Alternatives to ruffus
Compare ruffus alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to ruffus in 2026. Compare features, ratings, user reviews, pricing, and more from ruffus competitors and alternatives in order to make an informed decision for your business.
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1
LatchBio
LatchBio
Stop wresting with cloud infrastructure and broken informatics tools. Start discovering biological insights today. Scientific discovery is bottlenecked by the fragmentation of tooling across biology and bioinformatics teams. We built a harmonized bioinformatics platform between wet lab and dry lab in the cloud to help teams accelerate their R&D. Import raw data from your cloud, your service provider, or your team's instruments. Develop and deploy custom bioinformatics workflows in any language. Stop wrestling with your infrastructure. Easily run any workflow and keep a log of every analysis. Ready-to-go interactive visualizations for NGS data with point-and-click plots. Latch supports integration with your organization’s AWS S3. Access hundreds of terabytes of data in an organic filesystem you are familiar with. Define bioinformatics workflows and dynamically generate no-code interfaces using Python with tunable compute and storage. -
2
Mako
Mako
It provides a familiar, non-XML syntax that compiles into Python modules for maximum performance. Mako's syntax and API borrows from the best ideas of many others, including Django and Jinja2 templates, Cheetah, Myghty, and Genshi. Conceptually, Mako is an embedded Python (i.e. Python Server Page) language, which refines the familiar ideas of componentized layout and inheritance to produce one of the most straightforward and flexible models available, while also maintaining close ties to Python calling and scoping semantics. As templates are ultimately compiled into Python bytecode, Mako's approach is extremely efficient and was originally written to be just as fast as Cheetah. Today, Mako is very close in speed to Jinja2, which uses a similar approach and for which Mako was an inspiration. Can access variables from their enclosing scope as well as the template's request contextStarting Price: Free -
3
Seqera
Seqera
Seqera is a bioinformatics platform developed by the creators of Nextflow, designed to streamline and enhance the management of scientific data analysis workflows. It offers a comprehensive suite of tools, including the Seqera Platform for orchestrating scalable data pipelines, Seqera Pipelines for accessing a curated collection of open source workflows, Seqera Containers for simplifying container management, and Seqera Studios for interactive data analysis environments. It supports seamless integration with various cloud and on-premises infrastructures, ensuring reproducibility and compliance in scientific research. Integrate Seqera into existing on-premises systems and cloud platforms like AWS, GCP, and Azure, with no forced migrations. Maintain full control over data residency and scale globally, without compromising security or performance. -
4
imageio
imageio
Imageio is a Python library that provides an easy interface to read and write a wide range of image data, including animated images, volumetric data, and scientific formats. It is cross-platform, runs on Python 3.5+, and is easy to install. Imageio is written in pure Python, so installation is easy. Imageio works on Python 3.5+. It also works on Pypy. Imageio depends on Numpy and Pillow. For some formats, imageio needs additional libraries/executables (e.g. ffmpeg), which imageio helps you to download/install. If something doesn’t work as it should, you need to know where to search for causes. The overview on this page aims to help you in this regard by giving you an idea of how things work, and - hence - where things may go sideways.Starting Price: Free -
5
Illumina Connected Analytics
Illumina
Store, archive, manage, and collaborate on multi-omic datasets. Illumina Connected Analytics is a secure genomic data platform to operationalize informatics and drive scientific insights. Easily import, build, and edit workflows with tools like CWL and Nextflow. Leverage DRAGEN bioinformatics pipelines. Organize data in a secure workspace and share it globally in a compliant manner. Keep your data in your cloud environment while using our platform. Visualize and interpret your data with a flexible analysis environment, including JupyterLab Notebooks. Aggregate, query, and analyze sample and population data in a scalable data warehouse. Scale analysis operations by building, validating, automating, and deploying informatics pipelines. Reduce the time required to analyze genomic data, when swift results can be a critical factor. Enable comprehensive profiling to identify novel drug targets and drug response biomarkers. Flow data seamlessly from Illumina sequencing systems. -
6
CVXOPT
CVXOPT
