Skip to main content

PUBG JSON API wrapper and playback visualizer.

Project description

rtd pypi pyversions

Python PUBG JSON API Wrapper and (optional) playback visualizer.

Samples

Installation

To install chicken-dinner, use pip. This will install the core dependencies (requests library) which provide functionality to the API wrapper classes.

pip install chicken-dinner

To use the playback visualizations you will need to install the library with extra dependencies for plotting (matplotlib and pillow). For this you can also use pip:

pip install chicken-dinner[visual]

To generate the animations you will also need ffmpeg installed on your machine. On Max OSX you can install ffmpeg using brew.

brew install ffmpeg

You can install ffmpeg on other systems from here.

Usage

Working with the low-level API class.

from chicken_dinner.pubgapi import PUBGCore

api_key = "your_api_key"
pubgcore = PUBGCore(api_key, "pc-na")
shroud = pubgcore.players("player_names", "shroud")
print(shroud)

# {'data': [{'type': 'player', 'id': 'account.d50f...

Working with the high-level API class.

from chicken_dinner.pubgapi import PUBG

api_key = "your_api_key"
pubg = PUBG(api_key, "pc-na")
shroud = pubg.players_from_names("shroud")[0]
shroud_season = shroud.get_current_season()
squad_fpp_stats = shroud_season.game_mode_stats("squad", "fpp")
print(squad_fpp_stats)

# {'assists': 136, 'boosts': 313, 'dbnos': 550, 'daily_kills':...

Visualizing telemetry data

from chicken_dinner.pubgapi import PUBG

api_key = "your_api_key"
pubg = PUBG(api_key, "pc-na")
shroud = pubg.players_from_names("shroud")[0]
recent_match_id = shroud.match_ids[0]
recent_match = pubg.match(recent_match_id)
recent_match_telemetry = recent_match.get_telemetry()
recent_match_telemetry.playback_animation("recent_match.html")

Recommended playback settings:

telemetry.playback_animation(
    "match.html",
    zoom=True,
    labels=True,
    label_players=[],
    highlight_winner=True,
    label_highlights=True,
    size=6,
    end_frames=60,
    use_hi_res=False,
    color_teams=True,
    interpolate=True,
    damage=True,
    interval=2,
    fps=30,
)

See the documentation for more details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

chicken_dinner-0.5.1.tar.gz (12.1 MB view details)

Uploaded Source

Built Distribution

chicken_dinner-0.5.1-py3-none-any.whl (12.1 MB view details)

Uploaded Python 3

File details

Details for the file chicken_dinner-0.5.1.tar.gz.

File metadata

  • Download URL: chicken_dinner-0.5.1.tar.gz
  • Upload date:
  • Size: 12.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.3

File hashes

Hashes for chicken_dinner-0.5.1.tar.gz
Algorithm Hash digest
SHA256 42225f9a1e4bccf009ce4650df2a92d79ab3b2fc7525aade1831ac73e60ae9d4
MD5 e3f7cd1b8694e9cad5c540ecfdc4f528
BLAKE2b-256 1de9d3f7e74d9668bb052e7e273d62a49da73be3788f76d90e1687a26d37d9f3

See more details on using hashes here.

File details

Details for the file chicken_dinner-0.5.1-py3-none-any.whl.

File metadata

  • Download URL: chicken_dinner-0.5.1-py3-none-any.whl
  • Upload date:
  • Size: 12.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.2.0 requests-toolbelt/0.8.0 tqdm/4.23.4 CPython/3.6.3

File hashes

Hashes for chicken_dinner-0.5.1-py3-none-any.whl
Algorithm Hash digest
SHA256 c0c73941e6fa76340462d0f1779195115992822972394f0480e0e7b728b3461c
MD5 3ddd0f935689cfbbfb99bb9df3a29423
BLAKE2b-256 ebbc1ac83c21970997bb42b82207578bce8b34c341b7e13d99fd26863896ad45

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page