diff --git a/.env.sh b/.env.sh
deleted file mode 100644
index 9a588cb..0000000
--- a/.env.sh
+++ /dev/null
@@ -1,2 +0,0 @@
-export BIGQUERY_PROJECT=pycontw-225217
-export GOOGLE_APPLICATION_CREDENTIALS=$(pwd)/service-account.json
diff --git a/.env.template b/.env.template
index e03e148..1b8f2e4 100644
--- a/.env.template
+++ b/.env.template
@@ -1,4 +1,4 @@
-# get the complete env from other volunteers, please
+AIRFLOW_HOME=/opt/airflow
BIGQUERY_PROJECT=pycontw-225217
-DATATEAM_DISCORD_WEBHOOK=<>
-GOOGLE_APPLICATION_CREDENTIALS=/usr/local/airflow/service-account.json
\ No newline at end of file
+GOOGLE_APPLICATION_CREDENTIALS=/opt/airflow/service-account.json
+AIRFLOW__CORE__FERNET_KEY=paste-your-fernet-key-here
\ No newline at end of file
diff --git a/.github/workflows/python.yml b/.github/workflows/python.yml
index d64c203..8dba4af 100644
--- a/.github/workflows/python.yml
+++ b/.github/workflows/python.yml
@@ -21,8 +21,8 @@ jobs:
- name: Install dependencies
run: |
- pip install -U poetry==1.6.1
- poetry install
+ pip install -r requirements.txt -r requirements-dev.txt -c constraints-3.8.txt
+ pip install black==19.10b0 click==7.1.2
- name: Run linters
run: make lint
diff --git a/.gitignore b/.gitignore
index 7f64bea..d7f4c76 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,4 +1,5 @@
# project stuff
+.env.production
.env.staging
env
env.sh
diff --git a/Dockerfile b/Dockerfile
index 2daf57e..ee0124e 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,7 +1,9 @@
-FROM apache/airflow:1.10.13-python3.8
+ARG AIRFLOW_VERSION=1.10.15
+ARG PYTHON_VERSION=3.8
+
+FROM apache/airflow:${AIRFLOW_VERSION}-python${PYTHON_VERSION}
+
USER root
-ENV POETRY_CACHE_DIR='/var/cache/pypoetry' \
- GOOGLE_APPLICATION_CREDENTIALS='/usr/local/airflow/service-account.json'
RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 467B942D3A79BD29 \
&& apt-key adv --keyserver keyserver.ubuntu.com --recv-keys B7B3B788A8D3785C \
@@ -10,19 +12,22 @@ RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 467B942D3A79BD29 \
# 1. if you don't need postgres, remember to remove postgresql-dev and sqlalchemy
# 2. libglib2.0-0 libsm6 libxext6 libxrender-dev libgl1-mesa-dev are required by opencv
# 3. git is required by pip install git+https
- && pip install --no-cache-dir -U poetry==1.6.1 \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
-COPY pyproject.toml pyproject.toml
-COPY poetry.toml poetry.toml
-COPY poetry.lock poetry.lock
+COPY entrypoint.sh /entrypoint.sh
-RUN python -m poetry install --no-interaction --no-ansi --no-dev \
- # Cleaning poetry installation's cache for production:
- && rm -rf "$POETRY_CACHE_DIR" \
- && pip uninstall -yq poetry
+RUN chmod +x /entrypoint.sh
USER airflow
-COPY dags /usr/local/airflow/dags
-COPY airflow.cfg airflow.cfg
+
+COPY ./requirements.txt ${AIRFLOW_HOME}/requirements.txt
+COPY ./constraints-3.8.txt ${AIRFLOW_HOME}/constraints-3.8.txt
+
+RUN pip install --no-cache-dir -r ${AIRFLOW_HOME}/requirements.txt --constraint constraints-3.8.txt
+
+COPY airflow.cfg ${AIRFLOW_HOME}/airflow.cfg
+
+COPY --chown=airflow:root dags ${AIRFLOW_HOME}/dags
+
+ENTRYPOINT ["/entrypoint.sh"]
diff --git a/Dockerfile.test b/Dockerfile.test
index d613edb..a702ec5 100644
--- a/Dockerfile.test
+++ b/Dockerfile.test
@@ -1,5 +1,36 @@
-FROM davidtnfsh/pycon_etl:prod
-ENV AIRFLOW_TEST_MODE=True
-ENV FERNET_KEY="uMnRC6ingT/WjPzPiXLvbWTJYzaA3sJdJRVkinceVp4="
+ARG AIRFLOW_VERSION=1.10.15
+ARG PYTHON_VERSION=3.8
+
+FROM apache/airflow:${AIRFLOW_VERSION}-python${PYTHON_VERSION}
+
USER root
-COPY airflow.test.cfg airflow.cfg
\ No newline at end of file
+
+RUN apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 467B942D3A79BD29 \
+ && apt-key adv --keyserver keyserver.ubuntu.com --recv-keys B7B3B788A8D3785C \
+ && apt-get update \
+ && apt-get install -y --no-install-recommends git \
+ # 1. if you don't need postgres, remember to remove postgresql-dev and sqlalchemy
+ # 2. libglib2.0-0 libsm6 libxext6 libxrender-dev libgl1-mesa-dev are required by opencv
+ # 3. git is required by pip install git+https
+ && apt-get clean \
+ && rm -rf /var/lib/apt/lists/*
+
+COPY entrypoint.sh /entrypoint.sh
+
+RUN chmod +x /entrypoint.sh
+
+USER airflow
+
+COPY ./requirements.txt ${AIRFLOW_HOME}/requirements.txt
+COPY ./requirements-dev.txt ${AIRFLOW_HOME}/requirements-dev.txt
+COPY ./constraints-3.8.txt ${AIRFLOW_HOME}/constraints-3.8.txt
+
+RUN pip install --no-cache-dir -r ${AIRFLOW_HOME}/requirements.txt -r ${AIRFLOW_HOME}/requirements-dev.txt --constraint constraints-3.8.txt
+
+COPY airflow.cfg ${AIRFLOW_HOME}/airflow.cfg
+
+COPY --chown=airflow:root dags ${AIRFLOW_HOME}/dags
+
+ENV AIRFLOW_TEST_MODE=True
+
+ENTRYPOINT ["/entrypoint.sh"]
diff --git a/Makefile b/Makefile
index cabdf50..01efb92 100644
--- a/Makefile
+++ b/Makefile
@@ -1,17 +1,30 @@
-VENV_PREFIX=poetry run
-
lint:
- $(VENV_PREFIX) black . --check
- $(VENV_PREFIX) isort --check-only .
- $(VENV_PREFIX) flake8 .
- $(VENV_PREFIX) mypy dags/ tests/
+ black . --check
+ isort --check-only .
+ flake8 .
+ mypy dags/ tests/
format:
- $(VENV_PREFIX) black .
- $(VENV_PREFIX) isort .
+ black .
+ isort .
test:
- PYTHONPATH=./dags $(VENV_PREFIX) pytest
+ PYTHONPATH=./dags pytest
coverage:
- PYTHONPATH=./dags $(VENV_PREFIX) pytest --cov=dags tests
+ PYTHONPATH=./dags pytest --cov=dags tests
+
+build-dev:
+ docker-compose -f ./docker-compose-dev.yml build
+
+deploy-dev:
+ docker-compose -f ./docker-compose-dev.yml up -d
+
+down-dev:
+ docker-compose -f ./docker-compose-dev.yml down
+
+deploy-prod:
+ docker-compose -f ./docker-compose.yml up -d
+
+down-prod:
+ docker-compose -f ./docker-compose.yml down
diff --git a/README.md b/README.md
index 69e0f45..50d2cab 100644
--- a/README.md
+++ b/README.md
@@ -1,176 +1,141 @@
# PyConTW ETL
+
![Python CI](https://github.com/pycontw/PyCon-ETL/workflows/Python%20CI/badge.svg)
![Docker Image CI](https://github.com/pycontw/PyCon-ETL/workflows/Docker%20Image%20CI/badge.svg)
-Using Airflow to implement our ETL pipelines
+Using Airflow to implement our ETL pipelines.
+## Table of Contents
-[TOC]
+- [Prerequisites](#prerequisites)
+- [Installation](#installation)
+- [Configuration](#configuration)
+- [BigQuery (Optional)](#bigquery-optional)
+- [Running the Project](#running-the-project)
+ - [Local Environment with Docker](#local-environment-with-docker)
+ - [Production](#production)
+- [Contact](#contact)
-## Year to Year Jobs
+## Prerequisites
-這三個 job 什麼時候打開需要人工確認(麻煩當年的組長大大了),理論上是售票開始前我們要測試一下然後打開
+- [Python 3.8+](https://www.python.org/downloads/release/python-3811/)
+- [Docker](https://docs.docker.com/get-docker/)
+- [Git](https://git-scm.com/book/zh-tw/v2/%E9%96%8B%E5%A7%8B-Git-%E5%AE%89%E8%A3%9D%E6%95%99%E5%AD%B8)
+- [venv](https://docs.python.org/3/library/venv.html)
-1. `gcloud beta compute ssh --zone asia-east1-b data-team --project pycontw-225217 -- -NL 8080:localhost:8080`
-2. Navigate to
-3. 打開下列的 Airflow tasks:
- 1. `KKTIX_DISCORD_BOT_FOR_TEAM_REGISTRATION`: 每天送賣票的銷量資訊到 discord 給註冊組看
- 2. `KKTIX_TICKET_ORDERS_V3`: 每五分鐘就去抓最新的 kktix 資料進 BigQuery, 更新後 metabase 相關連的 dashboard 就會更新(售票完之後可以關掉)
- 3. `KLAVIYO_SEND_MAIL_V3`: 每年寄發行前信時啓動隨買即用, 已購票的用戶會批次寄發信件, 新的購票者也會批次派發送信
+## Installation
-## Dags
+There are several tools available to create a virtual environment in Python.
-* Dag 的命名規則請看這篇 [阿里巴巴大數據實戰](https://medium.com/@davidtnfsh/%E5%A4%A7%E6%95%B0%E6%8D%AE%E4%B9%8B%E8%B7%AF-%E9%98%BF%E9%87%8C%E5%B7%B4%E5%B7%B4%E5%A4%A7%E6%95%B0%E6%8D%AE%E5%AE%9E%E8%B7%B5-%E8%AE%80%E6%9B%B8%E5%BF%83%E5%BE%97-54e795c2b8c)
-* Please refer to [this article](https://medium.com/@davidtnfsh/%E5%A4%A7%E6%95%B0%E6%8D%AE%E4%B9%8B%E8%B7%AF-%E9%98%BF%E9%87%8C%E5%B7%B4%E5%B7%B4%E5%A4%A7%E6%95%B0%E6%8D%AE%E5%AE%9E%E8%B7%B5-%E8%AE%80%E6%9B%B8%E5%BF%83%E5%BE%97-54e795c2b8c) for naming guidline
- * examples
- 1. `ods/opening_crawler`: Crawlers written by @Rain. Those openings can be used for the recruitment board, which was implemented by @tai271828 and @stacy.
- 2. `ods/survey_cake`: A manually triggered uploader that would upload questionnaires to bigquery. The uploader should be invoked after we receive the surveycake questionnaire.
+Below are the steps to manage a virtual environment using `venv`:
-## Prerequisites
-1. [Install Python 3.8+](https://www.python.org/downloads/release/python-3811/)
-2. [Get Docker](https://docs.docker.com/get-docker/)
-3. [Install Git](https://git-scm.com/book/zh-tw/v2/%E9%96%8B%E5%A7%8B-Git-%E5%AE%89%E8%A3%9D%E6%95%99%E5%AD%B8)
-4. [Get npm](https://www.npmjs.com/get-npm)
-
-## Install
-1. `docker pull docker.io/apache/airflow:1.10.13-python3.8`
-2. Python dependencies:
- 1. `virtualenv venv`
- * `. venv/bin/activate`
- 2. `pip install poetry`
- 3. `poetry install`
-3. Npm dependencies for linter, formatter, and commit linter (optional):
- 1. `brew install npm`
- 2. `npm ci`
-
-## Commit
-1. `git add `
-2. `npm run check`: Apply all the linter and formatter
-3. `npm run commit`
-
-## PR
-Please use Gitlab Flow, otherwise, you cannot pass docker hub CI
-
-## Run
-
-### Local environment Python Script
-
-1. `. venv/bin/activate`
-2. `. ./.env.sh`
-3. `cd contrib`
-4. Check its command in [contrib/README.md](contrib/README.md)
-5. `python xxx.py`
-
-### Local environment Docker
-
-> Find @davidtnfsh if you don't have those secrets.
