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A little word cloud generator in Python. The code is tested against Python 2.7, 3.4, 3.5, 3.6 and 3.7. If you are using conda, you can install from the conda-forge channel. wordcloud depends on numpy and pillow. To save the wordcloud into a file, matplotlib can also be installed. If there are no wheels available for your version of python, installing the package requires having a C compiler set up.

Please see the README.txt. The ServitorConnect 4443 and Python Daemon and Intention Repeater Android are better because repeating once-per-hour is better than millions of times per second (or even 3Hz). The archive bundle includes binaries and source code for: MAX and Simple Intention Repeaters CUDA version for Windows/Linux Memory Frequency Generator Multi-Format to WAV Repeater Android app Sourcecode File/Image Writers Nesting Files Creator ...

Create a wordcloud for a Git repository. Can also create wordclouds from directories of source files or a single source file. wordle uses tox to automate testing and packaging, and pre-commit to maintain code quality. Tests are run with tox and pytest. To run tests for a specific Python version, such as Python 3.6. The documentation is powered by Sphinx. A local copy of the documentation can be built with tox. Type annotations are checked using mypy. Run mypy using tox.

KINGPIN - A New Paradigm Of Working in Action Connecting People, Process, System and Technology - Kingpin can understand all forms of collaborative tasks, interact naturally with team and systems and people at scale. Say goodbye to silo solutions. Make your work effortless and efficient with a single solution on connected architecture that takes care of all your management needs. Kingpin facilitates communication between different departments, external vendors and service providers to...

...By leveraging SMT (Satisfiability Modulo Theories) solvers, Souper symbolically analyzes LLVM Intermediate Representation (IR) to synthesize equivalent, more efficient expressions. It identifies peephole optimizations—small instruction-level improvements—that LLVM’s optimizer may overlook, thereby improving compiled code quality. Souper can operate in multiple modes: as a standalone analysis tool that extracts and solves SMT queries from LLVM bitcode, or as an LLVM optimization pass that applies discovered optimizations directly to the IR. It integrates seamlessly with Clang and LLVM tools and supports caching mechanisms (RAM or Redis) to accelerate repeated analyses. ...