Open Source Python Business Software for Mac - Page 12
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Python Business Software for Mac
View 444 business solutionsBrowse free open source Python Business Software for Mac and projects below. Use the toggles on the left to filter open source Python Business Software for Mac by OS, license, language, programming language, and project status.
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XISMuS
X-Ray Imaging Software for Multiple Samples
ATTENTION: Cumulative update 2.5.0 has been released!! The update works for any previous 2.x.x version. If upgrading from version v1.x.x, please download and install v2.0.0 first. IMPORTANT FIXES in respect to base v2.0.0 version: v.2.5.0 introduces the Differential Attenuation and Cube Viewer utilities, and migrates user database to *.json files v2.4.3 fixes a with K element in the fit-approx method v2.4.3 fixes and issue where saving plots with fit-approx or a auto-wizard could freeze the software v2.4.2 introduces Image Viewer to Mosaic v2.4.1 fixes an issue in merging H5 or EDF datasets with Mosaic Full changelog at https://linssab.github.io/history X-Ray Fluorescence Imaging Software for Multiple Samples is an open source software to manipulate and study macro-X-Ray Fluorescence (MA-XRF) datasets. XISMuS also works as a sample management tool, where you can easily change between datasets (samples) and compare, cross-interact and normalize them. -
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--UPDATE-- New Version is now integrated in the official PyMOL plugin repository! --UPDATE-- The BNI (Beyond Normal Interaction)- Tools is a plug in for the PyMOL molecular visualization system which adds additional functionalities and presets to the PyMOL GUI and also adds useful extended commands.
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cl-calc aims to be a simple command line calculator. It can handle precedence unlike a lot of graphical calculators. cl-calc is written in Python and requires PLY (Python-Lex-Yacc).
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iFlux
Tornado Web Based Framework
iFlux was rebooted!!! We are developing a Tornado Web Based Framework. Still in planning phase. Check us on openhub too: https://www.openhub.net/p/iflux Used to be: PHP Framework project based on Model-View-Controller MVC Desing Patern. iFlux is a MyFuses extension that makes easy build applications with i18n, form mapping, template engine like smarty and other advanced features. -
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pjscicalc
A scientific calculator written in Python
A scientific calculator written in Python, this project uses the wxPython and mpmath modules to create a scientific calculator suitable for use on a computer desktop. It is largely a rewrite and update of jscicalc. It has much higher precision. -
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pyLastFM graph is commandline tool for creating a nice looking graph time graph from Last.fm profile data. It uses the audioscrobbler.net XML interface and can create very high resolution output images.
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This is a neat little tool to visualize binary data in a graphical form. It's really interesting to look at different types of files.
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Build Securely on Azure with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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Information manager based on 3D cubes of knwoledgments. You can create a cube with 3 axis (or dimensions), each of them with several elements. The nexus between the elements of three axis compounds a value. From a cube, you can create 2D view queries
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School Club Management System
A Database Program To Keep Track of Members In a School Club
Keeping Track of Members Isn't an easy thing. Writing in pieces of papers isn't successful. This Program Makes It Easy To Manage and store data on students.This program has the basic database functions like Show,Search,Add,Edit and Delete. -
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3PT (short for Python based PowerPoint) is a project in which a basic, native Python based PowerPoint in- and export has been implemented. The created PPT files are compatible with PPT 97-2003.
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AI learning
AiLearning, data analysis plus machine learning practice
We actively respond to the Research Open Source Initiative (DOCX) . Open source today is not just open source, but datasets, models, tutorials, and experimental records. We are also exploring other categories of open source solutions and protocols. I hope you will understand this initiative, combine this initiative with your own interests, and do what you can. Everyone's tiny contributions, together, are the entire open source ecosystem. We are iBooker, a large open-source community, we-media, and online earning community, with a QQ group of more than 10,000 people and at least 10,000 subscribers. The number of Github Stars exceeds 60k, and it ranks in the top 100 of all Github organizations. The daily up of all its websites exceeds 4k, and the peak of Alexa ranking is 20k. Our core members are certified as CSDN blog experts and short-book programmers as excellent authors. We have established ApacheCN, a non-profit document, and tutorial translation project. -
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A Plone, Archetypes based product which provides reminder objects (a new eventlike content type) and a tool for processing reminder objects periodically.
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AWS Data Wrangler
Pandas on AWS, easy integration with Athena, Glue, Redshift, etc.
