boat-bee-mlのユーザ行動履歴のグラフの更新処理をboat-beeに移動する

.github/workflows/ci.yml

@@ -86,6 +86,20 @@ jobs:
       - run: make init
       - run: make format-check
 
+  report_user_action_graph:
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: lambda/report_user_action_graph
+    steps:
+      - uses: actions/[email protected]
+      - uses: actions/setup-python@v3
+        with:
+          python-version: "3.9.16"
+      - run: pip install pipenv
+      - run: make init
+      - run: make format-check
+
   export_dynamodb_table_to_s3_request:
     runs-on: ubuntu-latest
     defaults:
@@ -148,6 +162,7 @@ jobs:
         book_recommendation,
         report,
         report_review_graph,
+        report_user_action_graph,
         export_dynamodb_table_to_s3_request,
         export_dynamodb_table_to_s3_check_status,
       ]
@@ -183,6 +198,7 @@ jobs:
         book_recommendation,
         report,
         report_review_graph,
+        report_user_action_graph,
         export_dynamodb_table_to_s3_request,
         export_dynamodb_table_to_s3_check_status,
       ]

cdk/lib/bee-slack-app-stack.ts

@@ -474,6 +474,41 @@ export class BeeSlackAppStack extends Stack {
       schedule: Schedule.cron({ weekDay: "MON", hour: "0", minute: "0" }), // 毎週月曜日09:00(JST)に実行
       targets: [new LambdaFunction(reportReviewGraphFunction)],
     });
+
+    const reportUserActionGraphFunction = new Function(
+      this,
+      "ReportUserActionGraphLambda",
+      {
+        description: buildResourceDescription({
+          resourceName: "ReportUserActionGraphLambda",
+          stage,
+        }),
+        runtime: Runtime.FROM_IMAGE,
+        handler: Handler.FROM_IMAGE,
+        code: Code.fromAssetImage(
+          join(__dirname, "../../lambda/report_user_action_graph")
+        ),
+        environment: {
+          SLACK_CREDENTIALS_SECRET_ID: secret.secretName,
+          CONVERTED_DYNAMODB_JSON_BUCKET:
+            convertedDynamoDBJsonBucket.bucketName,
+        },
+        timeout: Duration.minutes(3),
+        memorySize: 1024,
+      }
+    );
+
+    convertedDynamoDBJsonBucket.grantRead(reportUserActionGraphFunction);
+    secret.grantRead(reportUserActionGraphFunction);
+
+    new Rule(this, "ReportUserActionGraphRule", {
+      description: buildResourceDescription({
+        resourceName: "ReportUserActionGraphRule",
+        stage,
+      }),
+      schedule: Schedule.cron({ weekDay: "MON", hour: "0", minute: "0" }), // 毎週月曜日09:00(JST)に実行
+      targets: [new LambdaFunction(reportUserActionGraphFunction)],
+    });
   }
 }
 

lambda/report_user_action_graph/.isort.cfg

@@ -0,0 +1,2 @@
+[settings]
+profile=black

lambda/report_user_action_graph/Dockerfile

@@ -0,0 +1,11 @@
+FROM --platform=linux/amd64 public.ecr.aws/lambda/python:3.9
+
+RUN pip install pipenv
+
+COPY Pipfile Pipfile.lock ./
+
+RUN pipenv install --system
+
+COPY index.py .
+
+CMD [ "index.lambda_handler" ]

lambda/report_user_action_graph/Makefile

@@ -0,0 +1,16 @@
+.PHONY: all
+all: init format-check
+
+.PHONY: init
+init:
+	pipenv install --dev
+
+.PHONY: format
+format:
+	pipenv run black ./
+	pipenv run isort ./
+
+.PHONY: format-check
+format-check:
+	pipenv run black --check ./
+	pipenv run isort ./ --check

lambda/report_user_action_graph/Pipfile

@@ -0,0 +1,17 @@
+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+slack-sdk = "==3.19.1"
+boto3 = "==1.21.35"
+pandas = "==1.3.3"
+seaborn = "==0.11.2"
+
+[dev-packages]
+black = "==22.3.0"
+isort = "==5.10.1"
+
+[requires]
+python_version = "3.9"

lambda/report_user_action_graph/README.md

@@ -0,0 +1,5 @@
+# report_user_action_graph
+
+ユーザの行動履歴のグラフを作成し、レポートを送信するハンドラ。メッセージを任意の Slack Incoming Webhook に送信する。
+
+送信先の Slack Incoming Webhook URL の指定方法は、[cdk](../../cdk/README.md)を参照。