CVXOPT is a free software package for convex optimization based on the Python programming language. It can be used with the interactive Python interpreter, on the command line by executing Python scripts, or integrated in other software via Python extension modules. Its main purpose is to make the development of software for convex optimization applications straightforward by building on Python’s extensive standard library and on the strengths of Python as a high-level programming language. Efficient Python classes for dense and sparse matrices (real and complex), with Python indexing and slicing and overloaded operations for matrix arithmetic. Interfaces to the linear programming solver in GLPK, the semidefinite programming solver in DSDP5, and the linear, quadratic and second-order cone programming solvers in MOSEK.Starting Price: Free -
7
NumPy
NumPy
Fast and versatile, the NumPy vectorization, indexing, and broadcasting concepts are the de-facto standards of array computing today. NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. NumPy supports a wide range of hardware and computing platforms, and plays well with distributed, GPU, and sparse array libraries. The core of NumPy is well-optimized C code. Enjoy the flexibility of Python with the speed of compiled code. NumPy’s high level syntax makes it accessible and productive for programmers from any background or experience level. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. With this power comes simplicity: a solution in NumPy is often clear and elegant.Starting Price: Free -
8
Microsoft Genomics
Microsoft
Instead of managing your own data centers, take advantage of Microsoft's scale and experience in running exabyte-scale workloads. Because Microsoft Genomics is on Azure, you have the performance and scalability of a world-class supercomputing center, on demand in the cloud. Take advantage of a backend network with MPI latency under three microseconds and non-blocking 32 gigabits per second (Gbps) throughput. This backend network includes remote direct memory access technology that enables parallel applications to scale to thousands of cores. Azure provides you with high memory and HPC-class CPUs to help you get results fast. Scale up and down based on what you need and pay only for what you use to reduce costs. Tackle data sovereignty requirements with a worldwide network of Azure data centers and adhere to your compliance requirements. Easily integrate into your existing pipeline code using a REST-based API and simple Python client. -
9
Edison Analysis
Edison Scientific
Edison Analysis is a next-generation scientific data-analysis agent built by Edison Scientific. It is the analytical engine underpinning their AI Scientist platform, Kosmos, and it’s available both on Edison’s platform and via API. Edison Analysis performs complex scientific data analysis by iteratively building and updating Jupyter notebooks in a dedicated environment; given a dataset plus a prompt, the agent explores, analyzes, and interprets the data to provide comprehensive insights, reports, and visualizations, very much like a human scientist. It supports execution of Python, R, and Bash code, and includes a full suite of common scientific-analysis packages in a Docker environment. Because all work is done within a notebook, the reasoning is fully transparent and auditable; users can inspect exactly how data was manipulated, which parameters were chosen, how conclusions were drawn, and can download the notebook and associated assets at any time.Starting Price: $50 per month -
10
pygame
pygame
Pygame is a set of Python modules designed for writing video games. Pygame adds functionality on top of the excellent SDL library. This allows you to create fully featured games and multimedia programs in the python language. Pygame is highly portable and runs on nearly every platform and operating system. Pygame is free. Released under the LGPL license, you can create open-source, freeware, shareware, and commercial games with it. With dual-core CPUs common, and 8-core CPUs cheaply available on desktop systems, making use of multi-core CPUs allows you to do more in your game. Selected pygame functions release the dreaded python GIL, which is something you can do from C code. Uses optimized C and assembly code for core functions. C code is often 10-20 times faster than python code, and assembly code can easily be 100x or more times faster than python code. Comes with many operating systems. Just an apt-get, emerge, pkg_add, or just install away.Starting Price: Free -
11
Plotly Dash
Plotly
Dash & Dash Enterprise let you build & deploy analytic web apps using Python, R, and Julia. No JavaScript or DevOps required. Through Dash, the world's largest companies elevate AI, ML, and Python analytics to business users at 5% the cost of a full-stack development approach. Deliver apps and dashboards that run advanced analytics: ML, NLP, forecasting, computer vision and more. Work in the languages you love: Python, R, and Julia. Reduce costs by migrating legacy, per-seat licensed software to Dash Enterprise's open-core, unlimited end-user pricing model. Move faster by deploying and updating Dash apps without an IT or DevOps team. Create pixel-perfect dashboards & web apps, without writing any CSS. Scale effortlessly with Kubernetes. Support mission-critical Python applications with high availability. -
12
broot
broot
