Repo created

tools/python/airmaps/README.md

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+# airmaps - building of maps using airflow.
+
+## Storage
+
+Repository of result and temporary files.
+Currently, the storage is a webdav server.
+
+## Description of DAGs:
+
+1. Update_planet - updates .o5m planet file.
+
+2. Build_coastline - builds coastline files.
+
+3. Generate_open_source_maps - builds free maps for maps.me
+
+All results will be published on the storage.

tools/python/airmaps/__init__.py

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+import os
+
+from airmaps.instruments import settings
+
+CONFIG_PATH = os.path.join(
+    os.path.dirname(os.path.join(os.path.realpath(__file__))),
+    "var",
+    "etc",
+    "airmaps.ini",
+)
+
+settings.init(CONFIG_PATH)

tools/python/airmaps/dags/build_coastline.py

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+import logging
+import os
+import shutil
+from datetime import timedelta
+
+from airflow import DAG
+from airflow.operators.python_operator import PythonOperator
+from airflow.utils.dates import days_ago
+
+from airmaps.instruments import settings
+from airmaps.instruments import storage
+from airmaps.instruments.utils import get_latest_filename
+from airmaps.instruments.utils import make_rm_build_task
+from airmaps.instruments.utils import put_current_date_in_filename
+from airmaps.instruments.utils import rm_build
+from maps_generator.generator import stages_declaration as sd
+from maps_generator.generator.env import Env
+from maps_generator.generator.env import WORLD_COASTS_NAME
+from maps_generator.maps_generator import run_generation
+
+logger = logging.getLogger("airmaps")
+
+
+DAG = DAG(
+    "Build_coastline",
+    schedule_interval=timedelta(days=1),
+    default_args={
+        "owner": "OMaps",
+        "depends_on_past": True,
+        "start_date": days_ago(0),
+        "email": settings.EMAILS,
+        "email_on_failure": True,
+        "email_on_retry": False,
+        "retries": 0,
+        "retry_delay": timedelta(minutes=5),
+        "priority_weight": 1,
+    },
+)
+
+COASTLINE_STORAGE_PATH = f"{settings.STORAGE_PREFIX}/coasts"
+
+
+def publish_coastline(**kwargs):
+    build_name = kwargs["ti"].xcom_pull(key="build_name")
+    env = Env(build_name=build_name)
+    for name in (f"{WORLD_COASTS_NAME}.geom", f"{WORLD_COASTS_NAME}.rawgeom"):
+        coastline = put_current_date_in_filename(name)
+        latest = get_latest_filename(name)
+        coastline_full = os.path.join(env.paths.coastline_path, coastline)
+        latest_full = os.path.join(env.paths.coastline_path, latest)
+        shutil.move(os.path.join(env.paths.coastline_path, name), coastline_full)
+        os.symlink(coastline, latest_full)
+
+        storage.wd_publish(coastline_full, f"{COASTLINE_STORAGE_PATH}/{coastline}")
+        storage.wd_publish(latest_full, f"{COASTLINE_STORAGE_PATH}/{latest}")
+
+
+def build_coastline(**kwargs):
+    env = Env()
+    kwargs["ti"].xcom_push(key="build_name", value=env.build_name)
+
+    run_generation(
+        env,
+        (
+            sd.StageDownloadAndConvertPlanet(),
+            sd.StageCoastline(use_old_if_fail=False),
+            sd.StageCleanup(),
+        ),
+    )
+    env.finish()
+
+
+BUILD_COASTLINE_TASK = PythonOperator(
+    task_id="Build_coastline_task",
+    provide_context=True,
+    python_callable=build_coastline,
+    on_failure_callback=lambda ctx: rm_build(**ctx),
+    dag=DAG,
+)
+
+
+PUBLISH_COASTLINE_TASK = PythonOperator(
+    task_id="Publish_coastline_task",
+    provide_context=True,
+    python_callable=publish_coastline,
+    dag=DAG,
+)
+
+
+RM_BUILD_TASK = make_rm_build_task(DAG)
+
+
+BUILD_COASTLINE_TASK >> PUBLISH_COASTLINE_TASK >> RM_BUILD_TASK

