Showing 11 open source projects for "numpy python 2.7"

View related business solutions
  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • Gen AI apps are built with MongoDB Atlas Icon
    Gen AI apps are built with MongoDB Atlas

    The database for AI-powered applications.

    MongoDB Atlas is the developer-friendly database used to build, scale, and run gen AI and LLM-powered apps—without needing a separate vector database. Atlas offers built-in vector search, global availability across 115+ regions, and flexible document modeling. Start building AI apps faster, all in one place.
    Start Free
  • 1
    Awkward Array

    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.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    pytablewriter

    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.
    Downloads: 2 This Week
    Last Update:
    See Project
  • 3
    autopep8

    autopep8

    A tool that automatically formats Python code to conform to the PEP 8

    autopep8 automatically formats Python code to conform to the PEP 8 style guide. It uses the pycodestyle utility to determine what parts of the code need to be formatted. autopep8 is capable of fixing most of the formatting issues that can be reported by pycodestyle. Correct deprecated or non-idiomatic Python code (via lib2to3). Use this for making Python 2.7 code more compatible with Python 3.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 4
    simplejson

    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. ...
    Downloads: 1 This Week
    Last Update:
    See Project
  • Simple, Secure Domain Registration Icon
    Simple, Secure Domain Registration

    Get your domain at wholesale price. Cloudflare offers simple, secure registration with no markups, plus free DNS, CDN, and SSL integration.

    Register or renew your domain and pay only what we pay. No markups, hidden fees, or surprise add-ons. Choose from over 400 TLDs (.com, .ai, .dev). Every domain is integrated with Cloudflare's industry-leading DNS, CDN, and free SSL to make your site faster and more secure. Simple, secure, at-cost domain registration.
    Sign up for free
  • 5
    orjson

    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. ...
    Downloads: 2 This Week
    Last Update:
    See Project
  • 6
    asammdf

    asammdf

    Fast Python reader and editor for ASAM MDF / MF4 (Measurement Format)

    *asammdf* is a fast Python parser and editor for ASAM (Associtation for Standardisation of Automation and Measuring Systems) MDF / MF4 (Measurement Data Format) files. It supports MDF versions 2 (.dat), 3 (.mdf) and 4 (.mf4). *asammdf* works on Python 2.7, and Python >= 3.4
    Downloads: 40 This Week
    Last Update:
    See Project
  • 7
    pylatexenc

    pylatexenc

    Simple LaTeX parser providing latex-to-unicode and unicode-to-latex

    Simple LaTeX parser providing latex-to-unicode and unicode-to-latex conversion. Python 3.4 or 2.7. The library is designed to be as backward-compatible as reasonably possible and is able to run on old Python versions should it be necessary. (Use the setup.py script directly if you have Python 3.7, poetry doesn't seem to work with old Python versions.) The pylatexenc.latexencode module provides a function unicode_to_latex() which converts a Unicode string into LaTeX text and escape sequences. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 8
    arxiv-collector

    arxiv-collector

    Little Python script to collect LaTeX sources for upload to the arXiv

    A little Python script to collect LaTeX sources for upload to the arXiv. Install with pip install arxiv-collector or conda install -c conda-forge arxiv-collector, or just download arxiv_collector.py, it's a stand-alone script with no dependencies. Works with any reasonable version of Python 3, or 2.7 if you really must.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 9

    xml2mif

    Tool for import Rosreestr XML files

    ...По результатам обработки формируется пакет файлов mid/mif для последующего импорта в GIS MapInfo. Поддерживается одновременная обработка большого количества файлов XML. Для работы требует установки в системе интерпретатора Python 2.7 (можно взять отсюда: https://www.python.org/ftp/python/2.7.9/python-2.7.9.msi https://www.python.org/ftp/python/2.7.9/python-2.7.9.amd64.msi Установить в конфигурации по умолчанию). В Linux необходимо в дополнение к имеющемуся Python установить пакет python-tk.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Build Securely on Azure with Proven Frameworks Icon
    Build Securely on Azure with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
    Download Now
  • 10
    Easy Equations

    Easy Equations

    Hand Written Equation Creator

    ...The focus of this utility is to provide user friendly access to write mathematical equations which is helpful for students, lecturers, mathematicians and Research persons who prefer using mathematical equations in a document, PowerPoint or web sites. Works on Windows as well as Linux platforms. Software Requirements: JDK 7 or higher. Linux Platform with kernel version 2.7 or higher.(for Linux users).python necessary only in linux environment to use COPY functionality.python is pre installed in recent linux distributions.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 11

    PySimpleTable

    Lightweight Python 2D table object with column headers

    For 2D data objects in Python, you have 3 main options: - Numpy Array - Pandas DataFrame (built on np.array) - SQL table Numpy and Pandas are great for working with a complete set of data, but not very efficient for building up row by row. SQL is good for building up the object row by row, but you have to write SQL and leave the world of Python objects.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next