Database Abstraction Library

Navigation

Verified details

These details have been verified by PyPI
Owner
organization icon SQLAlchemy
Maintainers
Avatar for CaselIT from gravatar.com CaselIT

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Mike Bayer
  • Requires: Python !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, >=2.7
Classifiers

Project description

PyPI PyPI - Python Version PyPI - Downloads

The Python SQL Toolkit and Object Relational Mapper

Introduction

SQLAlchemy is the Python SQL toolkit and Object Relational Mapper that gives application developers the full power and flexibility of SQL. SQLAlchemy provides a full suite of well known enterprise-level persistence patterns, designed for efficient and high-performing database access, adapted into a simple and Pythonic domain language.

Major SQLAlchemy features include:

  • An industrial strength ORM, built from the core on the identity map, unit of work, and data mapper patterns. These patterns allow transparent persistence of objects using a declarative configuration system. Domain models can be constructed and manipulated naturally, and changes are synchronized with the current transaction automatically.

  • A relationally-oriented query system, exposing the full range of SQL’s capabilities explicitly, including joins, subqueries, correlation, and most everything else, in terms of the object model. Writing queries with the ORM uses the same techniques of relational composition you use when writing SQL. While you can drop into literal SQL at any time, it’s virtually never needed.

  • A comprehensive and flexible system of eager loading for related collections and objects. Collections are cached within a session, and can be loaded on individual access, all at once using joins, or by query per collection across the full result set.

  • A Core SQL construction system and DBAPI interaction layer. The SQLAlchemy Core is separate from the ORM and is a full database abstraction layer in its own right, and includes an extensible Python-based SQL expression language, schema metadata, connection pooling, type coercion, and custom types.

  • All primary and foreign key constraints are assumed to be composite and natural. Surrogate integer primary keys are of course still the norm, but SQLAlchemy never assumes or hardcodes to this model.

  • Database introspection and generation. Database schemas can be “reflected” in one step into Python structures representing database metadata; those same structures can then generate CREATE statements right back out - all within the Core, independent of the ORM.

SQLAlchemy’s philosophy:

  • SQL databases behave less and less like object collections the more size and performance start to matter; object collections behave less and less like tables and rows the more abstraction starts to matter. SQLAlchemy aims to accommodate both of these principles.

  • An ORM doesn’t need to hide the “R”. A relational database provides rich, set-based functionality that should be fully exposed. SQLAlchemy’s ORM provides an open-ended set of patterns that allow a developer to construct a custom mediation layer between a domain model and a relational schema, turning the so-called “object relational impedance” issue into a distant memory.

  • The developer, in all cases, makes all decisions regarding the design, structure, and naming conventions of both the object model as well as the relational schema. SQLAlchemy only provides the means to automate the execution of these decisions.

  • With SQLAlchemy, there’s no such thing as “the ORM generated a bad query” - you retain full control over the structure of queries, including how joins are organized, how subqueries and correlation is used, what columns are requested. Everything SQLAlchemy does is ultimately the result of a developer- initiated decision.

  • Don’t use an ORM if the problem doesn’t need one. SQLAlchemy consists of a Core and separate ORM component. The Core offers a full SQL expression language that allows Pythonic construction of SQL constructs that render directly to SQL strings for a target database, returning result sets that are essentially enhanced DBAPI cursors.

  • Transactions should be the norm. With SQLAlchemy’s ORM, nothing goes to permanent storage until commit() is called. SQLAlchemy encourages applications to create a consistent means of delineating the start and end of a series of operations.

  • Never render a literal value in a SQL statement. Bound parameters are used to the greatest degree possible, allowing query optimizers to cache query plans effectively and making SQL injection attacks a non-issue.

Documentation

Latest documentation is at:

https://www.sqlalchemy.org/docs/

Installation / Requirements

Full documentation for installation is at Installation.

Getting Help / Development / Bug reporting

Please refer to the SQLAlchemy Community Guide.

Code of Conduct

Above all, SQLAlchemy places great emphasis on polite, thoughtful, and constructive communication between users and developers. Please see our current Code of Conduct at Code of Conduct.

License

SQLAlchemy is distributed under the MIT license.

