Search Results for "google-visualization-python"
Sort By:
Showing 82 open source projects for "google-visualization-python"
View related business solutions-
Veeam Data Platform v13.1 - Get Your Free TrialTry Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
1
python-benedict
dict subclass with keylist/keypath support
python-benedict is a dict subclass with keylist/keypath/keyattr support, I/O shortcuts (base64, cli, csv, ini, json, pickle, plist, query-string, toml, xls, xml, yaml) and many utilities... for humans, obviously. -
2
Extract TOTP/HOTP secrets
Extract one time password (OTP) secrets from QR codes
The Python script extract_otp_secrets.py extracts one-time password (OTP) secrets from QR codes exported by two-factor authentication (2FA) apps such as "Google Authenticator". -
3
Python JSONPath Next-Generation
JSONPath implementation for Python that aims to be standard compliant
A final implementation of JSONPath for Python that aims to be standard compliant, including arithmetic and binary comparison operators, as defined in the original JSONPath proposal. This package merges both jsonpath-rw and jsonpath-rw-ext and provides several AST API enhancements, such as the ability to update or remove nodes in the tree. This library provides a robust and significantly extended implementation of JSONPath for Python. -
4
srsly
Modern high-performance serialization utilities for Python
This package bundles some of the best Python serialization libraries into one standalone package, with a high-level API that makes it easy to write code that's correct across platforms and Pythons. This allows us to provide all the serialization utilities we need in a single binary wheel. Currently supports JSON, JSONL, MessagePack, Pickle, and YAML. Serialization is hard, especially across Python versions and multiple platforms. -
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
5
simplejson
simplejson is a simple, fast, extensible JSON encoder/decoder
simplejson is a simple, fast, complete, correct and extensible JSON <http://json.org> encoder and decoder for Python 3.3+ with legacy support for Python 2.5+. It is pure Python code with no dependencies but includes an optional C extension for a serious speed boost. simplejson is the externally maintained development version of the json library included with Python (since 2.6). This version is tested with the latest Python 3.8 and maintains backward compatibility with Python 3.3+ and the legacy Python 2.5 - Python 2.7 releases. ... -
6
Cortex Analyzers
Cortex Analyzers Repository
Analyzers can be written in any programming language supported by Linux such as Python, Ruby, Perl, etc. Refer to the How to Write and Submit an Analyzer page for details on how to write and submit one. -
7
SQLModel
SQL databases in Python, designed for simplicity, compatibility
SQLModel, SQL databases in Python, designed for simplicity, compatibility, and robustness. SQLModel is a library for interacting with SQL databases from Python code, with Python objects. It is designed to be intuitive, easy to use, highly compatible, and robust. SQLModel is based on Python-type annotations, and powered by Pydantic and SQLAlchemy. -
8
JSON Crack
Innovative and open-source visualization application
JSON Crack is a free, open-source data visualization app capable of visualizing data formats such as JSON, YAML, XML, CSV and more, into interactive graphs. With its intuitive and user-friendly interface, JSON Crack makes it easy to explore, analyze, and understand even the most complex data structures. Whether you're a developer working on a large-scale project or a data enthusiast looking to uncover hidden insights, JSON Crack has the tools and features you need to unlock the full potential of your data. -
9
StringZilla
10x faster string search, split, sort, and shuffle for long strings
...It matches the first few letters of words with hyper-scalar code to achieve memcpy speeds. The implementation fits into a single C 99 header file and uses different SIMD flavors and SWAR on older platforms. The Str is designed to replace long Python str strings and wrap our C-level API. On the other hand, the File memory-maps a file from persistent memory without loading its copy into RAM. The contents of that file would remain immutable, and the mapping can be shared by multiple Python processes simultaneously. A standard dataset pre-processing use case would be to map a sizeable textual dataset like Common Crawl into memory, spawn child processes, and split the job between them. -
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
10
jsonschema
An implementation of the JSON Schema specification for Python
jsonschema is an implementation of the JSON Schema specification for Python. Full support for Draft 2020-12, Draft 2019-09, Draft 7, Draft 6, Draft 4 and Draft 3. Lazy validation that can iteratively report all validation errors. Programmatic querying of which properties or items failed validation. -
11
pytablewriter
pytablewriter is a Python library to write a table in various formats
pytablewriter is a Python library to write a table in various formats: AsciiDoc / CSV / Elasticsearch / HTML / JavaScript / JSON / LaTeX / LDJSON / LTSV / Markdown / MediaWiki / NumPy / Excel / Pandas / Python / reStructuredText / SQLite / TOML / TSV / YAML. -
12
ScanAPI
Automated Integration Testing and Live Documentation for your API
