Search Results for "website using python"
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Showing 20 open source projects for "website using python"
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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
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. -
4
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. -
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5
FreeTAKServer
Situational Awareness Server compatible with TAK clients
FTS is a Python3 implementation of a TAK Server for devices like ATAK, WinTAK, and ITAK, it is cross-platform and runs from a multi-node installation on AWS down to the Android edition. It's free and open source (released under the Eclipse Public License. FTS allows you to connect ATAK clients to share geo-information, to chat with all the connected clients, exchange files and more. It intends to support all the major use cases of the original TAK server. -
6
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... -
7
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. -
8
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. -
9
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... -
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10
Kotlin multiplatform
Kotlin multiplatform / multi-format serialization
Kotlin serialization consists of a compiler plugin, that generates visitor code for serializable classes, a runtime library with core serialization API, and support libraries with various serialization formats. Using Kotlin Serialization requires Kotlin compiler 1.4.0 or higher. Make sure you have the corresponding Kotlin plugin installed in the IDE, no additional plugins for IDE are required. -
11
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. -
12
Connexion
Swagger/OpenAPI First framework for Python on top of Flask
Connexion is a framework on top of Flask that automagically handles HTTP requests defined using OpenAPI (formerly known as Swagger), supporting both v2.0 and v3.0 of the specification. Connexion allows you to write these specifications, then maps the endpoints to your Python functions. This is what makes it unique from other tools that generate the specification based on your Python code. You are free to describe your REST API with as much detail as you want and then Connexion guarantees that it will work as you specified. ... -
13
SAFRS
SqlAlchemy Flask-Restful Swagger Json:API OpenAPI
SAFRS exposes SQLAlchemy database models as a JSON:API web service and generates the corresponding swagger/OpenAPI. Database objects such as the User class from the demo.py example can be extended to include relationships with other objects. The demo_relationship.py contains the following extension of the User class where a relationship with the Book class is implemented. -
14
Go support for Protocol Buffers
The Go support for Google's protocol buffers
...You define how you want your data to be structured once, then you can use special generated source code to easily write and read your structured data to and from a variety of data streams and using a variety of languages. Protocol buffers currently support generated code in Java, Python, Objective-C, and C++. With our new proto3 language version, you can also work with Dart, Go, Ruby, and C#, with more languages to come. Package proto provides functions operating on protobuf messages such as cloning, merging, and checking equality, as well as binary serialization and text serialization. ... -
15
Inja
A Template Engine for Modern C++
Inja is a template engine for modern C++, loosely inspired by jinja for python. It has an easy and yet powerful template syntax with all variables, loops, conditions, includes, callbacks, and comments you need, nested and combined as you like. Inja uses the wonderful json library by nlohmann for data input. Most importantly, inja needs only two header files, which is (nearly) as trivial as integration in C++ can get. Of course, everything is tested on all relevant compilers. Inja is a... -
16
Showtime
A Minor Project made in Python using OMDb API and Tkinter for Frontend
A Minor Project made in Python using Tkinter for frontend which fetches Data about Movies/TV-Series from an Online Database and uses the OMDB REST API and pyImdb to show Information about movies. Github : https://github.com/Cyborg117/Showtime -
17
hyperjson
Python module for reading/writing JSON data using Rust's serde-json
A hyper-fast, safe Python module to read and write JSON data. Works as a drop-in replacement for Python's built-in json module. This is alpha software and there will be bugs, so maybe don't deploy to production just yet. -
18
Full Stack FastAPI Couchbase
Full stack, modern web application generator
Full stack, modern web application generator. Using FastAPI, Couchbase as a database, Docker, automatic HTTPS, and more. Couchbase has a great set of features that is not easily or commonly found in alternatives. REST backend tests based on Pytest, integrated with Docker, so you can test the full API interaction, independent on the database. As it runs in Docker, it can build a new data store from scratch each time (so you can use ElasticSearch, MongoDB, or whatever you want, and just test... -
19
Django REST Pandas
Serves up Pandas dataframes via the Django REST Framework
Django REST Pandas (DRP) provides a simple way to generate and serve pandas DataFrames via the Django REST Framework. The resulting API can serve up CSV (and a number of other formats for consumption by a client-side visualization tool like d3.js. The design philosophy of DRP enforces a strict separation between data and presentation. This keeps the implementation simple, but also has the nice side effect of making it trivial to provide the source data for your visualizations. This... -
20
Extended Memory Semantics (EMS)
Persistent shared object memory and parallelism for Node.js and Python
EMS makes possible persistent shared memory parallelism between Node.js, Python, and C/C++. Extended Memory Semantics (EMS) unifies synchronization and storage primitives to address several challenges of parallel programming. A modern multi-core server has 16-32 cores and nearly 1TB of memory, equivalent to an entire rack of systems from a few years ago. As a consequence, jobs formerly requiring a Map-Reduce cluster can now be performed entirely in shared memory on a single server without using distributed programming.
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