Project details

Verified details

These details have been verified by PyPI
Owner
organization icon SQLAlchemy
Maintainers
Avatar for CaselIT from gravatar.com CaselIT

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Mike Bayer
  • Requires: Python !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, >=2.7
Classifiers

Release history Release notifications | RSS feed

2.0.36

2.0.35

2.0.34

2.0.33

2.0.32

2.0.31

2.0.30

2.0.29

2.0.28

2.0.27

2.0.26

2.0.25

2.0.24

2.0.23

2.0.22

2.0.21

2.0.20

2.0.19

2.0.18

2.0.17

2.0.16

2.0.15

2.0.14

2.0.13

2.0.12

2.0.11

2.0.10

2.0.9

2.0.8

2.0.7

2.0.6

2.0.5.post1

2.0.5 yanked

Reason this release was yanked:

wheel files failed to build due to a test issue

2.0.4

2.0.3

2.0.2

2.0.1

2.0.0

2.0.0rc3 pre-release

2.0.0rc2 pre-release

2.0.0rc1 pre-release

2.0.0b4 pre-release

2.0.0b3 pre-release

2.0.0b2 pre-release

2.0.0b1 pre-release

1.4.54

1.4.53

1.4.52

1.4.51

1.4.50

1.4.49

1.4.48

1.4.47

1.4.46

This version

1.4.45

1.4.44

1.4.43

1.4.42

1.4.41

1.4.40

1.4.39

1.4.38

1.4.37

1.4.36

1.4.35

1.4.34 yanked

Reason this release was yanked:

critical caching issue identified, 1.4.35 resolves

1.4.33 yanked

Reason this release was yanked:

Regression when inserting orm models using insert. See https://github.com/sqlalchemy/sqlalchemy/issues/7878

