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

1.4.45

1.4.44

1.4.43

This version

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-1.4.42.tar.gz (8.3 MB view details)

Uploaded Source

Built Distributions

SQLAlchemy-1.4.42-cp311-cp311-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.11 Windows x86-64

SQLAlchemy-1.4.42-cp311-cp311-win32.whl (1.6 MB view details)

Uploaded CPython 3.11 Windows x86

SQLAlchemy-1.4.42-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.42-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-1.4.42-cp311-cp311-macosx_10_9_universal2.whl (1.6 MB view details)

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

SQLAlchemy-1.4.42-cp310-cp310-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.10 Windows x86-64

SQLAlchemy-1.4.42-cp310-cp310-win32.whl (1.6 MB view details)

Uploaded CPython 3.10 Windows x86

SQLAlchemy-1.4.42-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.42-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-1.4.42-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-1.4.42-cp310-cp310-macosx_10_15_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.10 macOS 10.15+ x86-64

SQLAlchemy-1.4.42-cp39-cp39-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.9 Windows x86-64

SQLAlchemy-1.4.42-cp39-cp39-win32.whl (1.6 MB view details)

Uploaded CPython 3.9 Windows x86

SQLAlchemy-1.4.42-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.42-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-1.4.42-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-1.4.42-cp39-cp39-macosx_10_15_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.9 macOS 10.15+ x86-64

SQLAlchemy-1.4.42-cp38-cp38-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.8 Windows x86-64

SQLAlchemy-1.4.42-cp38-cp38-win32.whl (1.6 MB view details)

Uploaded CPython 3.8 Windows x86

SQLAlchemy-1.4.42-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.42-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-1.4.42-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-1.4.42-cp38-cp38-macosx_10_15_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.8 macOS 10.15+ x86-64

SQLAlchemy-1.4.42-cp37-cp37m-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.7m Windows x86-64

SQLAlchemy-1.4.42-cp37-cp37m-win32.whl (1.6 MB view details)

Uploaded CPython 3.7m Windows x86

SQLAlchemy-1.4.42-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.42-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-1.4.42-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-1.4.42-cp37-cp37m-macosx_10_15_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.7m macOS 10.15+ x86-64

SQLAlchemy-1.4.42-cp36-cp36m-win_amd64.whl (1.6 MB view details)

Uploaded CPython 3.6m Windows x86-64

SQLAlchemy-1.4.42-cp36-cp36m-win32.whl (1.6 MB view details)

Uploaded CPython 3.6m Windows x86

SQLAlchemy-1.4.42-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (1.6 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

SQLAlchemy-1.4.42-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-1.4.42-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-1.4.42-cp36-cp36m-macosx_10_14_x86_64.whl (1.6 MB view details)

Uploaded CPython 3.6m macOS 10.14+ x86-64

SQLAlchemy-1.4.42-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-1.4.42-cp27-cp27m-win_amd64.whl (1.6 MB view details)

Uploaded CPython 2.7m Windows x86-64

SQLAlchemy-1.4.42-cp27-cp27m-win32.whl (1.6 MB view details)

Uploaded CPython 2.7m Windows x86

SQLAlchemy-1.4.42-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-1.4.42-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-1.4.42.tar.gz.

File metadata

  • Download URL: SQLAlchemy-1.4.42.tar.gz
  • Upload date:
  • Size: 8.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.10.0

File hashes

Hashes for SQLAlchemy-1.4.42.tar.gz
Algorithm Hash digest
SHA256 177e41914c476ed1e1b77fd05966ea88c094053e17a85303c4ce007f88eff363
MD5 52318b83e8931c5f5a459f54fe4be3e8
BLAKE2b-256 e4568ea85eaab7d93b58f9c213ad8fc5882838189a29fc8cc401d80710a12969

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 0501f74dd2745ec38f44c3a3900fb38b9db1ce21586b691482a19134062bf049
MD5 f63fdef6f4940d9bc137c08f9e11ee59
BLAKE2b-256 f948fe94926230ed45572f747f089e626c2444b4dc5785a85fb65028dcdbf160

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp311-cp311-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.42-cp311-cp311-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.42-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 6045b3089195bc008aee5c273ec3ba9a93f6a55bc1b288841bd4cfac729b6516
MD5 b4af4a41e7c3acb4617e1b8241b4ac26
BLAKE2b-256 e7176473b1634910b98fd005b1478443539ee3f18adc324008afc1983942220c

