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Common utilities for Camptocamp WSGI applications

Project description

Camptocamp WSGI utilities

This is a Python 3 library (>=3.5) providing common tools for Camptocamp WSGI applications:

  • Provide a small framework for gathering performance statistics about a web application (statsd protocol)
  • Allow to use a master/slave PostgresQL configuration
  • Logging handler for CEE/UDP logs
    • An optional view to change runtime the log levels
  • SQL profiler to debug DB performance problems, disabled by default. Warning, it will slow down everything.
  • A view to get the version information about the application and the installed packages
  • A framework for implementing a health_check service
  • Error handlers to send JSON messages to the client in case of error
  • A cornice service drop in replacement for setting up CORS

Also provide tools for writing acceptance tests:

  • A class that can be used from a py.test fixture to control a composition
  • A class that can be used from a py.text fixture to test a REST API

As an example on how to use it in an application provided by a Docker image, you can look at the test application in acceptance_tests/app. To see how to test such an application, look at acceptance_tests/tests.

Install

Custom Docker image (from PYPI library)

Here we didn't do a minimal install of c2cwsgiutils, but be put in place everything needed to monitor the application in integration and production environment.

The library is available in PYPI: https://pypi.python.org/pypi/c2cwsgiutils

Copy and adapt these template configuration file into your project:

You should install c2cwsgiutils with the tool you use to manage your pip dependencies.

In the Dockerfile you should add the following lines:

# Generate the version file.
RUN c2cwsgiutils-genversion $(git rev-parse HEAD)

CMD ["gunicorn", "--paste=/app/production.ini"]

# Default values for the environment variables
ENV \
    DEVELOPMENT=0 \
    SQLALCHEMY_POOL_RECYCLE=30 \
    SQLALCHEMY_POOL_SIZE=5 \
    SQLALCHEMY_MAX_OVERFLOW=25 \
    SQLALCHEMY_SLAVE_POOL_RECYCLE=30 \
    SQLALCHEMY_SLAVE_POOL_SIZE=5 \
    SQLALCHEMY_SLAVE_MAX_OVERFLOW=25\
    LOG_TYPE=console \
    OTHER_LOG_LEVEL=WARNING \
    GUNICORN_LOG_LEVEL=WARNING \
    GUNICORN_ACCESS_LOG_LEVEL=INFO \
    SQL_LOG_LEVEL=WARNING \
    C2CWSGIUTILS_LOG_LEVEL=WARNING \
    LOG_LEVEL=INFO

Add in your main function.

config.include("c2cwsgiutils.pyramid")
dbsession = c2cwsgiutils.db.init(config, "sqlalchemy", "sqlalchemy_slave")

config.scan(...)

# Initialize the health checks
health_check = c2cwsgiutils.health_check.HealthCheck(config)
health_check.add_db_session_check(dbsession)
health_check.add_alembic_check(dbsession, "/app/alembic.ini", 1)

The related environment variables:

