{"library":"stanza","title":"Stanza","type":"library","description":"Stanza, by the Stanford NLP Group, is a Python NLP library supporting over 70 human languages. It offers a fully neural pipeline for various text analysis tasks, including tokenization, multi-word token expansion, lemmatization, part-of-speech and morphological feature tagging, dependency parsing, and named entity recognition. Stanza also provides a stable Python interface to the Java Stanford CoreNLP Toolkit. Actively maintained, it receives regular updates, with the current version being 1.11.1.","language":"python","status":"active","last_verified":"Fri May 15","install":{"commands":["pip install stanza"],"cli":{"name":"stanza","version":""}},"imports":["import stanza"],"auth":{"required":false,"env_vars":[]},"links":{"homepage":"https://stanfordnlp.github.io/stanza/","github":"https://github.com/stanfordnlp/stanza","docs":null,"changelog":null,"pypi":"https://pypi.org/project/stanza/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null},"quickstart":{"code":"import stanza\n\n# Download an English model (only needs to be run once)\n# Stanza will auto-download if models are not found, but explicit download is good practice.\nstanza.download('en')\n\n# Initialize the English neural pipeline\nnlp = stanza.Pipeline('en')\n\n# Process some text\ntext = \"Barack Obama was born in Hawaii. He was the 44th President of the United States.\"\ndoc = nlp(text)\n\n# Access annotations\nprint(f\"Processing: '{text}'\")\nfor i, sent in enumerate(doc.sentences):\n    print(f\"\\nSentence {i+1}:\")\n    for word in sent.words:\n        print(f\"  {word.text}\\tUPOS: {word.upos}\\tLemma: {word.lemma}\\tDepRel: {word.deprel}\\tHead: {doc.sentences[0].words[word.head-1].text if word.head > 0 else 'ROOT'}\")\n\nprint(\"\\nNamed Entities:\")\nfor ent in doc.entities:\n    print(f\"  {ent.text}\\tType: {ent.type}\")","lang":"python","description":"This quickstart downloads the default English language model, initializes a Stanza pipeline, processes a sample text, and then prints out token-level annotations (UPOS, lemma, dependency relation) and named entities.","tag":null,"tag_description":null,"last_tested":null,"results":[]},"compatibility":{"tag":null,"tag_description":null,"last_tested":"2026-05-15","installed_version":"1.12.0","pypi_latest":"1.12.0","is_stale":false,"summary":{"python_range":"3.10–3.9","success_rate":90,"avg_install_s":69.5,"avg_import_s":3.74,"wheel_type":"wheel"},"results":[{"runtime":"python:3.10-alpine","python_version":"3.10","os_libc":"alpine (musl)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0,"mem_mb":0,"disk_size":"18.7M"},{"runtime":"python:3.10-slim","python_version":"3.10","os_libc":"slim (glibc)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":77.8,"import_time_s":5.55,"mem_mb":89,"disk_size":"4.7G"},{"runtime":"python:3.11-alpine","python_version":"3.11","os_libc":"alpine (musl)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0.01,"mem_mb":0,"disk_size":"20.6M"},{"runtime":"python:3.11-slim","python_version":"3.11","os_libc":"slim (glibc)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":73.2,"import_time_s":9.23,"mem_mb":96.1,"disk_size":"4.8G"},{"runtime":"python:3.12-alpine","python_version":"3.12","os_libc":"alpine (musl)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0,"mem_mb":0,"disk_size":"12.5M"},{"runtime":"python:3.12-slim","python_version":"3.12","os_libc":"slim (glibc)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":64.1,"import_time_s":11.47,"mem_mb":93.9,"disk_size":"4.8G"},{"runtime":"python:3.13-alpine","python_version":"3.13","os_libc":"alpine (musl)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0,"mem_mb":0,"disk_size":"12.2M"},{"runtime":"python:3.13-slim","python_version":"3.13","os_libc":"slim (glibc)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":63,"import_time_s":7.4,"mem_mb":96.3,"disk_size":"4.8G"},{"runtime":"python:3.9-alpine","python_version":"3.9","os_libc":"alpine (musl)","variant":"stanza","exit_code":0,"wheel_type":"wheel","failure_reason":null,"import_side_effects":"clean","install_time_s":null,"import_time_s":0,"mem_mb":0,"disk_size":"18.2M"},{"runtime":"python:3.9-slim","python_version":"3.9","os_libc":"slim (glibc)","variant":"stanza","exit_code":1,"wheel_type":null,"failure_reason":"timeout","import_side_effects":null,"install_time_s":null,"import_time_s":null,"mem_mb":null,"disk_size":null}]}}