Search Results for "python-ldap"
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Showing 332 open source projects for "python-ldap"
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Orange Data Mining
Orange: Interactive data analysis
Open source machine learning and data visualization. Build data analysis workflows visually, with a large, diverse toolbox. Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for... -
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folium
Python data, Leaflet.js maps
folium builds on the data wrangling strengths of the Python ecosystem and the mapping strengths of the leaflet.js library. Manipulate your data in Python, then visualize it in on a Leaflet map via folium. folium makes it easy to visualize data that’s been manipulated in Python on an interactive leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing rich vector/raster/HTML visualizations as markers on the map. The library has a number of built... -
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Matplotlib
matplotlib: plotting with Python
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. Matplotlib ships with several add-on toolkits, including 3D plotting with mplot3d, axes helpers in axes_grid1 and axis helpers in axisartist. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot -
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seaborn
Statistical data visualization in Python
Seaborn is a Python data visualization library based on matplotlib. It provides a high-level interface for drawing attractive and informative statistical graphics. Seaborn helps you explore and understand your data. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API lets you focus on what the different elements... -
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PyVista
3D plotting and mesh analysis through a streamlined interface
... for scientific plotting for presentations and research papers as well as a supporting module for other mesh-dependent Python modules. Easily integrate with NumPy and create a variety of geometries and plot them. You could use any geometry to create your glyphs, or even plot the points directly. Direct access to mesh analysis and transformation routines. Intuitive plotting routines with matplotlib similar syntax. -
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JUDI.jl
Julia Devito inversion
JUDI is a framework for large-scale seismic modeling and inversion and is designed to enable rapid translations of algorithms to fast and efficient code that scales to industry-size 3D problems. The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling... -
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PySR
High-Performance Symbolic Regression in Python and Julia
PySR is an open-source tool for Symbolic Regression: a machine learning task where the goal is to find an interpretable symbolic expression that optimizes some objective. Over a period of several years, PySR has been engineered from the ground up to be (1) as high-performance as possible, (2) as configurable as possible, and (3) easy to use. PySR is developed alongside the Julia library SymbolicRegression.jl, which forms the powerful search engine of PySR. The details of these algorithms are... -
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
.... Libraries from Python, R, C/Fortran, C++, and Java can also be used. -
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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... -
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JDF.jl
Julia DataFrames serialization format
... is called a JDF "file". JDF.jl is a pure-Julia solution and there are a lot of ways to do nifty things like compression and encapsulating the underlying struture of the arrays that's hard to do in R and Python. E.g. Python's numpy arrays are C objects, but all the vector types used in JDF are Julia data types. -
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PythonCall & JuliaCall
Python and Julia in harmony
Bringing Python® and Julia together in seamless harmony. Call Python code from Julia and Julia code from Python via a symmetric interface. Simple syntax, so the Python code looks like Python and the Julia code looks like Julia. Intuitive and flexible conversions between Julia and Python: anything can be converted, you are in control. Fast non-copying conversion of numeric arrays in either direction: modify Python arrays (e.g. bytes, array. array, numpy.ndarray) from Julia or Julia arrays from... -
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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... -
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HyperTools
A Python toolbox for gaining geometric insights
HyperTools is a library for visualizing and manipulating high-dimensional data in Python. It is built on top of matplotlib (for plotting), seaborn (for plot styling), and scikit-learn (for data manipulation). Functions for plotting high-dimensional datasets in 2/3D. Static and animated plots. Simple API for customizing plot styles. Set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more. Support for lists of Numpy arrays, Pandas dataframes... -
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gramm
Gramm is a complete data visualization toolbox for Matlab
... for GRAMmar of graphics for MATLAB. A similar library called Seaborn also exists for Python. Gramm has been used in many publications from varied fields and is particularily suited for neuroscience, from human movement psychophysics (Morel et al. 2017), to electrophysiology (Morel et al. 2016; Ferrea et al. 2017), human functional imaging (Wan et al. 2017) and animal training (Berger et al. 2017). -
