Metadata-Version: 1.1
Name: mo-logs
Version: 1.1.17056
Summary: More Logs! Structured Logging and Exception Handling
Home-page: https://github.com/klahnakoski/mo-logs
Author: Kyle Lahnakoski
Author-email: kyle@lahnakoski.com
License: MPL 2.0
Description: INCOMPLETE
        ==========
        
        More Logs - Structured Logging and Exception Handling
        =====================================================
        
        This library provides two main features
        
        -  **Structured logging** - output is all JSON (with options to
           serialize to text)
        -  **Exception handling weaved in** - Good logs must represent what
           happened, and that can not be done if the logging library is not
           intimately familiar with the (exceptional) code paths taken.
        
        Motivation
        ----------
        
        Exception handling and logging are undeniably linked. There are many
        instances where exceptions are raised and must be logged, and others
        where the subsuming system can fully handle the exception, and no log
        should be emitted. Exception handling semantics are great because they
        decouple the cause from the solution, but this can be at odds with clean
        logging - which couples raising and catching to make appropriate
        decisions about what to emit to the log.
        
        This logging module is additionally responsible for raising exceptions,
        collecting the trace and context, and then deducing if it must be
        logged, or if it can be ignored because something can handle it.
        
        **More Reading**
        
        -  **Structured Logging is Good** -
           https://sites.google.com/site/steveyegge2/the-emacs-problem
        
        Basic Usage
        -----------
        
        **Use ``Log.note()`` for all logging**
        
        .. code:: python
        
                Log.note("Hello, World!")
        
        There is no need to create logger objects. The ``Log`` module will keep
        track of what, where and who of every call.
        
        **Use named parameters**
        
        Do not use Python's formatting operator "``%``" nor it's ``format()``
        function. Using them will create a string at call time, which is a
        parsing nightmare for log analysis tools.
        
        .. code:: python
        
                Log.note("Hello, {{name}}!", name="World!")
        
        All logs are structured logs; the parameters will be included,
        unchanged, in the log structure. This library also expects all parameter
        values to be JSON- serializable so they can be stored/processed by
        downstream JSON tools.
        
        .. code:: javascript
        
                {//EXAMPLE STRUCTURED LOG
                    "template": "Hello, {{name}}!",
                    "param": {"name": "World!"},
                    "timestamp": 1429721745,
                    "thread": {
                        "name": "Main thread"
                    },
                    "location": {
                        "line": 3,
                        "file": "hello.py",
                        "method": "hello"
                    },
                    "machine": {
                        "python": "CPython",
                        "os": "Windows10",
                        "name": "ekyle-win"
                    }
                }
        
        **Instead of ``raise`` use ``Log.error()``**
        
        .. code:: python
        
                Log.error("This will throw an error")
        
        The actual call will always raise an exception, and it manipulates the
        stack trace to ensure the caller is appropriately blamed. Feel free to
        use the ``raise`` keyword (as in ``raise Log.error("")``), if that looks
        nicer to you.
        
        **Always chain your exceptions**
        
        The ``cause`` parameter accepts an ``Exception``, or a list of
        exceptions. Chaining is generally good practice that helps you find the
        root cause of a failure.
        
        .. code:: python
        
                try:
                    # Do something that might raise exception
                except Exception, e:
                    Log.error("Describe what you were trying to do", cause=e)
        
        **Always catch all ``Exceptions``**
        
        Catching all exceptions is preferred over the
        *only-catch-what-you-can-handle* strategy. First, exceptions are not
        lost because we are chaining. Second, we catch unexpected ``Exceptions``
        early and we annotate them with a description of what the local code was
        intending to do. This annotation effectively groups the possible errors
        (known, or not) into a class, which can be used by callers to decide on
        appropriate mitigation.
        
        To repeat: When using dependency injection, callers can not reasonably
        be expected to know about the types of failures that can happen deep
        down the call chain. This makes it vitally important that methods
        summarize all exceptions, both known and unknown, so their callers have
        the information to make better decisions on appropriate action.
        
        For example: An abstract document container, implemented on top of a SQL
        database, should not emit SQLExceptions of any kind: A caller that uses
        a document container should not need to know how to handle SQLExceptions
        (or any other implementation-specific exceptions). Rather, in this
        example, the caller should be told it "can not add a document", or "can
        not remove a document". This allows the caller to make reasonable
        desisions when they do occur. The original cause (the SQLException) is
        in the causal chain.
        
        **Use named parameters in your error descriptions too**
        
        Error logging accepts keyword parameters just like ``Log.note()`` does
        
        .. code:: python
        
                def worker(value):
                    try:
                        Log.note("Start working with {{key1}}", key1=value1)
                        # Do something that might raise exception
                    except Exception, e:
                        Log.error("Failure to work with {{key2}}", key2=value2, cause=e)
        
        **No need to formally type your exceptions**
        
        An exception can be uniquely identified by the first-parameter string
        template it is given; exceptions raised with the same template are the
        same type. You should have no need to create new exception sub-types.
        
        **Testing for exception "types"**
        
        This library advocates chaining exceptions early and often, and this
        hides important exception types in a long causal chain. MoLogs allows
        you to easily test if a type (or string, or template) can be found in
        the causal chain by using the ``in`` keyword:
        
        .. code:: python
        
                def worker(value):
                    try:
                        # Do something that might raise exception
                    except Exception, e:
                        if "Failure to work with {{key2}}" in e:
                            # Deal with exception thrown in above code, no matter
                            # how many other exception handlers where in the chain
        
        **If you can deal with an exception, then it will never be logged**
        
        When a caller catches an exception from a callee, it is the caller's
        responsibility to handle that exception, or re-raise it. There are many
        situations a caller can be expected to handle exceptions; and in those
        cases logging an error would be deceptive.
        