-
-> **⚠ WARNING: About .env**
-> Please don't use the .env for local development, or it might screw up the production tables.
-
-1. Build docker image:
- * Build a production image (for production): `docker build -t davidtnfsh/pycon_etl:prod --cache-from davidtnfsh/pycon_etl:prod -f Dockerfile .`
- If you want to build dev/test image, you also need to build this docker image first because dev/test image is on top of this production image. See below.
- * Build dev/test image (for dev/test): `docker build -t davidtnfsh/pycon_etl:test --cache-from davidtnfsh/pycon_etl:prod -f Dockerfile.test .`
-2. Fill in some secrets:
- 1. `cp .env.template .env.staging` for dev/test. `cp .env.template .env.production` instead if you are going to start a production instance.
- 2. Follow the instructions in `.env.` and fill in your secrets.
- If you are running the staging instance for development as a sandbox and not going to access any specific third-party service, leave the `.env.staging` as-is should be fine.
-3. Start the Airflow server:
- * production: `docker run --log-opt max-size=1m -p 8080:8080 --name airflow -v $(pwd)/dags:/usr/local/airflow/dags -v $(pwd)/service-account.json:/usr/local/airflow/service-account.json --env-file=./.env.production davidtnfsh/pycon_etl:prod webserver`
- * dev/test: `docker run -p 8080:8080 --name airflow -v $(pwd)/dags:/usr/local/airflow/dags -v $(pwd)/service-account.json:/usr/local/airflow/service-account.json --env-file=./.env.staging davidtnfsh/pycon_etl:test webserver`
- * Note the difference is just the env file name and the image cache.
-4. Portforward compute instance to your local and then navigate to :
- 1. `gcloud beta compute ssh --zone "asia-east1-b" "data-team" --project "pycontw-225217" -- -NL 8080:localhost:8080`
- 2. If Port 8080 is already in use. You need to stop the service occupied 8080 port on your local first.
-
- ![image](./docs/airflow.png)
-5. Setup Airflow's Variable and Connections:
- * Youtube: ![img](docs/youtube-connection.png)
-
-### Local environment Docker (Windows)
-> Do not use Windows Powershell; please use Command Prompt instead.
-
-> Find @davidtnfsh if you don't have those secrets.
-
-> **⚠ WARNING: About .env**
-> Please don't use the .env for local development, or it might screw up the production tables.
-
-1. Build docker image:
- * Build a production image (for production): `docker build -t davidtnfsh/pycon_etl:prod --cache-from davidtnfsh/pycon_etl:prod -f Dockerfile .`
- If you want to build dev/test image, you also need to build this docker image first because dev/test image is on top of this production image. See below.
- * Build dev/test image (for dev/test): `docker build -t davidtnfsh/pycon_etl:test --cache-from davidtnfsh/pycon_etl:prod -f Dockerfile.test .`
-2. Fill in some secrets:
- 1. `copy .env.template .env.staging` for dev/test. `copy .env.template .env.production` instead if you are going to start a production instance.
- 2. Follow the instructions in `.env.` and fill in your secrets.
- If you are running the staging instance for development as a sandbox, and not going to access any specific thrid-party service, leave the `.env.staging` as-is should be fine.
-3. Start the Airflow server:
- * production: `docker run -p 8080:8080 --name airflow -v "/$(pwd)"/dags:/usr/local/airflow/dags -v "/$(pwd)"/service-account.json:/usr/local/airflow/service-account.json --env-file=./.env.production davidtnfsh/pycon_etl:prod webserver`
- * dev/test: `docker run -p 8080:8080 --name airflow -v "/$(pwd)"/dags:/usr/local/airflow/dags -v "/$(pwd)"/service-account.json:/usr/local/airflow/service-account.json --env-file=./.env.staging davidtnfsh/pycon_etl:test webserver`
- * Note the difference are just the env file name and the image cache.
-4. Portforward compute instance to your local and then navigate to :
- 1. `gcloud beta compute ssh --zone "asia-east1-b" "data-team" --project "pycontw-225217" -- -N -L 8080:localhost:8080`
- 2. If Port 8080 is already in use. You need to stop the service occupied 8080 port on your local first.
-
-![image](./docs/airflow.png)
-
-#### BigQuery (Optional)
-1. Setup the Authentication of GCP:
- * After invoking `gcloud auth application-default login`, you'll get a credentials.json resides in `$HOME/.config/gcloud/application_default_credentials.json`. Invoke `export GOOGLE_APPLICATION_CREDENTIALS="/path/to/keyfile.json"` if you have it.
- * service-account.json: Please contact @david30907d using email, telegram, or discord. No worry about this json if you are running the sandbox staging instance for development.
-2. Give [Toy-Examples](#Toy-Examples) a try
-
-## Deployment & Setting Up Credentials/Env
-1. Login to the data team's server:
- 1. `gcloud compute ssh --zone "asia-east1-b" "data-team" --project "pycontw-225217"`
- 2. service:
- * ETL: `/home/zhangtaiwei/pycon-etl`
- * btw, metabase is located here: `/mnt/disks/data-team-additional-disk/pycontw-infra-scripts/data_team/metabase_server`
-2. Pull the latest codebase to this server: `sudo git pull`
-3. Add Credentials (only need to do once):
- * Airflow:
- * Connections:
- * kktix_api: `conn_id=kktix_api`, `host` and `extra(header)` are confidential since its KKTIX's private endpoint. Please DM @GTB or data team's teammembers for these credentials.
- * extra: `{"Authorization": "bearer xxx"}`
- * klaviyo_api: `conn_id=klaviyo_api`, `host` is https://a.klaviyo.com/api
- * Variables:
- * KLAVIYO_KEY: Create from https://www.klaviyo.com/account#api-keys-tab
- * KLAVIYO_LIST_ID: Create from https://www.klaviyo.com/lists
- * KLAVIYO_CAMPAIGN_ID: Create from https://www.klaviyo.com/campaigns
- * kktix_events_endpoint: url path of kktix's `hosting_events`, ask @gtb for details!
-
-### CI/CD
-Please check [.github/workflows](.github/workflows) for details
-
-## Tutorials
-
-BigQuery Example:
-
-```python
-from google.cloud import bigquery
-
-client = bigquery.Client(project='pycontw-225217')
-
-# Perform a query.
-QUERY = '''
- SELECT scenario.day2checkin.attr.diet FROM `pycontw-225217.ods.ods_opass_attendee_timestamp`
-'''
-query_job = client.query(QUERY) # API request
-rows = query_job.result() # Waits for query to finish
-
-for row in rows:
- print(row.diet)
+1. Create a Virtual Environment
+
+ To create a virtual environment, run the following command:
+
+ ```bash
+ python -m venv venv
+ ```
+
+ In this example, `venv` is the name of the virtual environment directory, but you can replace it with any name you prefer.
+
+2. Activate the Virtual Environment
+
+ After creating the virtual environment, activate it using the following command:
+
+ ```bash
+ source venv/bin/activate
+ ```
+
+3. Install Dependencies
+
+ After activating the virtual environment, you can install the required dependencies:
+
+ ```bash
+ # Install airflow and dev dependencies
+ pip install -r requirements.txt -r requirements-dev.txt -c constraints-3.8.txt
+
+ # black is conflict with click, so install it separately
+ pip install black==19.10b0 click==7.1.2
+ ```
+
+4. Deactivate the Virtual Environment
+
+ When you're done working in the virtual environment, you can deactivate it with:
+
+ ```bash
+ deactivate
+ ```
+
+## Configuration
+
+1. For development or testing, run `cp .env.template .env.staging`. For production, run `cp .env.template .env.production`.
+
+2. Follow the instructions in `.env.` and fill in your secrets.
+ If you are running the staging instance for development as a sandbox and do not need to access any specific third-party services, leaving `.env.staging` as-is should be fine.
+
+> Contact the maintainer if you don't have these secrets.
+
+> **⚠ WARNING: About .env**
+> Please do not use the .env file for local development, as it might affect the production tables.
+
+### BigQuery (Optional)
+
+Set up the Authentication for GCP:
+ *After running `gcloud auth application-default login`, you will get a credentials.json file located at `$HOME/.config/gcloud/application_default_credentials.json`. Run `export GOOGLE_APPLICATION_CREDENTIALS="/path/to/keyfile.json"` if you have it.
+ * service-account.json: Please contact @david30907d via email or Discord. You do not need this json file if you are running the sandbox staging instance for development.
+
+## Running the Project
+
+If you are a developer 👨💻, please check the [Contributing Guide](./docs/CONTRIBUTING.md).
+
+If you are a maintainer 👨🔧, please check the [Maintenance Guide](./docs/MAINTENANCE.md).
+
+### Local Environment with Docker
+
+For development/testing:
+
+```bash
+# Build the local dev/test image
+make build-dev
+
+# Create the Airflow DB volume during the first setup
+docker volume create --name=airflow-db-volume
+
+# Start dev/test services
+make deploy-dev
+
+# Stop dev/test services
+make down-dev
+```
+
+> The difference between production and dev/test compose files is that the dev/test compose file uses a locally built image, while the production compose file uses the image from Docker Hub.
+
+If you are a authorized maintainer, you can pull the image from the GCP Artifact Registry.
+
+Docker client must be configured to use the GCP Artifact Registry.
+
+```bash
+gcloud auth configure-docker asia-east1-docker.pkg.dev
```
-### Conventions
+Then, pull the image:
+
+```bash
+docker pull asia-east1-docker.pkg.dev/pycontw-225217/data-team/pycon-etl:{tag}
+```
+
+There are several tags available:
+
+- `cache`: cache the image for faster deployment
+- `test`: for testing purposes, including the test dependencies
+- `staging`: when pushing to the staging environment
+- `latest`: when pushing to the production environment
-* table name convention:
- ![img](https://miro.medium.com/max/1400/1*bppuEKMnL9gFnvoRHUO8CQ.png)
+### Production
+Please check the [Production Deployment Guide](./docs/DEPLOYMENT.md).
-## DevOps (Will deprecate this if we don't bump into out-of-disk issue any more)
+## Contact
-1. Find topk biggest folders: `du -a /var/lib/docker/overlay2 | sort -n -r | head -n 20`
-2. Show the folder size: `du -hs xxxx`
-3. delete those pretty big folder
-4. `df -h`
\ No newline at end of file
+[PyCon TW Volunteer Data Team - Discord](https://discord.com/channels/752904426057892052/900721883383758879)
diff --git a/airflow.cfg b/airflow.cfg
index 0fd77c4..09a458f 100644
--- a/airflow.cfg
+++ b/airflow.cfg
@@ -1,11 +1,11 @@
[core]
# The folder where your airflow pipelines live, most likely a
# subfolder in a code repository. This path must be absolute.
-dags_folder = /usr/local/airflow/dags
+dags_folder = /opt/airflow/dags
# The folder where airflow should store its log files
# This path must be absolute
-base_log_folder = /usr/local/airflow/logs
+base_log_folder = /opt/airflow/logs
# Airflow can store logs remotely in AWS S3, Google Cloud Storage or Elastic Search.
# Set this to True if you want to enable remote logging.
@@ -44,7 +44,7 @@ simple_log_format = %%(asctime)s %%(levelname)s - %%(message)s
# Log filename format
log_filename_template = {{ ti.dag_id }}/{{ ti.task_id }}/{{ ts }}/{{ try_number }}.log
log_processor_filename_template = {{ filename }}.log
-dag_processor_manager_log_location = /usr/local/airflow/logs/dag_processor_manager/dag_processor_manager.log
+dag_processor_manager_log_location = /opt/airflow/logs/dag_processor_manager/dag_processor_manager.log
# Name of handler to read task instance logs.
# Default to use task handler.
@@ -127,10 +127,10 @@ max_active_runs_per_dag = 16
# Whether to load the examples that ship with Airflow. It's good to
# get started, but you probably want to set this to False in a production
# environment
-load_examples = True
+load_examples = False
# Where your Airflow plugins are stored
-plugins_folder = /usr/local/airflow/plugins
+plugins_folder = /opt/airflow/plugins
# Secret key to save connection passwords in the db
fernet_key = $FERNET_KEY
@@ -573,7 +573,7 @@ print_stats_interval = 30
# ago (in seconds), scheduler is considered unhealthy.
# This is used by the health check in the "/health" endpoint
scheduler_health_check_threshold = 30
-child_process_log_directory = /usr/local/airflow/logs/scheduler
+child_process_log_directory = /opt/airflow/logs/scheduler
# Local task jobs periodically heartbeat to the DB. If the job has
# not heartbeat in this many seconds, the scheduler will mark the
@@ -823,7 +823,7 @@ git_sync_root = /git
git_sync_dest = repo
# Mount point of the volume if git-sync is being used.
-# i.e. /usr/local/airflow/dags
+# i.e. /opt/airflow/dags
git_dags_folder_mount_point =
# To get Git-sync SSH authentication set up follow this format
diff --git a/airflow.test.cfg b/airflow.test.cfg
deleted file mode 100644
index 2fabe5a..0000000
--- a/airflow.test.cfg
+++ /dev/null
@@ -1,990 +0,0 @@
-[core]
-# The folder where your airflow pipelines live, most likely a
-# subfolder in a code repository. This path must be absolute.
