Category: Computers

All things computing.

List the Roles for a User or Service Account in a Specific GCP Project

Posted on by rchapin

If you do not have web console permissions to do so, but have the ability to activate a service account that has the viewer permissions or IAM permissons to list IAM roles in a given project, the following is how you can list the roles for a given user or service account.

gcloud projects get-iam-policy <gcp-project> \
--filter="bindings.members:<email-address>" \
--flatten="bindings[].members" --format="table(bindings.role)"

Compiling Python Under Linux

Posted on by rchapin

The following should work with just about any version of Python. I am using it to compile, currently 3.10.x, on distros where those packages are not readily available for installation. The following is a quick how to on getting it compiled under both RedHat/CentOS/Almalinux and Debian based systems.

Download the Tarball for the Version You Want To Install

Download the tar.gz archive for the version that you want to install from here. Verify the download and then save the path to this file for later.

Install Dependencies

This assumes that you already have the “build-essentials” and kernel headers installed on the box, which is an exercise for the reader.

RedHat/CentOS/Almalinux

yum install -y bzip2-devel expat-devel gdbm-devel ncurses-devel openssl-devel readline-devel wget sqlite-devel tk-devel xz-devel zlib-devel libffi-devel gmp-devel libmpc-devel mpfr-devel openssl-devel liblzma-devel

Debian

apt install -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libsqlite3-dev libreadline-dev libffi-dev curl libbz2-dev liblzma-dev

Compile Python

The following enables a non-root user to unpack, compile, and install it into their home directory. Copy this file to /var/tmp/compile-python.sh and then run as follows

/var/tmp/compile-python.sh <path-to-tarball>
#!/bin/bash

set -u
set -e

# The path to the downloaded tarball
py_tarball=$1

export PY_DIR=$(echo $py_tarball | awk -F/ '{ print $NF }' | sed 's/.tgz//')
export PY_PREFIX=$(echo ~/usr/local/$PY_DIR | tr [:upper:] [:lower:])

mkdir -p ~/usr/local/src ~/usr/local/bin ~/usr/local/include $PY_PREFIX
rm -rf $PY_PREFIX
tar -xzf $py_tarball -C ~/usr/local/src/
cd ~/usr/local/src/$PY_DIR
./configure --prefix=$PY_PREFIX --exec-prefix=$PY_PREFIX
make && make install

Add the following to your PATH in ~/.bash_profile

PYTHON_HOME=~/usr/local/python-<version>

export PATH=$PATH:$PYTHON_HOME/bin

Using fc to Edit and Re-execute Bash Commands

Posted on by rchapin

I recently learned about the Bash built-in fc. It is a great tool that enables you to edit and re-execute commands from your bash history.

Oftentimes there is a command in your history that instead of just grepping through the history and then re-executing as-is you’ll want to make a modification or two. With fc you can first edit it in your favorite editor and then when closing the editor fc will execute the command.

For me, vim is my editor of choice. Add the following to your .bashrc and fc will automatically open vim for you.

export FCEDIT=vim

Then, simply run fc passing it the id of the command in your history that you want to edit and then execute.

fc 1234

Creating a Launch Config in VSCode to Debug a Python Invoke Script

Posted on by rchapin

I regularly use Python Invoke and Fabric for the automation of various tasks; from deploying code to developing my own set of tools for various projects. Following is an example on how to write a launch.json launch configuration for vscode so that you can step through the tasks.py code and debug it.

Assuming that you have created a virtual environment and pip installed invoke into it. And, assuming that you have defined a task in your tasks.py file as follows:

from invoke import task

@task()
def do_something(ctx, some_path, some_other_path):
    # Do something with data in these dirs . . .

The following is a template you can use for a launch configuration that you can use to debug your task. 

{
  "version": "0.2.0",
  "configurations": [
    {
      "name": "invoke",
      "type": "python",
      "request": "launch",
      // The complete path to the invoke python script in your virtual environment
      "program": "/my/virtualenv/path/bin/invoke",
      "justMyCode": false,
      // The args that you would otherwise enter on the command line
      // when invoking your task
      "args": [
        "do-something",
        "--some-path",
        "/var/tmp/a/",
        "--some-other-path",
        "/var/tmp/b/"
      ],
      "cwd": "/the/path/to/the/dir/that/contains/your/tasks/script",
    }
  ]
}

Using bq load Command to Load logicalType Partitioned Data into a BigQuery Table

Posted on by rchapin

Following is the syntax and bq load command that you need to issue if you want to load data in avro file into a partitioned BigQuery table based on avro field defined as a logicalType.