tools/python/airmaps/dags/build_maps.py

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+import logging
+from datetime import timedelta
+
+from airflow import DAG
+from airflow.operators.python_operator import PythonOperator
+from airflow.utils.dates import days_ago
+
+from airmaps.instruments import settings
+from airmaps.instruments import storage
+from airmaps.instruments.utils import make_rm_build_task
+from airmaps.instruments.utils import run_generation_from_first_stage
+from maps_generator.generator import stages_declaration as sd
+from maps_generator.generator.env import Env
+from maps_generator.generator.env import PathProvider
+from maps_generator.generator.env import get_all_countries_list
+from maps_generator.maps_generator import run_generation
+
+logger = logging.getLogger("airmaps")
+
+
+MAPS_STORAGE_PATH = f"{settings.STORAGE_PREFIX}/maps"
+
+
+class MapsGenerationDAG(DAG):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+
+        build_prolog_task = PythonOperator(
+            task_id="Build_prolog_task",
+            provide_context=True,
+            python_callable=MapsGenerationDAG.build_prolog,
+            dag=self,
+        )
+
+        build_epilog_task = PythonOperator(
+            task_id="Build_epilog_task",
+            provide_context=True,
+            python_callable=MapsGenerationDAG.build_epilog,
+            dag=self,
+        )
+
+        publish_maps_task = PythonOperator(
+            task_id="Publish_maps_task",
+            provide_context=True,
+            python_callable=MapsGenerationDAG.publish_maps,
+            dag=self,
+        )
+
+        rm_build_task = make_rm_build_task(self)
+
+        build_epilog_task >> publish_maps_task >> rm_build_task
+        for country in get_all_countries_list(PathProvider.borders_path()):
+            build_prolog_task >> self.make_mwm_operator(country) >> build_epilog_task
+
+    @staticmethod
+    def get_params(namespace="env", **kwargs):
+        return kwargs.get("params", {}).get(namespace, {})
+
+    @staticmethod
+    def build_prolog(**kwargs):
+        params = MapsGenerationDAG.get_params(**kwargs)
+        env = Env(**params)
+        kwargs["ti"].xcom_push(key="build_name", value=env.build_name)
+        run_generation(
+            env,
+            (
+                sd.StageDownloadAndConvertPlanet(),
+                sd.StageCoastline(),
+                sd.StagePreprocess(),
+                sd.StageFeatures(),
+                sd.StageDownloadDescriptions(),
+            ),
+        )
+
+    @staticmethod
+    def make_build_mwm_func(country):
+        def build_mwm(**kwargs):
+            build_name = kwargs["ti"].xcom_pull(key="build_name")
+            params = MapsGenerationDAG.get_params(**kwargs)
+            params.update({"build_name": build_name, "countries": [country,]})
+            env = Env(**params)
+            # We need to check existing of mwm.tmp. It is needed if we want to
+            # build mwms from part of planet.
+            tmp_mwm_name = env.get_tmp_mwm_names()
+            assert len(tmp_mwm_name) <= 1
+            if not tmp_mwm_name:
+                logger.warning(f"mwm.tmp does not exist for {country}.")
+                return
+
+            run_generation_from_first_stage(env, (sd.StageMwm(),), build_lock=False)
+
+        return build_mwm
+
+    @staticmethod
+    def build_epilog(**kwargs):
+        build_name = kwargs["ti"].xcom_pull(key="build_name")
+        params = MapsGenerationDAG.get_params(**kwargs)
+        params.update({"build_name": build_name})
+        env = Env(**params)
+        run_generation_from_first_stage(
+            env,
+            (
+                sd.StageCountriesTxt(),
+                sd.StageLocalAds(),
+                sd.StageStatistics(),
+                sd.StageCleanup(),
+            ),
+        )
+        env.finish()
+
+    @staticmethod
+    def publish_maps(**kwargs):
+        build_name = kwargs["ti"].xcom_pull(key="build_name")
+        params = MapsGenerationDAG.get_params(**kwargs)
+        params.update({"build_name": build_name})
+        env = Env(**params)
+        subdir = MapsGenerationDAG.get_params(namespace="storage", **kwargs)["subdir"]
+        storage_path = f"{MAPS_STORAGE_PATH}/{subdir}"
+        storage.wd_publish(env.paths.mwm_path, f"{storage_path}/{env.mwm_version}/")
+
+    def make_mwm_operator(self, country):
+        normalized_name = "__".join(country.lower().split())
+        return PythonOperator(
+            task_id=f"Build_country_{normalized_name}_task",
+            provide_context=True,
+            python_callable=MapsGenerationDAG.make_build_mwm_func(country),
+            dag=self,
+        )
+
+
+PARAMS = {"storage": {"subdir": "open_source"}}
+if settings.DEBUG:
+    PARAMS["env"] = {
+        # The planet file in debug mode does not contain Russia_Moscow territory.
+        # It is needed for testing.
+        "countries": ["Cuba", "Haiti", "Jamaica", "Cayman Islands", "Russia_Moscow"]
+    }
+
+OPEN_SOURCE_MAPS_GENERATION_DAG = MapsGenerationDAG(
+    "Generate_open_source_maps",
+    schedule_interval=timedelta(days=7),
+    default_args={
+        "owner": "OMaps",
+        "depends_on_past": True,
+        "start_date": days_ago(0),
+        "email": settings.EMAILS,
+        "email_on_failure": True,
+        "email_on_retry": False,
+        "retries": 0,
+        "retry_delay": timedelta(minutes=5),
+        "priority_weight": 1,
+        "params": PARAMS,
+    },
+)