The ROOT data analysis framework is used much in High Energy Physics (HEP) and has its own output format (.root). ROOT can be easily interfaced with software written in C++. For software tools in Python there exists pyROOT. Unfortunately, pyROOT does not work well with python3.4. broot is a small library that converts data in python numpy ndarrays to ROOT files containing trees with a branch for each array. The goal of this library is to provide a generic way of writing python numpy datastructures to ROOT files. The library should be portable and supports both python2, python3, ROOT v5 and ROOT v6 (requiring no modifications on the ROOT part, just the default installation). Installation of the library should only require a user to compile to library once or install it as a python package.Starting Price: Free -
13
Beautiful Soup
Beautiful Soup
Beautiful Soup is a library that makes it easy to scrape information from web pages. It sits atop an HTML or XML parser, providing Pythonic idioms for iterating, searching, and modifying the parse tree. Beautiful Soup's support for Python 2 was discontinued on December 31, 2020: one year after the sunset date for Python 2 itself. From this point onward, new Beautiful Soup development will exclusively target Python 3. The final release of Beautiful Soup 4 to support Python 2 was 4.9.3. Beautiful Soup is licensed under the MIT license, so you can also download the tarball, drop the bs4/ directory into almost any Python application (or into your library path) and start using it immediately.Starting Price: Free -
14
Pathway
Pathway
Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Pathway comes with an easy-to-use Python API, allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: you can use it in both development and production environments, handling both batch and streaming data effectively. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a scalable Rust engine based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with Docker and Kubernetes. -
15
Partek Flow
Partek
Partek bioinformatics software delivers powerful statistical and visualization tools in an easy-to-use interface. Researchers of all skill levels are empowered to explore genomic data quicker and easier than ever before. We turn data into discovery®. Pre-installed workflows and pipelines in our intuitive point-and-click interface make sophisticated NGS and array analysis attainable for any scientist. Custom and public statistical algorithms work in concert to easily and precisely distill NGS data into biological insights. Genome browser, Venn diagrams, heat maps, and other interactive visualizations reveal the biology of your next-generation sequencing and array data in brilliant color. Our Ph.D. scientists are always just a phone call away and ready to help with your NGS analysis any time you have questions. Designed specifically for the compute-intensive needs of next-generation sequencing applications with flexible installation and user management options. -
16
pexpect
pexpect
Pexpect makes Python a better tool for controlling other applications. Pexpect is a pure Python module for spawning child applications; controlling them, and responding to expected patterns in their output. Pexpect works like Don Libes’ Expect. Pexpect allows your script to spawn a child application and control it as if a human were typing commands. Pexpect can be used for automating interactive applications such as ssh, FTP, passwd, telnet, etc. It can be used to automate setup scripts for duplicating software package installations on different servers. It can be used for automated software testing. Pexpect is in the spirit of Don Libes’ Expect, but Pexpect is pure Python. Unlike other Expect-like modules for Python, Pexpect does not require TCL or Expect nor does it require C extensions to be compiled. It should work on any platform that supports the standard Python pty module. The Pexpect interface was designed to be easy to use.Starting Price: Free -
17
websockets
Python Software Foundation
An implementation of the WebSocket Protocol (RFC 6455 & 7692). websockets is a library for building WebSocket servers and clients in Python with a focus on correctness, simplicity, robustness, and performance. Built on top of asyncio, Python’s standard asynchronous I/O framework, it provides an elegant coroutine-based API. websockets is heavily tested for compliance with RFC 6455. Continuous integration fails under 100% branch coverage. websockets is built for production. For example, it was the only library to handle backpressure correctly before the issue became widely known in the Python community. Memory usage is optimized and configurable. A C extension accelerates expensive operations. It’s pre-compiled for Linux, macOS, and Windows and packaged in the wheel format for each system and Python version. websockets takes care of everything under the hood so you can focus on your application!Starting Price: Free -
18
zope.interface
Python Software Foundation