Given the following schema

{
  "type" : "record",
  "name" : "logicalType",
  "namespace" : "com.ryanchapin.tests",
  "fields" : [ {
    "name" : "id",
    "type" : [ "null", "string" ],
    "default" : null
  }, {
    "name" : "value",
    "type" : [ "null", "long" ],
    "default" : null
  }, {
    "name" : "day",
    "type" : {
      "type" : "int",
      "logicalType" : "date"
    }
  }
}

And the following BigQuery schema

[
  {
    "name": "id",
    "mode": "NULLABLE",
    "type": "STRING"
  },
  {
    "name": "value",
    "mode": "NULLABLE",
    "type": "INT64"
  },
  {
    "name": "day",
    "mode": "REQUIRED",
    "type": "DATE"
  }
]

Assuming that you have a correct avro data file (an exercise for the reader) that contains records that include values in the day column that are the number of days since the epoch, you can run the following bq load command to load that data into your table.

 bq --project_id my_project load --source_format=AVRO --time_partitioning_type=DAY --time_partitioning_field=day --use_avro_logical_types my_dataset.my_table gs://my_bucket/*.avro

Flush Commands to BASH History Immediately

Posted on by rchapin

I cannot take credit for figuring this one out. Original post is here.

TLDR; is to add the following to your ~/.bashrc

export PROMPT_COMMAND='history -a'

Following are the history configs that I use

######################################################################
shopt -s histappend
HISTSIZE=-1
HISTFILESIZE=-1
HISTCONTROL=ignoreboth
HISTTIMEFORMAT="[%F %T] "
export PROMPT_COMMAND='history -a'
######################################################################

Setting Per File Type Tab Configurations in VSCode

Posted on by rchapin

If you would like to have different tab configurations (tabs or spaces) along with the number of tab chars for different file types you can update your user settings.

The first thing you need to do is figure out what the file type code thinks the file that you want to change is. Open the file in vscode and then look at the bottom right of your window. In my case, I’m looking at an avro schema (.avsc) file:

In this case, code sees this file type as “JSON with Comments” and is configured to use spaces with 2 spaces per “tab”.

In order to change that, press CTRL+Shift+P and select “Preferences: Configure Language Specific Settings”. You will then be presented with a host of file types. Scroll down to the entry you want (JSON with comments) and take note of of the string within the parenthesis. That is the key that you will need to make an entry into settings.json. If you click on that entry it will open up your user settings.json. I was baffled by what to do next until I saw this stackoverflow post.

Once I read that, I knew what to add to the settings.json. Simply add a new key, defined at the root of the JSON object that is the string displayed in the parenthesis that you saw for the file type in the dropdown that was displayed after selecting “Preferences: Configure Language Specific Settings”.

The JSON in settings.json will look like the following

   "[jsonc]": {
        "editor.tabSize": 2,
        "editor.detectIndentation": false,
        "editor.insertSpaces": true,
        "editor.quickSuggestions": {
            "strings": true
        },
        "editor.suggest.insertMode": "replace",
        "gitlens.codeLens.scopes": [
            "document"
        ]
    }

Check the language specific settings docs for the configuration options.

VSCode Keyboard Shortcut to Toggle Visibility of the Explorer Side Panel

Posted on by rchapin

I usually have at least two panes in my IDE so that I can see two files, or different parts of the same file, at the same time. VSCode pegs the debug variables in the Explorer side bar so I also end up having to make that panel large at times to see the variables while debugging.

Following are the keybindings that you can add to enable you to toggle the visibility of the left-hand side panel.

Add the following to the keybindings.json file by typing CTRL+Shift+P and then enter Open Keyboard Shortcuts (JSON)

Under Linux this file should be in ~/.config/Code/User/keybindings.json

    {
        "key": "cmd+b",
        "command": "workbench.view.explorer"
    },
    {
        "key": "cmd+b",
        "command": "-workbench.view.explorer"
    },
    {
        "key": "cmd+b",
        "command": "workbench.action.toggleSidebarVisibility",
        "when": "explorerViewletVisible"
    },
    {
        "key": "cmd+b",
        "command": "-workbench.action.toggleSidebarVisibility",
        "when": "explorerViewletVisible"
    }
© 2005 Ryan Chapin