Awesome
Management Tools
A collection of Python scripts and packages to simplify OS X management.
Contents
- Download - get the .dmg
- System Requirements - what you need
- Contact - how to reach us
- Uninstall - removal of Management Tools
- Modules
- app_info - access applications' information
- fs_analysis - analyze mounted filesystems
- loggers - output data to logs
- plist_editor - modify plists properly
- slack - easily post to your team's Slack feed
- Scripts
- App Lookup - lookup an application's information
- Python Executable Bundler - bundle a Python project into a standalone script
- Management Logger - log data easily
- Management Email - simple email sender
- Python Package Creator - an automated .pkg creator for Python projects using 'setup.py'
- Update History - all of the major updates to Management Tools
Download
Download the latest installer here!
System Requirements
Management Tools has been tested to work with Mac OS X 10.8 through 10.10, and uses Python version 2.7.
Contact
If you have any comments, questions, or other input, either file an issue or send an email to us. Thanks!
Uninstall
To remove Management Tools from your system, download the .dmg and run the "Uninstall Management Tools" package to uninstall it. (Note that it will say "Installation Successful" but don't believe it - it will only remove files.)
Get Current Version
If you want to find your currently-installed Management Tools version, simply do:
$ python -m management_tools.__init__
Management Tools, version: x.y.z
Note that this will only work from version 1.6.3 on.
Modules
In Python, modules are designed to be imported into another project to make your life easier. These can be integrated into your packages by simply using:
from package import module
# Or if you want a particular method from within a module:
from package.module import method
# For example, if we want the app_info module:
from management_tools import app_info
# Or just the AppInfo class:
from management_tools.app_info import AppInfo
app_info
This module contains a class, AppInfo
, which can be used to get information about applications. Generally, you will do:
from management_tools.app_info import AppInfo
Then the class can be used to get information. It requires an argument upon creation which should tell it something identifiable about the application, such as a valid short name, a bundle path, or a bundle identifier. Once it has been created, you can access various useful bits about the application.
app = AppInfo('application name')
app.path # This reports the /path/to/the/application.app
app.plist # Returns a PlistEditor of the application's informational property
# list, generally located at <app.path>/Contents/Info.plist
app.bid # The application's bundle identifier
app.name # The full name of the application
So, for example, if we use com.apple.Safari
as our application (this is in interactive mode):
>>> from management_tools.app_info import AppInfo
>>> app = AppInfo('com.apple.Safari')
>>> app.path
'/Applications/Web Browsers/Safari.app'
>>> app.plist
/Applications/Web Browsers/Safari.app/Contents/Info.plist
>>> app.bid
'com.apple.Safari'
>>> app.name
'Safari'
>>>
Alternatively, the information can also be returned more simply for outputting purposes:
>>> from management_tools.app_info import AppInfo
>>> app = AppInfo('safari')
>>> app
Safari
BID: com.apple.Safari
Path: /Applications/Web Browsers/Safari.app
Info.plist: /Applications/Web Browsers/Safari.app/Contents/Info.plist
>>>
Finding Bundle Identifiers Manually
Bundle identifiers are the method Apple uses to manage its TCC databases. The AppInfo
class is good at finding them, but maybe you want to know more about where to find them yourself (for some reason).
In general, BIDs can be found in an application's Info.plist
file. If your application is located at /Applications/MyAwesomeApp.app
, then the plist file will most likely be located at /Applications/MyAwesomeApp.app/Contents/Info.plist
. Within this plist, you'll need to search for the string corresponding to the key CFBundleIdentifier
. So we could do:
$ defaults read /Applications/MyAwesomeApp.app/Contents/Info CFBundleIdentifier
The CFBundleIdentifier
key is supposed to be included for every application. If it's not there, then the application's developers did something wrong (or maybe they just did something different for a very particular reason).