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GoldenCheetah
Performance Software for Cyclists, Runners, Triathletes and Coaches
Analyze using summary metrics like BikeStress, TRIMP, or RPE. Extract insight via models like Critical Power and W'bal. Track and predict performance using models like Banister and PMC. Optimize aerodynamics using Virtual Elevation. Train indoors with ANT and BTLE trainers. Upload and Download with many cloud services including Strava, Withings, and Today's Plan. Import and export data to and from a wide range of bike computers and file formats. Track body measures, and equipment use and set... -
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PyCall.jl
Package to call Python functions from the Julia language
Package to call Python functions from the Julia language. This package provides the ability to directly call and fully interoperate with Python from the Julia language. You can import arbitrary Python modules from Julia, call Python functions (with automatic conversion of types between Julia and Python), define Python classes from Julia methods, and share large data structures between Julia and Python without copying them. -
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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... -
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pydna
Clone with Python! Data structures for double stranded DNA
Clone with Python! Data structures for double stranded DNA & simulation of homologous recombination, Gibson assembly, cut & paste cloning. Planning genetic constructs with many parts and assembly steps, such as recombinant metabolic pathways, are often difficult to properly document as is evident from the poor state of documentation in the scientific literature. The pydna python package provide a human-readable formal description of cloning and genetic assembly strategies in Python which allow... -
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IPyPlot
Fast and efficient plotting of images inside Python Notebooks
IPyPlot is a small python package offering fast and efficient plotting of images inside Python Notebooks. It's using IPython with HTML for faster, richer and more interactive way of displaying big numbers of images. -
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Mercury
Convert Python notebook to web app and share with non-technical users
Turn Python notebooks to web applications with open-source Mercury framework. Hide code and add interactive widgets. Non-technical users can tweak widgets and execute notebook with new parameters. The core of Mercury is Open Source under AGPLv3. We provide Mercury Pro with additional features, dedicated support and friendly commercial license. Mercury is a perfect tool to convert Python notebook to interactive web application and share with non-programmers. You define interactive widgets... -
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JILL.py
A cross-platform installer for the Julia programming language
The enhanced Python fork of JILL, Julia Installer for Linux (and every other platform), Light. -
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miepython
Mie scattering of light by perfect spheres
miepython is a pure Python module to calculate light scattering for non-absorbing, partially-absorbing, or perfectly-conducting spheres. Mie theory is used, following the procedure described by Wiscombe. This code has been validated against his results. This code provides functions for calculating the extinction efficiency, scattering efficiency, backscattering, and scattering asymmetry. Moreover, a set of angles can be given to calculate the scattering for a sphere at each of those angles. -
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leafmap
A Python package for interactive mapping and geospatial analysis
A Python package for geospatial analysis and interactive mapping in a Jupyter environment. Leafmap is a Python package for interactive mapping and geospatial analysis with minimal coding in a Jupyter environment. It is a spin-off project of the geemap Python package, which was designed specifically to work with Google Earth Engine (GEE). However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users... -
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VisPy
Main repository for Vispy
Vispy is an open-source, high-performance interactive visualization library in Python, designed for creating scientific visualizations and interactive plots. It leverages the power of modern Graphics Processing Units (GPUs) through OpenGL to render large datasets efficiently. Vispy supports a wide range of visualization types, including 2D plots, 3D visualizations, volume rendering, and more, making it suitable for scientific research, data analysis, and educational purposes. -
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Braket.jl
Experimental Julia implementation of the Amazon Braket SDK
Braket.jl is not an officially supported AWS product. This package is a Julia implementation of the Amazon Braket SDK allowing customers to access Quantum Hardware and Simulators. This is experimental software, and support may be discontinued in the future. For a fully supported SDK, please use the Python SDK. We may change, remove, or deprecate parts of the API when making new releases. Please review the CHANGELOG for information about changes in each release.
