Daily Interview: A Curated Chinese Tech Interview Cheat Sheet, Not a Textbook

Why This Repository Exists

Daily Interview tackles a specific pain: the overflow of scattered Chinese interview experience posts on platforms like Nowcoder and Zhihu. The README describes three problems: information overload, time pressure before interviews, and a lack of focus on what is actually asked. The project's answer is to curate only high-frequency questions and answers, aiming for precision over completeness. The intended audience is technical job seekers in China, specifically those applying for algorithm roles, development roles, or general technical positions. It is not a learning resource for beginners; it is a revision aid for people who already have a knowledge base and need a targeted refresher before an interview.

What the Content Covers and What It Omits

The repository organizes content into eight modules: algorithm basics, programming languages (Java, JavaScript, Python), computer fundamentals (OS, networking, databases, math), AI algorithms (ML, deep learning, NLP, CV), system design, development technologies (frontend, backend, big data), project experience, and behavioral interviews. The README explicitly states that it does not aim for full coverage and that knowledge evolves, so it focuses on core content. It also says it does not provide tutoring, because each person's weaknesses differ. This is a deliberate trade-off: you get a list of likely questions, but not the underlying theory. For example, an NLP question may list the mechanism of attention, but the answer is not meant to replace a textbook chapter. The project also includes LLM-related material added in July 2025, so the scope is current as of that date.

How the Project Is Structured for Fast Review

The README gives explicit study paths for different roles. For an algorithm position, the key modules are AI algorithms plus data structures, with math and computer fundamentals as support, and a suggested review time of 1-2 days before the interview. For development roles, the focus shifts to development technologies, data structures, and computer basics, with system design only for senior roles, and a half-day review is suggested. Universal preparation includes project experience and behavioral questions, with advice to prepare in advance and form your own expression templates. This role-based routing is the core mechanism: instead of reading everything, a candidate follows a prescribed sequence. The project also recommends marking weak points, practicing algorithm problems by hand, doing mock interviews with friends, and building personal notes from the content. These are study habits, not features of the repository itself, but they shape how the material is meant to be used.

Getting It Running: Reading Online or Cloning

The primary way to use Daily Interview is through the hosted website at https://datawhalechina.github.io/daily-interview/. The README calls this the best reading experience. There is no installation required for a reader. If you want to contribute or run it locally, the repository is on GitHub under datawhalechina/daily-interview, and the default branch is master. The README mentions a migration from Docsify to VitePress in August 2025, so the site is built with VitePress. To run it locally, you would clone the repository and use standard VitePress commands, though the README does not list specific commands. The update log states the migration improved build speed by over 99%, added a dual sidebar, local search with Chinese support, LaTeX math rendering, and code highlighting. For a reader, the practical step is just opening the URL. For a contributor, the project invites additions through GitHub Issues and Discussions, with named maintainers listed.

A Real Limitation: It Is a Cheat Sheet, Not a Teacher

The most significant limitation is that the project refuses to be comprehensive. The README says it does not aim for full coverage and does not provide remedial teaching. That means if you have a weak area, this repository will not help you build it up; it only tells you what questions might come up. For a candidate with gaps in, say, gradient descent math or OS scheduling, a list of questions without deep explanations is insufficient. Another limitation is the language: all content is in Chinese, so non-Chinese speakers cannot use it. The repository also has no release tags, so there is no versioned snapshot of content; the last push is dated 2026-07-08, but without releases, you cannot easily track what changed. The license is CC BY-NC-SA 4.0, which the README explains means non-commercial use only, and any derivatives must be shared under the same license. This is a real constraint if you wanted to incorporate questions into a paid course or a commercial interview prep service.

Alternatives and How They Differ

A direct alternative is LeetCode's discussion forum or the interview question banks on Nowcoder, which the README itself cites as sources of scattered information. The difference is that those platforms are crowdsourced and unstructured, with thousands of posts of varying quality. Daily Interview tries to filter that noise into a curated list. Another alternative is a formal textbook like 'Deep Learning' by Goodfellow or a machine learning course such as Andrew Ng's, which provide the underlying theory that Daily Interview deliberately omits. The difference in approach is fundamental: textbooks teach you why, while Daily Interview tells you what to expect. For system design, a resource like 'Designing Data-Intensive Applications' offers depth, but Daily Interview only gives a module label without detailed content visible in the README. If you need breadth or deep reasoning, those alternatives are better. If you need a last-minute review, Daily Interview's curation is the point.

Maintenance, Licensing, and Community Dynamics

The repository is under the Datawhale organization, a known Chinese open-source education group. The README lists active contributors, including a project lead and a core contributor with over 66 commits. The update log shows a major overhaul in August 2025, moving from Docsify to VitePress, and a previous update in July 2025 added LLM material. This suggests ongoing maintenance, but the last push date of 2026-07-08 is the only concrete signal in the material. The license is a point of caution: the README displays a CC BY-NC-SA 4.0 badge, but the GitHub repository metadata says GPL-3.0. This inconsistency is a genuine issue. The README's license section clearly describes CC BY-NC-SA 4.0 terms, including non-commercial use, but the repository's license field lists GPL-3.0. A user who clones the repository cannot be certain which license governs the content without checking the LICENSE file directly. That ambiguity is a red flag for any commercial or derivative use. The project also has no releases, so there is no formal versioning or changelog beyond the README's update history.

Editorial conclusion

Adopt Daily Interview if you are a Chinese-speaking candidate preparing for algorithm, AI, or development roles within 1-2 days of an interview and you want a condensed, high-frequency question set rather than a full curriculum. Do not adopt it if you need deep explanations, English content, or a comprehensive knowledge base, or if you plan any commercial use, since the CC BY-NC-SA 4.0 license forbids commercial redistribution. Before relying on it, verify that the material covers your specific job level and that you are comfortable with its non-commercial restriction, which also means any derivative you share must carry the same license. The repository's own history shows a migration in 2025 and an addition of LLM content, so check the last commit date to see if it is still active for your field.

Official sources

1. datawhalechina/daily-interview on GitHub
2. Issues
3. License: GPL-3.0
4. Project website
5. README