105 lines
4.4 KiB
Plaintext
105 lines
4.4 KiB
Plaintext
# Getting started with Julia
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{{< include ../_common_code.qmd >}}
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```{julia}
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#| echo: false
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#| results: "hidden"
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using CalculusWithJulia
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nothing
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```
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Julia is a freely available, open-source programming language aimed at technical computing.
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As it is open source, indeed with a liberal MIT license, it can be installed for free on many types of computers (though not phones or tablets).
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## Running Julia through the web
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There are a few services for running `Julia` through the web. Mentioned here is [Binder](https://mybinder.org), which provides a web-based interface to `Julia` built around `Jupyter`. `Jupyter` is a wildly successful platform for interacting with different open-source software programs.
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[launch binder](https://mybinder.org/v2/gh/CalculusWithJulia/CwJScratchPad.git/master)
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Clicking the launch link above will open a web page which provides a blank notebook, save for a package used by these notes. However, `Binder` is nowhere near as reliable as a local installation.
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## Installing Julia locally
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Installing `Julia` locally is not more difficult than installing other software.
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Binaries of `Julia` are provided at [julialang.org](http://julialang.org/downloads/). Julia has an official released version and a developmental version. Unless there is a compelling reason, the latest released version should be downloaded and installed for use.
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For Windows users, there is a `juliaup` program for managing the installation of Julia.
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The base `Julia` provides a *command-line interface*, or REPL (read-evaluate-parse).
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## Basic interactive usage
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Once installed, `Julia` can be started by clicking on an icon or typing `julia` at the command line. Either will open a *command line interface* for a user to interact with a `Julia` process. The basic workflow is easy: commands are typed then sent to a `Julia` process when the "return" key is pressed for a complete expression. Then the output is displayed.
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A command is typed following the *prompt*. An example might be `2 + 2`. To send the command to the `Julia` interpreter the "return" key is pressed. A complete expression or expressions will then be parsed and evaluated (executed). If the expression is not complete, `julia`'s prompt will still accept input to complete the expression. Type `2 +` to see. (The expression `2 +` is not complete, as the infix operator `+` expects two arguments, one on its left and one on its right.)
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```{julia}
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#| eval: false
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_
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_ _ _(_)_ | Documentation: https://docs.julialang.org
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(_) | (_) (_) |
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_ _ _| |_ __ _ | Type "?" for help, "]?" for Pkg help.
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| | | | | | |/ _` | |
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| | |_| | | | (_| | | Version 1.7.0 (2021-11-30)
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_/ |\__'_|_|_|\__'_| | Official https://julialang.org/ release
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|__/ |
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julia> 2 + 2
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4
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```
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Above, `julia>` is the prompt. These notes will not include the prompt, so that copying-and-pasting can be more easily used. Input and output cells display similarly, though with differences in coloring. For example:
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```{julia}
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2 + 2
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```
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While many prefer a command line for interacting with `Julia`, when learning a notebook interfaces is suggested. (An IDE like [Julia for Visual Studio Code](https://www.julia-vscode.org/) might be preferred for experienced programmers). In [Julia interfaces](./julia_interfaces.html), we describe two different notebook interfaces that are available through add-on packages.
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## Add-on packages
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`Julia` is well on its way towards 10,000 external add-on packages that enhance the offerings of base `Julia`. We refer to one, `CalculusWithJulia`, that is designed to accompany these notes. [Installation notes](./calculus_with_julia.html) are available.
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In `Julia` graphics are provided only by add-on packages – there is no built-in graphing. This is the case under `Pluto` or `Jupyter` or the command line.
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In these notes, we use the `Plots` package and its default backend. The `Plots` package provides a common interface to several different backends; this choice is easily changed. The `gr` backend is used in these notes, though for interactive use the `Plotly` backend has advantages; for more complicated graphics, `pyplot` has some advantages; for publication `PGFPlotsX` has advantages.
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The package, if installed, is loaded as any other package:
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```{julia}
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using Plots
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```
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With that in hand, to make a graph of a function over a range, we follow this pattern:
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```{julia}
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plot(sin, 0, 2pi)
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```
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