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Tkinter is a binding to the Tk GUI toolkit for Python. It is the standard Python interface to the Tk GUI toolkit, [1] and is Python's de facto standard GUI. [2] Tkinter is included with standard Linux, Microsoft Windows and macOS installs of Python. The name Tkinter comes from Tk interface.
tk_dialog – creates a modal dialog and waits for a response. tk_getOpenFile – pops up a dialog box for the user to select a file to open. tk_getSaveFile – pops up a dialog box for the user to select a file to save. tk_messageBox – pops up a message window and waits for a user response. tk_popup – posts a popup menu.
This is a simple "Hello world" module, depicting the creation of the two main objects in wxPython (the main window object and the application object), followed by passing the control to the event-driven system (by calling MainLoop()) which manages the user-interactive part of the program.
in Tcl [7] and other languages such as Perl [8] and Python, [9] TkZinc Archived 2017-12-07 at the Wayback Machine is an extended replacement for the Tk canvas, which adds support for hierarchical grouping, clipping, affine transformations, anti-aliasing, and specific items for air traffic control.
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record.
Since Base64 encoded data is approximately 33% larger than original data, it is recommended to use Base64 data URIs only if the server supports HTTP compression or embedded files are smaller than 1KB. The data, separated from the preceding part by a comma (,). The data is a sequence of zero or more octets represented as characters. The comma is ...
OpenTK, also known as The Open Toolkit library, is a C# graphics library superseding the Tao Framework. [1] It provides access to graphics tools contained in OpenGL, OpenCL, and OpenAL to a variety of CLR-based languages (C#, F#, etc.). [2]
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.