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Изворен канал @pythonotes · Post #421 · 23 мар.

Мы используем Makefile думая, что нет альтернатив, что это стандарт и всё такое. Но make это не запускалка команд, а система сборки. Мы фактически используем его не по назначению. И на самом деле альтернатива есть! Некоторое время назад я открыл для себя прекрасный инструмент - just. Он решает все проблемы make. just - это не система сборки как make, это именно исполнитель команд! Больше никаких Phony Targets и табуляций, привет нормальный синтаксис и передача аргументов!!! 😎 ⭐️Что умеет just: ✅ Автодокументирование команд Не нужно делать отдельную команду с докой, просто добавь комментарий # команда сборки build: ... $ just --list Available recipes: build # команда сборки Команда с именем default запускается по умолчанию если не указано другое, так что я обычно делаю так: default: just --list Теперь просто выполняем just и получаем доку из текущего файла. ✅ Удобная работа с переменными окружения # загрузить из .env set dotenv-load # глобальная переменная export PYTHONPATH := "./src" # переменная для команды test $TESTUNG="true": pytest ✅ Передача аргументов build target: @echo 'Build {{target}}...' команда запуска $ just build dev # Build dev... ✅ Выбор интерпретатора прямо в команде Пример с инлайн-скриптом на python: system: #!/usr/bin/env python3 import platform print(platform.system()) Эта же функция позволит выполнить скрипт как одну команду вместо перезапуска шела для каждой строки foo: #!/usr/bin/env sh for file in ls .; do echo $file done ✅ Выполнение команды в определенной директории. Можно указать как релятивный путь так и абсолютный [working-directory: 'backend'] build: docker compose build Также можно задать рабочую директорию глобально Там еще много интересного: - поддержка функций - автокомплиты и интеграции - экспрешены - алиасы команд - группировка команд - альтернативы команды под разные ОС - импорт других just-файлов - цветной вывод - ... и другие штуковины! Так что вперёд - ➡️ читать доку! Репозиторий: ➡️https://github.com/casey/just Статья: ➡️https://www.chicks.net/reference/file_formats/just/ ЗЫ. Кажется, на Makefile я уже не вернусь) #tools

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@meishi_sucai · Post #22862 · 27.02.2026 г., 07:36

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Data Science Jobs

@datasciencejobs · Post #2725 · 19.05.2025 г., 14:02

#vacancy#DataScience#remote#fulltime#Salmon Data Scientist (Junior+/Middle) 🌍 Preference will be given to candidates open to relocating to Manila; remote work is also possible with an initial working trip to Manila for 1–2 months Please note: we support remote work, but cannot hire candidates based in Russia or Belarus. Compensation: 4000-5000$ We’re looking for a thoughtful and detail-oriented Data Analyst / Data Scientist to join our team. In this role, you’ll work with large datasets, build clear visualizations, and deliver insights that directly shape decision-making while collaborating with analysts, engineers, and stakeholders across the company. Your future tasks: - Maintain and expand existing data science projects using Python, SQL, AWS, and GitLab - Analyze large datasets to uncover actionable insights and present them through dashboards and visual reports - Develop real-time monitoring tools to track key performance metrics - Collaborate cross-functionally with business analysts, software engineers, and stakeholders to understand requirements and deliver solutions What we expect from candidate: - 1+ years of experience in a similar data-focused role (data science, analytics, or related) - Strong SQL proficiency – able to write complex, optimized queries using joins, window functions, CTEs; experience with large-scale datasets is a plus - Proficient in Python for data science, using libraries such as Pandas, NumPy, and SciPy for analysis and automation - Solid grounding in statistical analysis – hypothesis testing, regression, distributions, and their application to real-world business use cases (e.g., A/B testing, forecasting) - Confident in data visualization – can build clear, effective visuals using Matplotlib, Seaborn, or tools like Tableau - Comfortable with version control systems – hands-on experience with GitLab (or similar tools like GitHub) - Experience with AWS is a plus Why join Salmon: - Passionate international team spanning the globe - Rapid professional growth. Merit (and merit only) rules the day - Reward for performance and long-term success of Salmon - Fast track to grow internationally - New office in Manila, Philippines - Relocation support for eligible candidates - Remote and hybrid options - Medical insurance, health and wellness benefits - Program of events and activities both online and in person 👉 More information and apply: @an_salmon

Data Science Jobs

@datasciencejobs · Post #2727 · 20.05.2025 г., 09:02

#vacancy#MachineLearning#remote#fulltime#Salmon Machine Learning Engineer 🌍 Preference will be given to candidates open to relocating to Manila; remote work is also possible with an initial working trip to Manila for 1–2 months Please note: we support remote work, but cannot hire candidates based in Russia or Belarus. Compensation: 4000-5000$ We’re looking for a curious and impact-driven Machine Learning Engineer to join our team and accelerate the development of robust, high-performing ML solutions across key business areas—including credit scoring, collection, antifraud, sales and other. This role combines hands-on development with strategic input, offering a chance to work on high-stakes, high-visibility projects from day one, collaborating with multiple departments and stakeholders to drive measurable business impact through better models What you'll do: - Own the end-to-end lifecycle of ML models: from EDA, feature generation, and hypothesis testing to production deployment and monitoring - Evaluate model performance and business impact, and iterate for continuous improvement - Explore and integrate new data sources (internal and external), identifying additional predictive signals - Contribute to advancements in modeling techniques, including geospatial and graph-based methods where relevant - Contribute to advancements in modeling techniques by exploring new algorithms and architectures What we’re looking for: - 2+ years of experience as a Machine Learning Engineer or Data Scientist, ideally in fintech or fast-paced product environments - Strong skills in Python and SQL; comfortable using Git - Solid foundation in classical ML techniques and Statistics; fluency in libraries, such as Pandas, Scikit-learn, NumPy, SciPy, Matplotlib/Seaborn/Plotly, Statsmodels, XGBoost/LightGBM/CatBoost etc. - Experience in credit risk modeling is a strong plus - Background in graph ML and/or experience with advanced geospatial analytics is an advantage - Experience working with AWS (or other cloud environments) is a plus Why join Salmon? What we’re building — Licensed neobank scaling modern financial services in Southeast Asia — Backed by global investors (ADQ, World Bank Group) with $60MM+ raised — Rapid product cycles: go from idea to launch in ~3 months — High-growth, high-impact market with global expansion potential What we offer — Remote or hybrid setup (GMT+5 to GMT+10 preferred) — New office in Manila with relocation support for eligible candidates — Competitive compensation in USD — Equity options and performance-based rewards — Medical insurance and wellness support — International team and fast career growth based on merit — Company-sponsored events and offsites 👉 More information and apply here: @an_salmon

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@meishi_sucai · Post #22982 · 30.03.2026 г., 01:55

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