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    <dc:date>2025-08-25T10:19:04+00:00</dc:date>
    <link>https://github.com/unkyulee/micro-journal</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[A repo of single task portable computer using raspberry pi. A potential successor to the sony Vaio P.]]></description>
<dc:subject>python diy raspberrypi 3d 3dprinting keyboard electronics</dc:subject>
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    <dc:creator>nico.ash</dc:creator><dc:subject>gis mapping maps programming python</dc:subject>
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    <link>https://blog.thea.codes/raster-vectorization-with-python/</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>electronics graphics vector pcb python</dc:subject>
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    <title>Pretty maps in Python | Hacker News</title>
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    <link>https://news.ycombinator.com/item?id=32170624</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>gis geo map mapping python</dc:subject>
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    <title>GitHub - crides/sqdg: Shoggot's SQDG but in CadQuery</title>
    <dc:date>2022-04-04T01:29:31+00:00</dc:date>
    <link>https://github.com/crides/sqdg</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>3d keycaps python keyboard</dc:subject>
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    <title>GitHub - DHI-GRAS/terracotta: A light-weight, versatile XYZ tile server, built with Flask and Rasterio</title>
    <dc:date>2021-07-28T11:39:01+00:00</dc:date>
    <link>https://github.com/DHI-GRAS/terracotta</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Terracotta is a pure Python tile server that runs as a WSGI app on a dedicated webserver or as a serverless app on AWS Lambda. It is built on a modern Python 3.6 stack, powered by awesome open-source software such as Flask, Zappa, and Rasterio.]]></description>
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    <dc:creator>nico.ash</dc:creator><description><![CDATA[Dactyl Manuform re-implemented in python, to design a high profile case.]]></description>
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    <title>GitHub - DidierRLopes/GamestonkTerminal: The next best thing after Bloomberg Terminal</title>
    <dc:date>2021-02-25T08:40:17+00:00</dc:date>
    <link>https://github.com/DidierRLopes/GamestonkTerminal</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[« The next best thing to a bloomberg terminal »]]></description>
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    <title>GitHub - AbnormalDistributions/e_paper_weather_display: Raspberry Pi weather display using Waveshare e-paper display and Open Weather Map API</title>
    <dc:date>2020-11-08T00:39:52+00:00</dc:date>
    <link>https://github.com/AbnormalDistributions/e_paper_weather_display</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Raspberry Pi weather display using Waveshare e-paper 7.5 inch display, Open Weather Map API, and Python. ]]></description>
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    <title>JSON Web Tokens - jwt.io</title>
    <dc:date>2020-07-17T09:45:29+00:00</dc:date>
    <link>https://jwt.io/#libraries-io</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>java python jwt libraries</dc:subject>
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<item rdf:about="https://github.com/JaidedAI/EasyOCR">
    <title>JaidedAI/EasyOCR: Ready-to-use OCR with 40+ languages supported including Chinese, Japanese, Korean and Thai</title>
    <dc:date>2020-07-08T15:13:57+00:00</dc:date>
    <link>https://github.com/JaidedAI/EasyOCR</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Usage

import easyocr
reader = easyocr.Reader(['th','en'])
reader.readtext('test.jpg')

Note: Instead of filepath 'test.jpg', you can also pass OpenCV image object or image file as bytes.

Model weight for chosen language will be automatically downloaded or you can download it manually from the following links and put it in '~/.EasyOCR/model' folder]]></description>
<dc:subject>ai github ocr opensource python</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
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<item rdf:about="https://github.com/tehmaze/diagram">
    <title>tehmaze/diagram: Text mode diagrams using UTF-8 characters and fancy colors</title>
    <dc:date>2020-06-10T14:20:35+00:00</dc:date>
    <link>https://github.com/tehmaze/diagram</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Text mode diagrams using UTF-8 characters and fancy colors (using Python).