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 e12c6949bae10f1012ab5c0ea52ab8db99adcb8c7b717938252137cdf694c775
MD5 2355b3fb48aca1e19222c5e13b3365ff
BLAKE2b-256 766cb39e461ef58f1012e29834411d011aad5c823b5246b1facdbc5cb59e1dde

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 11b2ec26c5d2eefbc3e6dca4ec3d3d95028be62320b96d687b6e740424f83b7d
MD5 003f566f5b7c67fe623ba3067eea3a7a
BLAKE2b-256 bb9961d04da449e6a26c0d09e44b4d4aa36b64f095ec824d001ff8b69fd46f56

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp311-cp311-macosx_10_9_universal2.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp311-cp311-macosx_10_9_universal2.whl
Algorithm Hash digest
SHA256 97ff50cd85bb907c2a14afb50157d0d5486a4b4639976b4a3346f34b6d1b5272
MD5 20b96685a5fed483db5d1ba3a857ac4b
BLAKE2b-256 7bdf1e6c333e55b88f2424f8aaa1c7585e62e3ba7ed28955116484b6d0030086

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 effc89e606165ca55f04f3f24b86d3e1c605e534bf1a96e4e077ce1b027d0b71
MD5 26130c6aa10f48e81080603ab6a445eb
BLAKE2b-256 6b313dc7d605e8343a6db5ccf62445fabcce9538372188cf650e14ed3069c1a6

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp310-cp310-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.42-cp310-cp310-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.42-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 e7e740453f0149437c101ea4fdc7eea2689938c5760d7dcc436c863a12f1f565
MD5 3cfdba37d06189542da30980cfe0db7b
BLAKE2b-256 2c65a1be943985b026c287956a8186064f48c9645ba7df3de56cee6d1439049c

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 b42c59ffd2d625b28cdb2ae4cde8488543d428cba17ff672a543062f7caee525
MD5 c64e3d8f543a014b6a8925dcb40bd1cd
BLAKE2b-256 c24055b16ea88754bcf6ffa68d0e77adfc031b8ef63f5e1514bc886c50f87658

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 df76e9c60879fdc785a34a82bf1e8691716ffac32e7790d31a98d7dec6e81545
MD5 2e503d791279f91b18294133f3cfc277
BLAKE2b-256 49d10d26f5fa4bff7c4735fcd1a7090a3bbb751c8ba5a393e24d267fa76094af

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 22459fc1718785d8a86171bbe7f01b5c9d7297301ac150f508d06e62a2b4e8d2
MD5 eb0d56c0e85cdfed53a982cf656f9ddf
BLAKE2b-256 8897e306ffcf852ccf6e1337ca82a3bc132b487e10691a8fd79567dc6558e403

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp310-cp310-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp310-cp310-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 2e56dfed0cc3e57b2f5c35719d64f4682ef26836b81067ee6cfad062290fd9e2
MD5 d1047cd2d8de86ad20289a1072dd26de
BLAKE2b-256 12f6d73cd1ff12d543e7e180865ffd702ba30f9eda58a925cb38753c7d603a53

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 5f966b64c852592469a7eb759615bbd351571340b8b344f1d3fa2478b5a4c934
MD5 281f9ce7f1c32de6d918de753e5718cf
BLAKE2b-256 aab848a94fce9a2a94dbf62d917c772a50432b54c4e6be5bb7282253e7873c8c

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp39-cp39-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.42-cp39-cp39-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.42-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 e4ef8cb3c5b326f839bfeb6af5f406ba02ad69a78c7aac0fbeeba994ad9bb48a
MD5 9feba781635a07ee27e1fc05ac8e4407
BLAKE2b-256 d71ab6c981279429db615d2401f7e4e4a784b957dc3a594983377d0d970f30a9

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 723e3b9374c1ce1b53564c863d1a6b2f1dc4e97b1c178d9b643b191d8b1be738
MD5 ce54134362f371780f3d4aa04857af12
BLAKE2b-256 069ba25769c4fce57ccea6bba96fa32216dea6d6c7d3dd03524c522c8b342f64

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 2fd49af453e590884d9cdad3586415922a8e9bb669d874ee1dc55d2bc425aacd
MD5 cd79cb14e6c0ec7257c18a303fab2a05
BLAKE2b-256 a0e0ea3b6d042613667146bae2c9c2c0666f971a87dbf1cb2d3fc2c10a6c696c