Brett Terpstra detailed a shell script to help with looking these up, which I will reproduce here for your convenience:
# Allows for searching of Bundle IDs by application name
# Written by Brett Terpstra
bid() {
local shortname location
# combine all args as regex
# (and remove ".app" from the end if it exists due to autocomplete)
shortname=$(echo "${@%%.app}"|sed 's/ /.*/g')
# if the file is a full match in apps folder, roll with it
if [ -d "/Applications/$shortname.app" ]; then
location="/Applications/$shortname.app"
else # otherwise, start searching
location=$(mdfind -onlyin /Applications -onlyin ~/Applications -onlyin /Developer/Applications 'kMDItemKind==Application'|awk -F '/' -v re="$shortname" 'tolower($NF) ~ re {print $0}'|head -n1)
fi
# No results? Die.
[[ -z $location || $location = "" ]] && echo "$1 not found, I quit" && return
# Otherwise, find the bundleid using spotlight metadata
bundleid=$(mdls -name kMDItemCFBundleIdentifier -r "$location")
# return the result or an error message
[[ -z $bundleid || $bundleid = "" ]] && echo "Error getting bundle ID for \"$@\"" || echo "$location: $bundleid"
}
If you were to put this in your source file (e.g. .bash_profile
), you can simply call it as a command and it will search for your application and return both the app's location and its bundle ID:
$ bid safari
/Applications/Safari.app: com.apple.Safari
fs_analysis
Sometimes you might want to get information about mounted filesystems. Command line tools such as df
and mount
are useful if you're a human, but they leave something to be desired if you write a lot of scripts. Enter fs_analysis
- a Python module designed to help you gather information on mounted filesystems.
fs_analysis
has three methods for polling the system about mounted filesystems:
get_responsible_fs(target)
finds which filesystem contains the given file or directory. The return value is the name of the filesystem, such as '/dev/disk0s2'.get_raw_fs_info(fs_name)
returns themount
information for the given filesystem, which will include the mount point and mount options.get_raw-fs_usage(mount_point)
gives output fromdf -P -k $mount_point
(but without the headers thatdf
usually puts on the first line).
Filesystem
Additionally (and most importantly), fs_analysis
introduces a Filesystem
class. To initialize a Filesystem
object, you must supply the constructor with the raw device name of the filesystem you want it to keep track of. Sometimes you may not know the device name but you might know a file or folder on the specified device, or even the mount point. Here's how I initialize my Filesystem
objects:
from management_tools import fs_analysis
device_name = fs_analysis.get_responsible_fs('/path/to/target')
fs_object = fs_analysis.Filesystem(device_name)
Objects of this type keep track of various bits of information regarding a particular filesystem:
Property Name | Description |
---|---|
name | The raw device name for the filesystem (e.g. /dev/disk2s1 ). |
mount_point | Where the device is mounted (e.g. /Volumes/MyFavoriteDisk ). |
type | What type of filesystem it is (HFS, NTFS, FAT, etc.). |
kblocks | Total number of 1024-byte blocks on the device. |
kblocks_used | Number of 1024-byte blocks that are used. |
kblocks_free | Number of 1024-byte blocks available for use. (kblocks_free + kblocks_used = kblocks ) |
bytes | Total number of bytes on the device (computed as 1024 x kblocks ). |
bytes_used | Number of bytes that are used (computed as 1024 x kblocks_used ). |
bytes_free | Number of bytes remaining unused (computed as 1024 x kblocks_free ). |
capacity | The percentage of space that has been used. (This is a rounded integer computed as kblocks_used / kblocks by the system.) |
properties | Any other properties the device may have (e.g. HFS, remote, nosuid, journaled, read-only, etc.). |
Additionally, the Filesystem
object's data can be refreshed by using the update()
method. This will cause the object to re-poll the system and gather new usage data.
Note that the properties are otherwise designed to be immutable, since they are descriptions of filesystems and not values for you to modify directly. I did this to ensure greater safety when using these objects. (What I mean is: you can't do fs_object.bytes = 100
or something like that.)
loggers
In our deployment, we like to log stuff. Logging things is a useful way to record information for later perusal, which can be quite helpful. Since I kept having to copy/paste our logging mechanisms from script to script, I just created a dedicated logging module.
There are three classes in this module: the generic Logger
, and the more specific FileLogger
and StreamLogger
(which both extend the base Logger
class). FileLogger
is used to output information to a file and/or the console, and StreamLogger
only outputs information to the console.
