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{"name": "cloud-duck", "metadata": {"name": "cloud-duck", "version": "0.0.0", "classifiers": ["Development Status :: 5 - Production/Stable", "Intended Audience :: Developers", "License :: OSI Approved", "Operating System :: OS Independent", "Programming Language :: JavaScript", "Programming Language :: Python :: 3 :: Only", "Programming Language :: Python :: 3.10", "Programming Language :: Python :: 3.11", "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", "Typing :: Typed"], "home_page": "https://github.com/malaysia.cryer/cloud-duck.git", "license": "Apache-2.0", "documentation_url": null, "dependencies": ["aws-cdk-lib", "constructs", "deploy-time-build", "jsii", "publication", "typeguard"], "summary": "CDK construct for creating an analysis environment using DuckDB for S3 data", "upload_time": 1735080863}, "documentation": ["<p align=\"center\">\n <img src=\"src/frontend/public/icon.png\" alt=\"CloudDuck Icon\" style=\"max-width: 400px; max-height: 400px;\" />\n</p>\n\nCloudDuck is a simple and easy-to-use analysis environment for S3 data, featuring DuckDB with built-in authentication.\n\n<p align=\"center\">\n <img src=\"images/duckdb-image.png\" alt=\"CloudDuck Display Image\" />\n</p>\n\n## Architecture\n\n![Architecture](images/architecture.png)\n\n## Installation\n\n```bash\nnpm i cloud-duck\n```\n\n## Usage\n\n### Deploy\n\n```python\nimport { CloudDuck } from 'cloud-duck';\n\ndeclare const logBucket: s3.IBucket;\n\nnew CloudDuck(this, 'CloudDuck', {\n // The S3 bucket to analyze\n // CloudDuck can access to all of the buckets in the account by default.\n // If you want to restrict the access, you can use the targetBuckets property.\n targetBuckets: [logBucket],\n});\n```\n\n### Add user to the Cognito User Pool\n\nAdd user to the Cognito User Pool to access the CloudDuck.\n\n### Access\n\nAccess to the CloudDuck with the cloudfront URL.\n\n```bash\n\u276f npx cdk deploy\n...\nAwsStack.CloudDuckDistributionUrl84FC8296 = https://dosjykpv096qr.cloudfront.net\nStack ARN:\narn:aws:cloudformation:us-east-1:123456789012:stack/AwsStack/dd0960c0-b3d5-11ef-bcfc-12cf7722116f\n\n\u2728 Total time: 73.59s\n```\n"], "modules": [{"name": "cloud-duck._jsii", "documentation": [], "functions": [{"name": "cloud-duck._jsii.check_type", "asynchronous": false, "params": [{"name": "argname", "type": {"name": "str", "xref": {"fqname": "functions.str", "project": "--std--"}, "params": null}, "default": null}, {"name": "value", "type": {"name": "object", "xref": {"fqname": "functions.object", "project": "--std--"}, "params": null}, "default": null}, {"name": "expected_type", "type": {"name": "typing.Any", "xref": {"fqname": "typing.Any", "project": "--std--"}, "params": null}, "default": null}], "returns": {"name": "typing.Any", "xref": {"fqname": "typing.Any", "project": "--std--"}, "params": null}, "documentation": []}], "variables": [{"name": "cloud-duck._jsii.__path__", "type": null, "documentation": []}, {"name": "cloud-duck._jsii.TYPEGUARD_MAJOR_VERSION", "type": null, "documentation": []}, {"name": "cloud-duck._jsii.__jsii_assembly__", "type": null, "documentation": []}], "classes": [], "exports": [{"name": "cloud-duck._jsii.__jsii_assembly__", "xref": {"fqname": "cloud-duck._jsii.__jsii_assembly__", "project": null}}]}, {"name": "cloud-duck", "documentation": ["<p align=\"center\">\n <img src=\"src/frontend/public/icon.png\" alt=\"CloudDuck Icon\" style=\"max-width: 400px; max-height: 400px;\" />\n</p>\n\nCloudDuck is a simple and easy-to-use analysis environment for S3 data, featuring DuckDB with built-in authentication.\n\n<p align=\"center\">\n <img src=\"images/duckdb-image.png\" alt=\"CloudDuck Display Image\" />\n</p>\n\n## Architecture\n\n![Architecture](images/architecture.png)\n\n## Installation\n\n```bash\nnpm i cloud-duck\n```\n\n## Usage\n\n### Deploy\n\n```python\nimport { CloudDuck } from 'cloud-duck';\n\ndeclare const logBucket: s3.IBucket;\n\nnew CloudDuck(this, 'CloudDuck', {\n // The S3 bucket to analyze\n // CloudDuck can access to all of the buckets in the account by default.\n // If you want to restrict the access, you can use the targetBuckets property.\n targetBuckets: [logBucket],\n});\n```\n\n### Add user to the Cognito User Pool\n\nAdd user to the Cognito User Pool to access the CloudDuck.\n\n### Access\n\nAccess to the CloudDuck with the cloudfront URL.\n\n```bash\n\u276f npx cdk deploy\n...