  • DEVELOPMENT: set to 1 to enable the development mode, default is 0.
  • SQLALCHEMY_URL: SQL alchemy URL, like postgresql://user:password@host:port/dbname.
  • SQLALCHEMY_POOL_RECYCLE: The SQL alchemy pool recycle, default is 30.
  • SQLALCHEMY_POOL_SIZE: The SQL alchemy pool size, default is 5.
  • SQLALCHEMY_MAX_OVERFLOW: SQL alchemy max overflow, default is 25.
  • SQLALCHEMY_SLAVE_URL: The SQL alchemy slave (read only) URL, like postgresql://user:password@host:port/dbname.
  • SQLALCHEMY_SLAVE_POOL_RECYCLE: The SQL alchemy slave pool recycle, default is 30.
  • SQLALCHEMY_SLAVE_POOL_SIZE: The SQL alchemy slave pool size, default is 5.
  • SQLALCHEMY_SLAVE_MAX_OVERFLOW: The SQL alchemy slave max overflow, default is 25.
  • GUNICORN_WORKERS: The number of workers, default is 2.
  • GUNICORN_THREADS: The number of threads per worker, default is 10.
  • LOG_TYPE: The types of logs, default is console, should be json on kubernetes to work well with elk.
  • LOG_LEVEL: The application log level, default is INFO.
  • SQL_LOG_LEVEL: The SQL query log level, WARNING: no logs, INFO: logs the queries, DEBUG also logs the results, default is WARNING.
  • GUNICORN_ERROR_LOG_LEVEL: The Gunicorn error log level, default is WARNING.
  • GUNICORN_ACCESS_LOG_LEVEL: The Gunicorn access log level, the logs have the level INFO, default is WARNING.
  • C2CWSGIUTILS_CONFIG: The fallback ini file to use by gunicorn, default is production.ini.
  • C2CWSGIUTILS_LOG_LEVEL: The c2c WSGI utils log level, default is WARNING.
  • OTHER_LOG_LEVEL: The log level for all the other logger, default is WARNING.

Those environment variables can be useful for investigation on production environments.

Docker (deprecated)

Or (deprecated) as a base Docker image: camptocamp/c2cwsgiutils:release_5 or ghcr.io/camptocamp/c2cwsgiutils:release_5

If you need an image with a smaller foot print, use the tags prefixed with -light. Those are without GDAL and without the build tools.

We deprecate the Docker image because:

  • The project wants to choose the base image.
  • The project pin different versions of the dependencies.

General config

In general, configuration can be done both with environment variables (taken first) or with entries in the production.ini file.

You can configure the base URL for accessing the views provided by c2cwsgiutils with an environment variable named C2C_BASE_PATH or in the production.ini file with a property named c2c.base_path.

A few REST APIs are added and can be seen with this URL: {C2C_BASE_PATH}.

Some APIs are protected by a secret. This secret is specified in the C2C_SECRET variable or c2c.secret property. It is either passed as the secret query parameter or the X-API-Key header. Once accessed with a good secret, a cookie is stored and the secret can be omitted.

An alternative of using C2C_SECRET is to use an authentication on GitHub, create the GitHub application.

Then it will redirect the user to the github authentication form if not already authenticated (using C2C_AUTH_GITHUB_CLIENT_ID, C2C_AUTH_GITHUB_CLIENT_SECRET and C2C_AUTH_GITHUB_SCOPE).

Then we will check if the user is allowed to access to the application, for that we check if the user has enough right on a GitHub repository (using C2C_AUTH_GITHUB_REPOSITORY and C2C_AUTH_GITHUB_REPOSITORY_ACCESS_TYPE).

Finally we store the session information in an encrypted cookie (using C2C_AUTH_SECRET and C2C_AUTH_COOKIE).

Configuration details:

Using the environment variable C2C_AUTH_GITHUB_REPOSITORY or the config key c2c.auth.github.repository to define the related GitHub repository (required).

Using the environment variable C2C_AUTH_GITHUB_ACCESS_TYPE or the config key c2c.auth.github.access_type to define the type of required access can be pull, push or admin (default is push)

Using the environment variable C2C_AUTH_GITHUB_CLIENT_ID or the config key c2c.auth.github.client_id to define the GitHub application ID (required)

Using the environment variable C2C_AUTH_GITHUB_CLIENT_SECRET or the config key c2c.auth.github.client_secret to define the GitHub application secret (required)

Using the environment variable C2C_AUTH_GITHUB_SCOPE or the config key c2c.auth.github.scope to define the GitHub scope (default is repo), see GitHub documentation

Using the environment variable C2C_AUTH_GITHUB_SECRET or the config key c2c.auth.github.auth.secret to define the used secret for JWD encryption (required, with a length at least of 16)

Using the environment variable C2C_AUTH_GITHUB_COOKIE or the config key c2c.auth.github.auth.cookie to define the used cookie name (default is c2c-auth-jwt)