Features

    Axial graphs
    Horizontal and vertical bar graphs
    Supports both 3 bit (16 color) and 8 bit (256 color) mode colors with various pre-defined palettes (see below)
    UTF-8 text graphics
]]></description>
<dc:subject>art cli github python visualization</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:21c773e28959/</dc:identifier>
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<item rdf:about="https://www.roguelynn.com/words/asyncio-we-did-it-wrong/">
    <title>asyncio: We Did It Wrong – roguelynn</title>
    <dc:date>2020-06-02T00:33:49+00:00</dc:date>
    <link>https://www.roguelynn.com/words/asyncio-we-did-it-wrong/</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[The Tutorial: Mayhem Mandrill

So having lived through that and survived, allow me to provide you a real-world example that actually comes from the real world. As I mentioned, one of the asyncio services we built is similar to a chaos monkey to do periodic hard restarts of our entire fleet of instances. We’ll build a simplified version, dubbing it “Mayhem Mandrill” which will listen for a pub/sub message as a trigger to go ahead and restart a host based off of that message. As we build this service, I’ll point out potential traps to avoid. This will essentially become the type of resource that past Lynn would have wanted a year or two ago.]]></description>
<dc:subject>async programming python</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
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<item rdf:about="https://bhavaniravi.com/blog/apache-airflow-introduction">
    <title>An Introduction to Apache Airflow</title>
    <dc:date>2020-06-02T00:31:47+00:00</dc:date>
    <link>https://bhavaniravi.com/blog/apache-airflow-introduction</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[An Introduction to Apache Airflow
What is Airflow?

    Airflow is a platform created by the community to programmatically author, schedule, and monitor workflows. 

Machine learning is the hot topic of the industry. It won't be so cool if not for the data processing involved

Airflow is an ETL(Extract, Transform, Load) workflow orchestration tool, used in data transformation pipelines.]]></description>
<dc:subject>automation python workflow</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:aeb28594efd7/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:automation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:workflow"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://vorpus.org/blog/notes-on-structured-concurrency-or-go-statement-considered-harmful/#nurseries-a-structured-replacement-for-go-statements">
    <title>Notes on structured concurrency, or: Go statement considered harmful — njs blog</title>
    <dc:date>2020-06-02T00:29:37+00:00</dc:date>
    <link>https://vorpus.org/blog/notes-on-structured-concurrency-or-go-statement-considered-harmful/#nurseries-a-structured-replacement-for-go-statements</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[

In this post, I want to convince you that nurseries aren't quirky or idiosyncratic at all, but rather a new control flow primitive that's just as fundamental as for loops or function calls. And furthermore, the other approaches we saw above – thread spawning and callback registration – should be removed entirely and replaced with nurseries.]]></description>
<dc:subject>async python</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:8a8f2ad8788c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:async"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://snarky.ca/how-the-heck-does-async-await-work-in-python-3-5/">
    <title>How the heck does async/await work in Python 3.5?</title>
    <dc:date>2020-06-02T00:27:37+00:00</dc:date>
    <link>https://snarky.ca/how-the-heck-does-async-await-work-in-python-3-5/</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Being a core developer of Python has made me want to understand how the language generally works. I realize there will always be obscure corners where I don't know every intricate detail, but to be able to help with issues and the general design of Python I feel like I should try and understand its core semantics and how things work under the hood.

But until recently I didn't understand how async/await worked in Python 3.5. I knew that yield from in Python 3.3 combined with asyncio in Python 3.4 had led to this new syntax. But having not done a lot of networking stuff -- which asyncio is not limited to but does focus on -- had led to me not really paying much attention to all of this async/await stuff. ]]></description>
<dc:subject>async python tutorial</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:6a10d205d0d5/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:async"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:tutorial"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/kotartemiy/newscatcher/blob/master/README.md">
    <title>newscatcher/README.md at master · kotartemiy/newscatcher</title>
    <dc:date>2020-06-02T00:22:40+00:00</dc:date>
    <link>https://github.com/kotartemiy/newscatcher/blob/master/README.md</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Newscatcher

Programmatically collect normalized news from (almost) any website.

Filter by topic, country, or language.

