packtpublishing / julia-programming-projects

Julia Programming Projects, published by Packt

Julia Programming Projects

This is the code repository for Julia Programming Projects, published by Packt.

**Learn Julia 1.x by building apps for data analysis, visualization, machine learning, and the web **

What is this book about?

Julia is a new programming language that offers a unique combination of performance and productivity. Its powerful features, friendly syntax, and speed are attracting a growing number of adopters from Python, R, and Matlab, effectively raising the bar for modern general and scientific computing.

This book covers the following exciting features:

• Leverage Julia's strengths, its top packages, and main IDE options
• Analyze and manipulate datasets using Julia and DataFrames
• Write complex code while building real-life Julia applications
• Develop and run a web app using Julia and the HTTP package
• Build a recommender system using supervised machine learning
• Perform exploratory data analysis
• Apply unsupervised machine learning algorithms
• Perform time series data analysis, visualization, and forecasting

If you feel this book is for you, get your copy today!

Instructions and Navigations

All of the code is organized into folders. For example, Chapter02.

The code will look like the following:

function articleinfo(content) 
  dom = articledom(content) 
  (extractcontent(dom.root), extractlinks(dom.root), extracttitle(dom.root), extractimage(dom.root)) 
end 

Following is what you need for this book: Data scientists, statisticians, business analysts, and developers who are interested in learning how to use Julia to crunch numbers, analyze data and build apps will find this book useful. A basic knowledge of programming is assumed.

With the following software and hardware list you can run all code files present in the book (Chapter 1-11).

Software and Hardware List

Chapter	Software required	OS required
1-11	Julia	Windows, Mac OS X, and Linux (Any)

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.

Related products

• Julia 1.0 Programming Cookbook [Packt] [Amazon]

• Julia 1.0 Programming - Second Edition [Packt] [Amazon]

Get to Know the Author

Adrian Salceanu has been a professional software developer for over 15 years. For the last 10, he's been leading agile teams in developing real-time, data-intensive web and mobile products. Adrian is a public speaker and an enthusiastic contributor to the open source community, focusing on high-performance web development. He's the organizer of the Barcelona Julia Users group and the creator of Genie, a high-performance, highly productive Julia web framework. Adrian has a Master's degree in computing and a postgraduate degree in advanced computer science.

Suggestions and Feedback

Click here if you have any feedback or suggestions.

Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost.
Simply click on the link to claim your free PDF.

https://packt.link/free-ebook/9781788292740

julia-programming-projects's Issues

Chapter 7

Hi Adrian,

Some problems in the chapter.
Please close the issue once they are solved and tell me what's been done.

Dataframes versions and casting

Using

### Dataframes version:	0.10.1
path_to_ratings  = "../chapter7_data/ratings.dat.txt"
ratings = CSV.read(path_to_ratings, header = false);

UserID | ProfileID | Rating
-- | -- | --
Nullable{Int64}(1) | Nullable{Int64}(133) | Nullable{Int64}(8)
Nullable{Int64}(1) | Nullable{Int64}(720) | Nullable{Int64}(6)

If I cast it manually then it works

ratings[:UserID] = Array{Int}(ratings[:UserID])
ratings[:ProfileID] = Array{Int}(ratings[:ProfileID])
ratings[:Rating] = Array{Int}(ratings[:Rating])
head(ratings, 3)

UserID | ProfileID | Rating
-- | -- | --
1 | 133 | 8
1 | 720 | 6
1 | 971 | 10

results differ

Training and train-test partitions need seeds to make results reproducible

0-element Array{Int64,1}

intersect(test_profile_ids, recommendations_to_profiles(recommend(recommender, 100, 100, [1:profile_counter...])))
0-element Array{Int64,1}

Loading csv file

I am using Julia 1.4.1
CSV.read("Map_of_Registered_Business_Locations.csv")
gives range range error with this message
df = CSV.read("Map_of_Registered_Business_Locations.csv", header = 1, delim = ',', missingstring = "", quotechar='"', escapechar='"', copycols=true)
ERROR: LoadError: ArgumentError: Day: 151 out of range (1:31)

Chapter 5, `HTTP.Server` not defined with v0.8.0

The sample hello.jl in Chapter 5 no longer works with [email protected], gets

UndefVarError: Server not defined

Downgrading to v0.7.1 works, so perhaps there has been API change in the package.

This is not a book issue and I can work with the older version during learning this book, but can someone possibly suggest a quick fix with new version for future reference?

Chapter 3 - run webcrawler.jl

On page 144, running webcrawler.jl as instructed julia webcrawler.jl will fail to load the required packages (HTTP, Gumbo). Got it working with julia --project=@. webcrawler.jl.

Running julia version 1.0.3 on Ubuntu 18.04.
Excellent book, btw, thank you, Adrian!

Chap4 comments

Causes the document to not be built for Travis

Based on the discussion I had here: JuliaDocs/Documenter.jl#1123

Julia-Programming-Projects/Chapter11/IssueReporter/docs/make.jl

Line 1 in d30b6ab

using Pkg

causes the document to not be built for Travis.

So it is better to have two make.jl and makeLocal.jl. makeLocal.jl can be the same as this book's advice. But for make.jl, we should remove 1st 4 lines.

A full working example is available here: https://github.com/juliamatlab/MatLang/tree/master/docs

My instructions are as follows:

To build the documentation locally

Running inside Julia REPL:

cd to docs folder cd("path to docs\\MatLang\\docs") and run the following command:

include("makeLocal.jl") 

Running inside OS Terminal:

cd to docs folder using OS terminal and run the following command (Julia path should be added to OS path):

julia --color=yes makeLocal.jl

Alternatively, you can use make.jl but using the following method:
cd to package folder using OS terminal and run the following commands:

julia -e 'using Pkg; Pkg.activate(); push!(LOAD_PATH, pwd());'
julia --project=docs/ -e 'using Pkg; Pkg.activate();  push!(LOAD_PATH,pwd());'

julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate();'
julia --project=docs/ --color=yes docs/make.jl

To build the documentation online using Travis

Use this Travis script:

- julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd()));
                                               Pkg.instantiate()'
- julia --project=docs/ docs/make.jl