Given an API specification, written in YAML/JSON format, ScanAPI hits the specified endpoints, runs the test cases, and generates a detailed report of this execution - which can also be used as the API documentation itself. With almost no Python knowledge, the user can define endpoints to be hit, the expected behavior for each response and will receive a full real-time diagnostic report of the API. -
13
orjson
Fast, correct Python JSON library supporting dataclasses, datetimes
orjson is a fast, correct JSON library for Python. It benchmarks as the fastest Python library for JSON and is more correct than the standard json library or other third-party libraries. It serializes dataclass, datetime, numpy, and UUID instances natively. orjson supports CPython 3.8, 3.9, 3.10, 3.11, and 3.12. It distributes amd64/x86_64, aarch64/armv8, arm7, POWER/ppc64le, and s390x wheels for Linux, amd64 and aarch64 wheels for macOS, and amd64 and i686/x86 wheels for Windows. orjson does not support PyPy. ... -
14
OSCAL
Open Security Controls Assessment Language (OSCAL)
NIST is developing the Open Security Controls Assessment Language (OSCAL), a set of hierarchical, XML-, JSON-, and YAML-based formats that provide a standardized representation of information pertaining to the publication, implementation, and assessment of security controls. OSCAL is being developed through a collaborative approach with the public. Public contributions to this project are welcome. With this effort, we are stressing the agile development of a set of minimal formats that are... -
15
msgspec
A fast serialization and validation library, with builtin
msgspec is a fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML. -
16
yq JSON
Command-line YAML, XML, TOML processor
Before using yq, you also have to install its dependency, jq. See the jq installation instructions for details and directions specific to your platform. On macOS, yq is also available on Homebrew use brew install python-yq. -
17
Remarshal
Convert between CBOR, JSON, MessagePack, TOML, and YAML
Convert between CBOR, JSON, MessagePack, TOML, and YAML. When installed, provides the command-line command remarshal as well as the short commands {cbor,json,msgpack,toml,yaml}2{cbor,json,msgpack,toml,yaml}. You can perform format conversion, reformatting, and error detection using these commands. CBOR, MessagePack, and YAML with binary fields cannot be converted to JSON or TOML. Binary fields are converted between CBOR, MessagePack, and YAML. -
18
Mashumaro
Fast and well tested serialization library on top of dataclasses
When using data classes, you often need to dump and load objects based on the schema you have. Mashumaro not only lets you save and load things in different ways, but it also does it super quickly. -
19
tmuxp
tmux session manager. built on libtmux
A session manager for tmux. Built on libtmux. -
20
pyserde
Yet another serialization library on top of dataclasses
Yet another serialization library on top of data classes, inspired by serde-rs. Declare a class with pyserde's @serde decorator. -
21
Alcinoe
Alcinoe Component Library For Delphi
Alcinoe is a library of visual and non-visual components for Delphi. These components can be used in commercial, shareware, freeware, and open-source projects at no cost. Alcinoe is compatible with Delphi Alexandria 11.3 (Patch #1). If you find this project useful, please consider giving it a 'star' on GitHub. It doesn't cost anything, but it helps to promote the code. To set up Alcinoe, first execute CompileAll.bat. This batch file handles a series of tasks: it retrieves and patches the... -
22
Canmatrix
Converting Can (Controller Area Network) Database Formats
Canmatrix is a Python package to read and write several CAN (Controller Area Network) database formats. Canmatrix implements a "Python Can Matrix Object" which describes the can-communication and the needed objects (Board units, Frames, Signals, Values, ...) Canmatrix also includes two Tools (can convert and can compare) for converting and comparing CAN databases. -
23
jello
CLI tool to filter JSON and JSON Lines data with Python syntax
Filter JSON and JSON Lines data with Python syntax. jello is similar to jq in that it processes JSON and JSON Lines data except jello uses standard python dict and list syntax. JSON or JSON Lines can be piped into jello via STDIN or can be loaded from a JSON file or JSON Lines files (JSON Lines are automatically slurped into a list of dictionaries). Once loaded, the data is available as a python list or dictionary object named '_'. -
24
Awkward Array
Manipulate JSON-like data with NumPy-like idioms
Awkward Array is a library for nested, variable-sized data, including arbitrary-length lists, records, mixed types, and missing data, using NumPy-like idioms. Arrays are dynamically typed, but operations on them are compiled and fast. Their behavior coincides with NumPy when array dimensions are regular and generalizes when they're not. -
25
JC
CLI tool and python library
...The JC parsers can also be used as python modules. In this case, the output will be a python dictionary, or a list of dictionaries, instead of JSON. Two representations of the data are available. The default representation uses a strict schema per parser and converts known numbers to int/float JSON values. Certain known values of None are converted to JSON null, known boolean values are converted, and, in some cases, additional semantic context fields are added.