tools/python/airmaps/dags/update_planet.py

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+import logging
+from datetime import timedelta
+
+from airflow import DAG
+from airflow.operators.python_operator import PythonOperator
+from airflow.utils.dates import days_ago
+
+from airmaps.instruments import settings
+from airmaps.instruments import storage
+from airmaps.instruments.utils import make_rm_build_task
+from maps_generator.generator import stages_declaration as sd
+from maps_generator.generator.env import Env
+from maps_generator.maps_generator import run_generation
+from maps_generator.utils.md5 import md5_ext
+
+logger = logging.getLogger("airmaps")
+
+
+DAG = DAG(
+    "Update_planet",
+    schedule_interval=timedelta(days=1),
+    default_args={
+        "owner": "OMaps",
+        "depends_on_past": True,
+        "start_date": days_ago(0),
+        "email": settings.EMAILS,
+        "email_on_failure": True,
+        "email_on_retry": False,
+        "retries": 0,
+        "retry_delay": timedelta(minutes=5),
+        "priority_weight": 1,
+    },
+)
+
+
+PLANET_STORAGE_PATH = f"{settings.STORAGE_PREFIX}/planet_regular/planet-latest.o5m"
+
+
+def update_planet(**kwargs):
+    env = Env()
+    kwargs["ti"].xcom_push(key="build_name", value=env.build_name)
+
+    if settings.DEBUG:
+        env.add_skipped_stage(sd.StageUpdatePlanet)
+
+    run_generation(
+        env,
+        (
+            sd.StageDownloadAndConvertPlanet(),
+            sd.StageUpdatePlanet(),
+            sd.StageCleanup(),
+        ),
+    )
+    env.finish()
+
+
+def publish_planet(**kwargs):
+    build_name = kwargs["ti"].xcom_pull(key="build_name")
+    env = Env(build_name=build_name)
+    storage.wd_publish(env.paths.planet_o5m, PLANET_STORAGE_PATH)
+    storage.wd_publish(md5_ext(env.paths.planet_o5m), md5_ext(PLANET_STORAGE_PATH))
+
+
+UPDATE_PLANET_TASK = PythonOperator(
+    task_id="Update_planet_task",
+    provide_context=True,
+    python_callable=update_planet,
+    dag=DAG,
+)
+
+
+PUBLISH_PLANET_TASK = PythonOperator(
+    task_id="Publish_planet_task",
+    provide_context=True,
+    python_callable=publish_planet,
+    dag=DAG,
+)
+
+
+RM_BUILD_TASK = make_rm_build_task(DAG)
+
+
+UPDATE_PLANET_TASK >> PUBLISH_PLANET_TASK >> RM_BUILD_TASK

tools/python/airmaps/instruments/settings.py

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+import sys
+from typing import AnyStr
+
+from maps_generator.generator import settings
+
+STORAGE_PREFIX = ""
+
+# Storage settings
+WD_HOST = ""
+WD_LOGIN = ""
+WD_PASSWORD = ""
+
+# Common section
+EMAILS = []
+
+settings.LOGGING["loggers"]["airmaps"] = {
+    "handlers": ["stdout", "file"],
+    "level": "DEBUG",
+    "propagate": True,
+}
+
+
+def get_airmaps_emails(emails: AnyStr):
+    if not emails:
+        return []
+
+    for ch in [",", ";", ":"]:
+        emails.replace(ch, " ")
+
+    return list(filter(None, [e.strpip() for e in emails.join(" ")]))
+
+
+def init(default_settings_path: AnyStr):
+    settings.init(default_settings_path)
+
+    # Try to read a config and to overload default settings
+    cfg = settings.CfgReader(default_settings_path)
+
+    # Storage section
+    global WD_HOST
+    global WD_LOGIN
+    global WD_PASSWORD
+
+    WD_HOST = cfg.get_opt("Storage", "WD_HOST", WD_HOST)
+    WD_LOGIN = cfg.get_opt("Storage", "WD_LOGIN", WD_LOGIN)
+    WD_PASSWORD = cfg.get_opt("Storage", "WD_PASSWORD", WD_PASSWORD)
+
+    # Common section
+    global EMAILS
+    emails = cfg.get_opt("Common", "EMAILS", "")
+    EMAILS = get_airmaps_emails(emails)
+
+    # Import all contains from maps_generator.generator.settings.
+    thismodule = sys.modules[__name__]
+    for name in dir(settings):
+        if not name.startswith("_") and name.isupper():
+            value = getattr(settings, name)
+            setattr(thismodule, name, value)
+
+    global STORAGE_PREFIX
+    if settings.DEBUG:
+        STORAGE_PREFIX = "/tests"