Using the environment variable C2C_AUTH_GITHUB_AUTH_URL or the config key c2c.auth.github.auth_url to define the GitHub auth URL (default is https://github.com/login/oauth/authorize)

Using the environment variable C2C_AUTH_GITHUB_TOKEN_URL or the config key c2c.auth.github.token_url to define the GitHub auth URL (default is https://github.com/login/oauth/access_token)

Using the environment variable C2C_AUTH_GITHUB_USER_URL or the config key c2c.auth.github.user_url to define the GitHub auth URL (default is https://api.github.com/user)

Using the environment variable C2C_AUTH_GITHUB_REPO_URL or the config key c2c.auth.github.repo_url to define the GitHub auth URL (default is https://api.github.com/repo)

Using the environment variable C2C_AUTH_GITHUB_PROXY_URL or the config key c2c.auth.github.auth.proxy_url to define a redirect proxy between GitHub and our application to be able to share an OAuth2 application on GitHub (default is no proxy). Made to work with this proxy.

Using the environment variable C2C_USE_SESSION or the config key c2c.use_session to define if we use a session. Currently, we can use the session to store a state, used to prevent CSRF, during OAuth2 login (default is false)

Pyramid

All the environment variables are usable in the configuration file using stuff like %(ENV_NAME)s.

To enable most of the features of c2cwsgiutils, you need to add this line to your WSGI main:

import c2cwsgiutils.pyramid
config.include(c2cwsgiutils.pyramid.includeme)

Error catching views will be put in place to return errors as JSON.

A custom loader is provided to run pyramid scripts against configuration files containing environment variables:

proutes c2c://production.ini      # relative path
proutes c2c:///app/production.ini # absolute path

A filter is automatically installed to handle the HTTP headers set by common proxies and have correct values in the request object (request.client_addr, for example). This filter is equivalent to what the PasteDeploy#prefix (minus the prefix part) does, but supports newer headers as well (Forwarded). If you need to prefix your routes, you can use the route_prefix parameter of the Configurator constructor.

Logging

Two new logging backends are provided:

  • c2cwsgiutils.pyramid_logging.PyramidCeeSysLogHandler: to send @cee formatted logs to syslog through UDP.
  • c2cwsgiutils.pyramid_logging.JsonLogHandler: to output (on stdout or stderr) JSON formatted logs.

Look at the logging configuration part of acceptance_tests/app/production.ini for paste and commands line.

The logging configuration is imported automatically by gunicorn, it is possible to visualize the dict config by setting the environment variable DEBUG_LOGCONFIG=1.

You can enable a view to configure the logging level on a live system using the C2C_LOG_VIEW_ENABLED environment variable. Then, the current status of a logger can be queried with a GET on {C2C_BASE_PATH}/logging/level?secret={C2C_SECRET}&name={logger_name} and can be changed with {C2C_BASE_PATH}/logging/level?secret={C2C_SECRET}&name={logger_name}&level={level}. Overrides are stored in Redis, if C2C_REDIS_URL (c2c.redis_url) or C2C_REDIS_SENTINELS is configured.

Database maintenance

You can enable a view to force usage of the slave engine using the C2C_DB_MAINTENANCE_VIEW_ENABLED environment variable. Then, the database can be made "readonly" with {C2C_BASE_PATH}/db/maintenance?secret={C2C_SECRET}&readonly=true. The current state is stored in Redis, if C2C_REDIS_URL (c2c.redis_url) or C2C_REDIS_SENTINELS is configured.

Request tracking

In order to follow the logs generated by a request across all the services (think separate processes), c2cwsgiutils tries to flag averything with a request ID. This field can come from the input as request headers (X-Request-ID, X-Correlation-ID, Request-ID or X-Varnish) or will default to a UUID. You can add an additional request header as source for that by defining the C2C_REQUEST_ID_HEADER environment variable (c2c.request_id_header).

In JSON logging formats, a request_id field is automatically added.

