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

This version

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-0.5.13.tar.gz (137.2 kB view details)

Uploaded Source

Built Distribution

jgtpy-0.5.13-py3-none-any.whl (151.0 kB view details)

Uploaded Python 3

File details

Details for the file jgtpy-0.5.13.tar.gz.

File metadata

  • Download URL: jgtpy-0.5.13.tar.gz
  • Upload date:
  • Size: 137.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for jgtpy-0.5.13.tar.gz
Algorithm Hash digest
SHA256 a8c7823929d3b8d88d459c05f853ac5aaab916b0eeae289b69c2337c3470e551
MD5 c8460c6ebfdb10cb0a038bdd684a2d12
BLAKE2b-256 4c0be1cba81522460f71bd8db22664112582f4acb3bf4234fc280dbc02b325b0

See more details on using hashes here.

File details

Details for the file jgtpy-0.5.13-py3-none-any.whl.

File metadata

  • Download URL: jgtpy-0.5.13-py3-none-any.whl
  • Upload date:
  • Size: 151.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for jgtpy-0.5.13-py3-none-any.whl
Algorithm Hash digest
SHA256 7466f906a57dd6f4d087ebb4c47b548a295b615992502ebe45d2eeed9d9ba8da
MD5 1944e0b838f8db9517abf9d53b1e5253
BLAKE2b-256 1255a2da3e4023e71d1d8df5dbfaa08b6f765b07e38a2c5eb49be43b788b31df

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