This package is intended to be independently reusable in any Python project. It is maintained by the Zope Toolkit project. This package provides an implementation of “object interfaces” for Python. Interfaces are a mechanism for labeling objects as conforming to a given API or contract. So, this package can be considered as an implementation of the Design By Contract methodology support in Python. Interfaces are objects that specify (document) the external behavior of objects that “provide” them. An interface specifies behavior through informal documentation in a doc string, attribute definitions, and invariants, which are conditions that must hold for objects that provide the interface. Attribute definitions specify specific attributes. They define the attribute name and provide documentation and constraints of attribute values. Attribute definitions can take a number of forms.Starting Price: Free -
19
Matplotlib
Matplotlib
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy).Starting Price: Free -
20
tox
tox
tox aims to automate and standardize testing in Python. It is part of a larger vision of easing the packaging, testing and release process of Python software. tox is a generic virtualenv management and test command-line tool you can use for checking that your package installs correctly with different Python versions and interpreters, running your tests in each of the environments, configuring your test tool of choice, and acting as a frontend to continuous integration servers, greatly reducing boilerplate and merging CI and shell-based testing. First, install tox with pip install tox. Then put basic information about your project and the test environments you want your project to run in into a tox.ini file residing right next to your setup.py file. You can also try generating a tox.ini file automatically, by running tox-quickstart and then answering a few simple questions. Install and test your project against Python2.7 and Python3.6.Starting Price: Free -
21
GlassFlow
GlassFlow
GlassFlow is a serverless, event-driven data pipeline platform designed for Python developers. It enables users to build real-time data pipelines without the need for complex infrastructure like Kafka or Flink. By writing Python functions, developers can define data transformations, and GlassFlow manages the underlying infrastructure, offering auto-scaling, low latency, and optimal data retention. The platform supports integration with various data sources and destinations, including Google Pub/Sub, AWS Kinesis, and OpenAI, through its Python SDK and managed connectors. GlassFlow provides a low-code interface for quick pipeline setup, allowing users to create and deploy pipelines within minutes. It also offers features such as serverless function execution, real-time API connections, and alerting and reprocessing capabilities. The platform is designed to simplify the creation and management of event-driven data pipelines, making it accessible for Python developers.Starting Price: $350 per month -
22
python-docx
python-docx
python-docx is a Python library for creating and updating Microsoft Word (.docx) files. Paragraphs are fundamental in Word. They’re used for body text, but also for headings and list items like bullets. You’re free to specify both width and height, but usually, you wouldn’t want to. If you specify only one, python-docx uses it to calculate the properly scaled value of the other. This way the aspect ratio is preserved and your picture doesn’t look stretched. If you don’t know what a Word paragraph style is you should definitely check it out. Basically, it allows you to apply a whole set of formatting options to a paragraph at once. python-docx allows you to create new documents as well as make changes to existing ones. Actually, it only lets you make changes to existing documents; it’s just that if you start with a document that doesn’t have any content, it might feel at first like you’re creating one from scratch.Starting Price: Free -
23
Avogadro
Avogadro
Avogadro is an advanced molecule editor and visualizer designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible high quality rendering and a powerful plugin architecture. Avogadro is a free, open-source molecular editor and visualization tool, designed for use on Mac, Windows, and Linux in computational chemistry, molecular modeling, bioinformatics, materials science, and related areas. It offers flexible high quality rendering and a powerful plugin architecture. -
24
Apache Airflow
The Apache Software Foundation
Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows. -
25
NetworkX
NetworkX
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Generators for classic graphs, random graphs, and synthetic networks. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. Network structure and analysis measures.Starting Price: Free -
26
yarl
Python Software Foundation
All URL parts, scheme, user, password, host, port, path, query, and fragment are accessible by properties. All URL manipulations produce a new URL object. Strings passed to constructor and modification methods are automatically encoded giving canonical representation as result. Regular properties are percent-decoded, use raw_ versions for getting encoded strings. Human-readable representation of URL is available as .human_repr(). PyPI contains binary wheels for Linux, Windows and MacOS. If you want to install yarl on another operating system (like Alpine Linux, which is not manylinux-compliant because of the missing glibc and therefore, cannot be used with our wheels) the tarball will be used to compile the library from the source code. It requires a C compiler and Python headers installed. Please note that the pure-Python (uncompiled) version is much slower. However, PyPy always uses a pure-Python implementation, and, as such, it is unaffected by this variable.Starting Price: Free -
