kchawla-pi

# Source: https://github.com/conda/conda/issues/7791#issuecomment-945676641
# Add this in .bashrc or .zshrc to deny the install commands if you are in the base environment.

# From https://github.com/conda/conda/issues/7791#issuecomment-946537246
# One case where this does not prevent from installing to base:
# If one uses pip in a conda environment, that has no pip installed, it will still install all the packages into the base environment.
# This may happen when an empty environment is created and then one simply runs pip install -r requirements.txt. 

# TODO: Do a `which pip` & compare it to conda base env path as an additional check for the pip() function.

kchawla-pi

from concurrent.futures import ThreadPoolExecutor, as_completed
import json
import urllib.request

with open('webapp.json', encoding='utf-8') as f:
    config = json.loads(f.read())

URLS = [
    'http://localhost:%d/?ident=%d' % (config['port'], ident)
    for ident in range(1, 1001)

kchawla-pi

# Install latest version nvidia-docker2 on PopOS 22.04
## PopOS does not take the latest upstream NVIDIA Container runtime which is needed to run the container
## Run the below steps

### Add a new preference entry in /etc/apt/preferences.d/pop-default-settings

Package: *
Pin: origin nvidia.github.io
Pin-Priority: 1002

kchawla-pi

#!/bin/bash

set -e

sudo apt-get -y install libsecret-1-0 libsecret-1-dev libglib2.0-dev
sudo make --directory=/usr/share/doc/git/contrib/credential/libsecret
git config --global credential.helper /usr/share/doc/git/contrib/credential/libsecret/git-credential-libsecret

kchawla-pi

sudo apt update
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt install nvidia-driver-535-server
sudo apt install linux-modules-nvidia-535-server-generic
sudo apt-cache policy linux-modules-nvidia-535-server-$(uname -r)
sudo apt install linux-modules-nvidia-535-server-generic
sudo reboot
sudo apt update
sudo lsmod | grep nouveau
sudo lsmod | grep nvidia

kchawla-pi

Implementing a basic plugin architecture shouldn't be a complicated task. The solution described here is working but you still have to import every plugin (inheriting from the base class).

This is my solution:

Basic project structure

$ tree

kchawla-pi

nats: encountered error
Traceback (most recent call last):
  File "/root/.local/lib/python3.10/site-packages/nats/aio/client.py", line 1301, in _select_next_server
    await self._transport.connect(
  File "/root/.local/lib/python3.10/site-packages/nats/aio/transport.py", line 118, in connect
    r, w = await asyncio.wait_for(
  File "/usr/local/lib/python3.10/asyncio/tasks.py", line 445, in wait_for
    return fut.result()
  File "/usr/local/lib/python3.10/asyncio/streams.py", line 48, in open_connection
    transport, _ = await loop.create_connection(

kchawla-pi

from pathlib import Path

text = Path(text_filepath).read_text()
image_data = Path(binary_filepath).read_bytes()

kchawla-pi

from pprint import pprint

import numpy as np
import pandas as pd


def fill_first_base_price_of_above_one_window(df, indices):
    df["window_base_price"].at[indices[-1]] = df["base_price"].at[indices[0]]

kchawla-pi

import warnings


def view_connectome(adjacency_matrix, 
                    node_coords, 
                    edge_threshold=None,
                    edge_cmap=cm.cyan_orange, 
                    symmetric_cmap=True,
                    linewidth=6., 
                    node_size=3.,