You can enable (disabled by default since it can have a cost) the flagging of the SQL requests as well by setting the C2C_SQL_REQUEST_ID environment variable (or c2c.sql_request_id in the .ini file). This will use the application name to pass along the request id. If you do that, you must include the application name in the PostgreSQL logs by setting log_line_prefix to something like "%a " (don't forget the space).

Then, in your application, it is recommended to transmit the request ID to the external REST APIs. Use the X-Request-ID HTTP header, for example. The value of the request ID is accessible through an added c2c_request_id attribute on the Pyramid Request objects. The requests module is patched to automatically add this header.

The requests module is also patched to monitor requests done without timeout. In that case, you can configure a default timeout with the C2C_REQUESTS_DEFAULT_TIMEOUT environment variable (c2c.requests_default_timeout). If no timeout and no default is specified, a warning is issued.

Metrics

To enable and configure the metrics framework, you can use:

  • STATS_VIEW (c2c.stats_view): if defined, will enable the stats view {C2C_BASE_PATH}/stats.json
  • STATSD_ADDRESS (c2c.statsd_address): if defined, send stats to the given statsd server
  • STATSD_PREFIX (c2c.statsd_prefix): prefix to add to every metric names
  • STATSD_USE_TAGS: If true, automatic metrics will use tags
  • STATSDTAG{tag_name}: To set a global tag for the service

If enabled, some metrics are automatically generated:

  • {STATSD_PREFIX}.route.{verb}.{route_name}.{status}: The time to process a query (includes rendering)
  • {STATSD_PREFIX}.render.{verb}.{route_name}.{status}: The time to render a query
  • {STATSD_PREFIX}.sql.{query}: The time to execute the given SQL query (simplified and normalized)
  • {STATSD_PREFIX}.requests.{scheme}.{hostname}.{port}.{verb}.{status}: The time to execute HTTP requests to outside services (only the time between the start of sending of the request and when the header is back with a chunk of the body)
  • {STATSD_PREFIX}.redis.{command}: The time to execute the given Redis command

You can manually measure the time spent on something like that:

from c2cwsgiutils import stats
with stats.timer_context(['toto', 'tutu']):
    do_something()

It will only add a timer event in case of success. If you want to measure both success and failures, do that:

from c2cwsgiutils import stats
with stats.outcome_timer_context(['toto', 'tutu']):
    do_something()

Other functions exists to generate metrics. Look at the c2cwsgiutils.stats module.

Look at the c2cwsgiutils-stats-db utility if you want to generate statistics (gauges) about the row counts.

SQL profiler

The SQL profiler must be configured with the C2C_SQL_PROFILER_ENABLED environment variable. That enables a view to query the status of the profiler ({C2C_BASE_PATH}/sql_profiler?secret={C2C_SECRET}) or to enable/disable it ({C2C_BASE_PATH}/sql_profiler?secret={C2C_SECRET}&enable={1|0}).

If enabled, for each SELECT query sent by SQLAlchemy, another query it done with EXPLAIN ANALYZE prepended to it. The results are sent to the c2cwsgiutils.sql_profiler logger.

Don't enable that on a busy production system. It will kill your performances.

Profiler

C2cwsgiutils provide an easy way to profile an application:

With a decorator:

from c2cwsgiutils.profile import Profiler

@Profile('/my_file.prof')
my_function():
    ...

Or with the with statement:

from c2cwsgiutils.profile import Profiler

with Profile('/my_file.prof'):
    ...

Then open your file with SnakeViz:

docker cp container_name:/my_file.prof .
pip install --user snakeviz
snakeviz my_file.prof

DB sessions

The c2cwsgiutils.db.init allows you to setup a DB session that has two engines for accessing a master/slave PostgresQL setup. The slave engine (read only) will be used automatically for GET and OPTIONS requests and the master engine (read write) will be used for the other queries.

