rticommunity / rticonnextdds-logparser

RTI Log Parser for Connext DDS is a command-line tool that processes and enhances Connext DDS log messages making it easier to debug applications.
https://www.rti.com/developers/rti-labs/easy-debugging-with-log-parser
Apache License 2.0
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RTI Log Parser for Connext DDS License Apache

RTI® Log Parser is a command-line tool that processes and enhances RTI Connext® DDS log messages, making it easier to debug applications. You can find a quick-start guide in the tutorial folder.

Features

Requirements

You will need Python 2.7 or 3.x. Log Parser works in any OS that supports Python including Linux, Mac OS and Windows.

Usage

python rtilogparser -i <log_file>

The output is generated in Markdown format, which is easy to read in raw format while also allowing you to convert the output into HTML using viewers like Atom or dillinger.

Additional features can be enabled or disabled with the following arguments:

Enable Connext DDS logs

By default, any application built with Connext DDS will print the errors from the middleware to the standard output. In order to take advantage of Log Parser, we recommend enabling the higher log verbosity and redirecting the output into a file. There are several ways to increase the log verbosity:

Tcsh

setenv NDDS_QOS_PROFILES 'str://"ALLALLTIMESTAMPED"'

Windows CMD

set NDDS_QOS_PROFILES=str://"ALLALLTIMESTAMPED"


## Compilation
It is not necessary to compile Log Parser since it uses Python. Optionally, the source code can be zipped into a single file with `create_redist.sh` to simplify the distribution. The zip file can be executed as a .py file. For example: `python rtilogparser -i log.txt`.

## Adding new logs
Log Parser can be extended to parse custom log messages from an application. This can be done by adding a prefix to the log message or adding a new regular expression to Log Parser.

### Log prefixes
Any log message starting with `#Custom: ` is parsed and will appear in the output with the prefix `[APP]`.

### Adding a parser
Log Parser can be extended to implement custom parsers, by following these steps:

1. Add the regular expression for the log message. Open *logparser/logs/custom/logs.py* and append a new *tuple* with the following format to the `regex` variable:

regex.append([custom.FUNCTION_NAME_TO_CALL_IF_MATCHED, LOG_REGEX])


2. Implement the function that will be called if the regular expression is matched. This function should call methods from the *logger* class like `send` for messages related to sending data. For instance:
```python
def on_accept_data(match, state, logger):
    # match is an array with the regular expression matched groups.
    # state is a dictionary where you can store and retrieve variables.
    # logger the logger that process the messages
    seqnum = parse_sn(match[0])
    logger.process("", "", "Reader accepted DATA (%d)" % seqnum, 1)