Created by newscatcherapi.com but you do not need anything from us or from anyone else to get the software going, it just works out of the box.]]></description>
<dc:subject>api library news python scraping</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:55e2e87f8a22/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:api"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:library"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:news"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:scraping"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://airflow.apache.org/">
    <title>Apache Airflow</title>
    <dc:date>2020-05-28T19:55:58+00:00</dc:date>
    <link>https://airflow.apache.org/</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. ]]></description>
<dc:subject>apache python workflow</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:48c565fd0dbd/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:apache"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:workflow"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://hynek.me/articles/waiting-in-asyncio/">
    <title>Waiting in asyncio · Homepage of Hynek Schlawack</title>
    <dc:date>2020-05-25T23:33:23+00:00</dc:date>
    <link>https://hynek.me/articles/waiting-in-asyncio/</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[One of the main appeals of using Python’s asyncio is being able to fire off many coroutines and run them concurrently. How many ways do you know for waiting for their results?

There’s quite a bit of them! However the different ways have different properties and all of them deserve their place. However I regularly have to look them up to find the right one
.]]></description>
<dc:subject>async python</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:0d17be4d3fd1/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:async"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/simonw/datasette">
    <title>simonw/datasette: A tool for exploring and publishing data</title>
    <dc:date>2020-05-25T10:07:33+00:00</dc:date>
    <link>https://github.com/simonw/datasette</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[A tool for exploring and publishing data

Datasette is a tool for exploring and publishing data. It helps people take data of any shape or size and publish that as an interactive, explorable website and accompanying API.

Datasette is aimed at data journalists, museum curators, archivists, local governments and anyone else who has data that they wish to share with the world.

Explore a demo, watch a video about the project or try it out by uploading and publishing your own CSV data.

    Comprehensive documentation: http://datasette.readthedocs.io/
    Examples: https://github.com/simonw/datasette/wiki/Datasettes
    Live demo of current master: https://latest.datasette.io/
]]></description>
<dc:subject>api database json python sqlite</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:2cdfe47adffe/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:api"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:database"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:json"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:sqlite"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/minimaxir/aitextgen">
    <title>minimaxir/aitextgen: A robust Python tool for text-based AI training and generation using GPT-2.</title>
    <dc:date>2020-05-20T17:30:13+00:00</dc:date>
    <link>https://github.com/minimaxir/aitextgen</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[A robust Python tool for text-based AI training and generation using OpenAI's GPT-2 architecture.

aitextgen is a Python package that leverages PyTorch, Huggingface Transformers and pytorch-lightning with specific optimizations for text generation using GPT-2, plus many added features. It is the successor to textgenrnn and gpt-2-simple, taking the best of both packages:

    Finetunes on a pretrained 124M GPT-2 model from OpenAI...or create your own GPT-2 model + tokenizer and train from scratch!
    Generates text faster than gpt-2-simple and with better memory efficiency! (even from the 1.5B GPT-2 model!)
    With Transformers, aitextgen preserves compatibility with the base package, allowing you to use the model for other NLP tasks, download custom GPT-2 models from the Huggingface model repository, and upload your own models! Also, it uses the included generate() function to allow a massive amount of control over the generated text.
    With pytorch-lightning, aitextgen trains models not just on CPUs and GPUs, but also multiple GPUs and (eventually) TPUs! It also includes a pretty training progress bar, with the ability to add optional loggers.
    The input dataset is its own object, allowing you to not only easily encode megabytes of data in seconds, cache, and compress it on a local computer before transporting to a remote server, but you are able to merge datasets without biasing the resulting dataset, or cross-train on multiple datasets to create blended output.