1.4.32

1.4.31

1.4.30

1.4.29

1.4.28

1.4.27

1.4.26

1.4.25

1.4.24

1.4.23

1.4.22

1.4.21

1.4.20

1.4.19

1.4.18

1.4.17

1.4.16

1.4.15

1.4.14

1.4.13

1.4.12

1.4.11

1.4.10

1.4.9

1.4.8

1.4.7

1.4.6

1.4.5

1.4.4

1.4.3

1.4.2

1.4.1

1.4.0

1.4.0b3 pre-release

1.4.0b2 pre-release

1.4.0b1 pre-release

1.3.24

1.3.23

1.3.22

1.3.21

1.3.20

1.3.19

1.3.18

1.3.17

1.3.16

1.3.15

1.3.14

1.3.13

1.3.12

1.3.11

1.3.10

1.3.9

1.3.8

1.3.7

1.3.6

1.3.5

1.3.4

1.3.3

1.3.2

1.3.1

1.3.0

1.3.0b3 pre-release

1.3.0b2 pre-release

1.3.0b1 pre-release

1.2.19

1.2.18

1.2.17

1.2.16

1.2.15

1.2.14

1.2.13

1.2.12

1.2.11

1.2.10

1.2.9

1.2.8

1.2.7

1.2.6

1.2.5

1.2.4

1.2.3

1.2.2

1.2.1

1.2.0

1.2.0b3 pre-release

1.2.0b2 pre-release

1.2.0b1 pre-release

1.1.18

1.1.17

1.1.16

1.1.15

1.1.14

1.1.13

1.1.12

1.1.11

1.1.10

1.1.9

1.1.8

1.1.7

1.1.6

1.1.5

1.1.4

1.1.3

1.1.2

1.1.1

1.1.0

1.1.0b3 pre-release

1.1.0b2 pre-release

1.1.0b1 pre-release

1.0.19

1.0.18

1.0.17

1.0.16

1.0.15

1.0.14

1.0.13

1.0.12

1.0.11

1.0.10

1.0.9

1.0.8

1.0.7

1.0.6

1.0.5

1.0.4

1.0.3

1.0.2

1.0.1

1.0.0

1.0.0b5 pre-release

1.0.0b4 pre-release

1.0.0b3 pre-release

1.0.0b2 pre-release

1.0.0b1 pre-release

0.9.10

0.9.9

0.9.8

0.9.7

0.9.6

0.9.5

0.9.4

0.9.3

0.9.2

0.9.1

0.9.0

0.8.7

0.8.6

0.8.5

0.8.4

0.8.3

0.8.2

0.8.1

0.8.0

0.8.0b2 pre-release

0.7.10

0.7.9

0.7.8

0.7.7

0.7.6

0.7.5

0.7.4

0.7.3

0.7.2

0.7.1

0.7.0

0.6.9

0.6.8

0.6.7

0.6.6

0.6.5

0.6.4

0.6.3

0.6.2

0.6.1

0.6.0

0.6beta3 pre-release

0.6beta2 pre-release

0.6beta1 pre-release

0.5.8

0.5.7

0.5.6

0.5.5

0.5.4

0.5.3

0.5.2

0.5.1

0.5.0

0.5.0rc4 pre-release

0.5.0rc3 pre-release

0.5.0rc2 pre-release

0.5.0rc1 pre-release

0.5.0beta3 pre-release

0.5.0beta2 pre-release

0.5.0beta1 pre-release

0.4.8

0.4.7

0.4.6

0.4.5

0.4.4

0.4.3

0.4.2

0.4.2b pre-release

0.4.2a pre-release

0.4.1

0.4.0

0.4.0beta6 pre-release

0.4.0beta5 pre-release

0.4.0beta4 pre-release

0.4.0beta3 pre-release

0.4.0beta2 pre-release

0.4.0beta1 pre-release

0.3.11

0.3.10

0.3.9

0.3.8

0.3.7

0.3.6

0.3.5

0.3.4

0.3.3

0.3.2

0.3.1

0.3.0

0.2.8

0.2.7

0.2.6

0.2.5

0.2.4

0.2.3

0.2.2

0.2.1

0.2.0

0.1.7

0.1.6

0.1.5

0.1.4

0.1.3

0.1.2

0.1.1

0.1.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

SQLAlchemy-1.4.45.tar.gz (8.5 MB view details)

Uploaded Source

Built Distributions

SQLAlchemy-1.4.45-cp311-cp311-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

SQLAlchemy-1.4.45-cp311-cp311-win32.whl (1.6 MB view details)

Uploaded CPython 3.11 Windows x86

SQLAlchemy-1.4.45-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.45-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp311-cp311-macosx_10_9_universal2.whl (1.6 MB view details)

Uploaded CPython 3.11 macOS 10.9+ universal2 (ARM64, x86-64)

SQLAlchemy-1.4.45-cp310-cp310-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

SQLAlchemy-1.4.45-cp310-cp310-win32.whl (1.6 MB view details)

Uploaded CPython 3.10 Windows x86

SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp310-cp310-macosx_10_15_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 macOS 10.15+ x86-64

SQLAlchemy-1.4.45-cp39-cp39-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

SQLAlchemy-1.4.45-cp39-cp39-win32.whl (1.6 MB view details)

Uploaded CPython 3.9 Windows x86

SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp39-cp39-macosx_10_15_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

SQLAlchemy-1.4.45-cp38-cp38-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

SQLAlchemy-1.4.45-cp38-cp38-win32.whl (1.6 MB view details)

Uploaded CPython 3.8 Windows x86

SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp38-cp38-macosx_10_15_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

SQLAlchemy-1.4.45-cp37-cp37m-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.7m Windows x86-64

SQLAlchemy-1.4.45-cp37-cp37m-win32.whl (1.6 MB view details)

Uploaded CPython 3.7m Windows x86

SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp37-cp37m-macosx_10_15_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.7m macOS 10.15+ x86-64

SQLAlchemy-1.4.45-cp36-cp36m-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.6m Windows x86-64

SQLAlchemy-1.4.45-cp36-cp36m-win32.whl (1.6 MB view details)

Uploaded CPython 3.6m Windows x86

SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.12+ x86-64 manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp36-cp36m-macosx_10_14_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.6m macOS 10.14+ x86-64

SQLAlchemy-1.4.45-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.6 MB view details)

Uploaded CPython 2.7mu manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp27-cp27m-win_amd64.whl (1.6 MB view details)

Uploaded CPython 2.7m Windows x86-64

SQLAlchemy-1.4.45-cp27-cp27m-win32.whl (1.6 MB view details)

Uploaded CPython 2.7m Windows x86

SQLAlchemy-1.4.45-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl (1.6 MB view details)

Uploaded CPython 2.7m manylinux: glibc 2.5+ x86-64

SQLAlchemy-1.4.45-cp27-cp27m-macosx_10_14_x86_64.whl (1.6 MB view details)

Uploaded CPython 2.7m macOS 10.14+ x86-64

File details

Details for the file SQLAlchemy-1.4.45.tar.gz.

