Project Euler Solutions

Overview

The code in this repository is a potential spoiler and you should NOT read NOR run it if you want to solve the problems yourself.

Project Euler problem solutions, written in multiple programming languages. For more information, check their website. Contributions are appreciated!

Table of Contents

1. Overview

2. Programming Languages

   • Python
   • C
   • C++
   • Go
   • JavaScript
   • Rust

3. Project Status

4. Adding Solutions

5. License

Programming Languages

Solutions are mainly implemented in Python3. For the future, solutions in Go, JavaScript, C and C++ will be added. Whenever possible, unit tests are implemented, too. Please consider contributing!

Python

Tests are implemented using the unittest module. Run tests with:

cd py_src
python3 test.py

C

To compile all solutions at once, type:

cd c_src/
make

To run test:

make test

To clean up binaries:

make clean

Unit tests are implemented using a custom framework (c_src/utest) with a basic set of assertion functions. Suggestions for improvements are welcome!

C++

Tested with g++8. First of all navigate to cpp_src and execute

cmake .

Afterwards you can build and run the tests with

make tests && ./tests.out

To build the problems use

make -j n

where n is the number of threads to use for the build. Now run with

./problem<number>.out

Go

The Go code in this repository is managed in another repository here. You can get the code by running:

go get github.com/DanielSchuette/goeulerproject

Then, run individual problem solutions, all problem solutions or the test suite:

go run main/problem<number>.go
sh install.sh --cover
go test .

JavaScript

The solutions are intended to be run with node from the command line:

npm install
node <solution_number.js> # or:
npm run <solution_number> # no 'js' extension required

Unit tests are implemented using Jest and can be run using:

npm run test # or:
jest # uses test.js as an entry point by default

Rust

To build the source files, you must have the Rust compiler (rustc) and Rust's package manager (cargo) installed. Then run:

cd rust_src

# builds and runs all solutions WITHOUT compiler optimizations
# faster build but slower execution times
cargo run

# build WITH compiler optimizations (much faster execution times)
cargo build --release
./target/release/rust_src

To run a certain problem, it must be selected via a ,-separated list or two :-separated integers that get expanded to a range:

cargo build -- 1,2,7 # runs problems 1, 2, and 7
cargo build -- 1,4:7 # runs problems 1 and 4 through 7

# or as arguments to the binary:
./target/release/rust_src 1,2,5:7

# run unit tests
cargo test

Project Status

The following table summarizes the current project status. The speed of the fastest solution per problem and programming language is shown as well (all test were run on a ThinkPad T440 with an Intel i5-4300U CPU). Rust solutions were built and run with --release flag for compiler optimizations. Solutions that are written in bold face and italics are still very slow and need improvement! The unit test coverage for all solutions is monitored via Travis and CodeCov.

Problem	Fastest Python	Fastest C	Fastest C++	Fastest JS	Fastest Go	Fastest Rust
1	+ (0.00s)	+ (0.00s)	compile time	+ (0.23s)	+ (0.00s)	+ (0.00s)
2	+ (0.00s)	+ (0.00s)	compile time	+ (0.17s)	+ (0.04s)	+ (0.00s)
3	+ (33.0s)	+ (0.01s)	+ (0.01s)	-	+ (0.83s)	+ (0.84s)
4	+ (0.09s)	-	+ (0.01s)	-	+ (0.07s)	+ (0.16s)
5	+ (0.00s)	-	+ (0.07s)	-	+ (6.74s)	+ (0.16s)
6	+ (0.00s)	-	+ (0.00s)	-	+ (0.00s)	+ (0.00s)
7	+ (0.29s)	-	+ (0.028s)	-	+ (5.14s)	+ (0.021s)
8	+ (0.00s)	-	-	-	+ (0.00s)	+ (0.00s)
9	+ (0.60s)	-	+ (0.01s)	-	+ (0.00s)	+ (0.01s)
10	+ (19.9s)	-	+ (0.66s)	-	+ (2.04s)	+ (0.98s)
11	+ (0.00)	-	-	-	-	+ (0.00s)
12	-	-	+ (0.08s)	-	-	+ (1.45s)
13	+ (0.00s)	-	-	-	-	+ (0.00s)
14	-	-	+ (0.25s)	-	-	+ (0.27s)
15	-	-	-	-	-	+ (0.00s)
16	+ (0.00s)	-	-	-	-	+ (0.00s)
17	-	-	-	-	-	+ (0.01s)
18	-	-	+ (0.00s)	-	-	+ (0.00s)
19	+ (0.00s)	-	+ (0.00s)	-	-	+ (0.00s)
20	-	-	-	-	-	+ (0.00s)
21	-	-	+ (0.02s)	-	-	+ (0.43s)
22	+ (0.02s)	-	-	-	-	+ (0.07s)
23	-	-	-	-	-	-
24	-	-	-	-	-	+ (0.03s)
25	+ (0.03s)	-	-	-	-	-
26	-	-	-	-	-	-
27	-	-	-	-	-	-
28	-	-	-	-	-	-
29	-	-	-	-	-	-
30	-	-	-	-	-	-
31	-	-	-	-	-	-
32	-	-	-	-	-	-
33	-	-	-	-	-	-
34	-	-	-	-	-	-
35	-	-	-	-	-	-
36	-	-	-	-	-	-
37	-	-	-	-	-	-
38	-	-	-	-	-	-
39	-	-	-	-	-	-
40	-	-	-	-	-	-
41	-	-	-	-	-	-
42	-	-	-	-	-	-
43	-	-	-	-	-	-
44	-	-	-	-	-	-
45	-	-	-	-	-	-
46	-	-	TBD	-	-	-
47	-	-	-	-	-	-
48	-	-	-	-	-	-
49	-	-	-	-	-	-
50	-	-	-	-	-	-
51	-	-	-	-	-	-
52	-	-	-	-	-	-
53	-	-	-	-	-	-
54	-	-	-	-	-	-
55	-	-	-	-	-	-
56	-	-	-	-	-	-
57	-	-	-	-	-	-
58	-	-	-	-	-	-
59	-	-	-	-	-	-
60	-	-	-	-	-	-
61	-	-	-	-	-	-
62	-	-	-	-	-	-
63	-	-	-	-	-	-
64	-	-	-	-	-	-
65	-	-	-	-	-	-
66	-	-	-	-	-	-
67	-	-	+ (0.00s)	-	-	+ (0.00s)
68	-	-	-	-	-	-
69	-	-	-	-	-	-

Adding Solutions

You can use the script gen_new_probl.sh to quickly generate a template for your problem solution. Problem number, author name and date will be automatically filled in. Javascript, Go and Rust are not yet fully supported, i.e. source files are created from templates but need to be modified to a certain amount.

E.g. to generate a template for your C++ solution to problem 123 use

./gen_new_problem.sh -l cpp -n 123

License

The code in this repository is MIT-licensed (see LICENSE.md for more information).