You can read more about aitextgen in the documentation!]]></description>
<dc:subject>ai python textgeneration deeplearning</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:0ca61341fb79/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:ai"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:textgeneration"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:deeplearning"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/willmcgugan/rich">
    <title>GitHub - willmcgugan/rich: Rich is a Python library for rich text and beautiful formatting in the terminal.</title>
    <dc:date>2020-05-16T09:36:27+00:00</dc:date>
    <link>https://github.com/willmcgugan/rich</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[The Rich API makes it easy to add colorful text (up to 16.7 million colors) with styles (bold, italic, underline etc.) to your script or application. Rich can also render pretty tables, progress bars, markdown, syntax highlighted source code, and tracebacks -- out of the box.]]></description>
<dc:subject>cli programming python shell terminal</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:b9bced7bf2d8/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:cli"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:programming"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:shell"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:terminal"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://zulko.github.io/moviepy/">
    <title>User Guide — MoviePy 1.0.2 documentation</title>
    <dc:date>2020-04-29T00:14:33+00:00</dc:date>
    <link>https://zulko.github.io/moviepy/</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[MoviePy is a Python module for video editing, which can be used for basic operations (like cuts, concatenations, title insertions), video compositing (a.k.a. non-linear editing), video processing, or to create advanced effects. It can read and write the most common video formats, including GIF.]]></description>
<dc:subject>editing python video</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:035d7627f28c/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:editing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:video"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/caoscott/SReC">
    <title>GitHub - caoscott/SReC: PyTorch Implementation of &quot;Lossless Image Compression through Super-Resolution&quot;</title>
    <dc:date>2020-04-07T21:43:29+00:00</dc:date>
    <link>https://github.com/caoscott/SReC</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[This is the official implementation of SReC in PyTorch. SReC frames lossless compression as a super-resolution problem and applies neural networks to compress images. SReC can achieve state-of-the-art compression rates on large datasets with practical runtimes. Training, compression, and decompression are fully supported and open-sourced.]]></description>
<dc:subject>compression imageprocessing machine-learning machinelearning image optimisation python</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:203d83862f84/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:compression"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:imageprocessing"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:machine-learning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:machinelearning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:image"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:optimisation"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/tobilg/python-lambda-layer-builder">
    <title>GitHub - tobilg/python-lambda-layer-builder: A build tool for creating optimized Python AWS Lambda layers</title>
    <dc:date>2020-04-01T06:25:03+00:00</dc:date>
    <link>https://github.com/tobilg/python-lambda-layer-builder</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Creates an AWS Lambda Layers structure that is optimized for: Lambda Layer directory structure, compiled library compatibility, and minimal file size.

This repo was created to address these issues:

    Many methods of creating Lambda zip files for Python functions don't work for Lambda Layers
        This is due to the fact Lambda Layers require specific library paths within the zip, where regular Lambda zips don't
    Compiled dependencies must be created in an environment that matches the Lambda runtime
    Reduce size of the layer by removing unnecessary libraries and files

Note: This script requires Docker and uses a container to mimic the Lambda environment.]]></description>
<dc:subject>python aws amazon</dc:subject>
<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:edb99dd2cf75/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:aws"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:amazon"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://news.ycombinator.com/item?id=22167121">
    <title>Ask HN: What are some interesting projects to reuse your old devices? | Hacker News</title>
    <dc:date>2020-02-15T10:37:39+00:00</dc:date>
    <link>https://news.ycombinator.com/item?id=22167121</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>service programming python diy ios server</dc:subject>
<dc:identifier>https://pinboard.in/u:nico.ash/b:27bbdaed0ea0/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:service"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:programming"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:diy"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:ios"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:server"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://martinheinz.dev/blog/13">
    <title>Martin Heinz - Personal Website &amp; Blog</title>
    <dc:date>2020-01-14T07:08:53+00:00</dc:date>
    <link>https://martinheinz.dev/blog/13</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>performance programming python</dc:subject>
<dc:identifier>https://pinboard.in/u:nico.ash/b:8423a01a40bb/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:performance"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:programming"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://info.crunchydata.com/blog/dynamic-vector-tiles-from-postgis">
    <title>Serving Dynamic Vector Tiles from PostGIS</title>
    <dc:date>2020-01-03T09:44:35+00:00</dc:date>
    <link>https://info.crunchydata.com/blog/dynamic-vector-tiles-from-postgis</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Serving Dynamic Vector Tiles from PostGIS
July 09, 2019 PAUL RAMSEY  PostgreSQL PostGIS
One of the most popular features of PostGIS 2.5 was the introduction of the "vector tile" output format, via the ST_AsMVT() function.
Vector tiles are a transport format for efficiently sending map data from a server to a client for rendering. The vector tile specification describes how raw data are quantized to a grid and then compressed using delta-encoding to make a very small package.
Prior to ST_AsMVT(), if you wanted to produce vector tiles from PostGIS you would use a rendering program (MapServer, GeoServer, or Mapnik) to read the raw data from the database, and process it into tiles.
Minimal Tile Architecture

With ST_AsMVT() it is now possible to move all that processing into the database, which opens up the possibility for very lightweight tile services that do little more than convert map tile requests into SQL for the database engine to execute


