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@willirath
willirath / SLURMCluster_vs_Singularity.ipynb
Last active July 30, 2025 13:57
Dask-Jobqueue SLURMCluster with Singularity
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@andersy005
andersy005 / PDFs.md
Last active May 27, 2020 01:02
Working with PDFs
@rabernat
rabernat / xarray_anomaly_calculations.ipynb
Created November 27, 2019 16:34
Xarray Anomaly Calculations
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@tatianamac
tatianamac / tatiana-mac-speaker-rider.md
Last active April 22, 2025 22:44
Tatiana Mac's Speaker Rider

Speaker Rider

by Tatiana Mac

Last updated 14 April 2021

What is a speaker rider?

As speaking comes with immense privilege, I have crafted a speaker rider to set expectations and boundaries around my engagement. I am grateful to all the conference organisers who have brilliantly hosted me. I would love to continue to exercise this privilege to speak at conferences, and use this privilege to make the landscape more accessible and beneficial to tech's most historically excluded and marginalised communities.

Considerations

😫 I provide a lot of explanations for those of you who never had to consider these things. Most thoughtful conferences I've attended check most of these boxes intrinsically, particularly when conference runners are experienced speakers. They get it.

@Seneral
Seneral / 0 Warning.md
Last active August 7, 2022 16:57
DOESN'T WORK ANYMORE - for workaround see https://gist.github.com/p3g4asus/597050997e01f8fd1fcf473fe6545a4fModified VLC YouTube playlist parsing script to support playlists with more than 200 videos. Verified it works with 1000+ videos, no duplicates and all included (minus deleted videos). Official version claims to support 100+, but actually o…
@wolfv
wolfv / run_conda_builds.py
Created July 28, 2019 18:13
Run many conda builds in parallel, as fast as possible.
from pathlib import Path
import jinja2
import yaml
from conda.models.match_spec import MatchSpec
import networkx as nx
# import matplotlib.pyplot as plt
import os, random, time, json
import workerpool
NO_BUILD_LOCAL_PKGS = True
@rabernat
rabernat / zarr_over_http.ipynb
Last active July 16, 2019 18:12
Zarr over http
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@jayascript
jayascript / data-science-process.md
Last active October 8, 2020 15:10
A basic outline of the steps I take to go from raw data to deployed model.

Data Science Process

Steps to take for a comprehensive analysis.

Stage 1: Define

Project background.

Step 1.1: Describe.

# See https://www.anaconda.com/understanding-and-improving-condas-performance/ for more info.
# help debug channel issues
show_channel_urls: true
# pip will always be installed with python
add_pip_as_python_dependency: true
# strict priority and conda-forge at the top will ensure
# that all of your packages will be from conda-forge unless they only exist on defaults
@micahhausler
micahhausler / jq-filter.sh
Last active September 21, 2023 07:27
GitHub collaborator finder
# Go to https://developer.github.com/v4/explorer/ and enter the graphql query with the query veriable:
# {"queryString": "your-githubuser-name"}
cat results.json |
jq '.data.user.repositories.edges[] | { Count: .node.collaborators.totalCount, Repo: .node.name} | select(.Count > 2)'