27
Eidogen-Sertanty Target Informatics Platform (TIP)
Eidogen-Sertanty
Eidogen-Sertanty's Target Informatics Platform (TIP) is the world's first structural informatics system and knowledgebase that enables researchers with the ability to interrogate the druggable genome from a structural perspective. TIP amplifies the rapidly expanding body of experimental protein structure information and transforms structure-based drug discovery from a low-throughput, data-scarce discipline into a high-throughput, data-rich science. Designed to help bridge the knowledge gap between bioinformatics and cheminformatics, TIP supplies drug discovery researchers with a knowledge base of information that is both distinct from and highly complementary to information furnished by existing bio- and cheminformatics platforms. TIP's seamless integration of structural data management technology with unique target-to-lead calculation and analysis capabilities enhances all stages of the discovery pipeline. -
28
urllib3
urllib3
urllib3 is a powerful, user-friendly HTTP client for Python. Much of the Python ecosystem already uses urllib3 and you should too. urllib3 brings many critical features that are missing from the Python standard libraries. Thread safety, connection pooling, client-side TLS/SSL verification. File uploads with multipart encoding. Helpers for retrying requests and dealing with HTTP redirects. Support for gzip, deflate, and brotli encoding. Proxy support for HTTP and SOCKS. 100% test coverage. urllib3 is one of the most downloaded packages on PyPI and is a dependency of many popular Python packages like Requests, Pip, and more! urllib3 is made available under the MIT License. The API Reference documentation provides API-level documentation. The User Guide is the place to go to learn how to use the library and accomplish common tasks. The more in-depth Advanced Usage guide is the place to go for lower-level tweaking.Starting Price: Free -
29
pyglet
pyglet
The cross-platform windowing and multimedia library for Python. pyglet is a powerful, yet easy-to-use Python library for developing games and other visually-rich applications on Windows, Mac OS X, and Linux. It supports windowing, user interface event handling, Joysticks, OpenGL graphics, loading images, and videos, and playing sounds and music. All of this with a friendly Pythonic API, that's simple to learn and doesn't get in your way. pyglet is provided under the BSD open-source license, allowing you to use it for both commercial and other open-source projects with very little restriction. No external dependencies or installation requirements. For most application and game requirements, pyglet needs nothing else besides Python, simplifying distribution and installation. This makes it easy to package your project with freezers such as PyInstaller. pyglet provides real platform native windows, allowing you to take advantage of multiple windows and multi-monitor desktops.Starting Price: Free -
30
Pylons
Python Software Foundation
The Pylons web framework is designed for building web applications and sites in an easy and concise manner. They can range from as small as a single Python module, to a substantial directory layout for larger and more complex web applications. Pylons comes with project templates that help boot-strap a new web application project, or you can start from scratch and set things up exactly as desired. A framework to make writing web applications in Python easy. Utilizes a minimalist, component-based philosophy that makes it easy to expand on. Harness existing knowledge about Python. Extensible application design. Fast and efficient, an incredibly small per-request call stack provides top performance. Uses existing and well-tested Python packages. Pylons 1.0 series is stable and production-ready but in maintenance-only mode. The Pylons Project now maintains the Pyramid web framework for future development. Pylons 1.0 users should strongly consider using Pyramid for their next project.Starting Price: Free -
31
Fabi.ai
Fabi.ai
Fabi.ai is an AI-powered, collaborative data analysis platform. It helps data teams turn data into insights thanks to a seamless integration between SQL, Python, AI and no-code. From Fabi.ai, data teams can build and share interactive dashboards and reports, data apps, or lightweight data pipelines, pushing insights to Google Sheets and Slack.Starting Price: $199/month -
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Geneyx
Geneyx