Here is a sample python to serve these vector tiles.]]></description>
<dc:subject>postgis vector map gis python</dc:subject>
<dc:identifier>https://pinboard.in/u:nico.ash/b:5e8fb83094ee/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:postgis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:vector"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:map"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:gis"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://nanonets.com/blog/ocr-with-tesseract/">
    <title>[Tutorial] OCR in Python with Tesseract, OpenCV and Pytesseract</title>
    <dc:date>2019-12-20T15:38:12+00:00</dc:date>
    <link>https://nanonets.com/blog/ocr-with-tesseract/</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>ocr tesseract python</dc:subject>
<dc:identifier>https://pinboard.in/u:nico.ash/b:c866adf9f547/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:ocr"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:tesseract"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://mitogen.networkgenomics.com/">
    <title>Mitogen — Mitogen Documentation</title>
    <dc:date>2019-11-23T07:58:14+00:00</dc:date>
    <link>https://mitogen.networkgenomics.com/</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Mitogen is a Python library for writing distributed self-replicating programs.

There is no requirement for installing packages, copying files around, writing shell snippets, upfront configuration, or providing any secondary link to a remote machine aside from an SSH connection. Due to its origins for use in managing potentially damaged infrastructure, the remote machine need not even have free disk space or a writeable filesystem.

It is not intended as a generic RPC framework; the goal is to provide a robust and efficient low-level API on which tools like Salt, Ansible, or Fabric can be built, and while the API is quite friendly and comparable to Fabric, ultimately it is not intended for direct use by consumer software.

The focus is to centralize and perfect the intricate dance required to run Python code safely and efficiently on a remote machine, while avoiding temporary files or large chunks of error-prone shell scripts, and supporting common privilege escalation techniques like sudo, potentially in combination with exotic connection methods such as WMI, telnet, or console-over-IPMI.

Automatic Bootstrap
Mitogen’s main feature is enabling your Python program to bootstrap and communicate with new copies of itself under its control running on remote machines, using only an existing installed Python interpreter and SSH client, something that by default can be found on almost all contemporary machines in the wild. To accomplish bootstrap, Mitogen uses a single 400 byte SSH command line and 8KB of its own source code sent to stdin of the remote SSH connection.]]></description>
<dc:subject>sysadmin ssh python</dc:subject>
<dc:identifier>https://pinboard.in/u:nico.ash/b:6321817a23c9/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:sysadmin"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:ssh"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
</rdf:Bag></taxo:topics>
</item>
<item rdf:about="https://github.com/idealo/imagededup">
    <title>GitHub - idealo/imagededup: 😎 Finding duplicate images made easy!</title>
    <dc:date>2019-10-07T19:40:32+00:00</dc:date>
    <link>https://github.com/idealo/imagededup</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[imagededup is a python package that simplifies the task of finding exact and near duplicates in an image collection.


This package provides functionality to make use of hashing algorithms that are particularly good at finding exact duplicates as well as convolutional neural networks which are also adept at finding near duplicates. An evaluation framework is also provided to judge the quality of deduplication for a given dataset]]></description>
<dc:subject>python deeplearning image neuralnetwork imageprocessing</dc:subject>
<dc:identifier>https://pinboard.in/u:nico.ash/b:26c52153ed62/</dc:identifier>
<taxo:topics><rdf:Bag>	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:python"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:deeplearning"/>
	<rdf:li rdf:resource="https://pinboard.in/u:nico.ash/t:image"/>
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<item rdf:about="https://minimaxir.com/2019/09/howto-gpt2/">
    <title>How To Make Custom AI-Generated Text With GPT-2 | Max Woolf's Blog</title>
    <dc:date>2019-09-15T08:39:18+00:00</dc:date>
    <link>https://minimaxir.com/2019/09/howto-gpt2/</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>text neuralnet textgeneration neuralnetwork textprocessing tutorial ia python</dc:subject>
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<item rdf:about="https://harrisonsand.com/imsi-catcher/">
    <title>Building a Passive IMSI Catcher</title>
    <dc:date>2019-09-13T23:36:03+00:00</dc:date>
    <link>https://harrisonsand.com/imsi-catcher/</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[An IMSI catcher is a device commonly used by law enforcement and intelligence agencies around the world to track mobile phones. They are designed to collect and log IMSI numbers, which are unique identifiers assigned to mobile phone subscriptions. Under certain circumstances, IMSI numbers can be linked back to personal identities, which inherently raises a number of privacy concerns]]></description>
<dc:subject>SDR softwareradio python radio</dc:subject>
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<item rdf:about="https://pypyjs.org/">
    <title>PyPy.js</title>
    <dc:date>2019-09-13T22:00:49+00:00</dc:date>
    <link>https://pypyjs.org/</link>
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<dc:subject>web webdev python javascript</dc:subject>
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<item rdf:about="https://github.com/pytroll/satpy">
    <title>GitHub - pytroll/satpy: Python package for earth-observing satellite data processing</title>
    <dc:date>2019-09-13T21:58:15+00:00</dc:date>
    <link>https://github.com/pytroll/satpy</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[The Satpy package is a python library for reading and manipulating meteorological remote sensing data and writing it to various image and data file formats. Satpy comes with the ability to make various RGB composites directly from satellite instrument channel data or higher level processing output. The pyresample package is used to resample data to different uniform areas or grids.