-dags_folder = /usr/local/airflow/dags
-
-# The folder where airflow should store its log files
-# This path must be absolute
-base_log_folder = /usr/local/airflow/logs
-
-# Airflow can store logs remotely in AWS S3, Google Cloud Storage or Elastic Search.
-# Set this to True if you want to enable remote logging.
-remote_logging = False
-
-# Users must supply an Airflow connection id that provides access to the storage
-# location.
-remote_log_conn_id =
-remote_base_log_folder =
-encrypt_s3_logs = False
-
-# Logging level
-logging_level = INFO
-
-# Logging level for Flask-appbuilder UI
-fab_logging_level = WARN
-
-# Logging class
-# Specify the class that will specify the logging configuration
-# This class has to be on the python classpath
-# Example: logging_config_class = my.path.default_local_settings.LOGGING_CONFIG
-logging_config_class =
-
-# Flag to enable/disable Colored logs in Console
-# Colour the logs when the controlling terminal is a TTY.
-colored_console_log = True
-
-# Log format for when Colored logs is enabled
-colored_log_format = [%%(blue)s%%(asctime)s%%(reset)s] {{%%(blue)s%%(filename)s:%%(reset)s%%(lineno)d}} %%(log_color)s%%(levelname)s%%(reset)s - %%(log_color)s%%(message)s%%(reset)s
-colored_formatter_class = airflow.utils.log.colored_log.CustomTTYColoredFormatter
-
-# Format of Log line
-log_format = [%%(asctime)s] {{%%(filename)s:%%(lineno)d}} %%(levelname)s - %%(message)s
-simple_log_format = %%(asctime)s %%(levelname)s - %%(message)s
-
-# Log filename format
-log_filename_template = {{ ti.dag_id }}/{{ ti.task_id }}/{{ ts }}/{{ try_number }}.log
-log_processor_filename_template = {{ filename }}.log
-dag_processor_manager_log_location = /usr/local/airflow/logs/dag_processor_manager/dag_processor_manager.log
-
-# Name of handler to read task instance logs.
-# Default to use task handler.
-task_log_reader = task
-
-# Hostname by providing a path to a callable, which will resolve the hostname.
-# The format is "package:function".
-#
-# For example, default value "socket:getfqdn" means that result from getfqdn() of "socket"
-# package will be used as hostname.
-#
-# No argument should be required in the function specified.
-# If using IP address as hostname is preferred, use value ``airflow.utils.net:get_host_ip_address``
-hostname_callable = socket:getfqdn
-
-# Default timezone in case supplied date times are naive
-# can be utc (default), system, or any IANA timezone string (e.g. Europe/Amsterdam)
-default_timezone = utc
-
-# The executor class that airflow should use. Choices include
-# SequentialExecutor, LocalExecutor, CeleryExecutor, DaskExecutor, KubernetesExecutor
-executor = SequentialExecutor
-
-# The SqlAlchemy connection string to the metadata database.
-# SqlAlchemy supports many different database engine, more information
-# their website
-# sql_alchemy_conn = sqlite:////tmp/airflow.db
-
-# The encoding for the databases
-sql_engine_encoding = utf-8
-
-# If SqlAlchemy should pool database connections.
-sql_alchemy_pool_enabled = True
-
-# The SqlAlchemy pool size is the maximum number of database connections
-# in the pool. 0 indicates no limit.
-sql_alchemy_pool_size = 5
-
-# The maximum overflow size of the pool.
-# When the number of checked-out connections reaches the size set in pool_size,
-# additional connections will be returned up to this limit.
-# When those additional connections are returned to the pool, they are disconnected and discarded.
-# It follows then that the total number of simultaneous connections the pool will allow
-# is pool_size + max_overflow,
-# and the total number of "sleeping" connections the pool will allow is pool_size.
-# max_overflow can be set to -1 to indicate no overflow limit;
-# no limit will be placed on the total number of concurrent connections. Defaults to 10.
-sql_alchemy_max_overflow = 10
-
-# The SqlAlchemy pool recycle is the number of seconds a connection
-# can be idle in the pool before it is invalidated. This config does
-# not apply to sqlite. If the number of DB connections is ever exceeded,
-# a lower config value will allow the system to recover faster.
-sql_alchemy_pool_recycle = 1800
-
-# Check connection at the start of each connection pool checkout.
-# Typically, this is a simple statement like "SELECT 1".
-# More information here:
-# https://docs.sqlalchemy.org/en/13/core/pooling.html#disconnect-handling-pessimistic
-sql_alchemy_pool_pre_ping = True
-
-# The schema to use for the metadata database.
-# SqlAlchemy supports databases with the concept of multiple schemas.
-sql_alchemy_schema =
-
-# The amount of parallelism as a setting to the executor. This defines
-# the max number of task instances that should run simultaneously
-# on this airflow installation
-parallelism = 256
-
-# The number of task instances allowed to run concurrently by the scheduler
-dag_concurrency = 64
-
-# Are DAGs paused by default at creation
-dags_are_paused_at_creation = True
-
-# The maximum number of active DAG runs per DAG
-max_active_runs_per_dag = 16
-
-# Whether to load the examples that ship with Airflow. It's good to
-# get started, but you probably want to set this to False in a production
-# environment
-load_examples = True
-
-# Where your Airflow plugins are stored
-plugins_folder = /usr/local/airflow/plugins
-
-# Secret key to save connection passwords in the db
-fernet_key = $FERNET_KEY
-
-# Whether to disable pickling dags
-donot_pickle = False
-
-# How long before timing out a python file import
-dagbag_import_timeout = 600
-
-# How long before timing out a DagFileProcessor, which processes a dag file
-dag_file_processor_timeout = 600
-
-# The class to use for running task instances in a subprocess
-task_runner = StandardTaskRunner
-
-# If set, tasks without a ``run_as_user`` argument will be run with this user
-# Can be used to de-elevate a sudo user running Airflow when executing tasks
-default_impersonation =
-
-# What security module to use (for example kerberos)
-security =
-
-# If set to False enables some unsecure features like Charts and Ad Hoc Queries.
-# In 2.0 will default to True.
-secure_mode = False
-
-# Turn unit test mode on (overwrites many configuration options with test
-# values at runtime)
-unit_test_mode = False
-
-# Whether to enable pickling for xcom (note that this is insecure and allows for
-# RCE exploits). This will be deprecated in Airflow 2.0 (be forced to False).
-enable_xcom_pickling = True
-
-# When a task is killed forcefully, this is the amount of time in seconds that
-# it has to cleanup after it is sent a SIGTERM, before it is SIGKILLED
-killed_task_cleanup_time = 60
-
-# Whether to override params with dag_run.conf. If you pass some key-value pairs
-# through ``airflow dags backfill -c`` or
-# ``airflow dags trigger -c``, the key-value pairs will override the existing ones in params.
-dag_run_conf_overrides_params = False
-
-# Worker initialisation check to validate Metadata Database connection
-worker_precheck = False
-
-# When discovering DAGs, ignore any files that don't contain the strings ``DAG`` and ``airflow``.
-dag_discovery_safe_mode = True
-
-# The number of retries each task is going to have by default. Can be overridden at dag or task level.
-default_task_retries = 0
-
-# Whether to serialises DAGs and persist them in DB.
-# If set to True, Webserver reads from DB instead of parsing DAG files
-# More details: https://airflow.apache.org/docs/stable/dag-serialization.html
-store_serialized_dags = False
-
-# Updating serialized DAG can not be faster than a minimum interval to reduce database write rate.
-min_serialized_dag_update_interval = 30
-
-# On each dagrun check against defined SLAs
-check_slas = True
-
-[cli]
-# In what way should the cli access the API. The LocalClient will use the
-# database directly, while the json_client will use the api running on the
-# webserver
-api_client = airflow.api.client.local_client
-
-# If you set web_server_url_prefix, do NOT forget to append it here, ex:
-# ``endpoint_url = http://localhost:8080/myroot``
-# So api will look like: ``http://localhost:8080/myroot/api/experimental/...``
-endpoint_url = http://localhost:8080
-
-[debug]
-# Used only with DebugExecutor. If set to True DAG will fail with first
-# failed task. Helpful for debugging purposes.
-fail_fast = False
-
-[api]
-# How to authenticate users of the API
-auth_backend = airflow.api.auth.backend.default
-
-[lineage]
-# what lineage backend to use
-backend =
-
-[atlas]
-sasl_enabled = False
-host =
-port = 21000
-username =
-password =
-
-[operators]
-# The default owner assigned to each new operator, unless
-# provided explicitly or passed via ``default_args``
-default_owner = airflow
-default_cpus = 1
-default_ram = 512
-default_disk = 512
-default_gpus = 0
-
-[hive]
-# Default mapreduce queue for HiveOperator tasks
-default_hive_mapred_queue =
-
-[webserver]
-# The base url of your website as airflow cannot guess what domain or
-# cname you are using. This is used in automated emails that
-# airflow sends to point links to the right web server
-base_url = http://localhost:8080
-
-# The ip specified when starting the web server
-web_server_host = 0.0.0.0
-
-# The port on which to run the web server
-web_server_port = 8080
-
-# Paths to the SSL certificate and key for the web server. When both are
-# provided SSL will be enabled. This does not change the web server port.
-web_server_ssl_cert =
-
-# Paths to the SSL certificate and key for the web server. When both are
-# provided SSL will be enabled. This does not change the web server port.
-web_server_ssl_key =
-
-# Number of seconds the webserver waits before killing gunicorn master that doesn't respond
-web_server_master_timeout = 600
-
-# Number of seconds the gunicorn webserver waits before timing out on a worker
-web_server_worker_timeout = 600
-
-# Number of workers to refresh at a time. When set to 0, worker refresh is
-# disabled. When nonzero, airflow periodically refreshes webserver workers by
-# bringing up new ones and killing old ones.
-worker_refresh_batch_size = 1
-
-# Number of seconds to wait before refreshing a batch of workers.
-worker_refresh_interval = 30
-
-# Secret key used to run your flask app
-# It should be as random as possible
-secret_key = l\xba,\xc3\x023\xca\x04\xdb\xf2\xf7\xfa\xb8#\xee>
-
-# Number of workers to run the Gunicorn web server
-workers = 2
-
-# The worker class gunicorn should use. Choices include
-# sync (default), eventlet, gevent
-worker_class = sync
-
-# Log files for the gunicorn webserver. '-' means log to stderr.
-access_logfile = -
-
-# Log files for the gunicorn webserver. '-' means log to stderr.
-error_logfile = -
-
-# Expose the configuration file in the web server
-expose_config = True
-
-# Expose hostname in the web server
-expose_hostname = True
-
-# Expose stacktrace in the web server
-expose_stacktrace = True
-
-# Set to true to turn on authentication:
-# https://airflow.apache.org/security.html#web-authentication
-authenticate = False
-
-# Filter the list of dags by owner name (requires authentication to be enabled)
-filter_by_owner = False
-
-# Filtering mode. Choices include user (default) and ldapgroup.