FileLogger
The FileLogger
class is built on a rotating file handler. The default is set to keep five backup files (so up to six files total) that are 10MB each. This logger can also output information to the console, allowing an easy way to output information and control verbosity while logging everything. The default log location is either /var/log/management/
for administrators with write access to that directory, or else ~/Library/Logs/Management/
for non-privileged users.
Example Usage
>>> from management_tools.loggers import FileLogger
>>> logger = FileLogger('test')
>>> logger.info("This is regular information.")
INFO: This is regular information.
>>> logger.debug("Super verbose (not logged by default, unless the level is changed).")
>>> logger.error("This is an error.")
ERROR: This is an error.
>>> logger.fatal("Danger, Will Robinson! Danger!")
CRITICAL: Danger, Will Robinson! Danger!
>>>
If we then go and look in (assuming this was run unprivileged) ~/Library/Logs/Management/test.log
:
2015-02-26 10:04:12,238 INFO: This is regular information.
2015-02-26 10:04:22,614 ERROR: This is an error.
2015-02-26 10:04:26,206 CRITICAL: Danger, Will Robinson! Danger!
There is also a file_logger
method to provide backwards compatibility with scripts written to use Management Tools versions less than 1.6.0:
def file_logger(name=None, level=INFO, path=None):
StreamLogger
StreamLogger
is used in situations where you want to provide a logger, but you may not want to write the data to file. I use this in scripts where I give the user the option of enabling logging through a command line flag. If they specify that they do not want information logged to a file, a StreamLogger
is used in place of the FileLogger
.
By default, StreamLogger
does not have the print_default
field set to True
. Instead, it redirects the actual log messages (with timestamps et al) and prints those to the console.
As with the FileLogger
, there is also a stream_logger
method to provide backwards compatibility with scripts written to use Management Tools versions less than 1.6.0:
def stream_logger(level=DEBUG):
General Logger Specifics
To easily get a logger with the default specifications, the module provides a method for each logger: FileLogger
has file_logger()
, and StreamLogger
has stream_logger()
. Simply do:
>>> from management_tools.loggers import stream_logger
>>> logger = stream_logger()
>>> logger.info("Time is an illusion. Lunchtime doubly so.")
2015-02-26 12:11:50,837 INFO: Time is an illusion. Lunchtime doubly so.
>>>
In most of my scripts, I allow the user to specify whether log events will be outputted to file, and if they are where to put that file. To make my life easier (and possibly yours too!), there is now a method to allow the programmatic generation of loggers appropriate to these options: get_logger()
.
def get_logger(name=None, log=False, level=INFO, path=None):
A simple usage example would be:
>>> from management_tools.loggers import get_logger
>>> logger = get_logger(name='fjords', log=True, path='/zz9/earth/norway')
>>>
This would return a FileLogger
, set to generate a file at /zz9/earth/norway/fjords.log
. If log
were set to False
, the file would not be used.
Logging Levels and Methods
There are six different logging levels supported (all of them except for VERBOSE
copy their values from the standard logging
module):
Logging Level | Default Value |
---|---|
CRITICAL | 50 (logging.CRITICAL ) |
ERROR | 40 (logging.ERROR ) |
WARNING | 30 (logging.WARNING ) |
INFO | 20 (logging.INFO ) |
DEBUG | 10 (logging.DEBUG ) |
VERBOSE | 5 |
Each of these levels of logging also has a corresponding method for generating logging output. Assuming you have a Logger
object named logger
:
Method | Purpose |
---|---|
logger.critical | Fatal errors that impede program flow. |
logger.error | Important errors that may yield undesired results. |
logger.warning | Issues that are not halting, but not ideal. |
logger.info | Regular information. |
logger.debug | Debugging information. |
logger.verbose | Very detailed information. |
Controlling Output
The console output can be controlled. Each of the logging methods has a signature such as:
def info(self, message, print_out=None, log=None):
print_out
and log
take booleans for arguments. If you pass True
to both (the default for FileLogger
), you get output to both the console (print_out
) and the logging file (log
). The defaults can be changed by modifying the logger's print_default
and log_default
fields, for example:
>>> from management_tools.loggers import FileLogger
>>> logger = FileLogger('test')
>>> logger.info("This must be Thursday. I never could get the hang of Thursdays.")
