Project Euler

Role in learning and careers

• Many commenters credit Project Euler (PE) with sparking or solidifying their love of programming, math, or computer science, often starting in high school or early university.
• Several say it directly contributed to landing their first dev job or choosing software as a career.
• One detailed story describes PE problems appearing almost verbatim in a job interview, leading to a life turnaround from drug use and academic failure to a stable dev career and a SaaS business.

Problem design, difficulty, and pedagogy

• Early problems (roughly first 50–100) are seen as accessible and highly fun; beyond that, many feel a growing need for deeper math (number theory, combinatorics, more “paper solutions”).
• People highlight the blend of elegant math tricks and brute-force optimization, noting that neither approach alone dominates.
• Example discussion: triangle “longest path” problems—some suggest transforming to a shortest-path graph problem, others point out dynamic programming on the triangle is simpler and that generic graph algorithms are overkill.

Languages, paradigms, and codecraft

• PE is widely used to learn new languages: Python, Rust, Haskell, OCaml, J, APL-like array languages, AWK, Livecode, Oberon-2, etc.
• Commenters enjoy reading others’ solutions, especially ultra-concise APL/J/Uiua code and math-heavy approaches.
• Some maintain repositories of their solutions as reference code; others regret treating them as throwaway.

Math background and recommended resources

• Beyond early problems, commenters report needing elementary number theory and related topics.
• “Concrete Mathematics” is specifically recommended as an ideal preparation for mid-to-late PE problems, matching the site’s focus on number theory, combinatorics, and computation.
• Some individual problems are linked to contest problems (e.g., Putnam) and solved using Markov chains or probability.

Community, site operations, and longevity

• Secret discussion forums per problem are remembered fondly.
• PE is praised for still releasing weekly problems, with a significant backlog and an active core team that refines user-submitted problems.
• Multiple reports of account or data loss (including after a disk crash) contrast with others whose accounts were recovered; some users now rely on local/source-controlled copies of their solutions.

AI, cheating, and LLMs

• There is concern and curiosity about users employing AI to solve problems, but many note it’s a “single-player game” where cheating mostly hurts oneself.
• One commenter tested an LLM that one-shot a correct solution for a later problem; others debate whether this is genuine reasoning or training-data regurgitation and whether such experiments are worthwhile.

Comparisons, alternatives, and related sites

• PE is often contrasted favorably with LeetCode: more fun, more mathematical, but less directly applicable to interviews (though some interviewers say they would value it).
• Other suggested resources: Advent of Code, Rosalind (bioinformatics), IBM’s “Ponder This” (described as harder and requiring more mathematical maturity), and various puzzle sites.
• freeCodeCamp’s integration of PE problems is noted as bringing PE to newer generations.

Onboarding, access, and quirks

• Users mention “Problem Zero” as a signup challenge involving big integers, which can expose language limitations (e.g., lack of bignums) and inspire implementing arbitrary-precision libraries.
• A few people report issues accessing or registering on the site (403 errors, captcha/confirmation failures).
• Minor side topics include Euler’s name pronunciation (“Oiler”) and nostalgia for earlier contest ecosystems like Google Code Jam.