Geneyx Analysis is a comprehensive solution for next-generation sequencing (NGS) data that can scale the process of FASTQ to clinical reports for hospital and commercial labs. This advanced platform integrates machine learning and AI-based features to identify novel biomedical insights, while also improving diagnostic yields and turnaround times. By providing a fully transparent and intuitive solution, Geneyx Analysis enables clinicians and researchers to have complete control over data analysis and alleviates the complexities of regulating in-house bioinformatics pipelines. Protocols can be fully customized to accommodate gene panels, exomes, and genomes, and our comprehensive annotation engine supports the analysis of all genetic variants including structural and copy number variations as well as regulatory elements. Together, Geneyx Analysis automates the diagnostic process from sequencer to report, while creating a comprehensive resource for novel variant discovery. -
33
h5py
HDF5
The h5py package is a Pythonic interface to the HDF5 binary data format. It lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays. Thousands of datasets can be stored in a single file, categorized and tagged however you want. H5py uses straightforward NumPy and Python metaphors, like dictionary and NumPy array syntax. For example, you can iterate over datasets in a file, or check out the .shape or .dtype attributes of datasets. You don't need to know anything special about HDF5 to get started. In addition to the easy-to-use high level interface, h5py rests on a object-oriented Cython wrapping of the HDF5 C API. Almost anything you can do from C in HDF5, you can do from h5py.Starting Price: Free -
34
CZ CELLxGENE Discover
CZ CELLxGENE
Select two custom cell groups based on metadata to find their top differentially expressed genes. Leverage millions of cells from the integrated CZ CELLxGENE corpus for powerful analysis. Execute interactive analyses on a dataset to explore how patterns of gene expression are determined by spatial, environmental, and genetic factors using an interactive speed no-code UI. Understand published datasets or use them as a launchpad to identify new cell sub-types and states. Census provides access to any custom slice of standardized cell data available on CZ CELLxGENE Discover in R and Python. Explore an interactive encyclopedia of 700+ cell types that provides detailed definitions, marker genes, lineage, and relevant datasets in one place. Browse and download hundreds of standardized data collections and 1,000+ datasets characterizing the functionality of healthy mouse and human tissues. -
35
PyQtGraph
PyQtGraph
PyQtGraph is a pure-python graphics and GUI library built on PyQt/PySide and NumPy. It is intended for use in mathematics/scientific/engineering applications. Despite being written entirely in python, the library is very fast due to its heavy leverage of NumPy for number crunching and Qt's GraphicsView framework for fast display. PyQtGraph is distributed under the MIT open-source license. Basic 2D plotting in interactive view boxes. Line and scatter plots. Data can be panned/scaled by mouse. Fast drawing for real-time data display and interaction. Displays most data types (int or float; any bit depth; RGB, RGBA, or luminance). Functions for slicing multidimensional images at arbitrary angles (great for MRI data). Rapid update for video display or real-time interaction. Image display with interactive lookup tables and level control. Mesh rendering with isosurface generation. Interactive viewports rotate/zoom with mouse. Basic 3D scenegraph for easier programming.Starting Price: Free -
36
openpyxl
openpyxl
openpyxl is a Python library to read/write Excel 2010 xlsx/xlsm/xltx/xltm files. It was born from a lack of an existing library to read/write natively from Python in the Office Open XML format. All kudos to the PHPExcel team as openpyxl was initially based on PHPExcel. By default, openpyxl does not guard against quadratic blowup or billion laughs XML attacks. To guard against these attacks install defusedxml. Install openpyxl using pip. It is advisable to do this in a Python virtualenv without system packages. Sometimes you might want to work with the checkout of a particular version. This may be the case if bugs have been fixed but a release has not yet been made. There is no need to create a file on the filesystem to get started with openpyxl. Just import the Workbook class and start work. Sheets are given a name automatically when they are created. Once you gave a worksheet a name, you can get it as a key of the workbook.Starting Price: Free -
37
Pillow
Pillow
The Python Imaging Library adds image processing capabilities to your Python interpreter. This library provides extensive file format support, an efficient internal representation, and fairly powerful image processing capabilities. The core image library is designed for fast access to data stored in a few basic pixel formats. It should provide a solid foundation for a general image processing tool. Pillow for enterprise is available via the Tidelift subscription. The Python Imaging Library is ideal for image archival and batch processing applications. You can use the library to create thumbnails, convert between file formats, print images, etc. The current version identifies and reads a large number of formats. Write support is intentionally restricted to the most commonly used interchange and presentation formats. The library contains basic image processing functionality, including point operations, filtering with a set of built-in convolution kernels, and color space conversions.Starting Price: Free -
