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Common utilities for Camptocamp WSGI applications

Project description

# Camptocamp WSGI utilities

This is a python 3 library 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 (enabled by setting the LOG_VIEW_SECRET env var) view (/logging/level)
to change runtime the log levels
* SQL profiler to debug DB performance problems, disabled by default. You must enable it by setting the
SQL_PROFILER_SECRET env var and using the view (/sql_profiler) to switch it ON and OFF. Warning,
it will slow down everything.
* A view to get the version information about the application and the installed packages (/versions.json)
* A framework for implementing a health_check service (/health_check)
* 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](acceptance_tests/app).
To see how to test such an application, look at [acceptance_tests/tests](acceptance_tests/tests).


## Install

The library is available in PYPI:
[https://pypi.python.org/pypi/c2cwsgiutils](https://pypi.python.org/pypi/c2cwsgiutils)

With pip:
```
pip install c2cwsgiutils
```


## 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`.


## Pyramid

A command line (`c2cwsgiutils_run`) is provided to start an HTTP server (gunicorn) with a WSGI application.
By default, it will load the application configured in `/app/production.ini`, but you can change that with
the `C2CWSGIUTILS_CONFIG` environment variable. 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 you WSGI main:

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

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


## 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](acceptance_tests/app/production.ini) for a usage example.

You can enable a view to configure the logging level on a live system using the `LOG_VIEW_SECRET` environment
variable. Then, the current status of a logger can be queried with a GET on
`{C2C_BASE_PATH}/logging/level?secret={LOG_VIEW_SECRET}&name={logger_name}` and can be changed with
`{C2C_BASE_PATH}/logging/level?secret={LOG_VIEW_SECRET}&name={logger_name}&level={level}`

Like all the other views expecting a `secret` parameter, you can pass the secret through the `X-API-Key`
header.


### Request tracking

In order to follow the logs generated by a request accross 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. For example:

```python
requests.get('http://example.com/toto', headers={'X-Request-ID': request.c2c_request_id})
```


## 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

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)

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

```python
from c2cwsgiutils import stats
with stats.timer_context('toto', 'tutu'):
do_something()
```

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

Look at the `c2cwsgiutils_stats_db.py` utility if you want to generate statistics (gauges) about the
row counts.


## SQL profiler

The SQL profiler must be configured with the `SQL_PROFILER_SECRET` environment variable. That enables a view
to query the status of the profiler (`{C2C_BASE_PATH}/sql_profiler?secret={SQL_PROFILER_SECRET}`) or to
enable/disable it (`{C2C_BASE_PATH}/sql_profiler?secret={SQL_PROFILER_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.


## DB sessions

The `c2cwsgiutils.db.setup_session` 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:

```ini
sqlalchemy.url = %(SQLALCHEMY_URL)s
sqlalchemy.pool_recycle = 30
sqlalchemy.pool_size = 5
sqlalchemy.max_overflow = 25

sqlalchemy_slave.url = %(SQLALCHEMY_URL_SLAVE)s
sqlalchemy_slave.pool_recycle = 30
sqlalchemy_slave.pool_size = 5
sqlalchemy_slave.max_overflow = 25
```

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

```python
from c2cwsgiutils.db import setup_session
def init(config):
global DBSession
DBSession = setup_session(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:

```python
from c2cwsgiutils.health_check import HealthCheck

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

```json
{
"status": 500,
"successes": ["db_engine_sqlalchemy", "db_engine_sqlalchemy_slave", "http://localhost/api/hello",
"alembic_app_alembic.ini"],
"failures": {
"custom": {
"message": "I'm not happy"
}
}
}
```

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](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.py [$GIT_TAG] $GIT_HASH`
command line. Usually done in the [Dockerfile](acceptance_tests/app/Dockerfile) of the WSGI application.


## Debugging

To enable the debugging interface, you must set the `DEBUG_VIEW_SECRET` environment variable or the
`c2c.debug_view_secret` variable. Then you can have dumps of a few things:

* every threads' stacktrace: `{C2C_BASE_PATH}/debug/stacks?secret={DEBUG_VIEW_SECRET}`
* memory usage: `{C2C_BASE_PATH}/debug/memory?secret={DEBUG_VIEW_SECRET}&limit=30`

It is possible to automatically reload gunicorn as soon as you change your local python code. For this you need
to have a specially tweaked `docker-compose.yml`:
```yml
services:
api:
environment:
GUNICORN_PARAMS: '-b :80 --threads 10 --timeout 60 --reload'
volumes:
- ./api/somepath:/app/somepath:ro
```
The GUNICORN\_PARAMS has the `--reload` parameter and your local python code is
mounted (read only) into the container.


## CORS

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

```python
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

By default, c2cwsgiutils will 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 disable this by setting `C2C_DISABLE_EXCEPTION_HANDLING` (`c2c.disable_exception_handling`) to "1".

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.disable_exception_handling = 1
```


# JSON pretty print

The standard JSON renderer is replaced by a version that indents the rendered JSON if the `?c2c_pretty`
parameter is present in the request.


## 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)


# 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:

```shell
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](setup.py).
* run `make release` to publish to PYPI.
* Commit and push to master.
* Tag the GIT commit.
* Rebase the `release_${MAJOR_VERSION}` branch to this commit and push the `release_${MAJOR_VERSION}` and
the tag to github. Make sure to do that at the same time so that Jenkins can see the tag when it builds
the branch.

We need the `release_${MAJOR_VERSION}` branch, so that Jenkins can build a new docker image for the major
versions every nights.


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