<commit_before>[core]
# The home folder for airflow, default is ~/airflow
airflow_home = /usr/local/airflow

# The folder where your airflow pipelines live, most likely a
# subfolder in a code repository
dags_folder = /usr/local/airflow/dags

# The folder where airflow should store its log files. This location
base_log_folder = /usr/local/airflow/logs

# The executor class that airflow should use. Choices include
# SequentialExecutor, LocalExecutor, CeleryExecutor
executor = CeleryExecutor

# The SqlAlchemy connection string to the metadata database.
# SqlAlchemy supports many different database engine, more information
# their website
sql_alchemy_conn = mysql://{DB_USER}:{DB_PASSWORD}@{DB_URI}/airflow

# The SqlAlchemy pool size is the maximum number of database connections
# in the pool.
sql_alchemy_pool_size = 5

# 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.
sql_alchemy_pool_recycle = 3600

# 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 = 1

# 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 = False

# 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 = /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 while filling the DagBag
dagbag_import_timeout = 30

[webserver]
# The base url of your website as airflow cannot guess what domain or
# cname you are using. This is use in automated emails that
# airflow sends to point links to the right web server
base_url = http://localhost:8080<commit_msg>Tune parallel execution strategy.<commit_after>[core]
# The home folder for airflow, default is ~/airflow
airflow_home = /usr/local/airflow

# The folder where your airflow pipelines live, most likely a
# subfolder in a code repository
dags_folder = /usr/local/airflow/dags

# The folder where airflow should store its log files. This location
base_log_folder = /usr/local/airflow/logs

# The executor class that airflow should use. Choices include
# SequentialExecutor, LocalExecutor, CeleryExecutor
executor = CeleryExecutor

# The SqlAlchemy connection string to the metadata database.
# SqlAlchemy supports many different database engine, more information
# their website
sql_alchemy_conn = mysql://{DB_USER}:{DB_PASSWORD}@{DB_URI}/airflow

# The SqlAlchemy pool size is the maximum number of database connections
# in the pool.
sql_alchemy_pool_size = 5

# 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.
sql_alchemy_pool_recycle = 3600

# 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 = 8

# The number of task instances allowed to run concurrently by the scheduler
dag_concurrency = 8

# Are DAGs paused by default at creation
dags_are_paused_at_creation = False

# The maximum number of active DAG runs per DAG
max_active_runs_per_dag = 1

# 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 = /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 while filling the DagBag
dagbag_import_timeout = 30

[webserver]
# The base url of your website as airflow cannot guess what domain or
# cname you are using. This is use in automated emails that
# airflow sends to point links to the right web server
base_url = http://localhost:8080
{'fraction_non_alphanumeric': 0.04767284229552644, 'fraction_numerical': 0.006778129236330773, 'mean_word_length': 4.756827048114435, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2248808', 'n_tokens_mistral': 1271, 'n_tokens_neox': 1212, 'n_words': 584}