tools/python/airmaps/instruments/storage.py

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+import logging
+
+import webdav.client as wc
+
+from airmaps.instruments import settings
+
+logger = logging.getLogger("airmaps")
+
+WD_OPTIONS = {
+    "webdav_hostname": settings.WD_HOST,
+    "webdav_login": settings.WD_LOGIN,
+    "webdav_password": settings.WD_PASSWORD,
+}
+
+
+def wd_fetch(src, dst):
+    logger.info(f"Fetch form {src} to {dst} with options {WD_OPTIONS}.")
+    client = wc.Client(WD_OPTIONS)
+    client.download_sync(src, dst)
+
+
+def wd_publish(src, dst):
+    logger.info(f"Publish form {src} to {dst} with options {WD_OPTIONS}.")
+    client = wc.Client(WD_OPTIONS)
+    tmp = f"{dst[:-1]}__/" if dst[-1] == "/" else f"{dst}__"
+    client.upload_sync(local_path=src, remote_path=tmp)
+    client.move(remote_path_from=tmp, remote_path_to=dst)

tools/python/airmaps/instruments/utils.py

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+import os
+import shutil
+from datetime import datetime
+from typing import Iterable
+
+from airflow.operators.python_operator import PythonOperator
+
+from maps_generator.generator.env import Env
+from maps_generator.generator.stages import Stage
+from maps_generator.generator.stages import get_stage_name
+from maps_generator.maps_generator import run_generation
+
+
+def put_current_date_in_filename(filename):
+    path, name = os.path.split(filename)
+    parts = name.split(".", maxsplit=1)
+    parts[0] += f"__{datetime.today().strftime('%Y_%m_%d')}"
+    return os.path.join(path, ".".join(parts))
+
+
+def get_latest_filename(filename, prefix=""):
+    path, name = os.path.split(filename)
+    parts = name.split(".", maxsplit=1)
+    assert len(parts) != 0, parts
+    parts[0] = f"{prefix}latest"
+    return os.path.join(path, ".".join(parts))
+
+
+def rm_build(**kwargs):
+    build_name = kwargs["ti"].xcom_pull(key="build_name")
+    env = Env(build_name=build_name)
+    shutil.rmtree(env.build_path)
+
+
+def make_rm_build_task(dag):
+    return PythonOperator(
+        task_id="Rm_build_task",
+        provide_context=True,
+        python_callable=rm_build,
+        dag=dag,
+    )
+
+
+def run_generation_from_first_stage(
+    env: Env, stages: Iterable[Stage], build_lock: bool = True
+):
+    from_stage = get_stage_name(next(iter(stages)))
+    run_generation(env, stages, from_stage, build_lock)

tools/python/airmaps/requirements.txt

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+omim-data-all
+omim-maps_generator
+apache-airflow [postgres]==1.10.10
+psycopg2-binary==2.8.4
+cryptography>=41.0.0
+webdavclient==1.0.8

tools/python/airmaps/requirements_dev.txt

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+-r ../maps_generator/requirements_dev.txt
+apache-airflow [postgres]==1.10.10
+psycopg2-binary==2.8.4
+cryptography>=41.0.0
+webdavclient==1.0.8

tools/python/airmaps/sandbox/.dockerignore

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+./.git*
+./android
+./iphone
+./xcode

tools/python/airmaps/sandbox/README.md

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+# Sandbox
+
+This project can show how airmaps works on your computer.
+
+## Setup
+
+You must have [docker](https://docs.docker.com/get-docker/) and [docker-compose](https://docs.docker.com/compose/install/).
+
+0. Change working directory:
+
+```sh
+$ cd omim/tools/python/airmaps/sandbox
+```
+
+1. Build airmaps service:
+
+```sh
+sandbox$ ./build.sh
+```
+
+2. Create storage(sandbox/storage directory):
+
+```sh
+sandbox$ ./create_storage.sh
+```
+
+Note: May be you need `sudo`, because `./create_storage.sh` to try change an owner of `sandbox/storage/tests` directory.
+
+## Usage
+
+### Starting
+
+0. Change working directory:
+
+```sh
+$ cd omim/tools/python/airmaps/sandbox
+```
+
+1. Run all services:
+
+```sh
+sandbox$ docker-compose up
+```
+
+2. Open http://localhost in your browser.
+
+Note: You can see the results of airmaps working in `sandbox/storage/tests`.
+
+### Stopping
+
+0. Change working directory:
+
+```sh
+$ cd omim/tools/python/airmaps/sandbox
+```
+
+1. Stop all services:
+   Push Ctrl+C and
+
+```sh
+sandbox$ docker-compose down
+```
+
+### Clean
+
+#### Clean storage and intermediate files:
+
+0. Change working directory:
+
+```sh
+$ cd omim/tools/python/airmaps/sandbox
+```
+
+1. Clean storage and intermediate files:
+
+```sh
+sandbox$ ./clean.sh
+```
+
+#### Remove images:
+
+0. Change working directory:
+
+```sh
+$ cd omim/tools/python/airmaps/sandbox
+```
+
+1. Remove images:
+
+```sh
+sandbox$ docker-compose rm
+```