lambda/report_user_action_graph/index.py

@@ -0,0 +1,178 @@
+import json
+import logging
+import os
+
+import boto3
+import pandas as pd
+import seaborn as sns
+from slack_sdk import WebClient
+from slack_sdk.errors import SlackApiError
+
+secretsmanager = boto3.client("secretsmanager")
+secret_id = os.environ["SLACK_CREDENTIALS_SECRET_ID"]
+secret_value = secretsmanager.get_secret_value(SecretId=secret_id)
+secret = json.loads(secret_value["SecretString"])
+
+SLACK_BOT_TOKEN = secret["BEE_OPERATION_BOT_SLACK_BOT_TOKEN"]
+SLACK_CHANNEL = secret["BEE_OPERATION_BOT_SLACK_CHANNEL"]
+
+
+def lambda_handler(event, context):
+    logger = logging.getLogger()
+
+    try:
+        df = load_items_from_dynamodb("user_action")
+
+        file_path = "/tmp/user_action_graph.png"
+
+        generate_user_action_graph(df, file_path)
+
+        upload_file_to_slack(
+            SLACK_BOT_TOKEN, SLACK_CHANNEL, file_path, "ユーザの行動履歴グラフを更新しました"
+        )
+    except Exception as e:
+        post_message_to_slack(SLACK_BOT_TOKEN, SLACK_CHANNEL, "ユーザの行動履歴グラフの更新に失敗しました")
+
+        logger.error("Error updating user action graph: {}".format(e))
+
+
+def load_items_from_dynamodb(item_id: str) -> pd.DataFrame:
+    """
+    DynamoDBからアイテムを取得する
+
+    Args:
+        item_id: アイテムの種別を表すキー。review、user、bookなど。
+    """
+    dynamodb_json_file = "/tmp/dynamodb_table.json"
+
+    s3 = boto3.client("s3")
+
+    s3.download_file(
+        os.environ["CONVERTED_DYNAMODB_JSON_BUCKET"],
+        "dynamodb_table.json",
+        dynamodb_json_file,
+    )
+
+    df = None
+
+    with open(dynamodb_json_file, "rt") as f:
+        df = pd.read_json(f)
+
+    return df[df["GSI_PK"] == item_id].reset_index()
+
+
+def upload_file_to_slack(
+    slack_token: str, channel: str, file_name: str, message: str
+) -> None:
+    """
+    Slackのチャンネルにファイルをアップロードする
+    """
+    logger = logging.getLogger()
+
+    try:
+        client = WebClient(token=slack_token)
+
+        client.files_upload(
+            channels=channel,
+            initial_comment=message,
+            file=file_name,
+        )
+
+    except SlackApiError as e:
+        logger.error("Error uploading file: {}".format(e))
+
+
+def post_message_to_slack(slack_token: str, channel: str, message: str) -> None:
+    """
+    Slackのチャンネルにメッセージを送信する
+    """
+    logger = logging.getLogger()
+
+    try:
+        client = WebClient(token=slack_token)
+
+        client.chat_postMessage(
+            channel=channel,
+            text=message,
+        )
+
+    except SlackApiError as e:
+        logger.error("Error post message: {}".format(e))
+
+
+def generate_user_action_graph(
+    df_user_action: pd.DataFrame, png_file_name: str
+) -> None:
+    """
+    user_actionの時系列グラフを作成し、画像ファイルとして保存する
+    """
+    df = _make_user_action_count_frame(df_user_action)
+
+    sns.set(rc={"figure.figsize": (30, 16)})
+
+    plot = sns.lineplot(data=df, x="index", y="created_at_date", hue="action")
+
+    plot.set_title("user action")
+    plot.set_xlabel("date")
+    plot.set_ylabel("action count")
+
+    plot.get_figure().savefig(png_file_name)
+
+
+def _make_user_action_count_frame(df_user_action: pd.DataFrame):
+    """
+    user_actionを日時ごとにカウントしたデータフレームを、user_action別で作成する
+    """
+
+    # 全てのuser_actionを集計する
+    df = _make_user_action_count_frame_one(df_user_action, "all")
+
+    action_name_list = [
+        "post_review_action",
+        "post_review_modal",
+        "app_home_opened",
+        "book_search_modal",
+        "book_search_result_modal",
+        "read_review_of_book_action",
+        "read_review_of_user_action",
+        "open_review_detail_modal_action",
+        "user_info_action",
+        "user_profile_modal",
+    ]
+
+    # 個別のuser_actionを集計する
+    for action_name in action_name_list:
+
+        df_specific_user_action = df_user_action[
+            df_user_action["action_name"] == action_name
+        ]
+
+        if df_specific_user_action.empty:
+            continue
+
+        df_tmp = _make_user_action_count_frame_one(df_specific_user_action, action_name)
+
+        df = pd.concat([df, df_tmp])
+
+    return df.reset_index()
+
+
+def _make_user_action_count_frame_one(df_user_action: pd.DataFrame, action):
+    """
+    user_actionを日時ごとにカウントしたデータフレームを作成する
+    """
+
+    df_user_action["created_at_date"] = df_user_action["created_at"].map(
+        lambda x: x[:10]
+    )
+
+    df = (
+        df_user_action["created_at_date"]
+        .value_counts()
+        .sort_index()
+        .to_frame()
+        .reset_index()
+    )
+    df["action"] = action
+
+    return df