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

This version

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

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-0.5.51.tar.gz (137.0 kB view details)

Uploaded Source

Built Distribution

jgtpy-0.5.51-py3-none-any.whl (150.8 kB view details)

Uploaded Python 3

File details

Details for the file jgtpy-0.5.51.tar.gz.

File metadata

  • Download URL: jgtpy-0.5.51.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-0.5.51.tar.gz
Algorithm Hash digest
SHA256 1dc6c80396d0d81cec467c6a4c84cb5026f481618d7936724491490de09371e2
MD5 7a95515aff87c393a2bd16a660ad2d07
BLAKE2b-256 d01e788deb8f982092ba459c433608f02bf147d53fca6a327b04244064a580f8

See more details on using hashes here.

File details

Details for the file jgtpy-0.5.51-py3-none-any.whl.

File metadata

  • Download URL: jgtpy-0.5.51-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-0.5.51-py3-none-any.whl
Algorithm Hash digest
SHA256 591a9e3bac9ec7839ff3fea06431580932a72aa4db30ccf19c080f91018466ca
MD5 3f821b62a526d867bdcdd4bb84a00ddc
BLAKE2b-256 759652fe62d60585cb62280278407c0d1496c3df9d1b549d0a745a25a6c4e0a3

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