{ "info": { "author": "Kajigga dev", "author_email": "kajigga+dev@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.2", "Programming Language :: Python :: 3.3", "Programming Language :: Python :: 3.4", "Programming Language :: Python :: 3.5", "Topic :: Software Development :: Libraries :: Application Frameworks" ], "description": "CanvasData Utilities\n=======================\n\n.. image:: https://travis-ci.org/kajigga/py_canvas_data.svg\n\nFull documentation \n\nThis python module is designed to make it easy to access Canvas Data files.\n\nCurrently, this module makes it possible to:\n\n - Convert downloaded Canvas Data files to CSV files with headers\n - export SQL table creation statements \n - list files for a table\n - download all files or files for a specific table\n - view the Canvas Data schema (fields, field types, etc)\n - connect to a database (uses sqlalchemy) to create tables, import data, run SQL queries\n\n\n----\n\nModule Usage\n------------\n\nThis module can be used programatically in other scripts and software. An\nexample of creating a canvas_data object is found below.::\n \n from canvas_data_utils.canvas_data_auth import CanvasData\n\n canvas_data_object = CanvasData(\n API_KEY=YOUR_API_KEY ,\n API_SECRET=YOUR_API_SECRET, \n base_folder = YOUR_BASE_DIR,\n data_folder = YOUR_DATA_DIR)\n\n \nOnce you have that object created, you can...\n\ngenerate mysql table creation statements\n\n::\n\n mysql_table_creation_statement = canvas_data_object.table_creation_statement('mysql')\n\ngenerate sqlite table creation statements\n\n::\n\n sqlite_table_creation_statement = canvas_data_object.table_creation_statement('sqlite')\n\ngenerate postgres table creation statements\n\n::\n\n postgres_table_creation_statement = canvas_data_object.table_creation_statement('postgres')\n\ncreate tables in a database given by a connection string\n\n::\n\n canvas_data_object.create_tables('sqlite:///{}'.format(db_filename))\n\nfetch the current schema (as json)\n\n::\n\n schema = canvas_data_object.fetch_schema()\n\nget a list of columns in a table\n\n::\n\n user_dim_columns = canvas_data_object.get_schema_columns( 'user_dim')\n\nconvert an text file download from TSV (Tab Separated Values) to CSV\n\n::\n\n canvas_data_object.convert_tsv_to_csv(tsv_filepath)\n\nlist all the tables in the schema\n\n::\n\n table_list = canvas_data_object.table_list()\n\ndownload and convert all files to CSV\n\n::\n\n canvas_data_object.convert_all_to_csv()\n\nlist all downloadable files for a table\n\n::\n\n file_list = canvas_data_object.list_all_files('user_dim')\n\n----\n\nConfig File\n------------\nYou need to create a config file somewhere. This config file is a typical .INI\nfile. It should look something like the following example.\n\n::\n\n [config]\n API_SECRET = replace_with_api_secret_from_canvas_data\n API_KEY = replace_with_api_key_from_canvas_data\n\n base_folder = /path/to/base/folder/for/downloads/\n data_folder = %(base_folder)s/test2\n\n connection_string = sqlite:///%(base_folder)s/sample.db\n\n\nNote: The connection_string configuration follows the connection pattern needed\nby SQLAlchemy at http://docs.sqlalchemy.org/en/rel_1_0/core/engines.html.\n\nThis library supports any database type than SQLAlchemy does.\n\n----\n\nCommand-line Tool\n-----------------\n\nThis library includes a command line utility called `canvasdata`.\n\nUsage\n-----\n\n::\n\n canvasdata [-h] [--config CONFIG] [-t TABLE] [--offline OFFLINE]\n {convert_to_csv,import,create_tables,reset,sql_create_statement,list_files,download,sample_queries,schema}\n\n optional arguments:\n -h, --help show this help message and exit\n --config CONFIG path to the configuration file\n -t TABLE specify a specific table\n --offline OFFLINE run in offline mode", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "UNKNOWN", "keywords": "database canvasdata development", "license": "MIT", "maintainer": null, "maintainer_email": null, "name": "pycanvasdata", "package_url": "https://pypi.org/project/pycanvasdata/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/pycanvasdata/", "project_urls": { "Download": "UNKNOWN", "Homepage": "UNKNOWN" }, "release_url": "https://pypi.org/project/pycanvasdata/0.0.3/", "requires_dist": null, "requires_python": null, "summary": "Python utilities for working with Canvas Data", "version": "0.0.3" }, "last_serial": 2069819, "releases": { "0.0.1": [ { "comment_text": "", "digests": { "md5": "1236568f39abe00e99a101fb868ed62e", "sha256": "0984cbf2528f4d3441eb798aa0b171a2f66e047df16d3728db45721564ae62c8" }, "downloads": -1, "filename": "pycanvasdata-0.0.1.tar.gz", "has_sig": false, "md5_digest": "1236568f39abe00e99a101fb868ed62e", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 11889, "upload_time": "2016-04-14T20:32:40", "url": "https://files.pythonhosted.org/packages/d5/74/ddd6f6d089c968aa168233f366462c67f879b89ffa41b5e1650a02c2e79f/pycanvasdata-0.0.1.tar.gz" } ], "0.0.2": [ { "comment_text": "", "digests": { "md5": "947212cebfd1e8281c3f093e45b4beef", "sha256": "58ee8d08dc73644b1c25520943d5fe1af332ddfc32948f897d0ee5680e91e156" }, "downloads": -1, "filename": "pycanvasdata-0.0.2.tar.gz", "has_sig": false, "md5_digest": "947212cebfd1e8281c3f093e45b4beef", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 12135, "upload_time": "2016-04-18T15:09:28", "url": "https://files.pythonhosted.org/packages/75/a4/13903ac86abaa1463f749c7fc0c3beec7f40a018fa29940fef92aaa9b976/pycanvasdata-0.0.2.tar.gz" } ], "0.0.3": [ { "comment_text": "", "digests": { "md5": "aff7e6df602d9d6438f6920324eb31ff", "sha256": "5ee7fae59ba68c66ee9f739a4d3e48ec22f2afe473afea0948990da7fbf3219c" }, "downloads": -1, "filename": "pycanvasdata-0.0.3.tar.gz", "has_sig": false, "md5_digest": "aff7e6df602d9d6438f6920324eb31ff", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 12117, "upload_time": "2016-04-18T17:03:45", "url": "https://files.pythonhosted.org/packages/37/6a/91b09639d711fdba06586e9fcced16653b963b644081d030ead17e3e9a88/pycanvasdata-0.0.3.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "aff7e6df602d9d6438f6920324eb31ff", "sha256": "5ee7fae59ba68c66ee9f739a4d3e48ec22f2afe473afea0948990da7fbf3219c" }, "downloads": -1, "filename": "pycanvasdata-0.0.3.tar.gz", "has_sig": false, "md5_digest": "aff7e6df602d9d6438f6920324eb31ff", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 12117, "upload_time": "2016-04-18T17:03:45", "url": "https://files.pythonhosted.org/packages/37/6a/91b09639d711fdba06586e9fcced16653b963b644081d030ead17e3e9a88/pycanvasdata-0.0.3.tar.gz" } ] }