tools/python/airmaps/sandbox/airmaps/Dockerfile

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+FROM python:3.6
+
+ARG TZ=Etc/UTC
+
+WORKDIR /omim/
+
+ADD . .
+
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    cmake \
+    libgl1-mesa-dev \
+    libsqlite3-dev \
+    qt5-default \
+    zlib1g-dev \
+    tzdata \
+    locales-all
+
+RUN ln -fs /usr/share/zoneinfo/$TZ /etc/localtime && \
+    dpkg-reconfigure --frontend noninteractive tzdata
+
+RUN ./tools/unix/build_omim.sh -rs generator_tool
+
+RUN pip install --upgrade pip
+
+RUN pip install werkzeug==0.16.0 \
+    SQLAlchemy==1.3.15 \
+    -r ./tools/python/airmaps/requirements_dev.txt

tools/python/airmaps/sandbox/airmaps/airflow.cfg

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+[core]
+# The folder where your airflow pipelines live, most likely a
+# subfolder in a code repository
+# This path must be absolute
+dags_folder = /omim/tools/python/airmaps/dags
+
+# The folder where airflow should store its log files
+# This path must be absolute
+base_log_folder = /airflow_home/logs
+
+# Airflow can store logs remotely in AWS S3, Google Cloud Storage or Elastic Search.
+# Users must supply an Airflow connection id that provides access to the storage
+# location. If remote_logging is set to true, see UPDATING.md for additional
+# configuration requirements.
+remote_logging = False
+remote_log_conn_id =
+remote_base_log_folder =
+encrypt_s3_logs = False
+
+# Logging level
+logging_level = INFO
+fab_logging_level = WARN
+
+# Logging class
+# Specify the class that will specify the logging configuration
+# This class has to be on the python classpath
+# logging_config_class = my.path.default_local_settings.LOGGING_CONFIG
+logging_config_class =
+
+# Log format
+# Colour the logs when the controlling terminal is a TTY.
+colored_console_log = True
+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
+
+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 = /airflow_home/logs/dag_processor_manager/dag_processor_manager.log
+
+# 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 = system
+
+# The executor class that airflow should use. Choices include
+# SequentialExecutor, LocalExecutor, CeleryExecutor, DaskExecutor, KubernetesExecutor
+executor = LocalExecutor
+
+# The SqlAlchemy connection string to the metadata database.
+# SqlAlchemy supports many different database engine, more information
+# their website
+sql_alchemy_conn = postgresql+psycopg2://postgres:postgres@db:5432/airflow
+
+# 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 = 32
+
+# The number of task instances allowed to run concurrently by the scheduler
+dag_concurrency = 16
+
+# 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 = False
+
+# Where your Airflow plugins are stored
+plugins_folder = /airflow_home/plugins
+
+# Secret key to save connection passwords in the db
+fernet_key = uoTKzPCjhVBsERkDylXY5g1hYeg7OAYjk_a_ek2YMwQ=
+
+# Whether to disable pickling dags
+donot_pickle = False
+
+# How long before timing out a python file import
+dagbag_import_timeout = 30
+
+# How long before timing out a DagFileProcessor, which processes a dag file
+dag_file_processor_timeout = 50
+
+# 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
+
+# Name of handler to read task instance logs.
+# Default to use task handler.
+task_log_reader = task
+
+# 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 backfill -c` or
+# `airflow trigger_dag -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
+
+
+[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
+
+[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
+
+# Default timezone to display all dates in the UI, can be UTC, system, or
+# any IANA timezone string (e.g. Europe/Amsterdam). If left empty the
+# default value of core/default_timezone will be used
+# Example: default_ui_timezone = America/New_York
+default_ui_timezone = system
+
+# 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 =
+web_server_ssl_key =
+
+# Number of seconds the webserver waits before killing gunicorn master that doesn't respond
+web_server_master_timeout = 120
+
+# Number of seconds the gunicorn webserver waits before timing out on a worker
+web_server_worker_timeout = 120
+
+# 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
+secret_key = temporary_key
+
+# Number of workers to run the Gunicorn web server
+workers = 4
+
+# 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 = -
+error_logfile = -
+
