{"id":28941236,"url":"https://github.com/pyfunc/load","last_synced_at":"2026-01-20T17:58:55.232Z","repository":{"id":300440315,"uuid":"1006166566","full_name":"pyfunc/load","owner":"pyfunc","description":"load alternatywa dla import w Pythonie, inspirowaną prostotą Go i Groovy.","archived":false,"fork":false,"pushed_at":"2025-06-21T18:28:15.000Z","size":30,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-21T18:29:26.136Z","etag":null,"topics":["dependency","from","go","groovy","import","importer","laod","package","pip","pipx","python"],"latest_commit_sha":null,"homepage":"https://pyfunc.github.io/load/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pyfunc.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-21T16:36:21.000Z","updated_at":"2025-06-21T18:28:18.000Z","dependencies_parsed_at":"2025-06-21T18:40:50.772Z","dependency_job_id":null,"html_url":"https://github.com/pyfunc/load","commit_stats":null,"previous_names":["pyfunc/load"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/pyfunc/load","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyfunc%2Fload","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyfunc%2Fload/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyfunc%2Fload/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyfunc%2Fload/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pyfunc","download_url":"https://codeload.github.com/pyfunc/load/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pyfunc%2Fload/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":261397491,"owners_count":23152492,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["dependency","from","go","groovy","import","importer","laod","package","pip","pipx","python"],"created_at":"2025-06-23T02:09:39.037Z","updated_at":"2026-01-20T17:58:53.598Z","avatar_url":"https://github.com/pyfunc.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🔥 Load - Modern Python Import Alternative\n\nLoad is a modern alternative to Python's `import` system, inspired by the simplicity of Go and Groovy. It provides automatic package installation, intelligent caching, and magic import syntax.\n\n## 🎯 Purpose\n\nLoad simplifies Python imports by:\n- Reducing boilerplate code\n- Automating package installation\n- Improving developer productivity\n- Making imports more intuitive\n\n## ✨ Features\n\n- **Automatic Package Installation**: Missing packages are installed on demand\n- **Smart Caching**: Modules are cached for faster subsequent imports\n- **Magic Import Syntax**: Import with just the package name\n- **Function-level Imports**: Use `@load` decorator to manage dependencies at function level\n- **Multiple Registries**: Support for PyPI, GitHub, GitLab, and private registries\n- **Python 2/3 Compatible**: Works across Python versions\n\n## 🚀 Quick Start\n\nInstall load using any of these methods:\n\n```bash\n# 1. Using curl (Linux/macOS/WSL)\ncurl -sSL https://load.pyfunc.com | python3 -\n\n# 2. Using PowerShell (Windows)\n(Invoke-WebRequest -Uri https://load.pyfunc.com -UseBasicParsing).Content | py -\n\n# 3. Using Poetry\npoetry add load\n\n# 4. Using pip\npip install load\n```\n\n## 📚 Documentation\n\nFor detailed documentation, please refer to:\n\n- [📚 Installation Guide](https://github.com/pyfunc/load/blob/main/docs/installation.md)\n- [💪 Usage Examples](https://github.com/pyfunc/load/blob/main/docs/usage.md)\n- [📦 Features List](https://github.com/pyfunc/load/blob/main/docs/features.md)\n- [🔧 API Reference](https://github.com/pyfunc/load/blob/main/docs/api.md)\n- [🎯 Examples](https://github.com/pyfunc/load/tree/main/examples)\n- [📊 Diagrams](https://github.com/pyfunc/load/blob/main/docs/diagrams.md)\n\n## 🎯 Function-level Dependency Loading\n\nUse the `@load` decorator to automatically handle dependencies for specific functions:\n\n```python\nfrom load import load_decorator as load\n\n@load('numpy', 'pandas', 'plt=matplotlib.pyplot')\ndef analyze_data():\n    import numpy as np\n    data = np.random.rand(10, 3)\n    plt.plot(data)\n    plt.show()\n\n# The required packages will be automatically installed when the function is first called\nanalyze_data()\n```\n\nFor more examples and advanced usage, see the [Decorator Documentation](docs/decorator_usage.md).\n\n## 🤝 Contributing\n\nWe welcome contributions! Please see [CONTRIBUTING.md](https://github.com/pyfunc/load/blob/main/CONTRIBUTING.md) for guidelines.