noahgift

version: 0.1

phases:
  install:
    commands:
      - pip install --upgrade pip
      - pip install -r requirements.txt
  pre_build:
    commands:
      - echo Pre-build phase...

noahgift

#Parse a log and yield ONLY one line
def parse_log(path):
  with open("logfile.txt") as myfile:
    res = myfile.readlines()
    for line in res:
      yield line

#generator pipeline
stream = parse_log("logfile.txt") # step 1
split_it = (line.split() for line in stream) #step 2

noahgift

pylint --disable=W0622,W0611,F0401,R0914,W0221,W0222,W0142,F0010,W0703,R0911 -f parseable heroku

noahgift

noahgift

noahgift

(.myrepo) ➜  myrepo git:(master) ✗ make lint
pylint --disable=R,C myrepolib cli web
No config file found, using default configuration

--------------------------------------------------------------------
Your code has been rated at 10.00/10 (previous run: 10.00/10, +0.00)

noahgift

(.myrepo) ➜  myrepo git:(master) ✗ make test
python -m pytest -vv --cov=myrepolib tests/*.py
============================================================ test session starts ============================================================
platform darwin -- Python 3.6.4, pytest-3.3.0, py-1.5.2, pluggy-0.6.0 -- /Users/noahgift/.myrepo/bin/python
cachedir: .cache
rootdir: /Users/noahgift/src/myrepo, inifile:
plugins: cov-2.5.1, nbval-0.7
collected 1 item                                                                                                                            

tests/test_myrepo.py::test_func PASSED                                                                                                [100%]

noahgift

for i in range(1,10):
    print(f"I like sharing python code this way up to {i} times")
print(f"Ok, tired now")

noahgift

#Python quick and dirty debugging

#1.  PDB or IPDB
#this is the most powerful debugging technique                                   
#Can also use ipdb:  https://pypi.org/project/ipdb/
def stuff():                                                                     
    #import pdb;pdb.set_trace()                                                  
    x = 1                                                                        
    y = 2                                                                        

noahgift

In [107]: from sklearn.linear_model import LogisticRegressionCV
In [108]: model_cv = LogisticRegressionCV(10)
In [109]: model_cv.fit(X_train, y_train)
Out[109]: LogisticRegressionCV(Cs=10, class_weight=None, cv=None, dual=False,           fit_intercept=True, intercept_scaling=1.0, max_iter=100,           multi_class='ovr', n_jobs=1, penalty='l2', random_state=None,           refit=True, scoring=None, solver='lbfgs', tol=0.0001, verbose=0)