+# Expose the configuration file in the web server
+# This is only applicable for the flask-admin based web UI (non FAB-based).
+# In the FAB-based web UI with RBAC feature,
+# access to configuration is controlled by role permissions.
+expose_config = False
+
+# 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
+
+# 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
+enable_proxy_fix = False
+
+# 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
+
+# Send anonymous user activity to your analytics tool
+# analytics_tool = # choose from google_analytics, segment, or metarouter
+# analytics_id = XXXXXXXXXXX
+
+[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
+# Uncomment and set the user/pass settings if you want to use SMTP AUTH
+# smtp_user = airflow
+# smtp_password = airflow
+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 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 = 40
+
+# The maximum and minimum concurrency that will be used when starting workers with the
+# "airflow 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
+# worker_autoscale = 16,12
+
+# 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 = sqla+mysql://airflow:airflow@localhost:3306/airflow
+
+# 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+mysql://airflow:airflow@localhost:3306/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
+# Ex: 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
+
+[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
+#
+#visibility_timeout = 21600
+
+[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
+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 = /airflow_home/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 = 8
+
+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
+
+[ldap]
+# set this to ldaps://<your.ldap.server>:<port>
+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 <dag_id> <task_id> <execution_date> --local -p <pickle_id>'
+# command on a mesos slave
+task_cpu = 1
+
+# Memory in MB required for running one task instance using
+# 'airflow run <dag_id> <task_id> <execution_date> --local -p <pickle_id>'
+# 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.
+# failover_timeout = 604800
+
+# Enable framework authentication for mesos
+# See http://mesos.apache.org/documentation/latest/configuration/
+authenticate = False
+
+# Mesos credentials, if authentication is enabled
+# default_principal = admin
+# default_secret = admin
+
+# 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.
+# docker_image_slave = puckel/docker-airflow
+
+[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)
+airflow_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 =
+# 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
+git_dags_folder_mount_point =
+
+# To get Git-sync SSH authentication set up follow this format
+#
+# airflow-secrets.yaml:
+# ---
+# apiVersion: v1
+# kind: Secret
+# metadata:
+#   name: airflow-secrets
+# data:
+#   # key needs to be gitSshKey
+#   gitSshKey: <base64_encoded_data>
+# ---
+# airflow-configmap.yaml:
+# apiVersion: v1
+# kind: ConfigMap
+# metadata:
+#   name: airflow-configmap
+# data:
+#   known_hosts: |
+#       github.com ssh-rsa <...>
+#   airflow.cfg: |
+#       ...
+#
+# git_ssh_key_secret_name = airflow-secrets
+# git_ssh_known_hosts_configmap_name = airflow-configmap
+git_ssh_key_secret_name =
+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 = <secret_name>` to your airflow config under the kubernetes section
+#
+# Secret Example:
+# apiVersion: v1
+# kind: Secret
+# metadata:
+#   name: git-credentials
+# data:
+#   GIT_SYNC_USERNAME: <base64_encoded_git_username>
+#   GIT_SYNC_PASSWORD: <base64_encoded_git_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 =
+
+# **kwargs 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 in **kwargs 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] }
+
+# Worker pods security context options
+# See:
+#   https://kubernetes.io/docs/tasks/configure-pod-container/security-context/
+
+# 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
+#     <environment_variable_key> = <environment_variable_value>
+#
+# 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__<SECTION>__<KEY>
+# 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
+#     <environment_variable_mount> = <kubernetes_secret_object>=<kubernetes_secret_key>
+#
+# 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__<SECTION>__<KEY>
+# 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