File metadata

  • Download URL: SQLAlchemy-1.4.45.tar.gz
  • Upload date:
  • Size: 8.5 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.0

File hashes

Hashes for SQLAlchemy-1.4.45.tar.gz
Algorithm Hash digest
SHA256 fd69850860093a3f69fefe0ab56d041edfdfe18510b53d9a2eaecba2f15fa795
MD5 3149ecb3aa245d057bad91484728c565
BLAKE2b-256 76d59ce70fd0d2858c72ecacff0c0518e9ddfbbaf4753b85e49f6d94ad74de36

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 db3ccbce4a861bf4338b254f95916fc68dd8b7aa50eea838ecdaf3a52810e9c0
MD5 07cb5bc810c998fb0567c9af7313ac83
BLAKE2b-256 3cb0db8883b93d63f476e37f214bb35ba36d07bd292917d3f5514125fc3aa565

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp311-cp311-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.45-cp311-cp311-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.45-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 1a92685db3b0682776a5abcb5f9e9addb3d7d9a6d841a452a17ec2d8d457bea7
MD5 f352bdfcabd9f02e2d2b4b5213825490
BLAKE2b-256 e6e645c8f4ed9310a41416c086f26d7c27013fdff5b5c9128964688449477d33

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 29a29d02c9e6f6b105580c5ed7afb722b97bc2e2fdb85e1d45d7ddd8440cfbca
MD5 21d4135bee92b49198a858af6c293ca5
BLAKE2b-256 bcd40ac4d824dec0bf638806ee249eaad3b09ad0dca735705866a12478dfb034

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 dc10423b59d6d032d6dff0bb42aa06dc6a8824eb6029d70c7d1b6981a2e7f4d8
MD5 6e160305ae6e9d4886f696cb9e4b1a78
BLAKE2b-256 a260649fd9b73fa1f1ea7d9b182451af818f599bca7ad3da7133dfcc57a23226

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 099efef0de9fbda4c2d7cb129e4e7f812007901942259d4e6c6e19bd69de1088
MD5 12e7c14f8225796c5516e84a956656f7
BLAKE2b-256 a7c7c0e5bc4dd98847747e6d7a408e9491cacd7cb989614e6c9c6be7c78529aa

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 16ad798fc121cad5ea019eb2297127b08c54e1aa95fe17b3fea9fdbc5c34fe62
MD5 6dd5cd0a4c8248c9bd11517f47e45f75
BLAKE2b-256 4b3b4d0b7528e8067eab04bb8814795669e58408194142741cce5222e17c7eb4

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp310-cp310-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.45-cp310-cp310-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.45-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 c8051bff4ce48cbc98f11e95ac46bfd1e36272401070c010248a3230d099663f
MD5 188193d9bcde918c848a70d538da0268
BLAKE2b-256 8676a9985b197c5f16c0c2447645bb8096bb34559d7165d1f6276347c6e0f6fb

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 06055476d38ed7915eeed22b78580556d446d175c3574a01b9eb04d91f3a8b2e
MD5 56f5e8e82bd3c1c1e5d3b7575a0e85b4
BLAKE2b-256 e564b89ff62587de50f38ff8d3cee1c2700acc730b966b32a60a16e0602f0c5f

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 96821d806c0c90c68ce3f2ce6dd529c10e5d7587961f31dd5c30e3bfddc4545d
MD5 f58522efb9884fbdcd291c79690a251b
BLAKE2b-256 16eef9d05f6ef9794b754cf46fd46103b8a3e54dc2dbbe7a7bcd431725321e72

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 081e2a2d75466353c738ca2ee71c0cfb08229b4f9909b5fa085f75c48d021471
MD5 f18c5c52f677a5d830ca4a06b7ccc9c2
BLAKE2b-256 4ae822c6a378131a10c62d4cc38d5ad4c661c9c94cdd1c641d94efe37a660024

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 ca152ffc7f0aa069c95fba46165030267ec5e4bb0107aba45e5e9e86fe4d9363
MD5 bf5942190424ab29e47586b05083333c
BLAKE2b-256 026a04f29a93dce9676a704c815ffa08508ac5b9a3720d6dc559d79df7457942

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 2d6f178ff2923730da271c8aa317f70cf0df11a4d1812f1d7a704b1cf29c5fe3
MD5 6e171ef7212a31e7a4bc059eec813828
BLAKE2b-256 2fe8059b9cea7bace156df468370a5348ee5427644dafb8c0c08d804c87c2e61

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp39-cp39-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.45-cp39-cp39-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.45-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 0e068b8414d60dd35d43c693555fc3d2e1d822cef07960bb8ca3f1ee6c4ff762
MD5 d9471544044d8744ac38ace0e754b258
BLAKE2b-256 0495f52eb937a8ea85a0f0253536c657f16ae721feb3bbcc34e3f0cc583c9c1b

