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

This version

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

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-0.5.46.tar.gz (137.0 kB view details)

Uploaded Source

Built Distribution

jgtpy-0.5.46-py3-none-any.whl (150.8 kB view details)

Uploaded Python 3

File details

Details for the file jgtpy-0.5.46.tar.gz.

File metadata

  • Download URL: jgtpy-0.5.46.tar.gz
  • Upload date:
  • Size: 137.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for jgtpy-0.5.46.tar.gz
Algorithm Hash digest
SHA256 c1f2980fb9bc05aed28174a6eaaa46879eff2c61721cb6fbaa152cc518b94924
MD5 8a6c7cf76b88652ce126a073d26786f3
BLAKE2b-256 88518df8992f51d5146b56d169412fc814a5c9a8727015cc022db090f2184397

See more details on using hashes here.

File details

Details for the file jgtpy-0.5.46-py3-none-any.whl.

File metadata

  • Download URL: jgtpy-0.5.46-py3-none-any.whl
  • Upload date:
  • Size: 150.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for jgtpy-0.5.46-py3-none-any.whl
Algorithm Hash digest
SHA256 f4ea314df8390391e38488476499b8e5ac2dadb5052b29b78936cca0a9accbf2
MD5 e64c46880f163a428583c827f7d22e67
BLAKE2b-256 52e80ab841287484cab72efde978a57410fbc8d0f9238b8a2af1664b3919e555

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