-# Ldap group filtering requires using the ldap backend
-#
-# Note that the ldap server needs the "memberOf" overlay to be set up
-# in order to user the ldapgroup mode.
-owner_mode = user
-
-# Default DAG view. Valid values are:
-# tree, graph, duration, gantt, landing_times
-dag_default_view = tree
-
-# "Default DAG orientation. Valid values are:"
-# LR (Left->Right), TB (Top->Bottom), RL (Right->Left), BT (Bottom->Top)
-dag_orientation = LR
-
-# Puts the webserver in demonstration mode; blurs the names of Operators for
-# privacy.
-demo_mode = False
-
-# The amount of time (in secs) webserver will wait for initial handshake
-# while fetching logs from other worker machine
-log_fetch_timeout_sec = 5
-
-# Time interval (in secs) to wait before next log fetching.
-log_fetch_delay_sec = 2
-
-# Distance away from page bottom to enable auto tailing.
-log_auto_tailing_offset = 30
-
-# Animation speed for auto tailing log display.
-log_animation_speed = 1000
-
-# By default, the webserver shows paused DAGs. Flip this to hide paused
-# DAGs by default
-hide_paused_dags_by_default = False
-
-# Consistent page size across all listing views in the UI
-page_size = 100
-
-# Use FAB-based webserver with RBAC feature
-rbac = False
-
-# Define the color of navigation bar
-navbar_color = #007A87
-
-# Default dagrun to show in UI
-default_dag_run_display_number = 25
-
-# Enable werkzeug ``ProxyFix`` middleware for reverse proxy
-enable_proxy_fix = False
-
-# Number of values to trust for ``X-Forwarded-For``.
-# More info: https://werkzeug.palletsprojects.com/en/0.16.x/middleware/proxy_fix/
-proxy_fix_x_for = 1
-
-# Number of values to trust for ``X-Forwarded-Proto``
-proxy_fix_x_proto = 1
-
-# Number of values to trust for ``X-Forwarded-Host``
-proxy_fix_x_host = 1
-
-# Number of values to trust for ``X-Forwarded-Port``
-proxy_fix_x_port = 1
-
-# Number of values to trust for ``X-Forwarded-Prefix``
-proxy_fix_x_prefix = 1
-
-# Set secure flag on session cookie
-cookie_secure = False
-
-# Set samesite policy on session cookie
-cookie_samesite =
-
-# Default setting for wrap toggle on DAG code and TI log views.
-default_wrap = False
-
-# Allow the UI to be rendered in a frame
-x_frame_enabled = True
-
-# Send anonymous user activity to your analytics tool
-# choose from google_analytics, segment, or metarouter
-# analytics_tool =
-
-# Unique ID of your account in the analytics tool
-# analytics_id =
-
-# Update FAB permissions and sync security manager roles
-# on webserver startup
-update_fab_perms = True
-
-# Minutes of non-activity before logged out from UI
-# 0 means never get forcibly logged out
-force_log_out_after = 0
-
-# The UI cookie lifetime in days
-session_lifetime_days = 30
-
-[email]
-email_backend = airflow.utils.email.send_email_smtp
-
-[smtp]
-
-# If you want airflow to send emails on retries, failure, and you want to use
-# the airflow.utils.email.send_email_smtp function, you have to configure an
-# smtp server here
-smtp_host = localhost
-smtp_starttls = True
-smtp_ssl = False
-# Example: smtp_user = airflow
-# smtp_user =
-# Example: smtp_password = airflow
-# smtp_password =
-smtp_port = 25
-smtp_mail_from = airflow@example.com
-
-[sentry]
-
-# Sentry (https://docs.sentry.io) integration
-sentry_dsn =
-
-[celery]
-
-# This section only applies if you are using the CeleryExecutor in
-# ``[core]`` section above
-# The app name that will be used by celery
-celery_app_name = airflow.executors.celery_executor
-
-# The concurrency that will be used when starting workers with the
-# ``airflow celery worker`` command. This defines the number of task instances that
-# a worker will take, so size up your workers based on the resources on
-# your worker box and the nature of your tasks
-worker_concurrency = 32
-
-# The maximum and minimum concurrency that will be used when starting workers with the
-# ``airflow celery worker`` command (always keep minimum processes, but grow
-# to maximum if necessary). Note the value should be max_concurrency,min_concurrency
-# Pick these numbers based on resources on worker box and the nature of the task.
-# If autoscale option is available, worker_concurrency will be ignored.
-# http://docs.celeryproject.org/en/latest/reference/celery.bin.worker.html#cmdoption-celery-worker-autoscale
-# Example: worker_autoscale = 16,12
-worker_autoscale = 32,12
-
-# When you start an airflow worker, airflow starts a tiny web server
-# subprocess to serve the workers local log files to the airflow main
-# web server, who then builds pages and sends them to users. This defines
-# the port on which the logs are served. It needs to be unused, and open
-# visible from the main web server to connect into the workers.
-worker_log_server_port = 8793
-
-# The Celery broker URL. Celery supports RabbitMQ, Redis and experimentally
-# a sqlalchemy database. Refer to the Celery documentation for more
-# information.
-# http://docs.celeryproject.org/en/latest/userguide/configuration.html#broker-settings
-broker_url = redis://redis:6379/1
-
-# The Celery result_backend. When a job finishes, it needs to update the
-# metadata of the job. Therefore it will post a message on a message bus,
-# or insert it into a database (depending of the backend)
-# This status is used by the scheduler to update the state of the task
-# The use of a database is highly recommended
-# http://docs.celeryproject.org/en/latest/userguide/configuration.html#task-result-backend-settings
-result_backend = db+postgresql://airflow:airflow@postgres/airflow
-
-# Celery Flower is a sweet UI for Celery. Airflow has a shortcut to start
-# it ``airflow flower``. This defines the IP that Celery Flower runs on
-flower_host = 0.0.0.0
-
-# The root URL for Flower
-# Example: flower_url_prefix = /flower
-flower_url_prefix =
-
-# This defines the port that Celery Flower runs on
-flower_port = 5555
-
-# Securing Flower with Basic Authentication
-# Accepts user:password pairs separated by a comma
-# Example: flower_basic_auth = user1:password1,user2:password2
-flower_basic_auth =
-
-# Default queue that tasks get assigned to and that worker listen on.
-default_queue = default
-
-# How many processes CeleryExecutor uses to sync task state.
-# 0 means to use max(1, number of cores - 1) processes.
-sync_parallelism = 0
-
-# Import path for celery configuration options
-celery_config_options = airflow.config_templates.default_celery.DEFAULT_CELERY_CONFIG
-
-# In case of using SSL
-ssl_active = False
-ssl_key =
-ssl_cert =
-ssl_cacert =
-
-# Celery Pool implementation.
-# Choices include: prefork (default), eventlet, gevent or solo.
-# See:
-# https://docs.celeryproject.org/en/latest/userguide/workers.html#concurrency
-# https://docs.celeryproject.org/en/latest/userguide/concurrency/eventlet.html
-pool = prefork
-
-# The number of seconds to wait before timing out ``send_task_to_executor`` or
-# ``fetch_celery_task_state`` operations.
-operation_timeout = 2
-
-[celery_broker_transport_options]
-
-# This section is for specifying options which can be passed to the
-# underlying celery broker transport. See:
-# http://docs.celeryproject.org/en/latest/userguide/configuration.html#std:setting-broker_transport_options
-# The visibility timeout defines the number of seconds to wait for the worker
-# to acknowledge the task before the message is redelivered to another worker.
-# Make sure to increase the visibility timeout to match the time of the longest
-# ETA you're planning to use.
-# visibility_timeout is only supported for Redis and SQS celery brokers.
-# See:
-# http://docs.celeryproject.org/en/master/userguide/configuration.html#std:setting-broker_transport_options
-# Example: visibility_timeout = 21600
-# visibility_timeout =
-
-[dask]
-
-# This section only applies if you are using the DaskExecutor in
-# [core] section above
-# The IP address and port of the Dask cluster's scheduler.
-cluster_address = 127.0.0.1:8786
-
-# TLS/ SSL settings to access a secured Dask scheduler.
-tls_ca =
-tls_cert =
-tls_key =
-
-[scheduler]
-# Task instances listen for external kill signal (when you clear tasks
-# from the CLI or the UI), this defines the frequency at which they should
-# listen (in seconds).
-job_heartbeat_sec = 5
-
-# The scheduler constantly tries to trigger new tasks (look at the
-# scheduler section in the docs for more information). This defines
-# how often the scheduler should run (in seconds).
-scheduler_heartbeat_sec = 5
-
-# After how much time should the scheduler terminate in seconds
-# -1 indicates to run continuously (see also num_runs)
-run_duration = -1
-
-# The number of times to try to schedule each DAG file
-# -1 indicates unlimited number
-num_runs = -1
-
-# The number of seconds to wait between consecutive DAG file processing
-processor_poll_interval = 1
-
-# after how much time (seconds) a new DAGs should be picked up from the filesystem
-min_file_process_interval = 0
-
-# How often (in seconds) to scan the DAGs directory for new files. Default to 5 minutes.
-dag_dir_list_interval = 300
-
-# How often should stats be printed to the logs. Setting to 0 will disable printing stats
-print_stats_interval = 30
-
-# If the last scheduler heartbeat happened more than scheduler_health_check_threshold
-# ago (in seconds), scheduler is considered unhealthy.
-# This is used by the health check in the "/health" endpoint
-scheduler_health_check_threshold = 30
-child_process_log_directory = /usr/local/airflow/logs/scheduler
-
-# Local task jobs periodically heartbeat to the DB. If the job has
-# not heartbeat in this many seconds, the scheduler will mark the
-# associated task instance as failed and will re-schedule the task.
-scheduler_zombie_task_threshold = 300
-
-# Turn off scheduler catchup by setting this to False.
-# Default behavior is unchanged and
-# Command Line Backfills still work, but the scheduler
-# will not do scheduler catchup if this is False,
-# however it can be set on a per DAG basis in the
-# DAG definition (catchup)
-catchup_by_default = True
-
-# This changes the batch size of queries in the scheduling main loop.
-# If this is too high, SQL query performance may be impacted by one
-# or more of the following:
-# - reversion to full table scan
-# - complexity of query predicate
-# - excessive locking
-# Additionally, you may hit the maximum allowable query length for your db.
-# Set this to 0 for no limit (not advised)
-max_tis_per_query = 512
-
-# Statsd (https://github.com/etsy/statsd) integration settings
-statsd_on = False
-statsd_host = localhost
-statsd_port = 8125
-statsd_prefix = airflow
-
-# If you want to avoid send all the available metrics to StatsD,
-# you can configure an allow list of prefixes to send only the metrics that
-# start with the elements of the list (e.g: scheduler,executor,dagrun)
-statsd_allow_list =
-
-# The scheduler can run multiple threads in parallel to schedule dags.
-# This defines how many threads will run.
-max_threads = 2
-authenticate = False
-
-# Turn off scheduler use of cron intervals by setting this to False.
-# DAGs submitted manually in the web UI or with trigger_dag will still run.
-use_job_schedule = True
-
-# Allow externally triggered DagRuns for Execution Dates in the future
-# Only has effect if schedule_interval is set to None in DAG
-allow_trigger_in_future = False
-
-[ldap]
-# set this to ldaps://:
-uri =
-user_filter = objectClass=*
-user_name_attr = uid
-group_member_attr = memberOf
-superuser_filter =
-data_profiler_filter =
-bind_user = cn=Manager,dc=example,dc=com
-bind_password = insecure
-basedn = dc=example,dc=com
-cacert = /etc/ca/ldap_ca.crt
-search_scope = LEVEL
-
-# This setting allows the use of LDAP servers that either return a
-# broken schema, or do not return a schema.
-ignore_malformed_schema = False
-
-[mesos]
-# Mesos master address which MesosExecutor will connect to.
-master = localhost:5050
-
-# The framework name which Airflow scheduler will register itself as on mesos
-framework_name = Airflow
-
-# Number of cpu cores required for running one task instance using
-# 'airflow run --local -p '
-# command on a mesos slave
-task_cpu = 1
-
-# Memory in MB required for running one task instance using
-# 'airflow run --local -p '
-# command on a mesos slave
-task_memory = 256
-
-# Enable framework checkpointing for mesos
-# See http://mesos.apache.org/documentation/latest/slave-recovery/
-checkpoint = False
-
-# Failover timeout in milliseconds.
