Metadata-Version: 1.1
Name: django-mongolog
Version: 0.9.3
Summary: A simple mongo based log handler for python/django
Home-page: https://github.com/gnulnx/django-mongolog
Author: John Furr
Author-email: john.furr@gmail.com
License: GPL V3
Download-URL: https://github.com/gnulnx/django-mongolog/tree/0.9.3
Description: MongoLog 
        ========
        .. image:: http://pepy.tech/badge/django-mongolog
            :target: http://pepy.tech/count/django-mongolog
        
        MongoLog is a simple Mongo based log handler that can be easly used
        with standard python/django logging.
        
        Please visit the `MongoLog Users Group <https://groups.google.com/forum/#!forum/mongolog-users>`_ with any questions/suggestions.   Thanks.
        
        .. image:: https://travis-ci.org/gnulnx/django-mongolog.svg?branch=master
            :target: https://travis-ci.org/gnulnx/django-mongolog
            
        .. image:: https://coveralls.io/repos/gnulnx/django-mongolog/badge.svg?branch=master&service=github 
            :target: https://coveralls.io/github/gnulnx/django-mongolog?branch=master
        
        .. image:: https://api.codacy.com/project/badge/grade/d8d4eaa24bbe4ae5afe608210e4b8d28
            :target: https://www.codacy.com/app/gnulnx/django-mongolog
         
        
        Quick start
        ----------- 
        
        1. Add "mongolog" to your INSTALLED_APPS like this
            .. code:: python
        
                INSTALLED_APPS = (
                    ...
                    'mongolog',
                )
        
        2. Add the SimpleMongoLogHandler to your LOGGING config.  
            .. code:: python
        
                LOGGING = {
                    'version': 1,
                    'handlers': {
                        'mongolog': {
                            'level': 'DEBUG',
                            'class': 'mongolog.SimpleMongoLogHandler',
                            
                            # Set the connection string to the mongo instance.  
                            'connection': 'mongodb://localhost:27017',
                            
                            # define mongo collection the log handler should use.  Default is mongolog
                            # This is useful if you want different handlers to use different collections
                            'collection': 'mongolog' 
                        },
                    },
                    # Define a logger for your handler.  We are using the root '' logger in this case
                    'loggers': {
                        '': {
                            'handlers': ['mongolog'],
                            'level': 'DEBUG',
                            'propagate': True
                        },
                    },
                }
        
        3) Start your management shell::
        
            ./manage.py shell
        
        4) Create a couple of log entries
            .. code:: python
            
                import logging
                import pymongo
                logger = logging.getLogger(__name__)
        
            One of the cool things about mongolog is that it can log complex data structures
            in a way that makes them both human parsable and queryable.  So for instance if 
            we create the following log message:
        
            .. code:: python
        
                
                # Pro Tip: You can copy and paste all of this
                
                LOG_MSG = {
                    'test': True,  
                    'test class': 'TestBaseMongoLogHandler',
                    'Life': {
                        'Domain': {
                            'Bacteria': [
                                {
                                    'name': ValueError,  # intentional bad value
                                    'description': 'Just a bad description'
                                }
                            ],
                            'Archaea': [],
                            'Eukaryota': [
                                {
                                    'name': 'Excavata', 
                                    'description': 'Various flagellate protozoa',
                                },
                                {   
                                    'name': 'Amoebozoa',
                                    'descritpion': 'most lobose amoeboids and slime moulds',
                                },
                                {
                                    'name': 'Opisthokonta',
                                    'description': 'animals, fungi, choanoflagellates, etc.',
                                },
                            ]
                        } 
                    }
                }
        
            Now let's log our message at each of the defined log levels...
        
            .. code:: python
        
                logger.debug(LOG_MSG)
                logger.info(LOG_MSG)
                logger.warn(LOG_MSG)
                logger.error(LOG_MSG)
                try:
                    raise ValueError("Bad Value")
                except ValueError as e:
                    logger.exception(LOG_MSG)
                    raise
        
        5) Now log into your mongo shell and look at some results
            .. code:: python
        
                ./mongo
        
                use mongolog
                db.mongolog.findOne({'level': "INFO"})
        
            Will produde a mongo document like:
        
