Enhanced JGTPy CDS, IDS, PDSP Services

Navigation

Verified details

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

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License
  • Author: GUillaume Isabelle
  • Tags data
  • Requires: Python >=3.7
  • Provides-Extra: dev-docs, dev-lint, dev-test
Classifiers

Project description

jgtpy (pdsp/ids/cds)

Enhanced JGTPy CDS, IDS, PDS Services

Installation

pip install -U jgtpy

Example

    >>> import pandas as pd
    >>> import jgtpy
    >>> df=jgtpy.getPH('EUR/USD','H4')
    >>>
    >>> # retrieve 3000 periods and generate from the DF
    >>> df=jgtpy.getPH('EUR/USD','H4',3000,with_index=False)
    >>> dfi=jgtpy.createFromDF(df)
    >>>
    >>> # Create with Timerange
    >>> start="11.17.2022 00:00:00"
    >>> end="11.25.2022 00:00:00"
    >>> df=jgtpy.createByRange("USD/CAD","m15",start,end)
    >>>
    >>> # offsets date for retreival
    >>> dtfirst_with_offset=jgtetl.svc_offset_dt_by_tf(dtfirst,ctx.timeframe)
    >>> df=createByRange(ctx.instrument,ctx.timeframe,dtfirst_with_offset,dtlast)

Project details

Verified details

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

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: MIT License
  • Author: GUillaume Isabelle
  • Tags data
  • Requires: Python >=3.7
  • Provides-Extra: dev-docs, dev-lint, dev-test
Classifiers

Release history Release notifications | RSS feed

0.5.100

0.5.99

0.5.98

0.5.97

0.5.96

0.5.95

0.5.94

0.5.93

0.5.92

0.5.91

0.5.90

0.5.89

0.5.88

0.5.87

0.5.86

0.5.85

0.5.84

0.5.83

0.5.82

0.5.81

0.5.80

0.5.79

0.5.78

0.5.77

0.5.76

0.5.75

0.5.74

0.5.73

0.5.72

0.5.71

0.5.70

0.5.69

0.5.68

0.5.66

0.5.65

0.5.63

0.5.62

0.5.60

0.5.59

0.5.58

0.5.57

0.5.56

0.5.55

0.5.54

0.5.53

0.5.52

0.5.51

0.5.50

0.5.49

0.5.48

0.5.47

0.5.46

0.5.45

0.5.44

0.5.43

0.5.42

0.5.41

0.5.40

0.5.39

0.5.38

0.5.37

0.5.36

0.5.35

0.5.34

0.5.33

0.5.32

0.5.31

0.5.30

0.5.29

0.5.28

0.5.27

0.5.23

0.5.22

0.5.21

0.5.20

0.5.19

0.5.18

0.5.17

0.5.16

0.5.15

0.5.14

0.5.13

0.5.12

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

0.4.100

0.4.93

0.4.92

0.4.91

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

This version

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

0.4.56

0.4.54

0.4.53

0.4.52

0.4.51

0.4.50

0.4.49

0.4.48

0.4.47

0.4.46

0.4.45

0.4.44

0.4.43

0.4.42

0.4.41

0.4.40

0.4.39

0.4.38

0.4.37

0.4.36

0.4.34

0.4.33

0.4.32

0.4.31

0.4.30

0.4.29

0.4.28

0.4.27

0.4.26

0.4.25

0.4.24

0.4.23

0.4.22

0.4.20

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

0.4.7

0.4.6

0.4.5

0.4.4

0.4.3

0.4.2

0.4.1

0.4.0

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

0.3.16

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

0.3.3

0.3.2

0.3.1

0.2.252

0.2.251

0.2.250

0.2.249

0.2.248

0.2.247

0.2.246

0.2.245

0.2.244

0.2.243

0.2.242

0.2.241

0.2.240

0.2.239

0.2.238

0.2.237

0.2.236

0.2.235

0.2.234

0.2.233

0.2.232

0.2.231

0.2.230

0.2.229

0.2.228

0.2.227

0.2.226

0.2.225

0.2.224

0.2.222

0.2.221

0.2.220

0.2.219

0.2.218

0.2.117

0.2.116

0.2.114

0.2.113

0.2.112

0.2.111

0.2.110

0.2.108

0.2.106

0.2.105

0.2.104

0.2.103

0.2.102

0.2.101

0.2.100

0.2.99

0.2.98

0.2.97

0.2.96

0.2.94

0.2.92

0.2.91

0.2.90

0.2.89

0.2.88

0.2.87

0.2.86

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

0.1.61

0.1.60

0.1.59

0.1.58

0.1.57

0.1.56

0.1.55

0.1.54

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

0.1.42

0.1.41

0.1.40

0.1.39

0.1.38

0.1.37

0.1.36

0.1.34

0.1.33

0.1.31

0.1.30

0.1.29

0.1.28

0.1.27

0.1.26

0.1.25

0.1.24

0.1.23

0.1.17

0.1.15

0.1.14

0.1.8

0.1.7

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

jgtpy-0.4.76.tar.gz (134.5 kB view details)

Uploaded Source

Built Distribution

jgtpy-0.4.76-py3-none-any.whl (147.4 kB view details)

Uploaded Python 3

File details

Details for the file jgtpy-0.4.76.tar.gz.

File metadata

  • Download URL: jgtpy-0.4.76.tar.gz
  • Upload date:
  • Size: 134.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for jgtpy-0.4.76.tar.gz
Algorithm Hash digest
SHA256 4384e112fa4505e0391a7c7e2f5a20c05dcb8d0a03d802549fb85096ca3579ac
MD5 dfef462a9bbf68ed84c4aaa9caf6feff
BLAKE2b-256 c178c1e646f65ed95b024ff6705493f83ef7ffc9621cc92c1d792733cba24245

See more details on using hashes here.

File details

Details for the file jgtpy-0.4.76-py3-none-any.whl.

File metadata

  • Download URL: jgtpy-0.4.76-py3-none-any.whl
  • Upload date:
  • Size: 147.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for jgtpy-0.4.76-py3-none-any.whl
Algorithm Hash digest
SHA256 6ed7d9cc78b5623b9d066cf35dedb1886565f9cb0d27edbe240f5387e63b7191
MD5 a639a00614511d74613f2f48f5744147
BLAKE2b-256 7027baeff9ed0d27e58226057e75a1f60811e193bcca95cfae1ba1bb574d562d

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