-# When checkpointing is enabled and this option is set, Mesos waits
-# until the configured timeout for
-# the MesosExecutor framework to re-register after a failover. Mesos
-# shuts down running tasks if the
-# MesosExecutor framework fails to re-register within this timeframe.
-# Example: failover_timeout = 604800
-# failover_timeout =
-
-# Enable framework authentication for mesos
-# See http://mesos.apache.org/documentation/latest/configuration/
-authenticate = False
-
-# Mesos credentials, if authentication is enabled
-# Example: default_principal = admin
-# default_principal =
-# Example: default_secret = admin
-# default_secret =
-
-# Optional Docker Image to run on slave before running the command
-# This image should be accessible from mesos slave i.e mesos slave
-# should be able to pull this docker image before executing the command.
-# Example: docker_image_slave = puckel/docker-airflow
-# docker_image_slave =
-
-[kerberos]
-ccache = /tmp/airflow_krb5_ccache
-
-# gets augmented with fqdn
-principal = airflow
-reinit_frequency = 3600
-kinit_path = kinit
-keytab = airflow.keytab
-
-[github_enterprise]
-api_rev = v3
-
-[admin]
-# UI to hide sensitive variable fields when set to True
-hide_sensitive_variable_fields = True
-
-[elasticsearch]
-# Elasticsearch host
-host =
-
-# Format of the log_id, which is used to query for a given tasks logs
-log_id_template = {{dag_id}}-{{task_id}}-{{execution_date}}-{{try_number}}
-
-# Used to mark the end of a log stream for a task
-end_of_log_mark = end_of_log
-
-# Qualified URL for an elasticsearch frontend (like Kibana) with a template argument for log_id
-# Code will construct log_id using the log_id template from the argument above.
-# NOTE: The code will prefix the https:// automatically, don't include that here.
-frontend =
-
-# Write the task logs to the stdout of the worker, rather than the default files
-write_stdout = False
-
-# Instead of the default log formatter, write the log lines as JSON
-json_format = False
-
-# Log fields to also attach to the json output, if enabled
-json_fields = asctime, filename, lineno, levelname, message
-
-[elasticsearch_configs]
-use_ssl = False
-verify_certs = True
-
-[kubernetes]
-# The repository, tag and imagePullPolicy of the Kubernetes Image for the Worker to Run
-worker_container_repository =
-worker_container_tag =
-worker_container_image_pull_policy = IfNotPresent
-
-# If True (default), worker pods will be deleted upon termination
-delete_worker_pods = True
-
-# Number of Kubernetes Worker Pod creation calls per scheduler loop
-worker_pods_creation_batch_size = 1
-
-# The Kubernetes namespace where airflow workers should be created. Defaults to ``default``
-namespace = default
-
-# The name of the Kubernetes ConfigMap containing the Airflow Configuration (this file)
-# Example: airflow_configmap = airflow-configmap
-airflow_configmap =
-
-# The name of the Kubernetes ConfigMap containing ``airflow_local_settings.py`` file.
-#
-# For example:
-#
-# ``airflow_local_settings_configmap = "airflow-configmap"`` if you have the following ConfigMap.
-#
-# ``airflow-configmap.yaml``:
-#
-# .. code-block:: yaml
-#
-# ---
-# apiVersion: v1
-# kind: ConfigMap
-# metadata:
-# name: airflow-configmap
-# data:
-# airflow_local_settings.py: |
-# def pod_mutation_hook(pod):
-# ...
-# airflow.cfg: |
-# ...
-# Example: airflow_local_settings_configmap = airflow-configmap
-airflow_local_settings_configmap =
-
-# For docker image already contains DAGs, this is set to ``True``, and the worker will
-# search for dags in dags_folder,
-# otherwise use git sync or dags volume claim to mount DAGs
-dags_in_image = False
-
-# For either git sync or volume mounted DAGs, the worker will look in this subpath for DAGs
-dags_volume_subpath =
-
-# For DAGs mounted via a volume claim (mutually exclusive with git-sync and host path)
-dags_volume_claim =
-
-# For volume mounted logs, the worker will look in this subpath for logs
-logs_volume_subpath =
-
-# A shared volume claim for the logs
-logs_volume_claim =
-
-# For DAGs mounted via a hostPath volume (mutually exclusive with volume claim and git-sync)
-# Useful in local environment, discouraged in production
-dags_volume_host =
-
-# A hostPath volume for the logs
-# Useful in local environment, discouraged in production
-logs_volume_host =
-
-# A list of configMapsRefs to envFrom. If more than one configMap is
-# specified, provide a comma separated list: configmap_a,configmap_b
-env_from_configmap_ref =
-
-# A list of secretRefs to envFrom. If more than one secret is
-# specified, provide a comma separated list: secret_a,secret_b
-env_from_secret_ref =
-
-# Git credentials and repository for DAGs mounted via Git (mutually exclusive with volume claim)
-git_repo =
-git_branch =
-git_subpath =
-
-# The specific rev or hash the git_sync init container will checkout
-# This becomes GIT_SYNC_REV environment variable in the git_sync init container for worker pods
-git_sync_rev =
-
-# Use git_user and git_password for user authentication or git_ssh_key_secret_name
-# and git_ssh_key_secret_key for SSH authentication
-git_user =
-git_password =
-git_sync_root = /git
-git_sync_dest = repo
-
-# Mount point of the volume if git-sync is being used.
-# i.e. /usr/local/airflow/dags
-git_dags_folder_mount_point =
-
-# To get Git-sync SSH authentication set up follow this format
-#
-# ``airflow-secrets.yaml``:
-#
-# .. code-block:: yaml
-#
-# ---
-# apiVersion: v1
-# kind: Secret
-# metadata:
-# name: airflow-secrets
-# data:
-# # key needs to be gitSshKey
-# gitSshKey:
-# Example: git_ssh_key_secret_name = airflow-secrets
-git_ssh_key_secret_name =
-
-# To get Git-sync SSH authentication set up follow this format
-#
-# ``airflow-configmap.yaml``:
-#
-# .. code-block:: yaml
-#
-# ---
-# apiVersion: v1
-# kind: ConfigMap
-# metadata:
-# name: airflow-configmap
-# data:
-# known_hosts: |
-# github.com ssh-rsa <...>
-# airflow.cfg: |
-# ...
-# Example: git_ssh_known_hosts_configmap_name = airflow-configmap
-git_ssh_known_hosts_configmap_name =
-
-# To give the git_sync init container credentials via a secret, create a secret
-# with two fields: GIT_SYNC_USERNAME and GIT_SYNC_PASSWORD (example below) and
-# add ``git_sync_credentials_secret = `` to your airflow config under the
-# ``kubernetes`` section
-#
-# Secret Example:
-#
-# .. code-block:: yaml
-#
-# ---
-# apiVersion: v1
-# kind: Secret
-# metadata:
-# name: git-credentials
-# data:
-# GIT_SYNC_USERNAME:
-# GIT_SYNC_PASSWORD:
-git_sync_credentials_secret =
-
-# For cloning DAGs from git repositories into volumes: https://github.com/kubernetes/git-sync
-git_sync_container_repository = k8s.gcr.io/git-sync
-git_sync_container_tag = v3.1.1
-git_sync_init_container_name = git-sync-clone
-git_sync_run_as_user = 65533
-
-# The name of the Kubernetes service account to be associated with airflow workers, if any.
-# Service accounts are required for workers that require access to secrets or cluster resources.
-# See the Kubernetes RBAC documentation for more:
-# https://kubernetes.io/docs/admin/authorization/rbac/
-worker_service_account_name =
-
-# Any image pull secrets to be given to worker pods, If more than one secret is
-# required, provide a comma separated list: secret_a,secret_b
-image_pull_secrets =
-
-# GCP Service Account Keys to be provided to tasks run on Kubernetes Executors
-# Should be supplied in the format: key-name-1:key-path-1,key-name-2:key-path-2
-gcp_service_account_keys =
-
-# Use the service account kubernetes gives to pods to connect to kubernetes cluster.
-# It's intended for clients that expect to be running inside a pod running on kubernetes.
-# It will raise an exception if called from a process not running in a kubernetes environment.
-in_cluster = True
-
-# When running with in_cluster=False change the default cluster_context or config_file
-# options to Kubernetes client. Leave blank these to use default behaviour like ``kubectl`` has.
-# cluster_context =
-# config_file =
-
-# Affinity configuration as a single line formatted JSON object.
-# See the affinity model for top-level key names (e.g. ``nodeAffinity``, etc.):
-# https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.12/#affinity-v1-core
-affinity =
-
-# A list of toleration objects as a single line formatted JSON array
-# See:
-# https://kubernetes.io/docs/reference/generated/kubernetes-api/v1.12/#toleration-v1-core
-tolerations =
-
-# Keyword parameters to pass while calling a kubernetes client core_v1_api methods
-# from Kubernetes Executor provided as a single line formatted JSON dictionary string.
-# List of supported params are similar for all core_v1_apis, hence a single config
-# variable for all apis.
-# See:
-# https://raw.githubusercontent.com/kubernetes-client/python/master/kubernetes/client/apis/core_v1_api.py
-# Note that if no _request_timeout is specified, the kubernetes client will wait indefinitely
-# for kubernetes api responses, which will cause the scheduler to hang.
-# The timeout is specified as [connect timeout, read timeout]
-kube_client_request_args = {{"_request_timeout" : [60,60] }}
-
-# Specifies the uid to run the first process of the worker pods containers as
-run_as_user =
-
-# Specifies a gid to associate with all containers in the worker pods
-# if using a git_ssh_key_secret_name use an fs_group
-# that allows for the key to be read, e.g. 65533
-fs_group =
-
-[kubernetes_node_selectors]
-
-# The Key-value pairs to be given to worker pods.
-# The worker pods will be scheduled to the nodes of the specified key-value pairs.
-# Should be supplied in the format: key = value
-
-[kubernetes_annotations]
-
-# The Key-value annotations pairs to be given to worker pods.
-# Should be supplied in the format: key = value
-
-[kubernetes_environment_variables]
-
-# The scheduler sets the following environment variables into your workers. You may define as
-# many environment variables as needed and the kubernetes launcher will set them in the launched workers.
-# Environment variables in this section are defined as follows
-# `` = ``
-#
-# For example if you wanted to set an environment variable with value `prod` and key
-# ``ENVIRONMENT`` you would follow the following format:
-# ENVIRONMENT = prod
-#
-# Additionally you may override worker airflow settings with the ``AIRFLOW____``
-# formatting as supported by airflow normally.
-
-[kubernetes_secrets]
-
-# The scheduler mounts the following secrets into your workers as they are launched by the
-# scheduler. You may define as many secrets as needed and the kubernetes launcher will parse the
-# defined secrets and mount them as secret environment variables in the launched workers.
-# Secrets in this section are defined as follows
-# `` = =``
-#
-# For example if you wanted to mount a kubernetes secret key named ``postgres_password`` from the
-# kubernetes secret object ``airflow-secret`` as the environment variable ``POSTGRES_PASSWORD`` into
-# your workers you would follow the following format:
-# ``POSTGRES_PASSWORD = airflow-secret=postgres_credentials``
-#
-# Additionally you may override worker airflow settings with the ``AIRFLOW____``
-# formatting as supported by airflow normally.
-
-[kubernetes_labels]
-
-# The Key-value pairs to be given to worker pods.
-# The worker pods will be given these static labels, as well as some additional dynamic labels
-# to identify the task.