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 876eb185911c8b95342b50a8c4435e1c625944b698a5b4a978ad2ffe74502908
MD5 cb28dec8fc94d4d534ec0c74fa6b6056
BLAKE2b-256 c42e71b7f0102bde7fc69c1049b35c2eaa7c9871220ec931043d45a4181ee4f2

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 5ce6929417d5dce5ad1d3f147db81735a4a0573b8fb36e3f95500a06eaddd93e
MD5 dce7ca9daca83d79030e7ede9bf6846e
BLAKE2b-256 055ae370ff71c01ac4cf73ba2355414111285b42611e58e2ee414d606f385dc5

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 a85723c00a636eed863adb11f1e8aaa36ad1c10089537823b4540948a8429798
MD5 c828682c8997b6bf6a1751090422a495
BLAKE2b-256 ec6715b2ea5e5c651a0ef91f1e0c02711ee3514a55325ef15111cade2bce48ba

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp38-cp38-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.42-cp38-cp38-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.42-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 f0f574465b78f29f533976c06b913e54ab4980b9931b69aa9d306afff13a9471
MD5 4f309d40a7d37e00177fe68a58e7db8e
BLAKE2b-256 88a250fa9c49126d6a2077161840cd31a4d7b1fa061b81f79b3ce13566952e0b

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 0ee377eb5c878f7cefd633ab23c09e99d97c449dd999df639600f49b74725b80
MD5 8c0b689265d720bb1637809bf05721e9
BLAKE2b-256 3613db9e5eb7b345d468a6c86aa8c330b905a3aa41dc81b3ff6e3aa9dbac4b86

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fdb94a3d1ba77ff2ef11912192c066f01e68416f554c194d769391638c8ad09a
MD5 65e59004fb20fa17b29c98b578341b6e
BLAKE2b-256 b6dd216ae403a9ff3d504c286960f4b747e760611b33d131be0c5eadee4f68ef

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 934472bb7d8666727746a75670a1f8d91a9cae8c464bba79da30a0f6faccd9e1
MD5 57f2ba30f2a166668e0703951e424f62
BLAKE2b-256 b54f0a26c099b8eae3855e29388179fb7baea3025de82f877616101e67f32c5f

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 3ab7c158f98de6cb4f1faab2d12973b330c2878d0c6b689a8ca424c02d66e1b3
MD5 bd8c816ec725ce440a9fd886f532b812
BLAKE2b-256 cbd08ed0c24be8bbe0608051daa6cad4398de7f76da68eafe2b598e6a83b5a59

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 04f2598c70ea4a29b12d429a80fad3a5202d56dce19dd4916cc46a965a5ca2e9
MD5 4722e55aef9017276060cde618337c76
BLAKE2b-256 dd578ff31ffddaa37c2a15fcb401942b7d74608f2025ec14749f32cec4becfb9

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp37-cp37m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.42-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.42-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 bd448b262544b47a2766c34c0364de830f7fb0772d9959c1c42ad61d91ab6565
MD5 6ad90bb151aa17889a70836127afabd6
BLAKE2b-256 2ad9364c9db537a09472ea6d2b6ddddc489677b260ad176b4f08c42ca7d8970e

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4948b6c5f4e56693bbeff52f574279e4ff972ea3353f45967a14c30fb7ae2beb
MD5 d82afec07f867e95f598ed924f744965
BLAKE2b-256 03943dd681e714e113d776dab1c3c5c265e22723c1ab344c327091552527436c

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9b01d9cd2f9096f688c71a3d0f33f3cd0af8549014e66a7a7dee6fc214a7277d
MD5 727d487960c332a52bd16bacc03f3435
BLAKE2b-256 72063f05a7f2213b26da60968a349ad17a0d2c9ecf34f2140966dd465046fabe

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 1811a0b19a08af7750c0b69e38dec3d46e47c4ec1d74b6184d69f12e1c99a5e0
MD5 f738814d641b1ed2303d36424340426d
BLAKE2b-256 822607302bcb5dddcb6ff9d6ce2fdd0bc1db73c5e6841c8995cf3932346f2240

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 9256563506e040daddccaa948d055e006e971771768df3bb01feeb4386c242b0
MD5 08e0d560858b73221eb6d0dad5948d0b
BLAKE2b-256 fbe711ad7b906622d2765974cb7814da3d9de6fe3021d8311ff8d5ac8e2060b9

