A data matching and canonicalization library with multipl database connector support

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for vaberry from gravatar.com vaberry

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Vince Berry
  • Maintainer: Vince Berry
  • Tags canonicalization , data-matching , database , entity-resolution , etl , mysql , natural language to sql , ner , nl2sql , nlp , sql
  • Requires: Python >=3.8
  • Provides-Extra: dev , fastapi
Classifiers
Report project as malware

Project description

CanonMap

CanonMap is a Python library for data matching and canonicalization with multiple database connector support. It uses a src/ layout and publishes the package canonmap.

Quick start

from canonmap import MappingPipeline, EntityMappingRequest

For more information, see the repository homepage.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for vaberry from gravatar.com vaberry

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License (MIT)
  • Author: Vince Berry
  • Maintainer: Vince Berry
  • Tags canonicalization , data-matching , database , entity-resolution , etl , mysql , natural language to sql , ner , nl2sql , nlp , sql
  • Requires: Python >=3.8
  • Provides-Extra: dev , fastapi
Classifiers

Release history Release notifications | RSS feed

1.0.2

1.0.1

0.4.90

0.4.89

0.4.88

0.4.87

0.4.86

0.4.85

0.4.84

0.4.83

0.4.82

0.4.81

0.4.80

0.4.79

0.4.78

0.4.77

0.4.76

0.4.75

0.4.74

0.4.73

0.4.72

0.4.71

0.4.70

0.4.69

0.4.68

0.4.67

0.4.66

0.4.65

0.4.64

0.4.63

0.4.62

0.4.61

0.4.60

0.4.59

0.4.58

0.4.57

This version

0.4.56

0.4.55

0.4.54

0.4.53

0.4.51

0.4.44

0.4.31

0.4.30

0.4.29

0.4.28

0.4.27

0.4.25

0.4.24

0.4.23

0.4.22

0.4.21

0.4.20

0.4.19

0.4.18

0.4.17

0.4.16

0.4.15

0.4.14

0.4.13

0.4.12

0.4.11

0.4.10

0.4.9

0.4.8

0.4.5

0.4.3

0.4.0

0.3.49

0.3.48

0.3.47

0.3.46

0.3.45

0.3.44

0.3.43

0.3.42

0.3.41

0.3.40

0.3.39

0.3.38

0.3.37

0.3.36

0.3.35

0.3.34

0.3.33

0.3.32

0.3.31

0.3.30

0.3.29

0.3.28

0.3.27

0.3.26

0.3.25

0.3.24

0.3.23

0.3.22

0.3.21

0.3.20

0.3.19

0.3.18

0.3.17

0.3.16

0.3.15

0.3.14

0.3.13

0.3.12

0.3.11

0.3.10

0.3.9

0.3.8

0.3.7

0.3.6

0.3.5

0.3.4

0.2.53

0.2.52

0.2.51

0.2.50

0.2.49

0.2.48

0.2.43

0.2.42

0.2.41

0.2.40

0.2.39

0.2.38

0.2.37

0.2.36

0.2.35

0.2.34

0.2.33

0.2.32

0.2.31

0.2.30

0.2.29

0.2.28

0.2.27

0.2.26

0.2.25

0.2.24

0.2.23

0.2.22

0.2.21

0.2.20

0.2.19

0.2.18

0.2.17

0.2.16

0.2.15

0.2.14

0.2.13

0.2.12

0.2.11

0.2.10

0.2.9

0.2.8

0.2.7

0.2.6

0.2.5

0.2.4

0.2.3

0.2.2

0.1.200

0.1.199

0.1.198

0.1.197

0.1.196

0.1.195

0.1.194

0.1.193

0.1.192

0.1.191

0.1.190

0.1.189

0.1.188

0.1.187

0.1.186

0.1.185

0.1.184

0.1.169

0.1.167

0.1.166

0.1.165

0.1.164

0.1.163

0.1.162

0.1.161

0.1.160

0.1.159

0.1.158

0.1.157

0.1.156

0.1.155

0.1.154

0.1.153

0.1.152

0.1.151

0.1.150

0.1.149

0.1.148

0.1.147

0.1.146

0.1.145

0.1.144

0.1.143

0.1.142

0.1.141

0.1.140

0.1.139

0.1.138

0.1.137

0.1.136

0.1.135

0.1.134

0.1.133

0.1.132

0.1.131

0.1.130

0.1.129

0.1.128

0.1.127

0.1.126

0.1.125

0.1.124

0.1.123

0.1.122

0.1.121

0.1.120

0.1.119

0.1.118

0.1.117

0.1.116

0.1.115

0.1.114

0.1.113

0.1.112

0.1.111

0.1.110

0.1.109

0.1.108

0.1.107

0.1.106

0.1.105

0.1.104

0.1.103

0.1.102

0.1.101

0.1.100

0.1.99

0.1.98

0.1.97

0.1.96

0.1.95

0.1.94

0.1.93

0.1.92

0.1.91

0.1.90

0.1.89

0.1.88

0.1.87

0.1.86

0.1.85

0.1.84

0.1.83

0.1.82

0.1.81

0.1.80

0.1.79

0.1.78

0.1.77

0.1.76

0.1.75

0.1.74

0.1.73

0.1.72

0.1.71

0.1.70

0.1.69

0.1.68

0.1.67

0.1.66

0.1.65

0.1.64

0.1.63

0.1.62

0.1.59

0.1.58

0.1.57

0.1.56

0.1.55

0.1.54

0.1.53

0.1.52

0.1.51

0.1.50

0.1.49

0.1.48

0.1.47

0.1.46

0.1.45

0.1.44

0.1.43

0.1.26

0.1.16

0.1.15

0.1.14

0.1.13

0.1.12

0.1.11

0.1.10

0.1.8

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

canonmap-0.4.56.tar.gz (27.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

canonmap-0.4.56-py3-none-any.whl (42.7 kB view details)

Uploaded Python 3

File details

Details for the file canonmap-0.4.56.tar.gz.

File metadata

  • Download URL: canonmap-0.4.56.tar.gz
  • Upload date:
  • Size: 27.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for canonmap-0.4.56.tar.gz
Algorithm Hash digest
SHA256 f9bbec7b828a8a96d64dcbc78ba4a375f857b06b83c0369d7939a375c8925c93
MD5 c15a8617cd60238d9ce2868b2a226a79
BLAKE2b-256 1d0890cbf1a48c4d4b9eb3375358ed1d278682b2d8add4eb3a08dc9ad66cd17e

See more details on using hashes here.

File details

Details for the file canonmap-0.4.56-py3-none-any.whl.

File metadata

  • Download URL: canonmap-0.4.56-py3-none-any.whl
  • Upload date:
  • Size: 42.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.5

File hashes

Hashes for canonmap-0.4.56-py3-none-any.whl
Algorithm Hash digest
SHA256 a9ededa64b459b7eda5929dc6ba9dd35831b3b8c1204c367c931741f14361625
MD5 2935da598b3fac42112e38ec5ef1bf4f
BLAKE2b-256 aa70e3ab97d127f14aea505482e769f3682862ca01488a74b787e836f77bc512

See more details on using hashes here.

Supported by

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