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Latest Onedrive for Windows Setup DataONE Python Products unknown 2019-07-03 CONTENTS 1 Utilities (for end users) 3 1.1 DataONE Command Line Utilities and Examples............................3 1.2 DataONE ONEDrive...........................................3 1.3 DataONE Command Line Interface...................................3 2 Member Node (for Member Node partners)5 2.1 Generic Member Node (GMN).....................................5 3 Python Libraries (for software developers)7 3.1 DataONE Common Library for Python.................................7 3.2 DataONE Client Library for Python...................................7 3.3 DataONE Science Metadata Validator for Python............................7 3.4 DataONE Test Utilities..........................................7 3.5 DataONE Dev Tools...........................................8 3.6 DataONE CSW Harvester........................................8 4 Contents 9 4.1 DataONE Utilities / Examples......................................9 4.2 DataONE ONEDrive........................................... 25 4.3 DataONE Command Line Interface (CLI)................................ 57 4.4 Generic Member Node (GMN)..................................... 85 4.5 Indices and tables............................................ 161 4.6 DataONE Common Library for Python................................. 162 4.7 Indices and tables............................................ 246 4.8 DataONE Client Library for Python................................... 246 4.9 Indices and tables............................................ 284 4.10 DataONE Science Metadata library for Python............................. 284 4.11 Indices and tables............................................ 292 4.12 DataONE Test Utilities.......................................... 292 Python Module Index 317 Index 321 i ii DataONE Python Products DataONE provides a number of products implemented in Python and Java, as part of the Investigator Toolkit (ITK). Potential users of these products include software developers, Member Node partners and end users. Only the Python products are outlined in this document. For software developers, DataONE provides development libraries implemented in Python. These provide functional- ity commonly needed by projects that interact with the DataONE infrastructure. It is recommended that applications implemented in Python use the libraries instead of interacting directly with the infrastructure as this is likely to reduce the development effort. For Member Node partners, DataONE provides a Member Node (MN) implemented in Python, called Generic Member Node (GMN). Lastly, DataONE provides various tools intended for end users, also implemented in Python. These include ONEDrive and the DataONE Command Line Client. CONTENTS 1 DataONE Python Products 2 CONTENTS CHAPTER ONE UTILITIES (FOR END USERS) 1.1 DataONE Command Line Utilities and Examples The DataONE Utilities / Examples package contains command line utilities for interacting with the DataONE infras- tructure. The utilities are implemented using the DataONE Common and Client libraries for Python. Effort has been put into keeping the implementations clear and easy to read, allowing the utilities to also serve as examples on how to use the DataONE Python libraries. After setup, all the utilities will be in the search path for the shell, so can be started from any directory. If using a virtual environment, the virtual environment must be active for the commands to work. 1.2 DataONE ONEDrive DataONE ONEDrive enables DataONE objects stored in Zotero citation manager libraries to be accessed like regular files on Windows, Mac OS X and Linux systems. This allows users to open remote DataONE objects locally and work with them as if they reside on the user’s computer. For instance, a spread sheet that is stored on a Member Node can be opened directly in Excel. DataONE objects can be added to a Zotero library via the ONEMercury search tool. Objects can also be added in all the other ways that Zotero supports. ONEDrive connects to a Zotero library and makes all DataONE objects within the library accessible as regular files. Zotero collections are represented as folders in the ONEDrive filesystem. 1.3 DataONE Command Line Interface The DataONE Command Line Interface (CLI) enables operations to be performed against the DataONE infrastructure from the command line. Supported operations include creating and retrieving DataONE objects, searching, updating access control rules and retrieving statistics. 