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

This version

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

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-0.5.80.tar.gz (138.2 kB view details)

Uploaded Source

Built Distribution

jgtpy-0.5.80-py3-none-any.whl (152.5 kB view details)

Uploaded Python 3

File details

Details for the file jgtpy-0.5.80.tar.gz.

File metadata

  • Download URL: jgtpy-0.5.80.tar.gz
  • Upload date:
  • Size: 138.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for jgtpy-0.5.80.tar.gz
Algorithm Hash digest
SHA256 8b30468bf97124c48101719266946def6fa19e5f402e1075d4897b9f1b9fe8b9
MD5 7b57510061440a5d4e9b602bfcb4c02a
BLAKE2b-256 d3a6125ad5ea6a6a86fc33098fbe51fb8ee02ebe81d76dda5e9b73cde8e4f201

See more details on using hashes here.

File details

Details for the file jgtpy-0.5.80-py3-none-any.whl.

File metadata

  • Download URL: jgtpy-0.5.80-py3-none-any.whl
  • Upload date:
  • Size: 152.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.10.14

File hashes

Hashes for jgtpy-0.5.80-py3-none-any.whl
Algorithm Hash digest
SHA256 75144336a0e8ae5bc59c7415c88f45b6be50b8457b7c4b31b890c4b00fe7fc39
MD5 bf494492c37a79194ab2e17c778474c5
BLAKE2b-256 238b4ad0fd8454e79aefd08fe0bc405becf6625ab47c8184fcd42860c32e61ea

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