\n\n## 📚 Documentation Index\n\n- [📚 Installation Guide](docs/installation.md)\n- [💪 Usage Examples](docs/usage.md)\n- [🎯 Function-level Imports](docs/decorator_usage.md)\n- [📦 Features List](docs/features.md)\n- [🔧 API Reference](docs/api.md)\n- [🎯 Examples](examples/)\n- [📊 Diagrams](docs/diagrams.md)\n\n## 🔗 Links\n\n- [GitHub Repository](https://github.com/pyfunc/load)\n- [PyPI Package](https://pypi.org/project/load)\n- [Examples](https://github.com/pyfunc/load/tree/main/examples)\n\n## 🔍 Real-World Example\n\n### Data Science Workflow\n\n```python\n# Traditional way\nimport numpy as np\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom sklearn.linear_model import LinearRegression\n\n# With Load\nfrom load import load, import_aliases\n\n# Single import\nnp = load('numpy')\n\n# Multiple imports with aliases\npd, plt, sns = import_aliases('pandas', 'plt=matplotlib.pyplot', 'seaborn')\n\n# Direct attribute access\nmodel = load('sklearn.linear_model.LinearRegression')()\n\n# Now use them as usual\ndata = pd.DataFrame({'x': [1, 2, 3], 'y': [1, 2, 3]})\nmodel.fit(data[['x']], data['y'])\nplt.scatter(data['x'], data['y'])\nplt.plot(data['x'], model.predict(data[['x']]), 'r')\nplt.show()\n```\n\n### Web Development\n\n```python\nfrom load import load, configure_private_registry\n\n# Configure private registry\nconfigure_private_registry(\n    name=\"company\",\n    index_url=\"https://pypi.company.com/simple/\"\n)\n\n# Import standard and private packages\nfastapi = load('fastapi')\ninternal_auth = load('company-auth', registry=\"company\")\n\napp = fastapi.FastAPI()\n\n@app.get(\"/\")\nasync def root():\n    return {\"message\": \"Hello World\"}\n```\n\n### 🔒 Prywatne rejestry\n\n```python\n# Prywatny PyPI firmy\nconfigure_private_registry(\n    name=\"company\",\n    index_url=\"https://pypi.company.com/simple/\"\n)\n\n# Prywatny GitLab z tokenem  \nconfigure_private_registry(\n    name=\"internal\", \n    base_url=\"https://gitlab.company.com/\",\n    token=\"your-token\"  # lub GITLAB_TOKEN env var\n)\n\n# Użyj\ncompany_lib = load(\"internal-package\", registry=\"company\")\nsecret_tool = load(\"team/secret-sauce\", registry=\"internal\")\n```\n\n## 🎯 Smart Loading - automatyczne wykrywanie\n\nLoad automatycznie wykrywa skąd ładować:\n\n```python\nload(\"json\")                    # → stdlib (nie instaluje)\nload(\"requests\")                # → PyPI  \nload(\"user/repo\")               # → GitHub\nload(\"gitlab.com/user/proj\")    # → GitLab\nload(\"./file.py\")               # → Lokalny plik\nload(\"https://example.com/x.py\") # → URL\n```\n\n## 🏢 Przykłady dla firm\n\n### Startup z GitHub\n```python\n# Najnowsze z GitHub zamiast PyPI\nml_lib = load(\"huggingface/transformers\")\nselenium = load(\"SeleniumHQ/selenium/py\") \nplaywright = load(\"microsoft/playwright-python\")\n```\n\n### Korporacja z prywatnymi rejestrami\n```python\n# Skonfiguruj rejestry firmy\nconfigure_private_registry(\"nexus\", \n    index_url=\"https://nexus.company.com/pypi/simple/\")\n\nconfigure_private_registry(\"artifactory\",\n    index_url=\"https://company.jfrog.io/pypi/simple/\")\n\n# Używaj\nauth_lib = load(\"company-auth\", registry=\"nexus\")\ninternal_api = load(\"team-api-client\", registry=\"artifactory\")\n```\n\n### Projekt z mieszanymi źródłami\n```python\ndef setup_project():\n    return {\n        # PyPI - stabilne wersje\n        'web': load(\"fastapi\"),\n        'db': load(\"sqlalchemy\"),\n        \n        # GitHub - najnowsze funkcje  \n        'ai': load(\"openai/openai-python\"),\n        'scraping': load(\"microsoft/playwright-python\"),\n        \n        # Prywatne - firmowe narzędzia\n        'auth': load(\"auth-service\", registry=\"company\"),\n        'monitoring': load(\"team/observability\", registry=\"internal\"),\n        \n        # Lokalne - logika biznesowa\n        'models': load(\"./models.py\"),\n        'utils': load(\"./utils.py\")\n    }\n```\n\n## 🔧 Zarządzanie rejestrami\n\n```python\n# Lista dostępnych rejestrów\nlist_registries()\n\n# Dodaj własny rejestr\nadd_registry(\"custom\", {\n    'index_url': 'https://pypi.custom.com/simple/',\n    'install_cmd': [sys.executable, \"-m\", \"pip\", \"install\", \"--index-url\"],\n    'description': 'Custom PyPI mirror'\n})\n\n# Szybka konfiguracja\nconfigure_private_registry(\"maven-central\", \n    index_url=\"https://maven.central.com/pypi/\")\n```\n\n## 🚀 Przykłady projektów\n\n### Data Science\n```python\ndef setup_ds():\n    return {\n        'pd': load(\"pandas\", \"pd\"),                    # PyPI\n        