3 DataONE Python Products 4 Chapter 1. Utilities (for end users) CHAPTER TWO MEMBER NODE (FOR MEMBER NODE PARTNERS) 2.1 Generic Member Node (GMN) The Generic Member Node (GMN) is a DataONE Member Node MN). It provides an implementation of MN APIs and can be used by organizations to expose their science data to DataONE if they do not wish to create their own, native MN. GMN can be used as a standalone MN or it can be used for exposing data that is already available on the web, to DataONE. When used in this way, GMN provides a DataONE compatible interface to existing data and does not store the data. GMN can also be used as a workbone or reference for a 3rd party MN implementation. If an organization wishes to donate storage space to DataONE, GMN can be set up as a replication target. 5 DataONE Python Products 6 Chapter 2. Member Node (for Member Node partners) CHAPTER THREE PYTHON LIBRARIES (FOR SOFTWARE DEVELOPERS) 3.1 DataONE Common Library for Python The DataONE Common Library for Python is a component of the DataONE Investigator Toolkit (ITK). It forms the foundation on which higher level components in the DataONE Python stack are built. It provides functionality commonly needed by clients, servers and other applications that interact with the DataONE infrastructure, including: • Serializing, deserializing, validating and type conversions for the DataONE XML types • Parsing and generating X.509 v3 certificates with DataONE extension • Parsing and generating OAI-ORE Resource Maps as used by DataONE • Utilities for working with XML documents, URLs, date-times, etc, in the context of DataONE 3.2 DataONE Client Library for Python The DataONE Client Library for Python works together with the DataONE Common Library for Python to provide functionality commonly needed by client software that connects to DataONE nodes. The main functionality provided by this library is a complete set of wrappers for all DataONE API methods. There are many details related to interacting with the DataONE API, such as creating MIME multipart messages, encoding parameters into URLs and handling Unicode. The wrappers hide these details, allowing the developer to communicate with nodes by calling native Python methods which take and return native Python objects. The wrappers also convert any errors received from the nodes into native exceptions, enabling clients to use Python’s concise exception handling system to handle errors. 3.3 DataONE Science Metadata Validator for Python The DataONE Science Metadata library for Python is a component of the DataONE Investigator Toolkit (ITK). It currently provides schema validation of DataONE Science Metadata XML documents. 3.4 DataONE Test Utilities The DataONE Test Utilities package contains various utilities for testing DataONE infrastructure components and clients. These include the Instance Generator, used for creating randomized System Metadata documents, and the Stress Tester, used for stress testing of Member Node implementations. The stress_tester can create many concurrent 7 DataONE Python Products connections to a Member Node and simultaneously create any number of randomly generated objects while running queries and object retrievals. There are also various Utilities. 3.5 DataONE Dev Tools 3.6 DataONE CSW Harvester 8 Chapter 3. Python Libraries (for software developers) CHAPTER FOUR CONTENTS 4.1 DataONE Utilities / Examples The DataONE Utilities / Examples package contains command line utilities for interacting with the DataONE infras- tructure. The utilities are implemented using the DataONE Common and Client libraries for Python. Effort has been put into keeping the implementations clear and easy to read, allowing the utilities to also serve as examples on how to use the DataONE Python libraries. After setup, all the utilities will be in the search path for the shell, so can be started from any directory. If using a virtual environment, the virtual environment must be active for the commands to work. Contents: 4.1.1 API d1_util package DataONE Utilities and Examples. A collection of scripts intended to be useful both as command line utilities and as examples on how to interact with the DataONE infrastructure via the DataONE Python stack. Although this directory is not a package, this __init__.py file is required for pytest to be able to reach test directories below this directory. Subpackages d1_util.tests package Submodules d1_util.tests.test_cert module Submodules d1_util.cert_check_cn module Submit a PEM (Base64) encoded X.509 v3 certificate to a CN for validation. 9 DataONE Python Products This is an example on how to use the DataONE Client and Common libraries for Python. It shows how to: • Submit a PEM (Base64) encoded X.509 v3 certificate, optionally containing a DataONE SubjectInfo extension, to a CN to check if it passes validation and to determine which DataONE subjects are authenticated by it. Example $ cert-check-cn –cert-pub /tmp/x509up_u1000 Notes: • Both the public and private key of the certificate are required. They may be in the same file, in which case only the --cert-pub
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