-# Should be supplied in the format: ``key = value``
\ No newline at end of file
diff --git a/commitlint.config.js b/commitlint.config.js
deleted file mode 100644
index 28fe5c5..0000000
--- a/commitlint.config.js
+++ /dev/null
@@ -1 +0,0 @@
-module.exports = {extends: ['@commitlint/config-conventional']}
diff --git a/constraints-3.8.txt b/constraints-3.8.txt
new file mode 100644
index 0000000..ff463f9
--- /dev/null
+++ b/constraints-3.8.txt
@@ -0,0 +1,349 @@
+# Editable install with no version control (apache-airflow==1.10.15)
+Babel==2.9.0
+Flask-Admin==1.5.4
+Flask-AppBuilder==2.3.4
+Flask-Babel==1.0.0
+Flask-Bcrypt==0.7.1
+Flask-Caching==1.3.3
+Flask-JWT-Extended==3.25.0
+Flask-Login==0.4.1
+Flask-OpenID==1.3.0
+Flask-SQLAlchemy==2.4.4
+Flask-WTF==0.14.3
+Flask==1.1.2
+GitPython==3.1.11
+JPype1==0.7.1
+JayDeBeApi==1.2.3
+Jinja2==2.11.2
+Mako==1.1.3
+Markdown==2.6.11
+MarkupSafe==1.1.1
+PyHive==0.6.3
+PyJWT==1.7.1
+PyNaCl==1.4.0
+PySmbClient==0.1.5
+PyYAML==5.3.1
+Pygments==2.7.2
+SQLAlchemy-JSONField==0.9.0
+SQLAlchemy-Utils==0.36.8
+SQLAlchemy==1.3.20
+Sphinx==3.3.1
+Unidecode==1.1.1
+WTForms==2.3.3
+Werkzeug==0.16.1
+adal==1.2.5
+aiohttp==3.7.3
+alabaster==0.7.12
+alembic==1.4.3
+amqp==2.6.1
+analytics-python==1.2.9
+ansiwrap==0.8.4
+apispec==1.3.3
+appdirs==1.4.4
+argcomplete==1.12.2
+asn1crypto==1.4.0
+astroid==2.4.2
+async-generator==1.10
+async-timeout==3.0.1
+atlasclient==1.0.0
+attrs==20.3.0
+aws-sam-translator==1.31.0
+aws-xray-sdk==2.6.0
+azure-common==1.1.26
+azure-core==1.9.0
+azure-cosmos==3.2.0
+azure-datalake-store==0.0.51
+azure-identity==1.5.0
+azure-keyvault-certificates==4.2.1
+azure-keyvault-keys==4.3.0
+azure-keyvault-secrets==4.2.0
+azure-keyvault==4.1.0
+azure-mgmt-containerinstance==1.5.0
+azure-mgmt-core==1.2.2
+azure-mgmt-datalake-nspkg==3.0.1
+azure-mgmt-datalake-store==0.5.0
+azure-mgmt-nspkg==3.0.2
+azure-mgmt-resource==15.0.0
+azure-nspkg==3.0.2
+azure-storage-blob==12.6.0
+azure-storage-common==2.1.0
+azure-storage==0.36.0
+backcall==0.2.0
+bcrypt==3.2.0
+beautifulsoup4==4.7.1
+billiard==3.6.3.0
+black==20.8b0
+blinker==1.4
+boto3==1.10.50
+boto==2.49.0
+botocore==1.13.50
+cached-property==1.5.2
+cachetools==4.1.1
+cassandra-driver==3.20.2
+cattrs==1.1.2
+celery==4.4.7
+certifi==2020.11.8
+cffi==1.14.4
+cfgv==3.2.0
+cfn-lint==0.42.0
+cgroupspy==0.1.6
+chardet==3.0.4
+click==6.7
+cloudant==0.5.10
+colorama==0.4.4
+colorlog==4.0.2
+configparser==3.5.3
+coverage==5.3
+croniter==0.3.36
+cryptography==3.2.1
+cx-Oracle==8.0.1
+datadog==0.39.0
+decorator==4.4.2
+defusedxml==0.6.0
+dill==0.3.3
+distlib==0.3.1
+dnspython==1.16.0
+docker-pycreds==0.4.0
+docker==3.7.3
+docopt==0.6.2
+docutils==0.15.2
+ecdsa==0.14.1
+elasticsearch-dsl==5.4.0
+elasticsearch==5.5.3
+email-validator==1.1.2
+entrypoints==0.3
+fastavro==1.2.0
+filelock==3.0.12
+flake8-colors==0.1.9
+flake8==3.8.4
+flaky==3.7.0
+flask-swagger==0.2.14
+flower==0.9.5
+freezegun==1.0.0
+fsspec==0.8.4
+funcsigs==1.0.2
+future-fstrings==1.2.0
+future==0.18.2
+gcsfs==0.7.1
+gitdb==4.0.5
+google-api-core==1.23.0
+google-api-python-client==1.12.8
+google-auth-httplib2==0.0.4
+google-auth-oauthlib==0.4.2
+google-auth==1.23.0
+google-cloud-bigquery-storage==2.1.0
+google-cloud-bigquery==2.4.0
+google-cloud-bigtable==1.6.0
+google-cloud-container==1.0.1
+google-cloud-core==1.4.3
+google-cloud-dlp==1.0.0
+google-cloud-language==1.3.0
+google-cloud-secret-manager==1.0.0
+google-cloud-spanner==1.19.1
+google-cloud-speech==1.3.2
+google-cloud-storage==1.33.0
+google-cloud-texttospeech==1.0.1
+google-cloud-translate==1.7.0
+google-cloud-videointelligence==1.16.1
+google-cloud-vision==1.0.0
+google-crc32c==1.0.0
+google-resumable-media==1.1.0
+googleapis-common-protos==1.52.0
+graphviz==0.15
+grpc-google-iam-v1==0.12.3
+grpcio-gcp==0.2.2
+grpcio==1.33.2
+gunicorn==20.0.4
+hdfs==2.5.8
+hmsclient==0.1.1
+httplib2==0.18.1
+humanize==3.1.0
+hvac==0.10.5
+identify==1.5.10
+idna==2.8
+imagesize==1.2.0
+importlib-metadata==2.1.1
+importlib-resources==1.5.0
+inflection==0.5.1
+ipdb==0.13.4
+ipython-genutils==0.2.0
+ipython==7.19.0
+iso8601==0.1.13
+isodate==0.6.0
+itsdangerous==1.1.0
+jedi==0.17.2
+jira==2.0.0
+jmespath==0.10.0
+json-merge-patch==0.2
+jsondiff==1.1.2
+jsonpatch==1.27
+jsonpickle==1.4.1
+jsonpointer==2.0
+jsonschema==3.2.0
+junit-xml==1.9
+jupyter-client==6.1.7
+jupyter-core==4.7.0
+kombu==4.6.11
+kubernetes==11.0.0
+lazy-object-proxy==1.4.3
+ldap3==2.8.1
+libcst==0.3.14
+lockfile==0.12.2
+marshmallow-enum==1.5.1
+marshmallow-sqlalchemy==0.23.1
+marshmallow==2.21.0
+mccabe==0.6.1
+mock==4.0.2
+mongomock==3.21.0
+more-itertools==8.6.0
+moto==1.3.14
+msal-extensions==0.3.0
+msal==1.6.0
+msrest==0.6.19
+msrestazure==0.6.4
+multi-key-dict==2.0.3
+multidict==5.0.2
+mypy-extensions==0.4.3
+mypy==0.720
+mysqlclient==1.3.14
+natsort==7.1.0
+nbclient==0.5.1
+nbformat==5.0.8
+nest-asyncio==1.4.3
+networkx==2.5
+nodeenv==1.5.0
+nteract-scrapbook==0.4.1
+ntlm-auth==1.5.0
+numpy==1.19.4
+oauthlib==3.1.0
+oscrypto==1.2.1
+packaging==20.7
+pandas-gbq==0.14.1
+pandas==1.1.4
+papermill==2.2.2
+parameterized==0.7.4
+paramiko==2.7.2
+parso==0.7.1
+pathspec==0.8.1
+pbr==5.5.1
+pendulum==1.4.4
+pexpect==4.8.0
+pickleshare==0.7.5
+pinotdb==0.1.1
+pipdeptree==1.0.0
+pluggy==0.13.1
+portalocker==1.7.1
+pre-commit==2.9.2
+presto-python-client==0.7.0
+prison==0.1.3
+prometheus-client==0.8.0
+prompt-toolkit==3.0.8
+proto-plus==1.11.0
+protobuf==3.14.0
+psutil==5.7.3
+psycopg2-binary==2.8.6
+ptyprocess==0.6.0
+py==1.9.0
+pyOpenSSL==20.0.0
+pyarrow==0.17.1
+pyasn1-modules==0.2.8
+pyasn1==0.4.8
+pycodestyle==2.6.0
+pycparser==2.20
+pycryptodomex==3.9.9
+pydata-google-auth==1.1.0
+pydruid==0.5.8
+pyflakes==2.2.0
+pykerberos==1.2.1
+pymongo==3.10.1
+pyparsing==2.4.7
+pyrsistent==0.17.3
+pysftp==0.2.9
+pytest-cov==2.10.1
+pytest-instafail==0.4.2
+pytest-timeouts==1.2.1
+pytest==5.4.3
+python-daemon==2.2.4
+python-dateutil==2.8.1
+python-editor==1.0.4
+python-http-client==3.3.1
+python-jenkins==1.7.0
+python-jose==3.2.0
+python-nvd3==0.15.0
+python-slugify==4.0.1
+python3-openid==3.2.0
+pytz==2020.4
+pytzdata==2020.1
+pywinrm==0.4.1
+pyzmq==20.0.0
+qds-sdk==1.16.1
+redis==3.5.3
+regex==2020.11.13
+requests-futures==0.9.4
+requests-kerberos==0.12.0
+requests-mock==1.8.0
+requests-ntlm==1.1.0
+requests-oauthlib==1.3.0
+requests-toolbelt==0.9.1
+requests==2.23.0
+responses==0.12.1
+rsa==4.6
+s3transfer==0.2.1
+sasl==0.2.1
+sendgrid==5.6.0
+sentinels==1.0.0
+sentry-sdk==0.19.4
+setproctitle==1.2
+six==1.15.0
+slackclient==1.3.2
+smmap==3.0.4
+snakebite-py3==3.0.5
+snowballstemmer==2.0.0
+snowflake-connector-python==2.3.6
+snowflake-sqlalchemy==1.2.4
+soupsieve==2.0.1
+sphinx-argparse==0.2.5
+sphinx-autoapi==1.0.0
+sphinx-copybutton==0.3.1
+sphinx-jinja==1.1.1
+sphinx-rtd-theme==0.5.0
+sphinxcontrib-applehelp==1.0.2
+sphinxcontrib-devhelp==1.0.2
+sphinxcontrib-dotnetdomain==0.4
+sphinxcontrib-golangdomain==0.2.0.dev0
+sphinxcontrib-htmlhelp==1.0.3
+sphinxcontrib-httpdomain==1.7.0
+sphinxcontrib-jsmath==1.0.1
+sphinxcontrib-qthelp==1.0.3
+sphinxcontrib-serializinghtml==1.1.4
+sshpubkeys==3.1.0
+sshtunnel==0.1.5
+tabulate==0.8.7
+tenacity==4.12.0
+text-unidecode==1.3
+textwrap3==0.9.2
+thrift-sasl==0.4.2
+thrift==0.13.0
+toml==0.10.2
+tornado==5.1.1
+tqdm==4.54.0
+traitlets==5.0.5
+typed-ast==1.4.1
+typing-extensions==3.7.4.3
+typing-inspect==0.6.0
+tzlocal==1.5.1
+unicodecsv==0.14.1
+uritemplate==3.0.1
+urllib3==1.25.11
+vertica-python==1.0.0
+vine==1.3.0
+virtualenv==20.2.1
+wcwidth==0.2.5
+websocket-client==0.54.0
+wrapt==1.12.1
+xmltodict==0.12.0
+yamllint==1.25.0
+yarl==1.6.3
+zdesk==2.7.1
+zipp==3.4.0
+zope.deprecation==4.4.0
diff --git a/dags/ods/google_search_console/udfs/google_search.py b/dags/ods/google_search_console/udfs/google_search.py
index 98110a7..a24fd32 100644
--- a/dags/ods/google_search_console/udfs/google_search.py
+++ b/dags/ods/google_search_console/udfs/google_search.py
@@ -1,11 +1,14 @@
import heapq
import os
+from pathlib import Path
import requests
import searchconsole
TOPK = 5
+AIRFLOW_HOME = os.getenv("AIRFLOW_HOME")
+
class GoogleSearchConsoleReporter(object):
def __init__(self):
@@ -27,9 +30,15 @@ def main(self):
self._send_report(report_msg)
def _get_report(self):
+ client_config_path = (
+ Path(AIRFLOW_HOME) / "dags/client_secret_google_search_console.json"
+ )
+ credentials_path = (
+ Path(AIRFLOW_HOME)
+ / "dags/client_secret_google_search_console_serialized.json"
+ )
account = searchconsole.authenticate(
- client_config="/usr/local/airflow/dags/client_secret_google_search_console.json",
- credentials="/usr/local/airflow/dags/client_secret_google_search_console_serialized.json",
+ client_config=client_config_path, credentials=credentials_path,
)
webproperty = account["https://tw.pycon.org/"]
return webproperty.query.range("today", days=-7).dimension("query").get()
diff --git a/dags/ods/kktix_ticket_orders/udfs/bigquery_loader.py b/dags/ods/kktix_ticket_orders/udfs/bigquery_loader.py
index 27aab34..fd9f61b 100644
--- a/dags/ods/kktix_ticket_orders/udfs/bigquery_loader.py
+++ b/dags/ods/kktix_ticket_orders/udfs/bigquery_loader.py
