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# Install the VisualDL. Preferably under a virtual environment or anaconda.
pip install --upgrade visualdl

# run a demo, vdl_create_scratch_log will create logs for testing.
vdl_create_scratch_log
visualdl --logdir=scratch_log --port=8080

# visit http://127.0.0.1:8080
sudo easy_install pip
pip install --upgrade virtualenv
sudo apt-get install python3-pip python3-dev python-virtualenv
virtualenv ~/vdl  # for Python2.7
virtualenv -p python3 ~/vdl for Python 3.x
source ~/vdl/bin/activate
pip install --upgrade visualdl

# run a demo, vdl_create_scratch_log will create logs for testing.
vdl_create_scratch_log
visualdl --logdir=scratch_log --port=8080

# visit http://127.0.0.1:8080
conda create -n vdl pip python=2.7 # or python=3.3, etc.
source activate vdl
pip install --upgrade visualdl

# run a demo, vdl_create_scratch_log will create logs for testing.
vdl_create_scratch_log
visualdl --logdir=scratch_log --port=8080

# visit http://127.0.0.1:8080
#Preferably under a virtualenv or anaconda.
git clone https://github.com/PaddlePaddle/VisualDL.git
cd VisualDL

python setup.py bdist_wheel
pip install --upgrade dist/visualdl-*.whl
import random
from visualdl import LogWriter

logdir = "./tmp"
logger = LogWriter(logdir, sync_cycle=10000)

# mark the components with 'train' label.
with logger.mode("train"):
    # create a scalar component called 'scalars/scalar0'
    scalar0 = logger.scalar("scalars/scalar0")

# add some records during DL model running.
for step in range(100):
    scalar0.add_record(step, random.random())
#include <cstdlib>
#include <string>
#include "visualdl/logic/sdk.h"

namespace vs = visualdl;
namespace cp = visualdl::components;

int main() {
  const std::string dir = "./tmp";
  vs::LogWriter logger(dir, 10000);

  logger.SetMode("train");
  auto tablet = logger.AddTablet("scalars/scalar0");

  cp::Scalar<float> scalar0(tablet);

  for (int step = 0; step < 1000; step++) {
    float v = (float)std::rand() / RAND_MAX;
    scalar0.AddRecord(step, v);
  }

  return 0;
}
visualdl --logdir <some log dir>