        .. code:: python
        
                def worker(value):
                    try:
                        Log.error("Failure to work with {{key3}}", key3=value3)
                    except Exception, e:
                        # Try something else
        
        **Use ``Log.warning()`` if your code can deal with an exception, but you
        still want to log it as an issue**
        
        .. code:: python
        
                def worker(value):
                    try:
                        Log.note("Start working with {{key4}}", key4=value4)
                        # Do something that might raise exception
                    except Exception, e:
                        Log.warning("Failure to work with {{key4}}", key4=value4, cause=e)
        
        **Don't loose your stack trace!**
        
        Be aware your ``except`` clause can also throw exceptions: In the event
        you catch a vanilla Python Exception, you run the risk of loosing its
        stack trace. To prevent this, wrap your exception in an ``Except``
        object, which will capture your trace for later use. Exceptions thrown
        from this ``Log`` library need not be wrapped because they already
        captured their trace. If you wrap an ``Except`` object, you simply get
        back the object you passed.
        
        ``python     try:         # DO SOME WORK           except Exception, e:         e = Except.wrap(e)         # DO SOME FANCY ERROR RECOVERY``
        
        Other forms
        -----------
        
        All the ``Log`` functions accept a ``default_params`` as a second
        parameter, like so:
        
        .. code:: python
        
                Log.note("Hello, {{name}}!", {"name": "World!"})
        
        this is meant for the situation your code already has a bundled
        structure you wish to use as a source of parameters. If keyword
        parameters are used, they will override the default values. Be careful
        when sending whole data structures, they will be logged!
        
        **Please, never use locals()**
        
        .. code:: python
        
                def worker(value):
                    name = "tout le monde!"
                    password = "123"
                    Log.note("Hello, {{name}}", locals())   # DO NOT DO THIS!
        
        Despite the fact using ``locals()`` is a wonderful shortcut for logging
        it is dangerous because it also picks up sensitive local variables. Even
        if ``{{name}}`` is the only value in the template, the whole
        ``locals()`` dict will be sent to the structured loggers for recording.
        
        Log 'Levels'
        ------------
        
        The ``logs`` module has no concept of logging levels it is expected that
        debug variables (variables prefixed with ``DEBUG_`` are used to control
        the logging output.
        
        .. code:: python
        
                # simple.py
                DEBUG_SHOW_DETAIL = True
        
                def worker():
                    if DEBUG_SHOW_DETAIL:
                        Log.note("Starting")
        
                    # DO WORK HERE
        
                    if DEBUG_SHOW_DETAIL:
                        Log.note("Done")
        
                def main():
                    try:
                        settings = startup.read_settings()
                        Log.start(settings.debug)
        
                        # DO WORK HERE
        
                    except Exception, e:
                        Log.error("Complain, or not", e)
                    finally:
                        Log.stop()
        
        These debug variables can be set by configuration file:
        
        .. code:: javascript
        
                // settings.json
                {
                    "debug":{
                        "constants":{"simple.DEBUG_SHOW_DETAILS":false}
                    }
                }
        
        Configuration
        -------------
        
        The ``logs`` module will log to the console by default.
        ``Log.start(settings)`` will redirect the logging to other streams, as
        defined by the settings:
        
        -  **log** - List of all log-streams and their parameters
        -  **trace** - Show more details in every log line (default False)
        -  **cprofile** - Used to enable the builtin python c-profiler (default
           False)
        -  **profile** - Used to enable pyLibrary's simple profiling (default
           False) (eg with Profiler("some description"):)
        -  **constants** - Map absolute path of module constants to the values
           that will be assigned. Used mostly to set debugging constants in
           modules.
        
        Of course, logging should be the first thing to be setup (aside from
        digesting settings of course). For this reason, applications should have
        the following structure:
        
        .. code:: python
        
                def main():
                    try:
                        settings = startup.read_settings()
                        Log.start(settings.debug)
        
                        # DO WORK HERE
        
                    except Exception, e:
                        Log.error("Complain, or not", e)
                    finally:
                        Log.stop()
        
        ::
        
                "log": [
                    {
                        "class": "logging.handlers.RotatingFileHandler",
                        "filename": "examples/logs/examples_etl.log",
                        "maxBytes": 10000000,
                        "backupCount": 100,
                        "encoding": "utf8"
                    },
                    {
                        "log_type": "email",
                        "from_address": "klahnakoski@mozilla.com",
                        "to_address": "klahnakoski@mozilla.com",
                        "subject": "[ALERT][DEV] Problem in ETL Spot",
                        "$ref": "file://~/private.json#email"
                    },
                    {
                        "log_type": "console"
                    }
                ]
        
        Problems with Python Logging
        ----------------------------
        
        | `Python's default ``logging``
          module <https://docs.python.org/2/library/logging.html#logging.debug>`__
          comes close to doing the right thing, but fails:
        |  \* It has keyword parameters, but they are expanded at call time so
          the values are lost in a string.
        |  \* It has ``extra`` parameters, but they are lost if not used by the
          matching ``Formatter``.
        |  \* It even has stack trace with ``exc_info`` parameter, but only if
          an exception is being handled. \* Python 2.x has no builtin exception
          chaining, but `Python 3
          does <https://www.python.org/dev/peps/pep-3134/>`__
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: Mozilla Public License 2.0 (MPL 2.0)