tools/python/airmaps/sandbox/airmaps/airmaps.ini

@@ -0,0 +1,82 @@
+[Main]
+# The path where the planet will be downloaded and the maps are generated.
+MAIN_OUT_PATH: /maps_build
+# If the flag DEBUG is set a special small planet file will be downloaded.
+DEBUG: 1
+
+
+[Developer]
+# The path where the generator_tool will be searched.
+BUILD_PATH: /omim-build-release
+# The path to the project directory omim.
+OMIM_PATH: /omim
+
+
+[Storage]
+# Webdaw settings.
+WD_HOST: webdav
+WD_LOGIN: alice
+WD_PASSWORD: secret1234
+
+
+[Generator tool]
+# The path to the omim/data.
+USER_RESOURCE_PATH: ${Developer:OMIM_PATH}/data
+# Do not change it. This is determined automatically.
+# NODE_STORAGE: map
+
+
+[Osm tools]
+# The path to the osmctools sources.
+OSM_TOOLS_SRC_PATH: ${Developer:OMIM_PATH}/tools/osmctools
+# The path where osmctools will be searched or will be built.
+OSM_TOOLS_PATH: /osmctools
+
+
+[Stages]
+# Run osmupdate tool for planet.
+NEED_PLANET_UPDATE: 0
+
+
+[Logging]
+# The path where maps_generator log will be saved.
+# LOG_FILE_PATH: generation.log
+
+
+[External]
+# The url to the planet file.
+# PLANET_URL:
+# The url to the file with md5 sum of the planet.
+# PLANET_MD5_URL:
+# The base url to WorldCoasts.geom and WorldCoasts.rawgeom (without file name).
+# Files latest_coasts.geom and latest_coasts.rawgeom must be at this URL.
+# For example, if PLANET_COASTS_URL = https://somesite.com/download/
+# The https://somesite.com/download/latest_coasts.geom url will be used to download latest_coasts.geom and
+# the https://somesite.com/download/latest_coasts.rawgeom url will be used to download latest_coasts.rawgeom.
+# PLANET_COASTS_URL:
+# The url to the subway file.
+SUBWAY_URL: https://cdn.organicmaps.app/subway.json
+
+# Urls for production maps generation.
+# UGC_URL:
+# HOTELS_URL:
+# PROMO_CATALOG_CITIES:
+# POPULARITY_URL:
+# FOOD_URL:
+# FOOD_TRANSLATIONS_URL:
+# SRTM_PATH:
+# ISOLINES_PATH:
+# UK_POSTCODES_URL:
+# US_POSTCODES_URL:
+
+
+[Common]
+# Auto detection.
+THREADS_COUNT: 0
+# Emails for mailing.
+# EMAILS:
+
+
+[Stats]
+# Path to rules for calculating statistics by type
+STATS_TYPES_CONFIG: ${Developer:OMIM_PATH}/tools/python/maps_generator/var/etc/stats_types_config.txt

tools/python/airmaps/sandbox/airmaps/run_airmaps_service.sh

@@ -0,0 +1,13 @@
+#!/usr/bin/env bash
+
+export PYTHONPATH=/omim/tools/python
+export AIRFLOW_HOME=/airflow_home
+
+# Initialize the database.
+airflow initdb
+
+# Start the web server, default port is 8880.
+airflow webserver -p 8880 &
+
+# Start the scheduler.
+airflow scheduler

tools/python/airmaps/sandbox/build.sh

@@ -0,0 +1,14 @@
+#!/usr/bin/env bash
+
+BUILD_PATH="$(dirname "$0")"
+OMIM_PATH="$(cd "${OMIM_PATH:-${BUILD_PATH}/../../../..}"; pwd)"
+
+echo "Build airmaps service.."
+
+mv "${OMIM_PATH}/.dockerignore" "${OMIM_PATH}/.dockerignore_" 2> /dev/null
+cp "${BUILD_PATH}/.dockerignore" ${OMIM_PATH}
+
+docker-compose build
+
+rm "${OMIM_PATH}/.dockerignore"
+mv "${OMIM_PATH}/.dockerignore_" "${OMIM_PATH}/.dockerignore" 2> /dev/null

tools/python/airmaps/sandbox/clean.sh

@@ -0,0 +1,10 @@
+#!/usr/bin/env bash
+
+BUILD_PATH="$(dirname "$0")"
+OMIM_PATH="$(cd "${OMIM_PATH:-${BUILD_PATH}/../../../..}"; pwd)"
+
+echo "Cleaning.."
+rm "${OMIM_PATH}/.dockerignore" 2> /dev/null
+mv "${OMIM_PATH}/.dockerignore_" "${OMIM_PATH}/.dockerignore" 2> /dev/null
+
+rm -r "${BUILD_PATH}/storage" 2> /dev/null

tools/python/airmaps/sandbox/create_storage.sh

@@ -0,0 +1,10 @@
+#!/usr/bin/env bash
+
+BUILD_PATH="$(dirname "$0")"
+
+echo "Creating storage.."
+mkdir -p "${BUILD_PATH}/storage/tests/coasts"
+mkdir -p "${BUILD_PATH}/storage/tests/maps/open_source"
+mkdir -p "${BUILD_PATH}/storage/tests/planet_regular"
+
+chown -R www-data:www-data "${BUILD_PATH}/storage/tests"

tools/python/airmaps/sandbox/docker-compose.yml

@@ -0,0 +1,41 @@
+version: "3"
+services:
+  webdav:
+    image: sashgorokhov/webdav
+    container_name: webdav
+    hostname: webdav
+    restart: always
+    environment:
+      USERNAME: alice
+      PASSWORD: secret1234
+    volumes:
+      - ./storage/tests:/media/tests
+
+  db:
+    image: postgres:12.2
+    container_name: db
+    hostname: db
+    restart: always
+    environment:
+      POSTGRES_DB: airflow
+      POSTGRES_USER: postgres
+      POSTGRES_PASSWORD: postgres
+
+  airmaps:
+    build:
+      context: ../../../..
+      dockerfile: ./tools/python/airmaps/sandbox/airmaps/Dockerfile
+      args:
+        - TZ=Europe/Moscow
+    container_name: airmaps
+    hostname: airmaps
+    restart: always
+    links:
+      - webdav
+      - db
+    ports:
+      - "80:8880"
+    command: ./tools/python/airmaps/sandbox/airmaps/run_airmaps_service.sh
+    volumes:
+      - ./airmaps/airflow.cfg:/airflow_home/airflow.cfg
+      - ./airmaps/airmaps.ini:/omim/tools/python/airmaps/var/etc/airmaps.ini

