nickynicolson

Problem

Top 1-3 problems that you want to solve

Solution

Outline proposed solution for each problem

Unique value proposition

nickynicolson

javascript: Promise.all([import('https://unpkg.com/turndown@6.0.0?module'), import('https://unpkg.com/@tehshrike/readability@0.2.0'), ]).then(async ([{
    default: Turndown
}, {
    default: Readability
}]) => {

  /* Optional vault name */
  const vault = "";

  /* Optional folder name such as "Clippings/" */

nickynicolson

Set up a dask gateway and print the dashboard URL

import dask_gateway

cluster = dask_gateway.GatewayCluster()
client = cluster.get_client()
cluster.scale(8)
print(cluster.dashboard_link)

nickynicolson

Linking Obsidian and Zotero

Setup

Zotero

Zotero desktop used to manage literature references, with zotfile and zotero better bibtex plugins used to manage PDF attachments and create / maintain biblatex format downloads respectively.

Obsidian

Obsidian used to manage notes and tasks, with the citations plugin used to access literature references from the Zotero biblatex format export.

nickynicolson

bash

Default behaviour

• history shows numbered command history, most recent last
• !n retrieves command number n and executes it
• !n:p retrieves command number n and places it into the command history without executing it. Up arrow then retrieves the command for editing

shopt

nickynicolson

nickynicolson

nickynicolson

import networkx as nx
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import mplleaflet
import sys

def main():
    inputfile=sys.argv[1]
    outputfile_base=sys.argv[2]

nickynicolson

import pandas as pd
from pandas.io.json import json_normalize
import requests
# IH API documented here: https://github.com/nybgvh/IH-API/wiki
url='http://sweetgum.nybg.org/science/api/v1/institutions'

def main():
    response = requests.get(url)
    results = response.json()
    # The JSON format record for an IH record has nested sections - the 

nickynicolson

from sklearn.metrics import confusion_matrix
import pandas as pd

def cm2df(cm, labels):
    df = pd.DataFrame()
    # rows
    for i, row_label in enumerate(labels):
        rowdata={}
        # columns
        for j, col_label in enumerate(labels):