@@ -13,12 +13,14 @@
FROM
`{TABLE}`
""" # nosec
+AIRFLOW_HOME = os.getenv("AIRFLOW_HOME")
def create_table_if_needed() -> None:
client = bigquery.Client(project=os.getenv("BIGQUERY_PROJECT"))
- base_path = Path(__file__).parent.parent
- sql_path = base_path / "sqls" / "create_table.sql"
- sql = sql_path.read_text().format(TABLE)
+ sql_filepath = (
+ Path(AIRFLOW_HOME) / "dags/ods/kktix_ticket_orders/sqls/create_table.sql"
+ )
+ sql = sql_filepath.read_text().format(TABLE)
client.query(sql)
client.query(DEDUPE_SQL)
diff --git a/dags/ods/survey_cake/dags/questionnaire_2_bigquery.py b/dags/ods/survey_cake/dags/questionnaire_2_bigquery.py
index e6c3528..792a1a3 100644
--- a/dags/ods/survey_cake/dags/questionnaire_2_bigquery.py
+++ b/dags/ods/survey_cake/dags/questionnaire_2_bigquery.py
@@ -1,15 +1,18 @@
"""
A crawler which would crawl the openings
"""
+from __future__ import annotations
+
import os
from datetime import datetime, timedelta
from pathlib import Path
-from typing import Dict
from airflow import DAG
from airflow.operators.python_operator import PythonOperator
from ods.survey_cake.udfs.survey_cake_csv_uploader import SurveyCakeCSVUploader
+AIRFLOW_HOME = os.getenv("AIRFLOW_HOME")
+
DEFAULT_ARGS = {
"owner": "davidtnfsh",
"depends_on_past": False,
@@ -27,7 +30,8 @@
)
with dag:
if bool(os.getenv("AIRFLOW_TEST_MODE")):
- FILENAMES: Dict[str, Dict] = {"fixtures/data_questionnaire.csv": {}}
+ filepath = Path(AIRFLOW_HOME) / "dags/fixtures/data_questionnaire.csv"
+ FILENAMES: dict[str, dict] = {str(filepath): {}}
else:
FILENAMES = {
"data_questionnaire.csv": {
diff --git a/dags/ods/survey_cake/udfs/survey_cake_csv_uploader.py b/dags/ods/survey_cake/udfs/survey_cake_csv_uploader.py
index 0d08052..b071d16 100644
--- a/dags/ods/survey_cake/udfs/survey_cake_csv_uploader.py
+++ b/dags/ods/survey_cake/udfs/survey_cake_csv_uploader.py
@@ -4,6 +4,8 @@
from google.cloud import bigquery
+AIRFLOW_HOME = os.getenv("AIRFLOW_HOME")
+
class SurveyCakeCSVUploader:
def __init__(self, filename):
@@ -42,9 +44,8 @@ def _export_dimension_table(question_id_dienstion_table):
for question_id, question in question_id_dienstion_table.items():
writer.writerow((question_id, question, self.year))
- with open(
- Path("/usr/local/airflow/dags") / self.filename, "r", encoding="utf-8-sig"
- ) as csvfile:
+ filepath = Path(AIRFLOW_HOME) / "dags" / self.filename
+ with open(filepath, "r", encoding="utf-8-sig") as csvfile:
rows = csv.reader(csvfile)
# skip header
header = next(iter(rows))
diff --git a/dags/ods/youtube/udfs/youtube_api.py b/dags/ods/youtube/udfs/youtube_api.py
index 15352fe..343ac5e 100644
--- a/dags/ods/youtube/udfs/youtube_api.py
+++ b/dags/ods/youtube/udfs/youtube_api.py
@@ -13,11 +13,13 @@
CHANNEL_ID = "UCHLnNgRnfGYDzPCCH8qGbQw"
MAX_RESULTS = 50
PROJECT = os.getenv("BIGQUERY_PROJECT")
+AIRFLOW_HOME = os.getenv("AIRFLOW_HOME")
def create_table_if_needed():
client = bigquery.Client(project=os.getenv("BIGQUERY_PROJECT"))
- sql = Path("dags/ods/youtube/sqls/create_table.sql").read_text().format(PROJECT)
+ sql_filepath = Path(AIRFLOW_HOME) / "dags/ods/youtube/sqls/create_table.sql"
+ sql = sql_filepath.read_text().format(PROJECT)
client.query(sql)
diff --git a/docker-compose-dev.yml b/docker-compose-dev.yml
new file mode 100644
index 0000000..2d080d8
--- /dev/null
+++ b/docker-compose-dev.yml
@@ -0,0 +1,36 @@
+version: '3.4'
+
+x-docker-common: &docker-common
+ env_file: .env.staging
+ image: pycon-etl
+ build:
+ context: .
+ dockerfile: Dockerfile.test
+ volumes:
+ - airflow-db-volume:/opt/airflow/
+ # you can comment out the following line if you don't have service-account.json
+ - ./service-account.json:/opt/airflow/service-account.json
+ restart: unless-stopped
+ logging:
+ driver: json-file
+ options:
+ max-size: 10m
+
+services:
+ airflow:
+ <<: *docker-common
+ container_name: airflow
+ ports:
+ - "8080:8080"
+ command: webserver
+
+ scheduler:
+ <<: *docker-common
+ container_name: scheduler
+ depends_on:
+ - airflow
+ command: scheduler
+
+volumes:
+ airflow-db-volume:
+ external: true
diff --git a/docker-compose.yml b/docker-compose.yml
new file mode 100644
index 0000000..3fe2950
--- /dev/null
+++ b/docker-compose.yml
@@ -0,0 +1,32 @@
+version: '3.4'
+
+x-docker-common: &docker-common
+ env_file: .env.production
+ image: asia-east1-docker.pkg.dev/pycontw-225217/data-team/pycon-etl:lastest
+ volumes:
+ - ./service-account.json:/opt/airflow/service-account.json
+ - airflow-db-volume:/opt/airflow/
+ restart: unless-stopped
+ logging:
+ driver: json-file
+ options:
+ max-size: 10m
+
+services:
+ airflow:
+ <<: *docker-common
+ container_name: airflow
+ ports:
+ - "8080:8080"
+ command: webserver
+
+ scheduler:
+ <<: *docker-common
+ container_name: scheduler
+ depends_on:
+ - airflow
+ command: scheduler
+
+volumes:
+ airflow-db-volume:
+ external: true
diff --git a/docs/CONTRIBUTING.md b/docs/CONTRIBUTING.md
new file mode 100644
index 0000000..18688f9
--- /dev/null
+++ b/docs/CONTRIBUTING.md
@@ -0,0 +1,79 @@
+# Contributing Guide
+
+## How to Contribute to this Project
+
+1. Clone this repository:
+
+ ```bash
+ git clone https://github.com/pycontw/pycon-etl
+ ```
+
+2. Create a new branch:
+
+ ```bash
+ git checkout -b
+ ```
+
+3. Make your changes.
+
+ > **NOTICE:** We are still using Airflow v1, so please read the official document [Apache Airflow v1.10.15 Documentation](https://airflow.apache.org/docs/apache-airflow/1.10.15/) to ensure your changes are compatible with our current version.
+
+ If your task uses an external service, add the connection and variable in the Airflow UI.
+
+4. Test your changes in your local environment:
+
+ - Ensure the DAG file is loaded successfully.
+ - Verify that the task runs successfully.
+ - Confirm that your code is correctly formatted and linted.
+ - Check that all necessary dependencies are included in `requirements.txt`.
+
+5. Push your branch:
+
+ ```bash
+ git push origin
+ ```
+
+6. Create a Pull Request (PR).
+
+7. Wait for the review and merge.
+
+8. Write any necessary documentation.
+
+## Release Management
+
+Please use [GitLab Flow](https://about.gitlab.com/topics/version-control/what-is-gitlab-flow/); otherwise, you cannot pass Docker Hub CI.
+
+## Dependency Management
+
+Airflow dependencies are managed by `requirements.txt` and `constraints-3.8.txt` via `pip`. It is not recommended to use `poetry` or other tools.
+
+`constraints-3.8.txt` is used to pin the version of the Airflow dependencies, and `requirements.txt` is used to install user-defined dependencies.
+
+Please add or update dependencies in `requirements.txt`. Do not modify `constraints-3.8.txt` unless Airflow is updated.
+
+For more information, refer to the [Airflow Installation Documentation](https://airflow.apache.org/docs/apache-airflow/1.10.15/installation.html).
+
+## Code Convention
+
+### Airflow DAG
+
+- Please refer to [this article](https://medium.com/@davidtnfsh/%E5%A4%A7%E6%95%B0%E6%8D%AE%E4%B9%8B%E8%B7%AF-%E9%98%BF%E9%87%8C%E5%B7%B4%E5%B7%B4%E5%A4%A7%E6%95%B0%E6%8D%AE%E5%AE%9E%E8%B7%B5-%E8%AE%80%E6%9B%B8%E5%BF%83%E5%BE%97-54e795c2b8c) for naming guidelines.
+
+ - Examples:
+ 1. `ods/opening_crawler`: Crawlers written by @Rain. These openings can be used for the recruitment board, which was implemented by @tai271828 and @stacy.
+ 2. `ods/survey_cake`: A manually triggered uploader that uploads questionnaires to BigQuery. The uploader should be invoked after we receive the SurveyCake questionnaire.
+
+- Table name convention:
+ ![img](https://miro.medium.com/max/1400/1*bppuEKMnL9gFnvoRHUO8CQ.png)
+
+### Format
+
+Please use `make format` to format your code before committing, otherwise, the CI will fail.
+
+### Commit Message
+
+It is recommended to use [Commitizen](https://commitizen-tools.github.io/commitizen/).
+
+### CI/CD
+
+Please check the [.github/workflows](.github/workflows) directory for details.
diff --git a/docs/DEPLOYMENT.md b/docs/DEPLOYMENT.md
new file mode 100644
index 0000000..231f184
--- /dev/null
+++ b/docs/DEPLOYMENT.md
@@ -0,0 +1,21 @@
+# Deployment Guide
+
+1. Login to the data team's server:
+ 1. Run: `gcloud compute ssh --zone "asia-east1-b" "data-team" --project "pycontw-225217"`
+ 2. Services:
+ * ETL: `/srv/pycon-etl`
+ * Metabase is located here: `/mnt/disks/data-team-additional-disk/pycontw-infra-scripts/data_team/metabase_server`
+
+2. Pull the latest codebase to this server: `git pull`
+
+3. Add credentials to the `.env.production` file (only needs to be done once).
+
+4. Start the services:
+
+```bash
+# Start production services
+make deploy-prod
+
+# Stop production services
+# make down-prod
+```
\ No newline at end of file
diff --git a/docs/MAINTENANCE.md b/docs/MAINTENANCE.md
new file mode 100644
index 0000000..74774cc
--- /dev/null
+++ b/docs/MAINTENANCE.md
@@ -0,0 +1,29 @@
+# Maintenance Guide
+
+## Disk Space
+
+Currently, the disk space is limited, so please check the disk space before running any ETL jobs.
+
+This section will be deprecated if we no longer encounter out-of-disk issues.