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 52b90c9487e4449ad954624d01dea34c90cd8c104bce46b322c83654f37a23c5
MD5 abade5c96af5ec9b8d6fbfeb1bf0736d
BLAKE2b-256 30a463c7f9518e6f4df01a1a85b72f692922f27eb5798283b0d9e31c69486ccd

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e91a5e45a2ea083fe344b3503405978dff14d60ef3aa836432c9ca8cd47806b6
MD5 636450cb08a3e7e428ba2ee821042984
BLAKE2b-256 b11d15f8a2f12ca685658469ba59c31a7348a15feb859839dfd5ed58a13319b4

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 f61e54b8c2b389de1a8ad52394729c478c67712dbdcdadb52c2575e41dae94a5
MD5 3fcccb229e907e98df0cd44408386439
BLAKE2b-256 4774ff0b3d5b63d1ba80852ff3c643d835080af30a0f26c18afbca5bebf73b73

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 2db887dbf05bcc3151de1c4b506b14764c6240a42e844b4269132a7584de1e5f
MD5 b11103032ecbccc8582d5d7b800330e5
BLAKE2b-256 d7dc65c49c30fdc9ecec4839e2ed5ef948db1df5ac17b96b528cb67d97c4d8bf

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 445914dcadc0b623bd9851260ee54915ecf4e3041a62d57709b18a0eed19f33b
MD5 50c517eb1ae92b0733a93c1d3810f3ae
BLAKE2b-256 0e452b9a703350dba3eb7bc55a01e8f0943fa147bc1ebdb768e2b570f5379222

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp38-cp38-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.45-cp38-cp38-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.45-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 55ddb5585129c5d964a537c9e32a8a68a8c6293b747f3fa164e1c034e1657a98
MD5 e483512d38b227b0d54a8a988766a6b3
BLAKE2b-256 2f1e5c5eef1ddeaec7f68c2d04fd8b884db140f8279d5599f82fb562abda4600

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 416fe7d228937bd37990b5a429fd00ad0e49eabcea3455af7beed7955f192edd
MD5 28c7582b70efd68e40e4a3b77c82a9c7
BLAKE2b-256 a124ec04bc32fb3c02581c5f3084f6a465dbc29bc43c58e75b938eb848c9ce5b

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 561605cfc26273825ed2fb8484428faf36e853c13e4c90c61c58988aeccb34ed
MD5 f502a1e8b519709ee79ad598fbb3c383
BLAKE2b-256 54408358b09f8ad8e51a7b75971ce4d5d7b71e33d2c585f6a23ff9e8c1abda14

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 7e32ce2584564d9e068bb7e0ccd1810cbb0a824c0687f8016fe67e97c345a637
MD5 850feccf69b29d626ae969248c7ced5a
BLAKE2b-256 7c2c1c5218ff0748ebc1e1d2795c44b2ba185bfd06b28dfdd3bfb66589b3b7e2

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 01aa76f324c9bbc0dcb2bc3d9e2a9d7ede4808afa1c38d40d5e2007e3163b206
MD5 d2d894277ac2678ec31c658e6cca76c2
BLAKE2b-256 213b44731855ae14773aaeb1297edbfd8b9bb05d0962e754138aa2343342d503

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 2d1539fbc82d2206380a86d6d7d0453764fdca5d042d78161bbfb8dd047c80ec
MD5 4c4c45d9aa226c1f3cfaf83550b5cba3
BLAKE2b-256 6f271498b7be0ae81578442f574aa3457e72519ba8ceaefdaf38a49ec2ed9e3f

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp37-cp37m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.45-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.45-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 715f5859daa3bee6ecbad64501637fa4640ca6734e8cda6135e3898d5f8ccadd
MD5 661d15d085bfcb3a116e1419f39781ef
BLAKE2b-256 9b84f401a27e4625f1aedd7d9f5d74a2e16b5fb05b3e50115c5596ba724cdcdd

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 d458fd0566bc9e10b8be857f089e96b5ca1b1ef033226f24512f9ffdf485a8c0
MD5 02af000a8e416cb1dd1417411f0d9f93
BLAKE2b-256 3640fdc7fd109ce9a4a41eea3b4b0781a24fd7f05fc8075eccfc18c3cf10b301

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 cd95a3e6ab46da2c5b0703e797a772f3fab44d085b3919a4f27339aa3b1f51d3
MD5 1303ca4d656dbb0c5305127404b111e9
BLAKE2b-256 61f1476d0e97364c0fe3e9c584831f43b50b30a794eea8586906858afc3dbff8