The documentation is available at http://satpy.readthedocs.org/.]]></description>
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<item rdf:about="https://github.com/nuno-faria/tiler">
    <title>GitHub - nuno-faria/tiler: 👷 Build images with images</title>
    <dc:date>2019-09-13T21:21:51+00:00</dc:date>
    <link>https://github.com/nuno-faria/tiler</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Tiler is a tool to create an image using all kinds of other smaller images (tiles). It is different from other mosaic tools since it can adapt to tiles with multiple shapes and sizes (i.e. not limited to squares).

An image can be built out of circles, lines, waves, cross stitches, legos, minecraft blocks, paper clips, letters, ... The possibilities are endless!]]></description>
<dc:subject>imageprocessing python</dc:subject>
<dc:identifier>https://pinboard.in/u:nico.ash/b:14d79fa6763b/</dc:identifier>
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<item rdf:about="https://github.com/rnd-team-dev/plotoptix/tree/master/examples/3_projects/moon">
    <title>plotoptix/examples/3_projects/moon at master · rnd-team-dev/plotoptix · GitHub</title>
    <dc:date>2019-09-01T21:21:57+00:00</dc:date>
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    <dc:creator>nico.ash</dc:creator><description><![CDATA[Data-viz project for ray-tracing the Moon model with the highest possible details. Data is downloaded from NASA resources. Read also the tutorial on Medium, and have a look at images on Behance.]]></description>
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<item rdf:about="https://github.com/plasticityai/supersqlite">
    <title>GitHub - plasticityai/supersqlite: A supercharged SQLite library for Python</title>
    <dc:date>2019-08-23T15:37:27+00:00</dc:date>
    <link>https://github.com/plasticityai/supersqlite</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[A feature-packed Python package and for utilizing SQLite in Python by Plasticity. It is intended to be a drop-in replacement to Python's built-in SQLite API, but without any limitations. It offers unique features like remote streaming over HTTP and bundling of extensions like JSON, R-Trees (geospatial indexing), and Full Text Search. SuperSQLite is also packaged with pre-compiled native binaries for SQLite and all of its extensions for nearly every platform as to avoid any C/C++ compiler errors during install.]]></description>
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<item rdf:about="https://medium.com/automation-generation/2018-advent/home">
    <title>2018 Advent – Automation Generation – Medium</title>
    <dc:date>2019-06-30T07:36:35+00:00</dc:date>
    <link>https://medium.com/automation-generation/2018-advent/home</link>
    <dc:creator>nico.ash</dc:creator><description><![CDATA[Posts about automated trading]]></description>
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<item rdf:about="https://enlight.nyc/projects/neural-network/">
    <title>Build a Neural Network in Python | Enlight</title>
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    <link>https://enlight.nyc/projects/neural-network/</link>
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<item rdf:about="https://github.com/cool-RR/pysnooper">
    <title>GitHub - cool-RR/PySnooper: Never use print for debugging again</title>
    <dc:date>2019-05-06T18:47:42+00:00</dc:date>
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<item rdf:about="https://heartbeat.fritz.ai/opencv-python-cheat-sheet-from-importing-images-to-face-detection-52919da36433">
    <title>OpenCV-Python Cheat Sheet: From Importing Images to Face Detection</title>
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<item rdf:about="https://www.dataquest.io/blog/making-538-plots/">
    <title>How to Generate FiveThirtyEight Graphs in Python – Dataquest</title>
    <dc:date>2019-04-16T05:44:48+00:00</dc:date>
