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git-from-the-bottom-up
- Git from the Bottom Up
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How Head Works in Git
Here's a great walk through for how Git works from the bottom up: https://jwiegley.github.io/git-from-the-bottom-up/
It's short, easy to understand and you'll understand HEAD.
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git-appraise – Distributed Code Review for Git
Very tangential:
Gerrit also stores some of its configs in a git repo. I was setting up a new instance, but couldn't get Admin permissions because the way my auth front-end didn't play well with the docker image's assumptions.
Gerrit already does a lot of its work via non-standard references. For example, you don't push to a branch, `refs/branches/foo`, you push to a separate `refs/for/foo` namespace that creates the review.
Similarly, Group config is stored in the All-Users git repo [1], but in references created after a UUID, in `refs/groups/UU/UUID`.
I ended up having a to exercise the plumbiest of plumbing commands [2] to create a new commit from scratch (from a tree, from the index, from blobs), to update the group ref to add myself to the Administrators group (this, of course, requires a local shell and permissions on the Gerrit host). It was a great way to exercise what I had learned in Git from the Bottom Up [3]
[1] https://gerrit-review.googlesource.com/Documentation/config-...
[2] https://git-scm.com/book/en/v2/Git-Internals-Git-Objects
[3] https://jwiegley.github.io/git-from-the-bottom-up/
- Setting up Huginn on Heroku
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Books for learning Git
I found Git from the Bottom Up helpful. It is very short as well. Then refer to the official book when you want more detail.
- Good git course and/or where to practice real life scenarios?
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the first time i had to deal with a huge git rebase conflict
I recently came across "Git from the Bottom Up by John Wiegley" (thanks to Coding Blocks podcast), he has a chapter about rebasing: https://jwiegley.github.io/git-from-the-bottom-up/1-Repository/7-branching-and-the-power-of-rebase.html
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Git-SIM: Visually simulate Git operations in your own repos with a single termi
You won't have to put your entire life on break in order to understand the fundamentals of git and why it works the way it works. Going through https://jwiegley.github.io/git-from-the-bottom-up/ and really understanding the material will take you a couple of hours at max, but will save you a lot of time in the future.
Wanting to understand things before using them is hardly elitism, not sure why you would think that.
Just like you probably don't want to fix bugs without understand the cause, it's hard to use a tool correctly unless you know how the tool works.
- What is the most efficient way of learning and comprehending Git?
PythonDataScienceHandbook
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About Data analyst, data scientist and data engineer, resources and experiences
Python Data Science Handbook
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Where to learn data science with python??
Python Data Science Handbook — learn to use Python libraries such as NumPy, Pandas, Matplotlib, Scikit-Learn, and related tools to effectively store, manipulate, and gain insight from data
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Book Recommendations
I don't know what tools you will be using but if you will be using Python you can start with Python Data Science Handbook by Jake VanderPlas and Data Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting DataData Science & Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data which gives a very good outlook on the data science and big data frame work. PS: Jake's book is also available as jupyter notebooks so you can read and run the code at the same time.
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Other programing options?
Python Data Science Handbook by Jake VanderPlas (https://jakevdp.github.io/PythonDataScienceHandbook/)
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Pathways out of GIS?
Otherwise you can work through courses on Datacamp, Coursera, Udemy, etc, or check out this book for a more general non-spatial perspective.
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Mastering Data Science: Top 10 GitHub Repos You Need to Know
7. Data Science Handbook Are you looking for a comprehensive guide to data science with Python? Look no further than the Data Science Handbook by Jake VanderPlas. This repository contains the entire book, which introduces essential tools and techniques used in data science, including IPython, NumPy, Pandas, Matplotlib, and Scikit-Learn. It’s a fantastic resource for anyone looking to deepen their understanding of data science concepts and best practices.
- Help a lady out (career advice(
- Resources for Current DE Interested in Learning Data Science
- Good book or course to learn Python for someone who is fluent in R?
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Python equivalent to R's ecosystem of open source educational materials
I can recommend https://jakevdp.github.io/PythonDataScienceHandbook/
What are some alternatives?
lisp-koans - Common Lisp Koans is a language learning exercise in the same vein as the ruby koans, python koans and others. It is a port of the prior koans with some modifications to highlight lisp-specific features. Structured as ordered groups of broken unit tests, the project guides the learner progressively through many Common Lisp language features.
django-livereload-server - Livereload functionality integrated with your Django development environment.
devdocs - API Documentation Browser
Exercism - Scala Exercises - Crowd-sourced code mentorship. Practice having thoughtful conversations about code.
mark-sweep - A simple mark-sweep garbage collector in C
Serpent.AI - Game Agent Framework. Helping you create AIs / Bots that learn to play any game you own!
git-appraise - Distributed code review system for Git repos
lego-mindstorms - My LEGO MINDSTORMS projects (using set 51515 electronics)
git-fire - :fire: Save Your Code in an Emergency
OSQuery - SQL powered operating system instrumentation, monitoring, and analytics.
emlop - EMerge LOg Parser