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 5ede1495174e69e273fad68ad45b6d25c135c1ce67723e40f6cf536cb515e20b
MD5 f7b871ebb9b19d0278198685f306e0a1
BLAKE2b-256 0dbc59745db61f516562d3830c41dbe51a6fdb191b55ec538ed4f7b29740cf86

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp36-cp36m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.42-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.42-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 a7dd5b7b34a8ba8d181402d824b87c5cee8963cb2e23aa03dbfe8b1f1e417cde
MD5 8f80ded4d0c21d398adac3ea6b148462
BLAKE2b-256 b3d796c7590e15529434be7da8334e1073787be8c0758b995af68d2887b5966a

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 15d878929c30e41fb3d757a5853b680a561974a0168cd33a750be4ab93181628
MD5 90b66e83758ca92748ce2c2dd1890166
BLAKE2b-256 9eca404a0749aeea211d0f313947420381e8298c98d03326e98811766582e2aa

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 4e1c5f8182b4f89628d782a183d44db51b5af84abd6ce17ebb9804355c88a7b5
MD5 92b3a1ad039d973ed4c8e7f2cb4daa90
BLAKE2b-256 d72e9d5079b01c474e14e2aa4fb6a8b422dd05adf71d56c7ba60e8108c402890

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-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-1.4.42-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 fa5b7eb2051e857bf83bade0641628efe5a88de189390725d3e6033a1fff4257
MD5 772cfdaaf1d8e7280062a1ac3bc95543
BLAKE2b-256 232265a8dc0e223dad59133fb684bf92cf7a55c84045fb4a459de4832bfce375

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp36-cp36m-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp36-cp36m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 6e39e97102f8e26c6c8550cb368c724028c575ec8bc71afbbf8faaffe2b2092a
MD5 2abb25a13c8852fe66bbd7499dbc9087
BLAKE2b-256 928b6910c90e735f288b21019fe6c5820db423ebeaf351f9b4aaa26bf27e6a10

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp27-cp27mu-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 9e3a65ce9ed250b2f096f7b559fe3ee92e6605fab3099b661f0397a9ac7c8d95
MD5 997008750466625fc62447b01d095c6c
BLAKE2b-256 e4155b674e5ea970527fb0225012f381891ea756925f822952d32e663f2ab660

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp27-cp27m-win_amd64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp27-cp27m-win_amd64.whl
Algorithm Hash digest
SHA256 6c9d004eb78c71dd4d3ce625b80c96a827d2e67af9c0d32b1c1e75992a7916cc
MD5 abf0849d3773fddf784abfb1f38d77ac
BLAKE2b-256 fabfa98d24c9e1ca37ecc06a24e08c1a486606800b98140482146baf894b2cfc

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp27-cp27m-win32.whl.

File metadata

  • Download URL: SQLAlchemy-1.4.42-cp27-cp27m-win32.whl
  • Upload date:
  • Size: 1.6 MB
  • Tags: CPython 2.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.8.10

File hashes

Hashes for SQLAlchemy-1.4.42-cp27-cp27m-win32.whl
Algorithm Hash digest
SHA256 1d0c23ecf7b3bc81e29459c34a3f4c68ca538de01254e24718a7926810dc39a6
MD5 d623b7213d0e02d737537dc8d17db8cc
BLAKE2b-256 e2697d605b8ca5bd692f72138ebdda7fe38e55ccb77008dfffb91c012506333f

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp27-cp27m-manylinux_2_5_x86_64.manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 ca9389a00f639383c93ed00333ed763812f80b5ae9e772ea32f627043f8c9c88
MD5 f48f627cd3a1eb1f9c192e96f32a1e08
BLAKE2b-256 d9b7f5d2123231039e7fc763543769bdcb14081788155f2101d2c51a906dc952

See more details on using hashes here.

File details

Details for the file SQLAlchemy-1.4.42-cp27-cp27m-macosx_10_14_x86_64.whl.

File metadata

File hashes

Hashes for SQLAlchemy-1.4.42-cp27-cp27m-macosx_10_14_x86_64.whl
Algorithm Hash digest
SHA256 28e881266a172a4d3c5929182fde6bb6fba22ac93f137d5380cc78a11a9dd124
MD5 0ce7deae7bfe67e18477a73be68f622b
BLAKE2b-256 ea5ff62bef0ea1f18a50514f71a925e50404a6ee81eac705f265cae3ed77e09e

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