This package provides a CLI tool and Python utility functions for manipulating SQLite databases. It's main features are:

• Pipe JSON (or CSV or TSV) directly into a new SQLite database file, automatically creating a table with the appropriate schema.

• Run in-memory SQL queries, including joins, directly against data in CSV, TSV or JSON files and view the results.

• Configure SQLite full-text search against your database tables and run search queries against them, ordered by relevance.

• Run transformations against your tables to make schema changes that SQLite ALTER TABLE does not directly support, such as changing the type of a column.

• Extract columns into separate tables to better normalize your existing data.

In order to be compatible with legacy web content when interpreting something like Content-Type: text/html; charset=latin1, tools need to use a particular set of aliases for encoding labels as well as some overriding rules. For example, US-ASCII and iso-8859-1 on the web are actually aliases for windows-1252, and a UTF-8 or UTF-16 BOM takes precedence over any other encoding declaration. The WHATWG Encoding standard defines all such details so that implementations do not have to reverse-engineer each other.

This module implements the Encoding standard and has encoding labels and BOM detection, but the actual implementation for encoders and decoders is Python’s.

This package provides easy download of thousands of pretrained models to perform tasks on different modalities such as text, vision, and audio.

These models can be applied on:

• Text, for tasks like text classification, information extraction, question answering, summarization, translation, and text generation, in over 100 languages.

• Images, for tasks like image classification, object detection, and segmentation.

• Audio, for tasks like speech recognition and audio classification.

Transformer models can also perform tasks on several modalities combined, such as table question answering, optical character recognition, information extraction from scanned documents, video classification, and visual question answering.

This package provides APIs to quickly download and use those pretrained models on a given text, fine-tune them on your own datasets and then share them with the community. At the same time, each Python module defining an architecture is fully standalone and can be modified to enable quick research experiments.

Transformers is backed by the three most popular deep learning libraries — Jax, PyTorch and TensorFlow — with a seamless integration between them.

PyCryptodome is a self-contained Python package of low-level cryptographic primitives. It's not a wrapper to a separate C library like OpenSSL. To the largest possible extent, algorithms are implemented in pure Python. Only the pieces that are extremely critical to performance (e.g., block ciphers) are implemented as C extensions.

You are expected to have a solid understanding of cryptography and security engineering to successfully use these primitives. You must also be able to recognize that some are obsolete (e.g., TDES) or even insecure (RC4).

It provides many enhancements over the last release of PyCrypto (2.6.1):

• Authenticated encryption modes (GCM, CCM, EAX, SIV, OCB)

• Accelerated AES on Intel platforms via AES-NI

• First-class support for PyPy

• Elliptic curves cryptography (NIST P-256 curve only)

• Better and more compact API (nonce and iv attributes for ciphers, automatic generation of random nonces and IVs, simplified CTR cipher mode, and more)

• SHA-3 (including SHAKE XOFs) and BLAKE2 hash algorithms

• Salsa20 and ChaCha20 stream ciphers

• scrypt and HKDF

• Deterministic (EC)DSA

• Password-protected PKCS#8 key containers

• Shamir’s Secret Sharing scheme

• Random numbers get sourced directly from the OS (and not from a CSPRNG in userspace)

• Cleaner RSA and DSA key generation (largely based on FIPS 186-4)

• Major clean-ups and simplification of the code base

This package provides drop-in compatibility with PyCrypto. It is one of two PyCryptodome variants, the other being python-pycryptodomex.

This package provides a Python library to communicate with Ledger Nano dongle.

Zope Location

Zope datetime.

grammars for babi

Zope Security Framework

Software Heritage Scheduler

Typing stubs for urllib3

Typing stubs for chardet.

Parse human-readable date/time text.

Software releasing made easy and repeatable.

This package provides typing stubs for urllib3.

Rule your architecture like a real developer.

python cffi bindings for the oniguruma regex engine

Thin Python wrapper for the US Census Geocoder

Front-end component renderer for Dash.

This package provides a command-line interface to Mathics3.

This package provides client-server SDK for Matrix.

This package implements schema validation for Xarray objects.

This package provides an implementation of Noise Protocol Framework.

This package provides a Flake8 lint for quotes.