Learning Log on JinerX blog

Docker Operations Cheatsheet

Thu, 26 Mar 2026 12:21:52 +0100

Theory
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namespaces - abstraction which makes it possible for the system to isolate processes from one another. Processes internally store a pointer to a namespaces when calling specified commands “dealing with” a specific kernel resource it first checks for appropriate namespace and returns appropriate data. Some important namespaces:
- PID namespaces - process isolation - container can only see processes made inside the container
- network namespace - netowork isolation - each container gets it’s own ports,ip addresses, etc. Connected via docker0 bridge to the host network.
- mount namespace - filesystem isolation - each container gets it’s own filesystem hierarchy, mount points etc.
cgroups - used to limit the system resources available to the container, CPU, memory etc.
union mount filesystem - filesystem technique used in docker containers. We define the filesystem in multiple layers (defined typically in Dockerfile) during build we only look at the “top”. If conflicting upper layers overwrite the lower layers. All layers beside the top one are read only, the top one is read/write.
docker daemon - runs in the background and manages the containers, volumes etc. We communicate with it via CLI. If docker is installed on linux we communicate with it via exposed socket at /var/run/docker.sock. If installed on a different system a virtual machine with linux is setup and we communicate with the docker via socket at the same location but within the VM.

Basic structures
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images - contain information about how to build the container.
containers - working instances where we actually operate and that do the “actual” work.
volumes - data storage objects can be mounted onto containers
networks - define how containers communicate with each other

Basic commands
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with all of those --help flag lists all available commands with a short description

Git Operations Cheatsheet

Sun, 22 Mar 2026 15:46:00 +0100

basics and setup
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git --version = git -v - get currently installed version
git status - see status
git init - initialize a repository in the current folder
git config - change configuration file, add --global for editing the global config
git add <file_name> - move the specified file to the staging area
git commit -m "<message>" - commiting the files currently in the staging area, if -m is not used then text editor will open for message

`.git` folder
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.git folder is created in every repository. It contains data necessary for the git to operate. Some of the more interesting things:

Local search

Thu, 19 Mar 2026 19:04:21 +0100

Local search is a simple approximation algorithm, which doesn’t necessarirly lead to the best result, instead it has a tendency to get stuck in a local minimum. Still if combined with other techniques like for example use of heuristics it can cheaply with low overhead improve the quality of the found solution.

pseudocode:

function local_search:
INPUT: graph of the state G = (V,E), cost function f
OUTPUT: found state

s <- generate_initial_state()

while (true): // we might want iteration amount limit in case the state space is infinite and the optimum unreachable
 s' <- s
 for n in get_neighbors(s):
 if f(n) < f(s'):
 s' <- n
 if (s' /= s):
 s <- s'
 else:
 break
return s

This pseudocode was written for a graph but can easily be generalized to any general solution space. Simply instead of looking at neighbours of a state we at states we can possibly “go to”.

Minimum Spanning Tree

Wed, 18 Mar 2026 16:25:43 +0100

Here we’re going to cover what are Minimum Spanning Trees (MSTs), methods for finding them and use cases.

What is a tree?
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In graph theory we call graph $T=(V,E)$ a tree if it is connected and it doesn’t have any cycles.

Forrest

We call a graph with no cycles a forrest (contrary to the tree it doesn’t need to be connected). In a forrest each connected component is a tree.

Introduction to Turing Machines

Fri, 06 Mar 2026 20:00:47 +0100

Here we’re going to cover the very basics of what are turing machines and what they are used for. To understand this post it’s best to be familiar with finite automata DFAs, NFAs, regular languages and context free grammars.

Motivation
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We as programmers want to use mathematics to study algorithms efficiently, but for that we need a formal mathematical notion of what an algorithm is. Additionally we want a way to figure out if a problem is computable - does there exist an algorithm solving a problem. Because of that we need some sort of mathematical entity where the notion of algorithms makes formal sense and which allows us to analyze those algorithms. This mathematical entity is the Turing Machine (TM).

Groups Abstract Algebra

Thu, 05 Mar 2026 17:25:33 +0100

Here we consider definition of a group and some simple properties, operations, examples.

Fromal definition
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Group
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A pair $(X, +)$ is called a group if $X$ is a set, $+$ is a function $+:X\times X\to X$ and:

operations are associative: $a + (b + c) = (a + b) + c$
X has an identity element 0 such that $\forall x\in X$ $x + 0 = 0 + x = x$
each element $x$ has an inverse $x^{-1}$: $x+ x^{-1} = x^{-1}+ x = 0$

Semigrups
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Semigroup is a wekaer structure than the group it does not require:

Learning Log on JinerX blog

Docker Operations Cheatsheet

Theory #

Basic structures #

Basic commands #

Git Operations Cheatsheet

basics and setup #

.git folder #

Local search

Minimum Spanning Tree

What is a tree? #

Introduction to Turing Machines

Motivation #

Groups Abstract Algebra

Fromal definition #

Group #

Semigrups #

Theory
#

Basic structures
#

Basic commands
#

basics and setup
#

`.git` folder
#

What is a tree?
#

Motivation
#

Fromal definition
#

Group
#

Semigrups
#