An AWS Professional Service open-source python initiative that extends the power of Pandas library to AWS connecting DataFrames and AWS data-related services. Easy integration with Athena, Glue, Redshift, Timestream, OpenSearch, Neptune, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON, and EXCEL). Built on top of other open-source projects like Pandas, Apache Arrow and Boto3, it offers abstracted functions to execute usual ETL tasks like load/unload data from Data Lakes, Data Warehouses, and Databases. Convert the column name to be compatible with Amazon Athena and the AWS Glue Catalog. Run a query against AWS CloudWatchLogs Insights and convert the results to Pandas DataFrame. Get QuickSight dashboard ID given a name and fails if there is more than 1 ID associated with this name. List IAM policy assignments in the current Amazon QuickSight account. -
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AWS SDK for pandas
Easy integration with Athena, Glue, Redshift, Timestream, Neptune
aws-sdk-pandas (formerly AWS Data Wrangler) bridges pandas with the AWS analytics stack so DataFrames flow seamlessly to and from cloud services. With a few lines of code, you can read from and write to Amazon S3 in Parquet/CSV/JSON/ORC, register tables in the AWS Glue Data Catalog, and query with Amazon Athena directly into pandas. The library abstracts efficient patterns like partitioning, compression, and vectorized I/O so you get performant data lake operations without hand-rolling boilerplate. It also supports Redshift, OpenSearch, and other services, enabling ETL tasks that blend SQL engines and Python transformations. Operational helpers handle IAM, sessions, and concurrency while exposing knobs for encryption, versioning, and catalog consistency. The result is a productive workflow that keeps your analytics in Python while leveraging AWS-native storage and query engines at scale. -
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AWS Step Functions Data Science SDK
For building machine learning (ML) workflows and pipelines on AWS
The AWS Step Functions Data Science SDK is an open-source library that allows data scientists to easily create workflows that process and publish machine learning models using Amazon SageMaker and AWS Step Functions. You can create machine learning workflows in Python that orchestrate AWS infrastructure at scale, without having to provision and integrate the AWS services separately. The best way to quickly review how the AWS Step Functions Data Science SDK works is to review the related example notebooks. These notebooks provide code and descriptions for creating and running workflows in AWS Step Functions Using the AWS Step Functions Data Science SDK. In Amazon SageMaker, example Jupyter notebooks are available in the example notebooks portion of a notebook instance. To run the AWS Step Functions Data Science SDK example notebooks locally, download the sample notebooks and open them in a working Jupyter instance. -
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AccountOverview is an open-source account overview application, to parse and visualize data from bank accounts, to gain insight into your financial status.
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AdEvaluator
Evaluate whether advertising works using sales data.
AdEvaluator(tm) evaluates the effect of advertising (or marketing, sales, or public relations) on sales and profits by analyzing a sales report in comma separated values (CSV) format from QuickBooks or other accounting programs. -
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Agenda
Agenda
Agenda de compromissos com data, hora e compromisso e agenda de endereços e telefones. Requer Python 2.7 e Python 2.7 PyGTK -
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Aloof, Angband Ladder OpenOffice filter
OpenOffice.org extension to process data from the Angband Ladder site
It will allow to - keep local copy of data from http://angband.oook.cz/ladder.php - get data updates on user command - do reports, charts, saves to various formats etc, what office suites usually do -
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AlphaPy
Python AutoML for Trading Systems and Sports Betting
AlphaPy is a Python-based AutoML framework tailored for trading systems and sports betting applications. Built on popular libraries like scikit-learn and pandas, it enables data scientists and speculators to craft predictive models, ensemble strategies, and automated forecasting systems with minimal setup. Run machine learning models using scikit-learn, Keras, xgboost, LightGBM, and CatBoost. Generate blended or stacked ensembles. Create models for analyzing the markets with MarketFlow. Develop trading systems and analyze portfolios using MarketFlow and Quantopian's pyfolio. -
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This project aims to develop means for advanced Arabic typesetting, including OpenType fonts and a text layout engine.
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Arize Phoenix
Uncover insights, surface problems, monitor, and fine tune your LLM
Phoenix provides ML insights at lightning speed with zero-config observability for model drift, performance, and data quality. Phoenix is an Open Source ML Observability library designed for the Notebook. The toolset is designed to ingest model inference data for LLMs, CV, NLP and tabular datasets. It allows Data Scientists to quickly visualize their model data, monitor performance, track down issues & insights, and easily export to improve. Deep Learning Models (CV, LLM, and Generative) are an amazing technology that will power many of future ML use cases. A large set of these technologies are being deployed into businesses (the real world) in what we consider a production setting.