Packages
Provides a DirectoryTree widget for Textual terminal UIs that works with local and remote filesystems including S3, GCS, Azure, GitHub, and SSH through universal-pathlib and fsspec.
Decodes compressed texture formats (BC, PVRTC, ETC, ASTC, ATC, Crunch) used in game assets and 3D applications, converting them to raw BGRA pixel data.
Backports Python 3.6's textwrap module to earlier Python versions, making APIs like shorten() and max_lines available across Python 2.6 and 3.x with improved Unicode handling.
textX is a meta-language for building Domain-Specific Languages (DSLs) in Python by defining a grammar that automatically generates a parser and meta-model for your language.
Provides high-level APIs for training, evaluating, and exporting machine learning models, encapsulating the full model lifecycle.
TF-Keras is the pure-TensorFlow implementation of Keras, providing a high-level API for building and training deep learning models with TensorFlow as the backend.
TF-Keras is a pure-TensorFlow implementation of Keras that provides a high-level deep learning API for building and training neural networks.
The nightly build is suitable for developers and researchers who can tolerate frequent changes and want early access to new features, but not for production systems…
Provides state-of-the-art TensorFlow model implementations and training solutions across computer vision, NLP, and other domains with official and research implementations.
tf-nightly provides nightly builds of TensorFlow, an open-source framework for numerical computation and machine learning that runs on CPUs, GPUs, TPUs, and edge devices.
tf-nightly-cpu provides a CPU-optimized nightly build of TensorFlow for numerical computation, machine learning, and deep learning across CPUs, GPUs, TPUs, and edge devices.
Patches Playwright to evade bot-detection systems by spoofing browser features and headers, reducing the likelihood of automated scripts being identified as non-human.
TensorFlow-Slim provides high-level layers, variable management, and training utilities that simplify defining, training, and evaluating neural network models in TensorFlow.
Provides a Conditional Random Field (CRF) layer for TensorFlow 2 Keras models, enabling sequence labeling tasks with built-in support for masking and mixed precision training.
Install only if you can verify compatibility with your TensorFlow and tensorflow-addons versions, and accept the risk that bugs or incompatibilities will not be fixed…
Converts TensorFlow, Keras, TensorFlow.js, and TFLite models to ONNX format via command line or Python API, enabling model portability across different inference runtimes.
Provides a library of ready-to-use public datasets formatted as tf.data.Datasets for machine learning workflows, handling download, preparation, and standardized access.
However, this is a nightly build (version 4.9.9.dev202510250044)—use the stable release for production unless you specifically need development features.
Performs fast fuzzy string matching on large datasets using TF-IDF vectorization and K-Nearest Neighbours, scaling better than traditional fuzzy matchers by avoiding O(n²) complexity.
However, the last update was in April 2023, there is no active maintenance, and testing is limited to a single use case.
Parses TensorFlow Lite (*.tflite) model files and provides a Python API to inspect their structure, operators, and metadata.
TensorFlow Lite runtime enables on-device machine learning inference on mobile and embedded devices with low latency and minimal binary size.
However, the dormant maintenance status means no recent updates or security patches; verify compatibility with your target model format and hardware before committing…
TensorFlow Probability provides probabilistic modeling, statistical inference, and Bayesian machine learning tools integrated with TensorFlow and JAX, including distributions, bijectors, inference algorithms, and probabilistic neural network layers.
tfparse parses and evaluates Terraform HCL configuration files using Go bindings to the canonical Terraform implementation and defsec evaluation engine.
Wraps the Terraform executable to facilitate testing Terraform modules from Python unit tests, exposing methods to set up fixtures, execute Terraform commands, and parse their output.
Install it if you write Python tests for Terraform modules.
tfx_bsl provides shared libraries and utilities used internally by TensorFlow eXtended (TFX) components and standalone TFX libraries like TFDV, TFMA, and TFT.
TgCrypto provides fast C-based implementations of AES-256 encryption in IGE, CTR, and CBC modes, designed specifically for Telegram's MTProto protocol and related cryptographic needs.
TGScheduler is a pure Python task scheduler that runs one-time or recurring tasks either in-process within threads, as forked processes, or synchronously.
Theano is a Python library for defining, optimizing, and evaluating mathematical expressions on CPUs and GPUs, with symbolic differentiation and tight NumPy integration.
Install only if required to run existing legacy code, and expect significant friction on modern systems.
Theano-PyMC is an optimizing compiler for mathematical expressions on multi-dimensional arrays, enabling GPU acceleration and automatic differentiation for numerical computations.
TheFuzz performs fuzzy string matching using Levenshtein Distance to find approximate matches between text sequences, with support for multiple matching strategies and batch processing.
However, note that it's aging—the last release was in January 2024—so verify whether the maintainers are still actively developing it or if it's in stable maintenance…
Theine is a high-performance in-memory cache with a Rust core, adaptive W-TinyLFU eviction, automatic expiration, and thread-safe operations including free-threading support.
However, the aging maintenance status (362 days since last release) means you should verify that its feature set and performance characteristics match your workload…
Thermo calculates temperature and pressure-dependent thermodynamic and transport properties for pure chemicals and mixtures, including phase equilibria calculations using equations of state.
Install it if you work with thermodynamic modeling, phase equilibria, or chemical property lookups; skip it if your work does not involve chemical engineering…
Thespian provides an Actor Model framework for building concurrent, distributed, and fault-tolerant applications in Python where independent actors communicate via message passing.
However, install friction is high and the project shows signs of aging—no release in 520 days despite Production/Stable status.
Thinc is a lightweight deep learning library offering a functional-programming API for composing models with type checking, supporting integration with PyTorch, TensorFlow, and MXNet.
Counts floating-point operations (MACs) and parameters in PyTorch neural network models to profile computational complexity.
Provides decorators to wrap functions for execution in thread pools, individual threads, or asyncio tasks, eliminating boilerplate code for common concurrency patterns.
Runs Tornado coroutines from synchronous Python code by wrapping an IOLoop in a thread, allowing you to call async functions and wait for their results.
Inspect and control the thread-pool size of native libraries (BLAS, OpenMP) used by scientific packages, preventing thread oversubscription in nested parallel workloads.
threatwire provides real-time network packet inspection and threat signature matching for building IDS/IPS pipelines in Python, combining packet capture, protocol decoding, and a pluggable signature engine with built-in IOC rules.
Thrift is the Python bindings for Apache Thrift, an RPC framework that generates code for serializing and transmitting structured data across language and platform boundaries.
Install only if your architecture actually calls for Thrift; it is not a general-purpose serialization library.
Implements SASL authentication transports for Thrift RPC clients, enabling secure authentication over Thrift connections using the TSaslClientTransport.
ThriftPy2 is a pure Python implementation of Apache Thrift that lets you load Thrift IDL files dynamically and build RPC clients and servers without code generation or compilation.
Install it if you need Thrift RPC without compilation overhead.
Implements rate limiting with multiple algorithms (Fixed Window, Sliding Window, Token Bucket, Leaky Bucket, GCRA) and storage backends (Redis, In-Memory), supporting both sync and async code.
Install it if you need flexible, performant rate limiting; skip it only if your use case is trivial or you require Python 3.8/3.9 support.