'np': load(\"numpy\", \"np\"),                     # PyPI  \n        'latest_sklearn': load(\"scikit-learn/scikit-learn\"), # GitHub\n        'utils': load(\"./ds_utils.py\")                 # Local\n    }\n```\n\n### Web Development  \n```python\ndef setup_web():\n    return {\n        'api': load(\"fastapi\"),                        # PyPI\n        'auth': load(\"company-sso\", registry=\"nexus\"), # Private\n        'monitoring': load(\"team/apm-client\", registry=\"gitlab\"), # GitLab\n        'models': load(\"./models.py\")                  # Local\n    }\n```\n\n### AI/ML Pipeline\n```python\ndef setup_ai():\n    return {\n        'torch': load(\"pytorch/pytorch\"),              # GitHub latest\n        'transformers': load(\"huggingface/transformers\"), # GitHub\n        'custom_models': load(\"team/ml-models\", registry=\"company\"), # Private\n        'preprocessing': load(\"./preprocess.py\")        # Local\n    }\n```\n\n## 📊 Popularne rejestry w praktyce\n\n### Dla startupów\n- **PyPI** - podstawowe biblioteki\n- **GitHub** - najnowsze wersje, eksperymenty\n- **Lokalne pliki** - własna logika\n\n### Dla korporacji\n- **PyPI** - sprawdzone, stable biblioteki\n- **Prywatny PyPI** - firmowe pakiety\n- **GitLab Enterprise** - internal repos\n- **Artifactory/Nexus** - cache i security scanning\n\n### Dla research\n- **GitHub** - cutting-edge research code\n- **PyPI** - etablowane biblioteki naukowe\n- **URL** - papers with code, direct downloads\n\n## 🔒 Bezpieczeństwo\n\n```python\n# Kontroluj źródła\nALLOWED_REGISTRIES = ['pypi', 'company', 'github-trusted']\n\ndef secure_load(name, registry=None):\n    if registry not in ALLOWED_REGISTRIES:\n        raise SecurityError(f\"Registry {registry} not allowed\")\n    return load(name, registry=registry)\n```\n\n## 🎉 Dlaczego Load?\n\n| Problem | Tradycyjnie | Z Load |\n|---------|-------------|--------|\n| Instalacja | `pip install pkg` | `load(\"pkg\")` |\n| GitHub repo | Clone, setup.py, pip install | `load(\"user/repo\")` |\n| Prywatny rejestr | Konfiguruj pip.conf | `load(\"pkg\", registry=\"company\")` |\n| Różne źródła | Różne komendy | `load()` dla wszystkiego |\n| Najnowsza wersja | Czekaj na PyPI | `load(\"user/repo\")` z GitHub |\n\n**Load - jeden interfejs do wszystkich rejestrów Python!** 🚀\n\n---\n\n**Skopiuj `load.py`, napisz `from load import *` i ładuj skąd chcesz!**\n\n## 🔥 Podsumowanie - Load z rejestrami\n\nLoad z obsługą wszystkich głównych rejestrów Python:\n\n### 📦 **Obsługiwane rejestry:**\n\n1. **PyPI** (~500k pakietów) - `load(\"requests\")`\n2. **GitHub** (~miliony repozytoriów) - `load(\"user/repo\")`  \n3. **GitLab** (~setki tysięcy) - `load(\"gitlab.com/user/proj\")`\n4. **Prywatne PyPI** - `load(\"pkg\", registry=\"company\")`\n5. **URL** - `load(\"https://example.com/lib.py\")`\n6. **Lokalne pliki** - `load(\"./utils.py\")`\n\n### 🚀 **Kluczowe funkcje:**\n\n- **Smart detection** - automatycznie wykrywa skąd ładować\n- **Auto-install** - instaluje co brakuje\n- **Cache w RAM** - szybkie powtórne ładowanie\n- **Prywatne rejestry** - obsługa firmowych PyPI/GitLab z tokenami\n- **Zero config** - działa od razu\n\n### 💪 **Użycie:**\n\n```python\nfrom load import *\n\n# Podstawowe\nhttp = requests()                           # PyPI\ndata = pd()                                # PyPI + alias\n\n# GitHub (najnowsze wersje)\nai = load(\"openai/openai-python\")          # GitHub\nml = load(\"huggingface/transformers\")      # GitHub\n\n# Prywatne firmy\nauth = load(\"company-auth\", registry=\"nexus\")\napi = load(\"team/api\", registry=\"gitlab\")\n\n# Lokalne\nutils = load(\"./utils.py\")\n```\n\n### 🏢 **Dla firm:**\n\n```python\n# Skonfiguruj raz\nconfigure_private_registry(\"company\", \n    index_url=\"https://pypi.company.com/simple/\")\n\n# Używaj wszędzie\ninternal_lib = load(\"secret-package\", registry=\"company\")\n```\n\n### 🎯 **Główne zalety:**\n\n1. **Jeden interfejs** do wszystkich źródeł\n2. **Automatyczne wykrywanie** - nie musisz pamiętać skąd co\n3. **Obsługa tokenów** dla prywatnych repozytoriów\n4. **Szybkie** dzięki cache w RAM\n5. **Proste jak w Go** - jedna funkcja `load()`\n\n**Rezultat:** Zamiast kombinować z `pip install`, `git clone`, konfiguracją pip.conf - po prostu `load()` i działa! 🚀","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpyfunc%2Fload","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpyfunc%2Fload","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpyfunc%2Fload/lists"}