INFO: This must be Thursday. I never could get the hang of Thursdays.
>>> logger.print_default = False
>>> logger.info("For a moment, nothing happened. Then, after a second or so, nothing continued to happen.")
>>> logger.log_default = False
>>> logger.info("Oh no, not again!")
>>> logger.info("So long, and thanks for all the fish!", print_out=True)
INFO: So long, and thanks for all the fish!
>>>
If we then go and look in ~/Library/Logs/Management/test.log
(assuming this was run unprivileged):
2015-02-26 11:37:44,394 INFO: This must be Thursday. I never could get the hang of Thursdays.
2015-02-26 11:38:00,347 INFO: For a moment, nothing happened. Then, after a second or so, nothing continued to happen.
Custom Prompts
When log messages are outputted to the console, they are by default prepended with their logging level name (in all caps). You can override the prompt for each level. Note that this is only for console output and not for the actual log messages.
>>> from management_tools import loggers
>>> logger = loggers.StreamLogger('ford', loggers.INFO, True, False)
>>> logger.info("How would you react if I said that I'm not from Guildford at all, but from a small planet somewhere in the vicinity of Betelgeuse?")
INFO: How would you react if I said that I'm not from Guildford at all, but from a small planet somewhere in the vicinity of Betelgeuse?
>>> logger.set_prompt(loggers.INFO, 'Ford: ')
>>> logger.info("The point is that I am now a perfectly safe penguin, and my colleague here is rapidly running out of limbs!")
Ford: The point is that I am now a perfectly safe penguin, and my colleague here is rapidly running out of limbs!
>>>
plist_editor
Many Apple services and applications utilize property list files, usually referred to simply as 'plists'. These files can be modified to contain all kinds of information.
However, editing the files can be somewhat of a hassle. Since Mac OS X 10.9 "Mavericks", plist files are periodically cached and then rewritten asynchronously to the disk. What this means is that if you modify a plist with a plaintext editor, there is no guarantee that the changes will remain permanently. This is not exactly the ideal way for things to be done.
OS X contains a command called defaults
. This command provides the necessary mechanism to modify plist files without the asynchronous caching having a negative effect on your work. This plist_editor
module contains a class, PlistEditor
, which allows you to modify plist files using this defaults
command (but without you having to actually make the calls).
from management_tools.plist_editor import PlistEditor
plist = PlistEditor('/path/to/file.plist')
slack
Lots of teams are using the neat Slack application for communication. Slack also provides an easy-to-use API for setting up bots, which our team decided to use to report problems in a sort of makeshift dashboard. To make that job even easier, I've added a high-level class for interacting with a Slack Incoming Webhook.
from management_tools.slack import IncomingWebhooksSender
The IncomingWebhooksSender
is able to abstract away a lot of the effort of posting to your Slack team. The constructor takes an integration URL (provided when you activate Incoming Webhooks for a given channel) and can additionally take the following arguments:
Argument | Purpose |
---|---|
bot_name | The name for your bot, like "testbot" or "Errors From My Script". |
icon_url | You can specify a URL to an image that your bot will use as an avatar. |
icon_emoji | You can also use any of the available Slack emojis as an icon. This overrides icon_url . |
channel | The default channel for your bot. Any bot can post to any channel, though. |
markdown | Whether your bot supports Markdown formatting. The default is True. |
And an IncomingWebhooksSender
object has the following public methods:
Method | Purpose |
---|---|
send_message(message) | Sends a text message with all default settings. |
send_message_to_channel(message, channel) | Sends a text message to a specific channel with all default settings. |
success(message?) | Sends a check mark and a message (if given). |
warning(message?) | Sends a warning sign with a message (if given). |
error(message?) | Sends a red circle with a message (if given). |
send_dictionary(dictionary) | Converts a dictionary to JSON and sends it. This is to get around any restrictions in the object. |
(Where arguments with a ?
are optional.)
The Slack API's documentation on incoming webhooks can be found here.