\nAwsStack.CloudDuckDistributionUrl84FC8296 = https://dosjykpv096qr.cloudfront.net\nStack ARN:\narn:aws:cloudformation:us-east-1:123456789012:stack/AwsStack/dd0960c0-b3d5-11ef-bcfc-12cf7722116f\n\n\u2728 Total time: 73.59s\n```"], "functions": [{"name": "cloud-duck.check_type", "asynchronous": false, "params": [{"name": "argname", "type": {"name": "str", "xref": {"fqname": "functions.str", "project": "--std--"}, "params": null}, "default": null}, {"name": "value", "type": {"name": "object", "xref": {"fqname": "functions.object", "project": "--std--"}, 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{"name": "wlgen", "metadata": {"name": "wlgen", "version": "1.2", "classifiers": [], "home_page": null, "license": null, "documentation_url": null, "dependencies": ["ruff", "setuptools"], "summary": "A recursive wordlist generator written in python", "upload_time": 1735081627}, "documentation": ["[![Codacy Badge](https://api.codacy.com/project/badge/Grade/0a096cae2cdf489690eb6e0b4aa80c86)](https://app.codacy.com/app/tehw0lf/wlgen?utm_source=github.com&utm_medium=referral&utm_content=tehw0lf/wlgen&utm_campaign=Badge_Grade_Dashboard)\n[![Build Status](https://travis-ci.com/tehw0lf/wlgen.svg?branch=master)](https://travis-ci.com/tehw0lf/wlgen) [![codecov](https://codecov.io/gh/tehw0lf/wlgen/branch/master/graph/badge.svg)](https://codecov.io/gh/tehw0lf/wlgen)\n\n# Description\n\nA recursive wordlist generator written in Python.\nFor each string position, custom character sets can be defined.\n\n# Prerequisites\n\nPython 3.x (developed on Python 3.6.4)\n\n# Instructions\n\n## Installation\n\nTo install from GitHub:\n\n```\ngit clone https://github.com/tehw0lf/wlgen.git\ncd wlgen\npython setup.py test (optional unit tests to ensure functionality)\npip install .\n```\n\nTo install from PyPI:\n\n```\npip install wlgen\n```\n\n## Which function should I use?\n\nCurrently there are three implementations to generate a wordlist.\n`gen_wordlist` builds the whole list in memory before writing it, `gen_words` is a generator that is memory efficient but slower.\n`gen_wordlist_iter` uses `itertools.product` to generate the wordlist, which is recommended for lists that are too large to be built by `gen_wordlist`.\nBoth algorithms calculate the n-ary cartesian product of the input character sets.\n"], "modules": [{"name": "wlgen.tests", "documentation": [], "functions": [], "variables": [], "classes": [{"name": "wlgen.tests.wlgen_test", "bases": ["unittest.TestCase"], "methods": [{"name": "wlgen.tests.wlgen_test.setUp", "asynchronous": false, "params": [{"name": "self", "type": null, "default": null}], "returns": null, "documentation": []}, {"name": "wlgen.tests.wlgen_test.test_mixed_words", "asynchronous": false, "params": [{"name": "self", "type": null, "default": null}], "returns": null, "documentation": []}, {"name": "wlgen.tests.wlgen_test.test_mixed_list", "asynchronous": false, "params": [{"name": "self", "type": null, "default": null}], "returns": null, "documentation": []}, {"name": "wlgen.tests.wlgen_test.test_mixed_iter", "asynchronous": false, "params": [{"name": "self", "type": null, "default": null}], "returns": null, "documentation": []}], "class_variables": [], "instance_variables": [], "inner_classes": [], "documentation": []}], "exports": []}, {"name": "wlgen", "documentation": [], "functions": [{"name": "wlgen.gen_wordlist", "asynchronous": false, "params": [{"name": "charset", "type": null, "default": null}], "returns": null, "documentation": ["Recursively build a wordlist in memory\n\nRecursively builds a wordlist in memory, then returns complete list\nwhich can be written to a file using either stdout or by specifying\nan output file. The wordlist is being built bottom-up by combining\nthe current string position's character set with its previous one(s).\n\nThe input charset is assumed to be unique and sorted.\nExample: {0: '123', 1: 'ABC', 2: '!\"\u00a7 '}"]}, {"name": "wlgen.gen_wordlist_iter", "asynchronous": false, "params": [{"name": "charset", "type": null, "default": null}], "returns": null, "documentation": ["Generates a wordlist using itertools.product"]}, {"name": "wlgen.gen_words", "asynchronous": false, "params": [{"name": "charset", "type": null, "default": null}, {"name": "positions", "type": null, "default": "..."}, {"name": "prev_iter", "type": null, "default": "..."}], "returns": null, "documentation": ["Recursively generate wordlist word for word\n\nRecursively generates a wordlist word for word, based on a given\nsets of characters. charset is a dictionary containing character\nsets for each string position of the generated words.\n\nThe input charset is assumed to be unique and sorted.\nExample: {0: '123', 1: 'ABC', 2: '!\"\u00a7 '}"]}], "variables": [], "classes": [], "exports": []}]}

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