Open Source Python Data Management Systems - Page 20
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Python Data Management Systems
View 4396 business solutionsBrowse free open source Python Data Management Systems and projects below. Use the toggles on the left to filter open source Python Data Management Systems by OS, license, language, programming language, and project status.
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data-diff
Efficiently diff rows across two different databases
We're excited to announce the launch of a new open-source product, data-diff that makes comparing datasets across databases fast at any scale. data-diff automates data quality checks for data replication and migration. In modern data platforms, data is constantly moving between systems, and at the modern data volume and complexity, systems go out of sync all the time. Until now, there has not been any tooling to ensure that when the data is correctly copied. Replicating data at scale, across hundreds of tables, with low latency and at a reasonable infrastructure cost is a hard problem, and most data teams we’ve talked to, have faced data quality issues in their replication processes. The hard truth is that the quality of the replication is the quality of the data. Since copying entire datasets in batch is often infeasible at the modern data scale, businesses rely on the Change Data Capture (CDC) approach of replicating data using a continuous stream of updates. -
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dbt-re-data
re_data - fix data issues before your users & CEO would discover them
re_data is an open-source data reliability framework for the modern data stack. Currently, re_data focuses on observing the dbt project (together with underlaying data warehouse - Postgres, BigQuery, Snowflake, Redshift). Data transformations in re_data are implemented and exposed as models & macros in this dbt package. Gather all relevant outputs about your data in one place using our cloud. Invite your team and debug it easily from there. Go back in time, and see your past metadata. Set up Slack notifications to always know when a new report is produced or an existing one got updated. -
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Easy-to-learn interactive 2d plot program. Can overlay images, xy-data, and mathematical functions. Function parameters can be tuned with sliders; functions can also be automatically fitted to data. Written in Python, cross-platform, but currently broken
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electricityMap
A real-time visualisation of the CO2 emissions of electricity
Real-time visualization of the Greenhouse Gas (in terms of CO2 equivalent) footprint of electricity consumption built with d3.js and mapbox GL. Real-time data is defined as a data source with an hourly (or better) frequency, delayed by less than 2hrs. It should provide a breakdown by generation type. Often fossil fuel generation (coal/gas/oil) is combined under a single heading like 'thermal' or 'conventional', this is not a problem. Citizens should not be responsible for the emissions associated with all the products they export, but only for what they consume. Consumption-based accounting (CBA) is a very important aspect of climate policy and allows assigning responsibility to consumers instead of producers. Furthermore, this method is robust to governments relocating dirty production to neighboring countries in order to green their image while still importing from it. -
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Fitta is a program for making and plotting statistical fits, simple and weighted fit, high quality plots thanks to the matplotlib library
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fooltrader
Quant framework for stock
Build a standard data schema, and then implement various connectors to import systems you are familiar with for analysis. fooltrader is a quantitative analysis trading system designed using big data technology, including data capture, cleaning, structuring, calculation, display, backtesting and trading. Its goal is to provide a unified framework for the whole market (stock, futures, bonds, foreign exchange, digital currency, macroeconomics, etc.) for research, backtesting, forecasting, and trading. Its applicable objects include quantitative traders, teachers, and students majoring in finance, people interested in economic data, programmers, and people who like freedom and the spirit of exploration. You could write the Strategy using an event-driven or time walkway and view and analyze the performance in a uniform way. -
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g2 is an easy to use, portable and powerful 2D graphics library. It provides a comprehensive set of functions for simultaneous generation of graphical output on different types of devices.
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is a interactive molecular visualisation program designed especially designed for coarse-grained simulation of non-spherical particles. Ellipsoids (Gay-Berne), disks, and custom shaped uniaxial particle (e.g. pear-shaped particles) can be represented.
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geemap
A Python package for interactive geospaital analysis and visualization
A Python package for interactive geospatial analysis and visualization with Google Earth Engine. Geemap is a Python package for geospatial analysis and visualization with Google Earth Engine (GEE), which is a cloud computing platform with a multi-petabyte catalog of satellite imagery and geospatial datasets. During the past few years, GEE has become very popular in the geospatial community and it has empowered numerous environmental applications at local, regional, and global scales. GEE provides both JavaScript and Python APIs for making computational requests to the Earth Engine servers. Compared with the comprehensive documentation and interactive IDE (i.e., GEE JavaScript Code Editor) of the GEE JavaScript API, the GEE Python API has relatively little documentation and limited functionality for visualizing results interactively. The geemap Python package was created to fill this gap. -
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This is a collection of Python functions, with which data can be exported from the Python environment to a file which can be viewed in GoogleEarth.