As an example, say you have the incoming webhook URL https://hooks.slack.com/services/ABCDE/EDCBA/12345
. To use this with IncomingWebhooksSender
, do:
from management_tools.slack import IncomingWebhooksSender as IWS
url = "https://hooks.slack.com/services/ABCDE/EDCBA/12345"
bot = IWS(url, bot_name="My Test Bot", channel="#bot-channel")
bot.send_message("This is a test!")
bot.send_message_to_channel("Another test...", "#different-channel")
Note that your channel names must start with either #
for regular channels or @
for direct messages. You'll get an error if you don't use one of those. However, if you choose to leave the channel blank then your bot will post to the default channel for your incoming webhook URL.
Scripts
The scripts are mostly just simple frontends for using the modules above. For example: perhaps you want to log something, but you don't want to go through the trouble of importing the logger and setting it up. Instead, just use the Management Logger script and it will do the work for you.
App Lookup
This serves as a quick interface to the app_info
module. When calling the script, simply supply identifiers for applications and it will return the application's given name, bundle ID, path, and Info.plist path.
$ app_lookup.py safari
Safari
BID: com.apple.Safari
Path: /Applications/Web Browsers/Safari.app
Info.Plist /Applications/Web Browsers/Safari.app/Contents/Info.plist
Python Executable Bundler
A while ago I learned that Python scripts can be bundled together in standalone 'executables'. I did this manually for a while, and then created this script to automate it.
Effectively what happens is this takes the Pythonic contents of a directory (i.e. all the .py
files) and compresses them into a zipped structure. A shebang is catted in to the zip and then chmoded to produce an 'executable'. Note that that main entrance point of the script must be named __main__.py
for this to work properly.
Usage of the script is simple. If you are within the directory of Python files:
$ executable_bundler.py -o mybundle
adding: __main__.py (deflated 71%)
adding: something.py (deflated 67%)
You will then find a file named mybundle
in the current directory that can be run with:
$ ./mybundle
This produces the same results as:
$ python __main__.py
Management Logger
The Management Logger is an interface for the file_logger
from above. Calling Management Logger allows you to easily write a log entry to a file quickly and efficiently. Calling the script involves:
$ management_logger.py file "This is an entry in my log."
This will log the line "This is an entry in my log."
to a file named file.log
located in one of two places: either /var/log/management/
if the calling user has root privileges, or else ~/Library/Logs/Management/
.
Management Email
Management Email is designed to allow your scripts to send emails easily and with minimal setup. The script has many options available, but generally only a couple of them need to actually be supplied:
Option | Purpose |
---|---|
-h , --help | Prints usage instructions. |
-v , --version | Prints version information. |
-n , --no-log | Prevents logs from being written to file (instead they'll come through stdio). |
-l log , --log log | Uses log as the destination for logging output. |
-f file , --file file | Attaches file to the email as a plaintext document. |
-u subject , --subject subject | Places subject in the message header. |
-s server , --smtp-server server | Send the mail through server . |
-p port , --smtp-port port | Connect to the server via port port . |
-U user , --smtp-username user | Connect to the server as user . |
-P pass , --smtp-password pass | Connect to the server with password pass . |
-F address , --smtp-from address | Send the mail from address . |
-T address , --smtp-to address | Send the mail to address . |
Additionally, a message can be supplied by itself in a quoted string.
In an effort to simplify administration, many of the options can be set through environment variables. These variables are:
Variable Name | Correlating command-line flag |
---|---|
MANAGEMENT_SMTP_SERVER | -s , --smtp-server |
MANAGEMENT_SMTP_PORT | -p , --smtp-port |
MANAGEMENT_SMTP_USER | -U , --smtp-username |
MANAGEMENT_SMTP_PASS | -P , --smtp-password |
MANAGEMENT_SMTP_FROM | -F , --smtp-from |
MANAGEMENT_SMTP_TO | -T , --smtp-to |
Environment variables can easily be set by running a command such as:
$ export MANAGEMENT_SMTP_SERVER='mail.example.com'
Note that environment variables must be declared using the export
functionality for the script to be able to pick up on them. It is conceivable to have these set globally, but that is outside the scope of this summary.
Python Package Creator
The Python Package Creator (also 'PyPkg') will create an OS X-compatible .pkg
file containing the contents of a Python project. The project must use the setup.py
system, which is documented here. If you aren't using this system to manage your Python projects, you may want to consider changing to it.
