PDF

Python utility library for compositing PDF documents with reportlab

pdfdoc-py Python utility library for compositing PDF documents with reportlab. Installation The pdfdoc-py package can be installed directly from the source code: $ git clone https://github.com/michaelgale/pdfdoc-py.git $ cd pdfdoc-py $ python setup.py install Usage After installation, the package can imported: $ python >>> import pdfdoc >>> pdfdoc.__version__ Example of making a label sheet with 25 labels on Avery 5262 self-adhesive label sheets: from pdfdoc import * ld = LabelDoc(“my_labels.pdf”, style=AVERY_5262_LABEL_DOC_STYLE) labels = [i for i in range(25)] for label, row, […]

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Visualization

A Python library for processing and visualization of trajectories and other spatial-temporal data

PyMove PyMove is a Python library for processing and visualization of trajectories and other spatial-temporal data. Main Features PyMove proposes: A familiar and similar syntax to Pandas; Clear documentation; Extensibility, since you can implement your main data structure by manipulating other data structures such as Dask DataFrame, numpy arrays, etc., in addition to adding new modules; Flexibility, as the user can switch between different data structures; Operations for data preprocessing, pattern mining and data visualization. Creating a Virtual Environment It […]

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Search

Generate custom detailed survey paper with topic clustered sections and proper citations

Auto-Research A no-code utility to generate a detailed well-cited survey with topic clustered sections (draft paper format) and other interesting artifacts from a single research query. Data Provider: arXiv Open Archive Initiative OAI Requires: python 3.7 or above poppler-utils list of requirements in requirements.txt 8GB disk space 13GB CUDA(GPU) memory – for a survey of 100 searched papers(max_search) and 25 selected papers(num_papers) Demo : Video Demo : https://drive.google.com/file/d/1-77J2L10lsW-bFDOGdTaPzSr_utY743g/view?usp=sharing Kaggle Re-usable Demo : https://www.kaggle.com/sidharthpal/auto-research-generate-survey-from-query ([TIP] click ‘edit and run’ to run […]

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Deep Learning

A library for preparing and evaluating scalable deep learning hybrid recommender systems

collie A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch. Collie is a library for preparing, training, and evaluating implicit deep learning hybrid recommender systems, named after the Border Collie dog breed. Collie offers a collection of simple APIs for preparing and splitting datasets, incorporating item metadata directly into a model architecture or loss, efficiently evaluating a model’s performance on the GPU, and so much more. Above all else though, Collie is built with […]

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Data Analysis

Provides APIs for scientific and bioinformatic data analysis

Toolchest provides APIs for scientific and bioinformatic data analysis. It allows you to abstract away the costliness of running tools on your own resources by running the same jobs on secure, powerful remote servers. Installation The Toolchest client is available on PyPI: pip install toolchest-client Usage Using a tool in Toolchest is as simple as: import toolchest_client as toolchest toolchest.set_key(“YOUR_TOOLCHEST_KEY”) toolchest.kraken2( tool_args=””, inputs=”path/to/input.fastq”, output_path=”path/to/output.fastq”, ) For a list of available tools, see the documentation. Configuration To use Toolchest, you must […]

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CMS

A Static Site and Blog Generator build with python

Nikola In goes content, out comes a website, ready to deploy. Why Static Websites? Static websites are safer, use fewer resources, and avoid vendor and platform lock-in. You can read more about this in the Nikola Handbook What Can Nikola Do? It has many features, but here are some of the nicer ones: Blogs, with tags, feeds, archives, comments, etc. Themable Fast builds, thanks to doit Flexible, extensible via the dozens of available plugins Small codebase (programmers can understand all […]

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Framework

A framework for Web3 Python applications and smart contracts

Ape Framework Ape is a framework for Web3 Python applications and smart contracts, with advanced functionality for testing, deployment, and on-chain interactions. Dependencies python3 version 3.6 or greater, python3-dev Installation via pip You can install the latest release via pip: pip install eth-ape via setuptools You can clone the repository and use setuptools for the most up-to-date version: git clone https://github.com/ApeWorX/ape.git cd ape python3 setup.py install Quick Usage Ape is primarily meant to be used as a command line tool. […]

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API

Python Client for Algorithmia Algorithms and Data API

Algorithmia Common Library (python) Python client library for accessing the Algorithmia API For API documentation. Algorithm Development Kit This package contains the algorithmia-adk development kit, simply add from Algorithmia import ADK into your workflow to access it. Install from PyPi The official Algorithmia python client is available on PyPi.Install it with pip: pip install algorithmia Install from source Build algorithmia client wheel: python setup.py bdist_wheel Install a wheel manually: pip install –user –upgrade dist/algorithmia-*.whl from directory containing setup.py and the […]

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