+
+1. Find the largest folders:
+ ```bash
+ du -a /var/lib/docker/overlay2 | sort -n -r | head -n 20
+ ```
+2. Show the folder size:
+ ```bash
+ du -hs xxxx
+ ```
+3. Delete the large folders identified.
+4. Check disk space:
+ ```bash
+ df -h
+ ```
+
+## Token Expiration
+
+Some API tokens might expire, so please check them regularly.
+
+## Year-to-Year Jobs
+
+Please refer to [Dev Data Team - Year to Year Jobs - HackMD](https://hackmd.io/R417olqPQSWnQYY1Oc_-Sw?view) for more details.
diff --git a/entrypoint.sh b/entrypoint.sh
new file mode 100644
index 0000000..f2938d1
--- /dev/null
+++ b/entrypoint.sh
@@ -0,0 +1,43 @@
+#!/bin/bash
+# Exit script on first error
+set -e
+
+# Check if the AIRFLOW_HOME variable is set
+if [ -z "${AIRFLOW_HOME}" ]; then
+ echo 'AIRFLOW_HOME not set'
+ exit 1
+fi
+
+# Create Fernet key if not exists
+if [ -z "${AIRFLOW__CORE__FERNET_KEY}" ]; then
+ echo "Fernet key not set. Generating a new one."
+ export AIRFLOW__CORE__FERNET_KEY=$(python -c 'from cryptography.fernet import Fernet; print(Fernet.generate_key().decode())')
+ echo "Fernet key generated and set."
+ echo "[WARNING] Please save the AIRFLOW__CORE__FERNET_KEY for future use."
+else
+ echo "Fernet key exists."
+fi
+
+# Check if the database exists and initialize it if not
+if [ ! -f "${AIRFLOW_HOME}/airflow.db" ]; then
+ airflow initdb
+ echo 'Database initialized'
+else
+ echo 'Database existed'
+fi
+
+# Check if the GCP service account is provided
+if [ -z "${GOOGLE_APPLICATION_CREDENTIALS}" ]; then
+ echo "No GCP service account provided, set to default path"
+ export GOOGLE_APPLICATION_CREDENTIALS="${AIRFLOW_HOME}/service-account.json"
+fi
+
+# Check if the command is provided
+if [ -z "$1" ]; then
+ echo "No command provided. Usage: $0 {airflow_command}"
+ exit 1
+fi
+
+# Execute the provided Airflow command
+echo "Running command: airflow $@"
+exec airflow "$@"
diff --git a/package-lock.json b/package-lock.json
deleted file mode 100644
index 700f0ec..0000000
--- a/package-lock.json
+++ /dev/null
@@ -1,9302 +0,0 @@
-{
- "name": "python_project_template",
- "version": "1.0.0",
- "lockfileVersion": 2,
- "requires": true,
- "packages": {
- "": {
- "name": "python_project_template",
- "version": "1.0.0",
- "license": "ISC",
- "dependencies": {
- "commitizen": "^4.1.2",
- "cz-conventional-changelog": "^3.1.0",
- "dot-prop": "^5.2.0",
- "husky": "^1.3.1",
- "lint-staged": "^8.1.5",
- "lodash": "^4.17.19",
- "minimist": "^1.2.5"
- },
- "devDependencies": {
- "@commitlint/cli": "^9.1.2",
- "@commitlint/config-conventional": "^8.3.4",
- "cz-emoji": "^1.3.1"
- }
- },
- "node_modules/@babel/code-frame": {
- "version": "7.12.13",
- "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.12.13.tgz",
- "integrity": "sha512-HV1Cm0Q3ZrpCR93tkWOYiuYIgLxZXZFVG2VgK+MBWjUqZTundupbfx2aXarXuw5Ko5aMcjtJgbSs4vUGBS5v6g==",
- "devOptional": true,
- "dependencies": {
- "@babel/highlight": "^7.12.13"
- }
- },
- "node_modules/@babel/helper-validator-identifier": {
- "version": "7.12.11",
- "resolved": "https://registry.npmjs.org/@babel/helper-validator-identifier/-/helper-validator-identifier-7.12.11.tgz",
- "integrity": "sha512-np/lG3uARFybkoHokJUmf1QfEvRVCPbmQeUQpKow5cQ3xWrV9i3rUHodKDJPQfTVX61qKi+UdYk8kik84n7XOw==",
- "devOptional": true
- },
- "node_modules/@babel/highlight": {
- "version": "7.12.13",
- "resolved": "https://registry.npmjs.org/@babel/highlight/-/highlight-7.12.13.tgz",
- "integrity": "sha512-kocDQvIbgMKlWxXe9fof3TQ+gkIPOUSEYhJjqUjvKMez3krV7vbzYCDq39Oj11UAVK7JqPVGQPlgE85dPNlQww==",
- "devOptional": true,
- "dependencies": {
- "@babel/helper-validator-identifier": "^7.12.11",
- "chalk": "^2.0.0",
- "js-tokens": "^4.0.0"
- }
- },
- "node_modules/@babel/runtime": {
- "version": "7.12.13",
- "resolved": "https://registry.npmjs.org/@babel/runtime/-/runtime-7.12.13.tgz",
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- "dependencies": {
- "regenerator-runtime": "^0.13.4"
- }
- },
- "node_modules/@commitlint/cli": {
- "version": "9.1.2",
- "resolved": "https://registry.npmjs.org/@commitlint/cli/-/cli-9.1.2.tgz",
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- "yargs": "^15.1.0"
- },
- "bin": {
- "commitlint": "cli.js"
- },
- "engines": {
- "node": ">=v8.17.0"
- }
- },
- "node_modules/@commitlint/cli/node_modules/@commitlint/execute-rule": {
- "version": "9.1.2",
- "resolved": "https://registry.npmjs.org/@commitlint/execute-rule/-/execute-rule-9.1.2.tgz",
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- },
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- "funding": {
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- }
- },
- "node_modules/@commitlint/cli/node_modules/cosmiconfig": {
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diff --git a/package.json b/package.json
deleted file mode 100644
index 1be5ace..0000000
--- a/package.json
+++ /dev/null
@@ -1,62 +0,0 @@
-{
- "name": "python_project_template",
- "version": "1.0.0",
- "description": "[![Build Status](https://github.com/david30907d/pyproject_template.svg?token=FjZQpfwxUNPpEosXv6sy&branch=master)](https://github.com/david30907d/pyproject_template)",
- "main": "index.js",
- "scripts": {
- "test": "pytest --cov=contrib --cov-fail-under=10 --cov-report=term-missing tests",
- "commit": "git-cz",
- "check": "lint-staged"
- },
- "husky": {
- "hooks": {
- "pre-commit": "lint-staged",
- "commit-msg": "commitlint -E HUSKY_GIT_PARAMS; pip freeze | safety check --full-report --stdin"
- }
- },
- "lint-staged": {
- "tests/*.py": [
- "pytest --cov=dags --cov=contrib --cov-fail-under=10 --cov-report=term-missing"
- ],
- "**/*.py": [
- "isort",
- "black",
- "flake8 --config .flake8",
- "mypy --ignore-missing-imports",
- "bandit",
- "git add"
- ],
- "**/Dockerfile*": [
- "hadolint --ignore DL3008 --ignore DL3013 --ignore DL3018 --ignore DL3002"
- ]
- },
- "repository": {
- "type": "git",
- "url": "git+https://github.com/david30907d/pyproject_template.git"
- },
- "author": "",
- "license": "ISC",
- "bugs": {
- "url": "https://github.com/david30907d/pyproject_template/issues"
- },
- "homepage": "https://github.com/david30907d/pyproject_template#readme",
- "dependencies": {
- "commitizen": "^4.1.2",
- "cz-conventional-changelog": "^3.1.0",
- "dot-prop": "^5.2.0",
- "husky": "^1.3.1",
- "lint-staged": "^8.1.5",
- "lodash": "^4.17.19",
- "minimist": "^1.2.5"
- },
- "devDependencies": {
- "@commitlint/cli": "^9.1.2",
- "@commitlint/config-conventional": "^8.3.4",
- "cz-emoji": "^1.3.1"
- },
- "config": {
- "commitizen": {
- "path": "cz-emoji"
- }
- }
-}
diff --git a/poetry.lock b/poetry.lock
deleted file mode 100644
index f41924d..0000000
--- a/poetry.lock
+++ /dev/null
@@ -1,3307 +0,0 @@
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-[package.extras]
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-
-[[package]]
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-optional = false
-python-versions = ">=3.8"
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-
-[package.dependencies]
-pytz = "*"
-
-[[package]]
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-python-versions = "*"
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- {file = "unicodecsv-0.14.1.tar.gz", hash = "sha256:018c08037d48649a0412063ff4eda26eaa81eff1546dbffa51fa5293276ff7fc"},
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-[[package]]
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-python-versions = ">=3.6"
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-
-[[package]]
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-optional = false
-python-versions = ">=3.8"
-files = [
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-
-[package.extras]
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-h2 = ["h2 (>=4,<5)"]
-socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
-zstd = ["zstandard (>=0.18.0)"]
-
-[[package]]
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-
-[[package]]
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-
-[package.extras]
-dev = ["coverage", "pallets-sphinx-themes", "pytest", "sphinx", "sphinx-issues", "tox"]
-termcolor = ["termcolor"]
-watchdog = ["watchdog"]
-
-[[package]]
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-
-[package.dependencies]
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-
-[package.extras]
-email = ["email-validator"]
-
-[[package]]
-name = "zipp"
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-description = "Backport of pathlib-compatible object wrapper for zip files"
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-
-[package.extras]
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-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
-
-[[package]]
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-version = "4.4.0"
-description = "Zope Deprecation Infrastructure"
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-python-versions = "*"
-files = [
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-
-[package.dependencies]
-setuptools = "*"
-
-[package.extras]
-docs = ["Sphinx"]
-test = ["zope.testrunner"]
-
-[metadata]
-lock-version = "2.0"
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diff --git a/poetry.toml b/poetry.toml
deleted file mode 100644
index 084377a..0000000
--- a/poetry.toml
+++ /dev/null
@@ -1,2 +0,0 @@
-[virtualenvs]
-create = false
diff --git a/pyproject.toml b/pyproject.toml
index 991056c..78671a0 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,41 +1,3 @@
-[tool.poetry]
-name = "pycon-etl"
-version = "0.1.0"
-description = ""
-authors = ["davidtnfsh "]
-
-[tool.poetry.dependencies]
-python = "^3.8.0"
-requests = "^2.26.0"
-apache-airflow = "1.10.13"
-searchconsole = "^0.0.4"
-pydantic = "^1.8.2"
-google-cloud-bigquery = {version = "^2.24.0", python = ">=3.7.1,<3.10"}
-pandas = "^1.3.2"
-pyarrow = "^5.0.0"
-StrEnum = "^0.4.6"
-Flask-OAuthlib = "^0.9.6"
-Flask-OpenID = "1.3.0"
-pygsheets = "^2.0.6"
-# https://github.com/pallets/markupsafe/issues/304
-MarkupSafe = "==2.0.1"
-docutils = "^0.20"
-
-[tool.poetry.dev-dependencies]
-safety = "^1.9.0"
-bandit = "^1.6.2"
-pytest-cov = "^2.8.1"
-black = "^19.10b0"
-mypy = "^0.770"
-pytest = "^5.4.1"
-flake8 = "^3.8.3"
-isort = "^5.6.4"
-
-[build-system]
-requires = ["setuptools", "poetry>=0.12"]
-build-backend = "poetry.masonry.api"
-
-
[tool.black]
line-length = 88
include = '\.pyi?$'
@@ -84,4 +46,4 @@ profile = "black"
'*/virtualenv/*',
'*/virtualenvs/*',
'*/tests/*'
- ]
+ ]
\ No newline at end of file
diff --git a/requirements-dev.txt b/requirements-dev.txt
new file mode 100644
index 0000000..823aace
--- /dev/null
+++ b/requirements-dev.txt
@@ -0,0 +1,8 @@
+bandit
+black
+flake8
+isort
+mypy
+pytest
+pytest-cov
+safety
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..4d73139
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,11 @@
+# Please use pip to manage airflow dependencies.
+apache-airflow==1.10.15
+
+# Editable install with no version specified.
+google-cloud-bigquery
+pandas
+pyarrow
+pydantic<2
+pygsheets
+requests
+searchconsole