There are a few options that can be given to the script:
Option | Purpose |
---|---|
-h , --help | Prints usage information. |
-v , --version | Prints version information. |
--dirty | Prevents cleanup after the package has been created. |
--no-image | Does not produce the .dmg file and instead leaves the .pkg s in a pkgs subfolder. |
--name file_name | The name of the .pkg file will be file_name . The special values #NAME and #VERSION can be used to get the name and version information from setup.py . |
--pkg-version version | Manually sets the version information for the package, both for the name and for the package's receipt once installed. |
--dest destination | The .pkg file will be created at destination . Note that this is relative to the path given to the script. |
--extras directory | The contents of directory will be added to the top level of the disk image produced. This is useful for readmes and configuration files. |
--sign signature | Allows you to digitally sign the package with an identity so that it will be trusted. See Apple's documentation on code signing. |
--python python_executable | The setup.py script will be run using the Python executable at python_executable . |
As an example, this Management Tools package (in the /pkg/
directory) was created by running the following from within the Management Tools directory:
$ pypkg.py edu.utah.scl.management-tools ./setup.py --python /usr/bin/python --dest pkg
Uninstaller
PyPkg automatically produces another .pkg
file to uninstall whatever package you just produced. You can simply double-click it and it will remove the contents of the previously-installed package, and it will also forget that package from the receipts database. This is significantly easier than the previous method of running an uninstallation script from the terminal. By default this uninstallation package will be produced on the same level as the installation package, so you will be able to decide how to distribute them.
Update History
This is a reverse-chronological list of updates to this project.
Date | Version | Update Description |
---|---|---|
2016-02-03 | 1.9.1 | Updated Slack module and documentation. |
2015-10-13 | 1.9.0 | Added Slack incoming webhooks module. This allows easy bot-posting via the Slack API. |
2015-03-26 | 1.8.1 | Updated fs_analysis.Filesystem objects to have bytes properties. |
2015-03-20 | 1.8.0 | Introduced fs_analysis - simple filesystem information for Python. |
2015-02-26 | 1.7.0 | Significant rewrite of the loggers module. Provides greater flexibility and more options in the creation of logger objects. |
2015-02-24 | 1.6.4 | Custom logging prompts. |
2015-02-19 | 1.6.3 | Now you can get the current installed version of Management Tools by doing python -m management_tools.__init__ ! |
2015-02-06 | 1.6.2 | Logging level update (it was broken before). |
2015-02-05 | 1.6.1 | Can now set the logging level in get_logger() method. |
2015-02-05 | 1.6.0 | Massive overhaul of loggers system. Now there's a Logger class that can be used more easily. |
2014-07-15 | 1.5.13 | PyPkg now supporst an "extras" directory option. Useful for readmes and config files for your package deployments. |
2014-06-26 | 1.5.10 | Signing update. PyPkg supports code developer signatures. Good for deploying. |
2014-06-26 | 1.5.9 | After building the installation and uninstallation packages, PyPkg now wraps them in a disk image. |
2014-06-26 | 1.5.8 | Removed the uninstallation script and now PyPkg produces real uninstallation packages. Much better. |
2014-06-25 | 1.5.7 | Adjusted paths that were causing issues. |
2014-06-25 | 1.5.6 | Set custom version numbers for packages made with PyPkg. |
2014-06-24 | 1.5.4 | Can now prevent PyPkg from doing post-clean (leaving files in-place to be perused). |
2014-06-24 | 1.5.2 | PyPkg now supports custom installation locations. |
2014-06-24 | 1.5.1 | New uninstaller script for PyPkg. |
2014-06-23 | 1.5.0 | Started on the "Python Package Creator" (pypkg.py ). Much better than the executable bundler from before. |
2014-06-16 | 1.4.0 | Added new management_email.py script for sending of emails. |
2014-06-11 | 1.3.2 | Increased the size of log files to 10MB. |
2014-05-14 | 1.3.1 | app_info.py now finds applications' executable files. |
2014-05-07 | 1.2.1 | Updated setup.py and significant improvements to README documentation. |
2014-05-02 | 1.2 | Changed project name from "Helpful Tools" to "Management Tools". Probably a good move. |
2014-04-22 | 0.9 | Began the project as a merge of some in-house tools. |