            .. code:: python
        
                {
                    "_id" : ObjectId("5664a22bdd162ca58f0693d2"),
                    "name" : "__builtin__",
                    "thread" : NumberLong("140735229362944"),
                    "level" : "INFO",
                    "process" : 42383,
                    "module" : "<console>",
                    "filename" : "<console>",
                    "func" : "<module>",
                    "time" : ISODate("2015-12-06T21:01:31.258Z"),
                    "msg" : {
                        "test" : true,
                        "Life" : {
                            "Domain" : {
                                "Eukaryota" : [
                                    {
                                        "name" : "Excavata",
                                        "description" : "Various flagellate protozoa"
                                    },
                                    {
                                        "name" : "Amoebozoa",
                                        "descritpion" : "most lobose amoeboids and slime moulds"
                                    },
                                    {
                                        "name" : "Opisthokonta",
                                        "description" : "animals, fungi, choanoflagellates, etc."
                                    }
                                ],
                                "Archaea" : [ ],
                                "Bacteria" : [
                                    {
                                        "name" : "<type 'exceptions.ValueError'>",
                                        "description" : "Just a bad description"
                                    }
                                ]
                            }
                        },
                        "test class" : "TestBaseMongoLogHandler"
                    },
                    "path" : "<console>",
                    "line" : 1
                }
        
            Take a look at the "msg" section and you will notice that all of the information from our LOG_MSG
            is contained under that key in standard mongo data structures.  This means that we can query 
            based on our log message.  For example in your mongo shell try the following queries:
        
            .. code:: javascript
        
                // Find all documents logged with a 'test' key
                > db.mongolog.find({'msg.test': {$exists: true}}).count()
                5
        
                // Find all documents that have a Eukaryota name in the list of  ["Amoebozoa", "Opisthokonta"]
                > db.mongolog.find({
                    'msg.Life.Domain.Eukaryota.name': {
                        $in: ["Amoebozoa", "Opisthokonta"]
                    }
                  }).count()
                1
        
                // Same as above but only those documents logged at level INFO
                >db.mongolog.find({
                    'level': 'INFO',
                    'msg.Life.Domain.Eukaryota.name': {$in: ["Amoebozoa", "Opisthokonta"]}, 
                }).count()
                1
        
                // And again at level ERROR.  
                >db.mongolog.find({
                    'level': 'INFO',
                    'msg.Life.Domain.Eukaryota.name': {$in: ["Amoebozoa", "Opisthokonta"]}, 
                }).count()
                2
                
                // Notice that now two records are returned.  This is because
                // logger.exception(...) also logs at level ERROR, but also notice that if when we
                // pretty print the records...
                >db.mongolog.find({
                    'level': 'ERROR',
                    'msg.Life.Domain.Eukaryota.name': {$in: ["Amoebozoa", "Opisthokonta"]}, 
                }).pretty()
        
                // ...that one of the entries has exception info.  When running in a real environment
                // and not the console the 'trace' section will be populated with the full stack trace.
                "exception" : {
                    "info" : [
                        "<type 'exceptions.ValueError'>",
                        "Bad Value",
                        "<traceback object at 0x106853b90>"
                    ],
                    "trace" :
                     null
                }
                
        Management Commands (Django Only)
        ---------------------------------
        
        1) ml_purge
        
        The ml_urge command is used to clean up mongo collections. The command has two basic modes:  --purge and --delete. Purge will remove all documents and delete will remove documents older than {n} day's.
        
        To backup and PURGE all documents from the collection defined in mongolog handler
            ./manage.py ml_purge --purge --backup -logger mongolog
        
        To remove all documents older than 14 days without backing up first
            ./manage.py ml_purge --delete 14 -logger mongolog
        
        
        Future  Roadmap
        ---------------
        
        Currently mongolog has pretty solid support for logging arbitrary datastructures.  If it finds
        an object it doesn't know how to natively serialize it will try to convert it to str().  
        
        The next steps are to create a set of most used query operations for probing the log.
        
        Please give a shout out with `feedback <https://groups.google.com/forum/#!forum/mongolog-users>`_ and feature requests.
        
        Thanks
        
Platform: UNKNOWN
Classifier: Environment :: Web Environment
Classifier: Framework :: Django
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Framework :: Django
Classifier: Framework :: Django :: 1.9
Classifier: Framework :: Django :: 2.0
Classifier: Topic :: Internet :: WWW/HTTP
Classifier: Topic :: Internet :: WWW/HTTP :: Dynamic Content