To use that, your production.ini must look like that:

sqlalchemy.url = %(SQLALCHEMY_URL)s
sqlalchemy.pool_recycle = %(SQLALCHEMY_POOL_RECYCLE)s
sqlalchemy.pool_size = %(SQLALCHEMY_POOL_SIZE)s
sqlalchemy.max_overflow = %(SQLALCHEMY_MAX_OVERFLOW)s

sqlalchemy_slave.url = %(SQLALCHEMY_SLAVE_URL)s
sqlalchemy_slave.pool_recycle = %(SQLALCHEMY_SLAVE_POOL_RECYCLE)s
sqlalchemy_slave.pool_size = %(SQLALCHEMY_SLAVE_POOL_SIZE)s
sqlalchemy_slave.max_overflow = %(SQLALCHEMY_SLAVE_MAX_OVERFLOW)s

And your code that initializes the DB connection must look like that:

import c2cwsgiutils.db

def main(config):
    c2cwsgiutils.db.init(config, 'sqlalchemy', 'sqlalchemy_slave', force_slave=[
        "POST /api/hello"
    ])[0]

You can use the force_slave and force_master parameters to override the defaults and force a route to use the master or the slave engine.

Health checks

To enable health checks, you must add some setup in your WSGI main (usually after the DB connections are setup). For example:

from c2cwsgiutils.health_check import HealthCheck

def custom_check(request):
    global not_happy
    if not_happy:
        raise Exception("I'm not happy")
    return "happy"

health_check = HealthCheck(config)
health_check.add_db_session_check(models.DBSession, at_least_one_model=models.Hello)
health_check.add_url_check('http://localhost:8080/api/hello')
health_check.add_custom_check('custom', custom_check, 2)
health_check.add_alembic_check(models.DBSession, '/app/alembic.ini', 3)

Then, the URL {C2C_BASE_PATH}/health_check?max_level=3 can be used to run the health checks and get a report looking like that (in case of error):

{
  "status": 500,
  "successes": {
    "db_engine_sqlalchemy": { "timing": 0.002 },
    "db_engine_sqlalchemy_slave": { "timing": 0.003 },
    "http://localhost/api/hello": { "timing": 0.01 },
    "alembic_app_alembic.ini_alembic": { "timing": 0.005, "result": "4a8c1bb4e775" }
  },
  "failures": {
    "custom": {
      "message": "I'm not happy",
      "timing": 0.001
    }
  }
}

The levels are:

  • 0: Don't add checks at this level. This max_level is used for doing a simple ping.
  • 1: Checks for anything vital for the usefulness of the service (DB, redis, ...). This is the max_level set by default and used by load balancers to determine if the service is alive.
  • >=2: Use those at your convenience. Pingdom and CO are usually setup at max_level=100. So stay below.

The URL {C2C_BASE_PATH}/health_check?checks=<check_name> can be used to run the health checks on some checks, coma separated list.

When you instantiate the HealthCheck class, two checks may be automatically enabled:

  • If redis is configured, check that redis is reachable.
  • If redis is configured and the version information is available, check that the version matches across all instances.

Look at the documentation of the c2cwsgiutils.health_check.HealthCheck class for more information.

SQLAlchemy models graph

A command is provided that can generate Doxygen graphs of an SQLAlchemy ORM model. See acceptance_tests/app/models_graph.py how it's used.

Version information

If the /app/versions.json exists, a view is added ({C2C_BASE_PATH}/versions.json) to query the current version of a app. This file is generated by calling the c2cwsgiutils-genversion [$GIT_TAG] $GIT_HASH command line. Usually done in the Dockerfile of the WSGI application.

Metrics

The path /metrics provide some metrics for Prometheus. By default we have the smap pss, but we can easily add the rss, size or your custom settings:

Example:

from import c2cwsgiutils.metrics import add_provider, Provider, MemoryMapProvider

class CustomProvider(Provider):
    def __init__(self):
        super().__init__("my_metrics", "My Metric")

    def get_data(self):
        return [({'metadata_key': 'matadata_value'}, metrics_value)]

add_provider(MemoryMapProvider('rss'))
add_provider(CustomProvider())

Custom scripts

To have the application initialized in a script you should use the c2cwsgiutils.setup_process.bootstrap_application_from_options function.

