GAM VS Installation

GAM and GAMADV-XTD3 -- Command line tool for managing G Suite. Allows me to run scripts to manage accounts. Very useful for setting student photos on their G Suite accounts. Great tool for any G Suite admin.

#!/usr/bin/env python2 """ # Purpose: For a Google Drive User(s), show all drive file ACLs for files shared with users outside of your account. # Note: This script can use Basic or Advanced GAM: # https://github.com/jay0lee/GAM # https://github.com/taers232c/GAMADV-XTD3 # Usage: # 1: Get users in account # $ Basic: gam print users > accountusers.csv # $ Advanced: gam redirect csv ./accountusers.csv print users # 2: Get ACLs for all files, if you don't want all users, replace all users with your user selection in the command below # $ Basic: gam all users print filelist id title permissions owners > filelistperms.csv # $ Advanced: gam config auto_batch_min 1 redirect csv ./filelistperms.csv multiprocess all users print filelist fields id,title,permissions,owners.emailaddress # 3: From that list of ACLs, output a CSV file with headers "Owner,driveFileId,driveFileTitle,permissionId,role,emailAddress" # that lists the driveFileIds and permissionIds for all ACLs with the non-account users # (n.b., driveFileTitle, role, and emailAddress are not used in the next step, they are included for documentation purposes) # $ python GetSharedWithNonAccountUsersDriveACLs.py accountusers.csv filelistperms.csv deleteperms.csv # 4: Inspect deleteperms.csv, verify that it makes sense and then proceed # 5: Delete the ACLs # $ gam csv deleteperms.csv gam user "~Owner" delete drivefileacl "~driveFileId" "~permissionId" """ import csv import re import sys FILE_NAME = 'name' ALT_FILE_NAME = 'title' QUOTE_CHAR = '"' # Adjust as needed LINE_TERMINATOR = '\n' # On Windows, you probably want '\r\n' PERMISSIONS_N_TYPE = re.compile(r"permissions.(\d+).type") if (len(sys.argv) > 3) and (sys.argv[3] != '-'): outputFile = open(sys.argv[3], 'wb') else: outputFile = sys.stdout outputCSV = csv.DictWriter(outputFile, ['Owner', 'driveFileId', 'driveFileTitle', 'permissionId', 'role', 'emailAddress'], lineterminator=LINE_TERMINATOR, quotechar=QUOTE_CHAR) outputCSV.writeheader() if (len(sys.argv) > 2) and (sys.argv[2] != '-'): inputFile = open(sys.argv[2], 'rbU') else: inputFile = sys.stdin accountUsers = set("[email protected]") usersFile = open(sys.argv[1], 'rbU') for row in csv.DictReader(usersFile, quotechar=QUOTE_CHAR): accountUsers.add(row['primaryEmail']) usersFile.close() for row in csv.DictReader(inputFile, quotechar=QUOTE_CHAR): for k, v in row.iteritems(): mg = PERMISSIONS_N_TYPE.match(k) if mg and v == 'user': permissions_N = mg.group(1) if row.get('permissions.{0}.deleted'.format(permissions_N)) == 'True': continue emailAddress = row['permissions.{0}.emailAddress'.format(permissions_N)] if row['permissions.{0}.role'.format(permissions_N)] != 'owner' and emailAddress not in accountUsers: outputCSV.writerow({'Owner': row['owners.0.emailAddress'], 'driveFileId': row['id'], 'driveFileTitle': row.get(FILE_NAME, row.get(ALT_FILE_NAME, 'Unknown')), 'permissionId': 'id:{0}'.format(row['permissions.{0}.id'.format(permissions_N)]), 'role': row['permissions.{0}.role'.format(permissions_N)], 'emailAddress': emailAddress}) if inputFile != sys.stdin: inputFile.close() if outputFile != sys.stdout: outputFile.close()

GAM - Google Workspace. I don't know what I'd do without this.

use GAM to share and accept on users behalf https://github.com/jay0lee/GAM It's incredibly powerful and it's all command line.

GAM If you have not yet have the pleasure of using GAM, I would highly recommend trying it out -- it's not exactly pertinent to this post, but if you've not used it, it's amazing, and a huge time saver when trying to manage Google sometimes.

It's easy enough to stumble through, and Google provides training online. Also, look into GAM, https://github.com/jay0lee/GAM. Best tool you can ever use.

We had to do this a couple years ago when we moved ~500 accounts from one Workspace tenant to another. We used MigrationWiz and GAM to make it less painful, but it still wasn't the prettiest thing ever. If we had to do it over again we'd probably use Google Workspace Migrate which wasn't an option back then.

GAM is probably your best bet. You can run a query for suspended accounts and move them to a specified OU. You can also run a query for users with last logon time equal to whatever and then move those accounts.

If it's a very regular process / procedure, you may want to look at https://github.com/jay0lee/GAM

Do check out GAM, it might do it (not all at Google know about this tool): https://github.com/jay0lee/GAM/releases

"The site" is actually just their blog. The github repo at https://github.com/netbox-community/netbox is more like the real homepage and has a good presentation.

Sweet! If it ends up anything like Netbox it will be so sweet. By looking at the screenshots I am very excited to see this implemented!

NetBox Release v3.6.6 is now live (as of November 29, 2023)!

Take a look at netbox. https://netbox.dev/

Pre-trained systems dominate AI today (as deep as the P in GPT). My team and I have been researching and building alternatives given how the hallucination, blackbox and other problems don't seem solvable within* the current paradigm.

One of our first applications is a network automation solution for Netbox-- locally trained AI Agents unique to each Netbox account to predict roles of newly added devices given the current local list of devices, like a context-aware autocomplete.

Agents are lightweight by design, this particular Netbox Agent is 40-neuron, and when hooked up demo.netbox.dev and consistently gets 80%+ accuracy predicting device roles even when trained on ~60 devices only.

Try it out: https://aolabs-netbox.streamlit.app/

You can use dummy data from demo.netbox.dev. More on Netbox: https://github.com/netbox-community/netbox

We'd keen for feedback, if this is useful, how we could extend it if it is, or if it sparks other application ideas.

* Somebody has to be the pre-trainer, leaving an irreducible gap of misunderstanding between AI and its application which we are trying to diminish by adding a layer of local training.

Before upgrading, please: 1. Verify in release notes changelog if any new breaking changes might affect you. You can also review the NetBox Issues on GitHub to see if any new issues have arisen that might affect you. 2. Next, refer to the Upgrading to a new NetBox Release guide for steps to upgrade your instance.

I've been looking into some projects for some opensource software i use and noticed a few of them have empty __init__.py files (for example https://github.com/netbox-community/netbox/blob/develop/netbox/core/__init__.py)

IT wise, It's been a fair few years since I've been in a department that does asset management, we used to use GLPI with it's warts and all, which got replace with https://github.com/netbox-community/netbox