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 88f4ad3b081c0dbb738886f8d425a5d983328670ee83b38192687d78fc82bd1e
MD5 c08ddd02c7a9e14ce9f3a92ced0bebd6
BLAKE2b-256 96e7444a9b55ef00d40792aa8f2282119731087a57737f2f740e5a4e47fbdf3a

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 6a91b7883cb7855a27bc0637166eed622fdf1bb94a4d1630165e5dd88c7e64d3
MD5 b94f9a9e488888287ec018adcedd5cd3
BLAKE2b-256 71499c6e48b10a345f8598e1ba226a432b97a9038e3ec90a5ad9e0b4aaf0adc4

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 5953e225be47d80410ae519f865b5c341f541d8e383fb6d11f67fb71a45bf890
MD5 08c3bddb2e0e5cd0b33ce8a519985d8a
BLAKE2b-256 09cf39bcab83026ff69be4c6d09182c69301778bce4ab201eb962c9d1b18c09b

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp36-cp36m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.45-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.45-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 a3bcd5e2049ceb97e8c273e6a84ff4abcfa1dc47b6d8bbd36e07cce7176610d3
MD5 048f68e4009ba8f0bdf6d3d4da6bc6a6
BLAKE2b-256 985915ac67654fe53c9dd0dcd19331ea121cb93a33ee40c8d8e236ae5ac7c161

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 a87f8595390764db333a1705591d0934973d132af607f4fa8b792b366eacbb3c
MD5 3a8de213df643d53bb2d22f8e9e1f9b4
BLAKE2b-256 660ca88074b7df5903263dc450dd3caf3e94f29f60743d27c163993102af37b1

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f7944b04e6fcf8d733964dd9ee36b6a587251a1a4049af3a9b846f6e64eb349a
MD5 df426b11ddaac38ff0c50834b6e912ef
BLAKE2b-256 fee3b47563d19b19fb451eeef3c4e163f360da0b615c4c18d490e862b0a2ca03

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 9a21c1fb71c69c8ec65430160cd3eee44bbcea15b5a4e556f29d03f246f425ec
MD5 4fd7483de5ac88fdd72f6c4ab5971178
BLAKE2b-256 fae46f1661f3f51ce442d6b359237d1b1b2a0b807b9d0b2ed30ad7dd7ca18859

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp36-cp36m-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp36-cp36m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 a62ae2ea3b940ce9c9cbd675489c2047921ce0a79f971d3082978be91bd58117
MD5 21feabed4b279ca7f1878f1b79d9aed3
BLAKE2b-256 785b44b602836cb71c574cf953a1a22db8778d43bcecb2915cbfb5d3a2300f41

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 6cd53b4c756a6f9c6518a3dc9c05a38840f9ae442c91fe1abde50d73651b6922
MD5 d65dba6bddf29bb980ae6e78fe0de45c
BLAKE2b-256 7542ec54a5ce9aa617736586c8e65e38101f7c67e1bd2686064a9cd23861f584

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp27-cp27m-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 13578d1cda69bc5e76c59fec9180d6db7ceb71c1360a4d7861c37d87ea6ca0b1
MD5 948046ae447498b1a435c24f358520cb
BLAKE2b-256 62ff8ff1884e152cc08a0429751f37e597c1da06b49ca8bb191cd6c16e118b25

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp27-cp27m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.45-cp27-cp27m-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 2.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.45-cp27-cp27m-win32.whl
Algorithm Hash digest
SHA256 26b8424b32eeefa4faad21decd7bdd4aade58640b39407bf43e7d0a7c1bc0453
MD5 0a7bac18cb07a8b5d0946256f0e457c1
BLAKE2b-256 eb9a6857daea1331a68e06aa1e64165930501667c53b957cb06525d20456e053

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 9b7025d46aba946272f6b6b357a22f3787473ef27451f342df1a2a6de23743e3
MD5 39cfa5e3434c895cc6266742176ccf4e
BLAKE2b-256 962afa5b8106f9043ade53bcaf5edf0e21cd591a451d2c2c1467f52f69479e6c

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.45-cp27-cp27m-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.45-cp27-cp27m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 f1d3fb02a4d0b07d1351a4a52f159e5e7b3045c903468b7e9349ebf0020ffdb9
MD5 39005d845ee9f083c83c41747f7c061b
BLAKE2b-256 2461e75bd397660234ef7ce6ab384ac41f160c6ee1f874ce5327fbea4e1574fb

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page