Example of main function:

def main() -> None:
    parser = argparse.ArgumentParser(description="My scrypt.")
    # Add your argument here
    c2cwsgiutils.setup_process.fill_arguments(parser)
    args = parser.parse_args()
    env = c2cwsgiutils.setup_process.bootstrap_application_from_options(args)
    settings = env["registry"].settings

    # Add your code here

If you need an access to the database you should add:

    engine = c2cwsgiutils.db.get_engine(settings)
    session_factory = c2cwsgiutils.db.get_session_factory(engine)
    with transaction.manager:
        # Add your code here

If you need the database connection without the application context, you can replace:

    env = c2cwsgiutils.setup_process.bootstrap_application_from_options(args)
    settings = env["registry"].settings

by:

    loader = pyramid.scripts.common.get_config_loader(args.config_uri)
    loader.setup_logging(parse_vars(args.config_vars) if args.config_vars else None)
    settings = loader.get_settings()

Debugging

To enable the debugging interface, you must set the C2C_DEBUG_VIEW_ENABLED environment variable. Then you can have dumps of a few things:

  • every threads' stacktrace: {C2C_BASE_PATH}/debug/stacks?secret={C2C_SECRET}
  • memory usage: {C2C_BASE_PATH}/debug/memory?secret={C2C_SECRET}&limit=30&analyze_type=builtins.dict&python_internals_map=false
  • object ref: {C2C_BASE_PATH}/debug/show_refs.dot?secret={C2C_SECRET}&analyze_type=gunicorn.app.wsgiapp.WSGIApplication&analyze_id=12345&max_depth=3&too_many=10&filter=1024&no_extra_info&backrefs analyze_type and analyze_id should not ve used toogether, you can use it like:
    curl "<URL>" > /tmp/show_refs.dot
    dot -Lg -Tpng /tmp/show_refs.dot > /tmp/show_refs.png
    
  • memory increase when calling another API: {C2C_BASE_PATH}/debug/memory_diff?path={path_info}&secret={C2C_SECRET}&limit=30&no_warmup
  • sleep the given number of seconds (to test load balancer timeouts): {C2C_BASE_PATH}/debug/sleep?secret={C2C_SECRET}&time=60.2
  • see the HTTP headers received by WSGI: {C2C_BASE_PATH}/debug/headers?secret={C2C_SECRET}&status=500
  • return an HTTP error: {C2C_BASE_PATH}/debug/error?secret={C2C_SECRET}&status=500

To ease local development, the views are automatically reloaded when files change. In addition, the filesystem is mounted by the docker-compose.override.yaml file. Make sure not to use such file / mechanism in production.

Broadcast

Some c2cwsgiutils APIs effect or query the state of the WSGI server. Since only one process out of the 5 (by default) time the number of servers gets a query, only this one will be affected. To avoid that, you can configure c2cwsgiutils to use Redis pub/sub to broadcast those requests and collect the answers.

The impacted APIs are:

  • {C2C_BASE_PATH}/debug/stacks
  • {C2C_BASE_PATH}/debug/memory
  • {C2C_BASE_PATH}/logging/level
  • {C2C_BASE_PATH}/sql_profiler

The configuration parameters are:

  • C2C_REDIS_URL (c2c.redis_url): The URL to the Redis single instance to use
  • C2C_REDIS_OPTIONS: The Redis options, comma separated list of <key>=<value>, the value is parsed as YAML
  • C2C_REDIS_SENTINELS: The coma separated list of Redis host:port sentinel instances to use
  • C2C_REDIS_SERVICENAME: The redis service name in case of using sentinels
  • C2C_REDIS_DB: The redis database number in case of using sentinels
  • C2C_BROADCAST_PREFIX (c2c.broadcast_prefix): The prefix to add to the channels being used (must be different for 2 different services)

If not configured, only the process receiving the request is impacted.