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gusty
Making DAG construction easier
gusty allows you to control your Airflow DAGs, Task Groups, and Tasks with greater ease. gusty manages collections of tasks, represented as any number of YAML, Python, SQL, Jupyter Notebook, or R Markdown files. A directory of task files is instantly rendered into a DAG by passing a file path to gusty's create_dag function. gusty also manages dependencies (within one DAG) and external dependencies (dependencies on tasks in other DAGs) for each task file you define. All you have to do is provide a list of dependencies or external_dependencies inside of a task file, and gusty will automatically set each task's dependencies and create external task sensors for any external dependencies listed. gusty works with both Airflow 1.x and Airflow 2.x, and has even more features, all of which aim to make the creation, management, and iteration of DAGs more fluid, so that you can intuitively design your DAG and build your tasks. -
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Harkay un software desarrollado en Python para la administraccion de un firewall de acceso a internet diseñado teniendo en cuenta su facilidad de uso y potencia. La politica por defecto es denegar todo habilitando puntualmente lo que se desea.
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harmonypy
Integrate multiple high-dimensional datasets with fuzzy k-means
Harmony is an algorithm for integrating multiple high-dimensional datasets. harmonypy is a port of the harmony R package by Ilya Korsunsky. Harmony is a general-purpose R package with an efficient algorithm for integrating multiple data sets. It is especially useful for large single-cell datasets such as single-cell RNA-seq. -
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hui
hewies user interface - 3D scientific visualisation tool
Python project with goal to provide FOSS library to extract, analyse and visualise data in a 3D fashion. The instance will connect to a data source, ods sheet, csv, sql DB, pyodbc the instance will analyse and/or transform the data to be presented to the visualisation functionality the instance will visualise the data in a 3D fashion, likely using third party FOSS -
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i-Map - Plot Geolocation from Images
Automatically plots latitude, longitude from images on Google maps.
i-Map is a Photo metadata forensic tool for Geo-location analysis of images that are clicked from GPS enabled devices. In this tool, you can load 100s of images from a suspect's device and analyze them to know various locations where photos were clicked on mobile phone/tablet. After loading images, with a single click, iMap plots all the images on World Map to visually check where they have been captured, generate timeline and activity of suspect and match them with CDR (Call Detail Record) Details. To generate a report, you can export this data into PDF or Excel file according to your requirements. -
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iMir
Integrated pipeline for HT miRNA-Seq data analysis
Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. To allow a flexible and comprehensive analysis of smallRNA-Seq data we designed a novel modular pipeline, called iMir, integrating multiple open source modules and resource in an automated workflow, devising different statistical approaches to analyze data rigorously. iMir comprises also a Graphical User Interface (GUI), so that the pipeline is particularly suited for biologist and early stage bioinformaticians and produces both graphics and text outputs. -
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This is the public icram.de code repository filled with code/code-snippets and other useful stuff.
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ipcvis
Visualize Inter Process Communication
Small python script that can visualize Inter Process Communication on Linux. It can create a graph of TCP and Unix sockets, pipes and also process hierarchy. Short (59 sec) demo visualizing ssh client connecting to ssh server on the same Ubuntu host: http://youtu.be/8XFKwzkexQY Longer (2 min 13 sec) demo visualizing ZoneMinder surveillance solution operation (stopping, starting, enabling and viewing camera): http://youtu.be/kM7klE61Ibk Tested on Ubuntu 14.10 and Debian 7. Quick start on Ubuntu/Debian: # apt-get install graphviz python-pygraphviz # ./ipcvis.py -
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ipychart
The power of Chart.js with Python
Create charts with Python in a very similar way to creating charts using Chart.js. The charts created are fully configurable, interactive, and modular and are displayed directly in the output of the cells of your jupyter notebook environment. Charts are fully interactive, you can hover it to display tooltips and select the information you want to see directly from the output cell of your notebook. All the types of charts present in Chart.js are exposed in ipychart. Even complex features such as mixed-types charts are available. Charts are highly customizable and all Chart.js options are available in ipychart. You have complete control over the appearance of your chart. -
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ipycytoscape
A Cytoscape Jupyter widget
A widget enabling interactive graph visualization with cytoscape.js in JupyterLab and the Jupyter Notebook. -
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istSOS
Free and Open Source Sensor Observation Service Data Management System
istSOS is an OGC SOS server implementation written in Python. istSOS allows for managing and dispatch observations from monitoring sensors according to the Sensor Observation Service standard. The project provides also a Graphical user Interface that allows for easing the daily operations and a RESTful Web api for automatizing administration procedures. istSOS is released under the GPL License, and runs on all major platforms (Windows, Linux, Mac OS X), even though tests were conducted under a Linux environment.