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<item rdf:about="https://github.com/taxpon/openpyscad">
    <title>GitHub - taxpon/openpyscad: Python library to generate OpenSCAD source code. This library provides intuitive interface when you handle 3D data.</title>
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    <dc:creator>nico.ash</dc:creator><description><![CDATA[Python library to generate OpenSCAD source code.]]></description>
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<dc:source>https://pinboard.in/</dc:source>
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<item rdf:about="https://github.com/raycewest/pykeeb">
    <title>GitHub - raycewest/pykeeb: Python wrappers for OpenSCAD for parametrically generating 3d-printable MX or ALPS keyboard plates.</title>
    <dc:date>2019-03-09T13:33:19+00:00</dc:date>
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<item rdf:about="https://github.com/raycewest/pyergo60">
    <title>GitHub - raycewest/pyergo60: Reference project for pykeeb, and one of my daily driver keyboards.</title>
    <dc:date>2019-03-09T13:32:47+00:00</dc:date>
    <link>https://github.com/raycewest/pyergo60</link>
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<item rdf:about="http://nlp.seas.harvard.edu/NamedTensor2">
    <title>Tensor Considered Harmful Pt. 2</title>
    <dc:date>2019-01-14T20:46:13+00:00</dc:date>
    <link>http://nlp.seas.harvard.edu/NamedTensor2</link>
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<item rdf:about="https://github.com/SolidCode/SolidPython">
    <title>GitHub - SolidCode/SolidPython: A python frontend for solid modelling that compiles to OpenSCAD</title>
    <dc:date>2019-01-02T07:49:26+00:00</dc:date>
    <link>https://github.com/SolidCode/SolidPython</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>3dprinting cad 3d python</dc:subject>
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<item rdf:about="https://blog.socialcops.com/technology/engineering/camelot-python-library-pdf-data/">
    <title>Announcing Camelot, a Python Library to Extract Tabular Data from PDFs - SocialCops</title>
    <dc:date>2018-10-17T20:52:44+00:00</dc:date>
    <link>https://blog.socialcops.com/technology/engineering/camelot-python-library-pdf-data/</link>
    <dc:creator>nico.ash</dc:creator><dc:subject>data pdf python scraping table</dc:subject>
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<item rdf:about="https://towardsdatascience.com/how-to-build-your-own-neural-network-from-scratch-in-python-68998a08e4f6">
    <title>How to build your own Neural Network from scratch in Python</title>
    <dc:date>2018-10-06T20:00:22+00:00</dc:date>
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<item rdf:about="http://treyhunner.com/2018/09/stop-writing-lambda-expressions/">
    <title>Stop writing lambda expressions in Python - Trey Hunner</title>
    <dc:date>2018-10-05T07:02:29+00:00</dc:date>
    <link>http://treyhunner.com/2018/09/stop-writing-lambda-expressions/</link>
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<dc:identifier>https://pinboard.in/u:nico.ash/b:f68321dbbd1d/</dc:identifier>
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<item rdf:about="https://vinta.ws/code/parallel-tasks-in-python-concurrent-futures.html">
    <title>Parallel tasks in Python: concurrent.futures – I failed the Turing Test</title>
    <dc:date>2018-04-25T20:43:50+00:00</dc:date>
    <link>https://vinta.ws/code/parallel-tasks-in-python-concurrent-futures.html</link>
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<dc:source>https://pinboard.in/</dc:source>
<dc:identifier>https://pinboard.in/u:nico.ash/b:70a1397ebca4/</dc:identifier>
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<item rdf:about="https://github.com/jeffgran/ManuForm">
    <title>GitHub - jeffgran/ManuForm: Design files for my ManuForm custom keyboard</title>
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