tools/python/airmaps/setup.py

@@ -0,0 +1,36 @@
+#!/usr/bin/env python3
+import os
+import sys
+
+import setuptools
+
+module_dir = os.path.abspath(os.path.dirname(__file__))
+sys.path.insert(0, os.path.join(module_dir, "..", "..", ".."))
+
+from pyhelpers.setup import chdir
+from pyhelpers.setup import get_version
+from pyhelpers.setup import get_requirements
+
+
+with chdir(os.path.abspath(os.path.dirname(__file__))):
+    setuptools.setup(
+        name="omim-airmaps",
+        version=str(get_version()),
+        author="CoMaps",
+        author_email="info@comaps.app",
+        description="This package contains tools for generating maps with Apache Airflow.",
+        url="https://codeberg.org/comaps",
+        package_dir={"airmaps": ""},
+        package_data={"": ["var/**/*"]},
+        packages=[
+            "airmaps",
+            "airmaps.dags",
+            "airmaps.instruments",
+        ],
+        classifiers=[
+            "Programming Language :: Python :: 3",
+            "License :: OSI Approved :: Apache Software License",
+        ],
+        python_requires=">=3.6",
+        install_requires=get_requirements(),
+    )

tools/python/airmaps/var/etc/airmaps.ini.default

@@ -0,0 +1,82 @@
+[Main]
+# The path where the planet will be downloaded and the maps are generated.
+MAIN_OUT_PATH: ~/maps_build
+# If the flag DEBUG is set a special small planet file will be downloaded.
+DEBUG: 1
+
+
+[Developer]
+# The path where the generator_tool will be searched.
+BUILD_PATH: ~/omim-build-release
+# The path to the project directory omim.
+OMIM_PATH: ~/omim
+
+
+[Storage]
+# Webdaw settings.
+# WD_HOST:
+# WD_LOGIN:
+# WD_PASSWORD:
+
+
+[Generator tool]
+# The path to the omim/data.
+USER_RESOURCE_PATH: ${Developer:OMIM_PATH}/data
+# Do not change it. This is determined automatically.
+# NODE_STORAGE: map
+
+
+[Osm tools]
+# The path to the osmctools sources.
+OSM_TOOLS_SRC_PATH: ${Developer:OMIM_PATH}/tools/osmctools
+# The path where osmctools will be searched or will be built.
+OSM_TOOLS_PATH: ~/osmctools
+
+
+[Stages]
+# Run osmupdate tool for planet.
+NEED_PLANET_UPDATE: 0
+
+
+[Logging]
+# The path where maps_generator log will be saved.
+# LOG_FILE_PATH: generation.log
+
+
+[External]
+# The url to the planet file.
+# PLANET_URL:
+# The url to the file with md5 sum of the planet.
+# PLANET_MD5_URL:
+# The base url to WorldCoasts.geom and WorldCoasts.rawgeom (without file name).
+# Files latest_coasts.geom and latest_coasts.rawgeom must be at this URL.
+# For example, if PLANET_COASTS_URL = https://somesite.com/download/
+# The https://somesite.com/download/latest_coasts.geom url will be used to download latest_coasts.geom and
+# the https://somesite.com/download/latest_coasts.rawgeom url will be used to download latest_coasts.rawgeom.
+# PLANET_COASTS_URL:
+# The url to the subway file.
+SUBWAY_URL: https://cdn.organicmaps.app/subway.json
+
+# Urls for production maps generation.
+# UGC_URL:
+# HOTELS_URL:
+# PROMO_CATALOG_CITIES:
+# POPULARITY_URL:
+# FOOD_URL:
+# FOOD_TRANSLATIONS_URL:
+# SRTM_PATH:
+# ISOLINES_PATH:
+# UK_POSTCODES_URL:
+# US_POSTCODES_URL:
+
+
+[Common]
+# Auto detection.
+THREADS_COUNT: 0
+# Emails for mailing.
+# EMAILS:
+
+
+[Stats]
+# Path to rules for calculating statistics by type
+STATS_TYPES_CONFIG: ${Developer:OMIM_PATH}/tools/python/maps_generator/var/etc/stats_types_config.txt