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Ratings and Reviews 0 Ratings
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What is waiting?
Waiting is a lightweight library crafted to simplify the task of waiting for certain conditions to be fulfilled. It essentially halts execution until a specified function evaluates to True, providing a variety of operational modes to choose from. Furthermore, Waiting integrates smoothly with flux for simulating timelines, making it even more versatile. The most straightforward way to use it involves supplying a function for monitoring, and it is easy to wait indefinitely; if your predicate produces a result, that result becomes the output of wait(). Additionally, you can establish a timeout period, and if this time elapses without the predicate being satisfied, an exception will be raised. By default, the library checks the predicate every second, but this interval can be modified using the sleep_seconds parameter. When working with multiple predicates, Waiting presents two effective aggregation methods: any and all. These methods resemble Python's built-in any() and all(), but they ensure that a predicate is not called more often than necessary, which is especially advantageous for predicates that are resource-heavy and time-consuming. By optimizing these functions, Waiting significantly improves both the efficiency of asynchronous operations and the overall user experience, making it an essential tool for developers. In summary, this library not only simplifies waiting processes but also enhances performance through its thoughtful design.
What is ggplot2?
ggplot2 serves as a powerful framework for crafting graphics in a declarative style, based on concepts from The Grammar of Graphics. Users are encouraged to provide their datasets while defining how to link variables to visual aesthetics and determining which graphical components to use, with ggplot2 handling the complex underlying processes. Having established a solid presence for over a decade, ggplot2 is favored by countless users, leading to the generation of millions of visualizations. This widespread adoption generally ensures that ggplot2 maintains a stable framework over time. When revisions are made, they typically focus on adding new functionalities or parameters, rather than changing the existing ones; alterations to current behaviors are only executed when absolutely essential. For newcomers eager to learn ggplot2, it is highly recommended to pursue a structured introduction rather than relying solely on fragmented documentation, as this will lead to a deeper and more cohesive understanding of the tool. Utilizing tutorials and beginner-friendly resources not only enhances the learning process but also equips users with practical skills to effectively leverage ggplot2 in their projects. By immersing oneself in guided learning, one can build a solid foundation for mastering data visualization techniques.
API Availability
Has API
API Availability
Has API
Pricing Information
Free
Free Version
Free Trial Offered?
Pricing Information
Pricing not provided
Free Version
Free Trial Offered?
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Python Software Foundation
Company Location
United States
Company Website
pypi.org/project/waiting/
Company Facts
Organization Name
ggplot2
Company Website
ggplot2.tidyverse.org
Categories and Features
Categories and Features
Data Visualization
Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery