We want to get summary stats about the Kew herbarium by WCVP taxonomy at family level, using the herbarium data in GBIF.
Any field that is searchable in the GBIF data portal is also eligible for faceting, eg it is possible to get a summary report of the numbers of records in each country using this API call:
Though each occurrence record has a family field, it is not used for searching so cannot be used to facet.
This gist shows you how to use langchain to reformat text input data (representing specimens) into a structured output defined by a python class. For ease of use, it uses the groq API, so that no local installation of an LLM is required.
You'll need python and to install the langchain-groq package, which is specified in requirements.txt
You'll also need to sign up for a groq API key at https://console.groq.com/keys, and you'll need to store this key in an environment variable (GROQ_API_KEY) on your local system.
| 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/" */ |
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)
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 used to manage notes and tasks, with the citations plugin used to access literature references from the Zotero biblatex format export.
| 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] |