CORS

To have CORS compliant views, define your views like that:

from c2cwsgiutils import services
hello_service = services.create("hello", "/hello", cors_credentials=True)

@hello_service.get()
def hello_get(request):
    return {'hello': True}

Exception handling

c2cwsgiutils can install exception handling views that will catch any exception raised by the application views and will transform it into a JSON response with a HTTP status corresponding to the error.

You can enable this by setting C2C_ENABLE_EXCEPTION_HANDLING (c2c.enable_exception_handling) to "1".

In development mode (DEVELOPMENT=1), all the details (SQL statement, stacktrace, ...) are sent to the client. In production mode, you can still get them by sending the secret defined in C2C_SECRET in the query.

If you want to use pyramid_debugtoolbar, you need to disable exception handling and configure it like that:

pyramid.includes =
    pyramid_debugtoolbar
debugtoolbar.enabled = true
debugtoolbar.hosts = 0.0.0.0/0
debugtoolbar.intercept_exc = debug
debugtoolbar.show_on_exc_only = true
c2c.enable_exception_handling = 0

JSON pretty print

Some JSON renderers are available:

  • json: the normal JSON renderer (default).
  • fast_json: a faster JSON renderer using ujson.
  • cornice_json: the normal JSON renderer wrapped around cornice CorniceRenderer.
  • cornice_fast_json: a faster JSON renderer wrapped around cornice CorniceRenderer.

Both pretty prints the rendered JSON. While this adds significant amount of whitespace, the difference in bytes transmitted on the network is negligible thanks to gzip compression.

The fast_json renderer is using ujson which is faster, but doesn't offer the ability to change the rendering of some types (the default parameter of json.dumps). This will interact badly with papyrus and such.

The cornice versions should be used to avoid the "'JSON' object has no attribute 'render_errors'" error.

Sentry integration

The stacktraces can be sent to a sentry.io service for collection. To enable it, you must set the SENTRY_URL (c2c.sentry_url) to point the the project's public DSN.

A few other environment variables can be used to tune the info sent with each report:

  • SENTRY_EXCLUDES (c2c.sentry.excludes): list of loggers (colon separated, without spaces) to exclude for sentry
  • GIT_HASH (c2c.git_hash): will be used for the release
  • SENTRY_CLIENT_RELEASE: If not equal to "latest", will be taken for the release instead of the GIT_HASH
  • SENTRY_CLIENT_ENVIRONMENT: the environment (dev, int, prod, ...)
  • SENTRY_CLIENT_IGNORE_EXCEPTIONS: list (coma separated) of exceptions to ignore (defaults to SystemExit)
  • SENTRY_TAG_...: to add other custom tags
  • SENTRY_LEVEL: starting from what logging level to send events to Sentry (defaults to ERROR)
  • SENTRY_TRACES_SAMPLE_RATE: The percentage of events to send to sentry in order to compute the performance. Value between 0 and 1, default is 0.

Developer info

You will need docker (>=1.12.0), docker-compose (>=1.10.0) and make installed on the machine to play with this project. Check available versions of docker-engine with apt-get policy docker-engine and eventually force install the up-to-date version using a command similar to apt-get install docker-engine=1.12.3-0~xenial.

To lint and test everything, run the following command:

make

Make sure you are strict with the version numbers:

  • bug fix version change: Nothing added, removed or changed in the API and only bug fix version number changes in the dependencies
  • minor version change: The API must remain backward compatible and only minor version number changes in the dependencies
  • major version change: The API and the dependencies are not backward compatible

To make a release:

  • Change the the version in setup.py.
  • Commit and push to master.
  • Tag the GIT commit.
  • Add the new branch name in the .github/workflows/rebuild.yaml and .github/workflows/audit.yaml files.

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5.1.0

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