38
python-sql
Python Software Foundation
python-sql is a library to write SQL queries in a pythonic way. Simple selects, select with where condition. Select with join or select with multiple joins. Select with group_by and select with output name. Select with order_by, or select with sub-select. Select on other schema and insert query with default values. Insert query with values, and insert query with query. Update query with values. Update query with where condition. Update query with from the list. Delete query with where condition, and delete query with sub-query. Provides limit style, qmark style, and numeric style.Starting Price: Free -
39
statsmodels
statsmodels
statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. An extensive list of result statistics is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.Starting Price: Free -
40
QIAGEN CLC Genomics Workbench
QIAGEN Digital Insights
QIAGEN CLC Genomics Workbench is a powerful solution that works for everyone, no matter the workflow. Cutting-edge technology and unique features and algorithms widely used by scientific leaders in industry and academia make it easy to overcome challenges associated with data analysis. User-friendly bioinformatics software solutions allow for comprehensive analysis of your NGS data, including de novo assembly of whole genomes and transcriptomes, resequencing analysis (WGS, WES and targeted panel support), variant calling, RNA-seq, ChIP-seq and DNA methylation (bisulfite sequencing analysis). Analyze your RNA-seq and small RNA (miRNA, lncRNA) data with easy-to-use transcriptomics workflows for differential expression analysis at gene and transcript levels. QIAGEN CLC Genomics Workbench is developed to support a wide range of NGS bioinformatics applications. -
41
Towhee
Towhee
You can use our Python API to build a prototype of your pipeline and use Towhee to automatically optimize it for production-ready environments. From images to text to 3D molecular structures, Towhee supports data transformation for nearly 20 different unstructured data modalities. We provide end-to-end pipeline optimizations, covering everything from data decoding/encoding, to model inference, making your pipeline execution 10x faster. Towhee provides out-of-the-box integration with your favorite libraries, tools, and frameworks, making development quick and easy. Towhee includes a pythonic method-chaining API for describing custom data processing pipelines. We also support schemas, making processing unstructured data as easy as handling tabular data.Starting Price: Free -
42
Bioconductor
Bioconductor
The Bioconductor project aims to develop and share open source software for precise and repeatable analysis of biological data. We foster an inclusive and collaborative community of developers and data scientists. Resources to maximize the potential of Bioconductor. From basic functionalities to advanced features, our tutorials, guides, and documentation have you covered. Bioconductor uses the R statistical programming language and is open source and open development. It has two releases each year and an active user community. Bioconductor provides Docker images for every release and provides support for Bioconductor use in AnVIL. Founded in 2001, Bioconductor is an open-source software project widely used in bioinformatics and biomedical research. It hosts over 2,000 R packages contributed by over 1,000 developers, with over 40 million downloads per year. Bioconductor has been cited in more than 60,000 scientific publications.Starting Price: Free -
43
pandas
pandas
pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language. Tools for reading and writing data between in-memory data structures and different formats: CSV and text files, Microsoft Excel, SQL databases, and the fast HDF5 format. Intelligent data alignment and integrated handling of missing data: gain automatic label-based alignment in computations and easily manipulate messy data into an orderly form.Aggregating or transforming data with a powerful group by engine allowing split-apply-combine operations on data sets. Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. Even create domain-specific time offsets and join time series without losing data. -
44
waiting
Python Software Foundation
waiting is a small library for waiting for stuff to happen. It basically waits for a function to return True, in various modes. Waiting is compatible with flux for simulated timelines. The most basic usage is when you have a function you want to wait for. Waiting forever is very simple. If your predicate returns a value, it will be returned as the result of wait(). A timeout parameter can also be specified. When a timeout expires without the predicate being fulfilled, an exception is thrown. Sleeping polls the predicate at a certain interval (by default 1 second). The interval can be changed with the sleep_seconds argument. When waiting for multiple predicates, waiting provides two simple facilities to help aggregate them, any and all. They resemble Python’s built-in any() and all(), except that they don’t call a predicate once it has been satisfied (this is useful when the predicates are inefficient and take time to complete).Starting Price: Free -
