_client.notifications import NotificationsAPIClient | ||
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def handler(event, context): | ||
SECRET_ID = os.environ["SECRET_ID"] | ||
LOG_GROUP_NAMES = os.environ["LOG_GROUP_NAMES"] | ||
EMAIL_SECRET = os.environ["EMAIL_SECRET"] | ||
TEMPLATE_ID = os.environ["TEMPLATE_ID"] | ||
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secrets_client = boto3.client("secretsmanager") | ||
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response = secrets_client.get_secret_value(SecretId=SECRET_ID) | ||
api_key = response["SecretString"] | ||
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notifications_client = NotificationsAPIClient(api_key) | ||
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response = secrets_client.get_secret_value(SecretId=EMAIL_SECRET) | ||
email_address = response["SecretString"] | ||
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now = dt.now() | ||
current_date = dt.strftime(now.date(), "%Y/%m/%d") | ||
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# Query | ||
query = f"""fields detail.data.user_id as `User`, detail.data.user_name as `Employee Email Address` | ||
| filter detail.data.type = "s" | ||
| filter detail.data.connection = "github" | ||
| stats max(@timestamp) as `Last login date` by "{current_date}" as `Effective Date of Data`, \ | ||
`User`, `Employee Email Address` | ||
| sort `Last login date` desc | ||
""" | ||
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# Date range | ||
year = dt.now().year | ||
current_month = dt.now().month | ||
previous_month = current_month - 1 | ||
end_datetime = dt(year, current_month, 1, 0, 0, 0) | ||
if previous_month == 0: | ||
previous_month = 12 | ||
end_datetime = dt(year, current_month, 1, 0, 0, 0) | ||
year = year - 1 | ||
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start_datetime = dt(year, previous_month, 1, 0, 0, 0) | ||
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# Read logs | ||
dataframe = wr.cloudwatch.read_logs( | ||
log_group_names=LOG_GROUP_NAMES, | ||
query=query, | ||
start_time=start_datetime, | ||
end_time=end_datetime, | ||
) | ||
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# Datestamp | ||
datestamp = end_datetime.strftime(format="%Y_%m_%d") | ||
dataframe["Last login date"] = pd.to_datetime( | ||
dataframe["Last login date"], format="%Y-%m-%d %H:%M:%S.%f" | ||
).apply(lambda x: str(dt.strftime(x, "%Y/%m/%d"))) | ||
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# Save to Excel | ||
excel_filename = f"/tmp/jml_extract_{datestamp}.xlsx" | ||
dataframe.to_excel(excel_filename, index=False, sheet_name="Data") | ||
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# Send email notification | ||
with open(excel_filename, "rb") as f: | ||
try: | ||
response = notifications_client.send_email_notification( | ||
email_address=email_address, | ||
template_id=TEMPLATE_ID, | ||
personalisation={ | ||
"date": current_date, | ||
"link_to_file": prepare_upload(f), | ||
}, | ||
) | ||
except HTTPError as e: | ||
print(e) | ||
raise e |
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awswrangler==3.5.1 | ||
boto3==1.34.19 | ||
botocore==1.34.19 | ||
pandas==2.1.4 | ||
notifications-python-client==9.0.0 | ||
openpyxl==3.1.2 |