45
Bokeh
Bokeh
Bokeh makes it simple to create common plots, but also can handle custom or specialized use-cases. Plots, dashboards, and apps can be published in web pages or Jupyter notebooks. Python has an incredible ecosystem of powerful analytics tools: NumPy, Scipy, Pandas, Dask, Scikit-Learn, OpenCV, and more. With a wide array of widgets, plot tools, and UI events that can trigger real Python callbacks, the Bokeh server is the bridge that lets you connect these tools to rich, interactive visualizations in the browser. Microscopium is a project maintained by researchers at Monash University. It allows researchers to discover new gene or drug functions by exploring large image datasets with Bokeh’s interactive tools. Panel is a tool for polished data presentation that utilizes the Bokeh server. It is created and supported by Anaconda. Panel makes it simple to create custom interactive web apps and dashboards by connecting user-defined widgets to plots, images, tables, or text.Starting Price: Free -
46
IronPython
IronPython
IronPython is an open-source implementation of the Python programming language which is tightly integrated with .NET. IronPython can use .NET and Python libraries, and other .NET languages can use Python code just as easily. Experience a more interactive .NET and Python development experience with Python Tools for Visual Studio. IronPython is an excellent addition to .NET, providing Python developers with the power of the .NET. Existing .NET developers can also use IronPython as a fast and expressive scripting language for embedding, testing, or writing a new application from scratch. The CLR is a great platform for creating programming languages, and the DLR makes it all the better for dynamic languages. Also, the .NET (base class library, presentation foundation, etc.) gives developers an amazing amount of functionality and power. IronPython uses Python syntax and standard libraries and so your Python code will need to be updated accordingly.Starting Price: Free -
47
Pluto
Pluto Biosciences
Since its founding in 2021 from the Wyss Institute at Harvard University, Pluto has become a trusted partner of life sciences organizations around the country ranging from biotech start-ups to public biopharma companies. Our cloud-based platform gives scientists the ability to manage all of their data, run bioinformatics analyses, and create interactive and publication-quality visualizations. The platform is currently being used for a wide variety of biological applications, from preclinical / translational science research, to cell and gene therapies, drug discovery and development, to clinical research. -
48
gevent
gevent
gevent is a coroutine-based Python networking library that uses greenlet to provide a high-level synchronous API on top of the libev or libuv event loop. gevent is inspired by eventlet but features a more consistent API, simpler implementation and better performance. Read why others use gevent and check out the list of the open source projects based on gevent.Starting Price: Free -
49
Scapy
Scapy
Scapy is a powerful interactive packet manipulation program. It is able to forge or decode packets of a wide number of protocols, send them on the wire, capture them, match requests and replies, and much more. It can easily handle most classical tasks like scanning, tracerouting, probing, unit tests, attacks, or network discovery (it can replace hping, 85% of nmap, arpspoof, arp-sk, arping, tcpdump, tshark, p0f, etc.). It also performs very well at a lot of other specific tasks that most other tools can’t handle, like sending invalid frames, injecting your own 802.11 frames, combining technics (VLAN hopping+ARP cache poisoning, VOIP decoding on WEP encrypted channel), etc. Scapy runs natively on Linux, Windows, OSX, and on most Unixes with libpcap. The same code base now runs natively on both Python 2 and Python 3. Scapy development uses the Git version control system. Scapy reference repository is hosted on GitHub.Starting Price: Free -
50
Qlucore Omics Explorer
Qlucore
Qlucore Omics Explorer is so easy to use that you no longer have to depend on an expert in bioinformatics to explore and analyze your Omics and NGS data sets. Qlucore Omics Explorer is a D.I.Y next-generation bioinformatics software for research in life science, plant- and biotech industries, as well as academia. The powerful and flexible visualization-based data analysis tool with inbuilt powerful statistics delivers immediate results and provides instant exploration and visualization of big data. The software is developed to allow the workflow which best suits you and your experiments and maximizes the outcome of your research. By combining instant visualization with powerful statistics and flexible selection methods, you will be able to see your results immediately. As a user, you decide your own workflow and starting point. You are in control and can tailor the exploration to meet your specific needs.
