Search is not available for this dataset
text
stringlengths 75
104k
|
---|
def members(group_id):
"""List user group members."""
page = request.args.get('page', 1, type=int)
per_page = request.args.get('per_page', 5, type=int)
q = request.args.get('q', '')
s = request.args.get('s', '')
group = Group.query.get_or_404(group_id)
if group.can_see_members(current_user):
members = Membership.query_by_group(group_id, with_invitations=True)
if q:
members = Membership.search(members, q)
if s:
members = Membership.order(members, Membership.state, s)
members = members.paginate(page, per_page=per_page)
return render_template(
"invenio_groups/members.html",
group=group,
members=members,
page=page,
per_page=per_page,
q=q,
s=s,
)
flash(
_(
'You are not allowed to see members of this group %(group_name)s.',
group_name=group.name
),
'error'
)
return redirect(url_for('.index')) |
def leave(group_id):
"""Leave group."""
group = Group.query.get_or_404(group_id)
if group.can_leave(current_user):
try:
group.remove_member(current_user)
except Exception as e:
flash(str(e), "error")
return redirect(url_for('.index'))
flash(
_(
'You have successfully left %(group_name)s group.',
group_name=group.name
),
'success'
)
return redirect(url_for('.index'))
flash(
_(
'You cannot leave the group %(group_name)s',
group_name=group.name
),
'error'
)
return redirect(url_for('.index')) |
def approve(group_id, user_id):
"""Approve a user."""
membership = Membership.query.get_or_404((user_id, group_id))
group = membership.group
if group.can_edit(current_user):
try:
membership.accept()
except Exception as e:
flash(str(e), 'error')
return redirect(url_for('.requests', group_id=membership.group.id))
flash(_('%(user)s accepted to %(name)s group.',
user=membership.user.email,
name=membership.group.name), 'success')
return redirect(url_for('.requests', group_id=membership.group.id))
flash(
_(
'You cannot approve memberships for the group %(group_name)s',
group_name=group.name
),
'error'
)
return redirect(url_for('.index')) |
def remove(group_id, user_id):
"""Remove user from a group."""
group = Group.query.get_or_404(group_id)
user = User.query.get_or_404(user_id)
if group.can_edit(current_user):
try:
group.remove_member(user)
except Exception as e:
flash(str(e), "error")
return redirect(urlparse(request.referrer).path)
flash(_('User %(user_email)s was removed from %(group_name)s group.',
user_email=user.email, group_name=group.name), 'success')
return redirect(urlparse(request.referrer).path)
flash(
_(
'You cannot delete users of the group %(group_name)s',
group_name=group.name
),
'error'
)
return redirect(url_for('.index')) |
def accept(group_id):
"""Accpet pending invitation."""
membership = Membership.query.get_or_404((current_user.get_id(), group_id))
# no permission check, because they are checked during Memberships creating
try:
membership.accept()
except Exception as e:
flash(str(e), 'error')
return redirect(url_for('.invitations', group_id=membership.group.id))
flash(_('You are now part of %(name)s group.',
user=membership.user.email,
name=membership.group.name), 'success')
return redirect(url_for('.invitations', group_id=membership.group.id)) |
def new_member(group_id):
"""Add (invite) new member."""
group = Group.query.get_or_404(group_id)
if group.can_invite_others(current_user):
form = NewMemberForm()
if form.validate_on_submit():
emails = filter(None, form.data['emails'].splitlines())
group.invite_by_emails(emails)
flash(_('Requests sent!'), 'success')
return redirect(url_for('.members', group_id=group.id))
return render_template(
"invenio_groups/new_member.html",
group=group,
form=form
)
flash(
_(
'You cannot invite users or yourself (i.e. join) to the group '
'%(group_name)s',
group_name=group.name
),
'error'
)
return redirect(url_for('.index')) |
def locate_spheres(image, feature_rad, dofilter=False, order=(3 ,3, 3),
trim_edge=True, **kwargs):
"""
Get an initial featuring of sphere positions in an image.
Parameters
-----------
image : :class:`peri.util.Image` object
Image object which defines the image file as well as the region.
feature_rad : float
Radius of objects to find, in pixels. This is a featuring radius
and not a real radius, so a better value is frequently smaller
than the real radius (half the actual radius is good). If ``use_tp``
is True, then the twice ``feature_rad`` is passed as trackpy's
``diameter`` keyword.
dofilter : boolean, optional
Whether to remove the background before featuring. Doing so can
often greatly increase the success of initial featuring and
decrease later optimization time. Filtering functions by fitting
the image to a low-order polynomial and featuring the residuals.
In doing so, this will change the mean intensity of the featured
image and hence the good value of ``minmass`` will change when
``dofilter`` is True. Default is False.
order : 3-element tuple, optional
If `dofilter`, the 2+1D Leg Poly approximation to the background
illumination field. Default is (3,3,3).
Other Parameters
----------------
invert : boolean, optional
Whether to invert the image for featuring. Set to True if the
image is dark particles on a bright background. Default is True
minmass : Float or None, optional
The minimum mass/masscut of a particle. Default is None, which
calculates internally.
use_tp : Bool, optional
Whether or not to use trackpy. Default is False, since trackpy
cuts out particles at the edge.
Returns
--------
positions : np.ndarray [N,3]
Positions of the particles in order (z,y,x) in image pixel units.
Notes
-----
Optionally filters the image by fitting the image I(x,y,z) to a
polynomial, then subtracts this fitted intensity variation and uses
centroid methods to find the particles.
"""
# We just want a smoothed field model of the image so that the residuals
# are simply the particles without other complications
m = models.SmoothFieldModel()
I = ilms.LegendrePoly2P1D(order=order, constval=image.get_image().mean())
s = states.ImageState(image, [I], pad=0, mdl=m)
if dofilter:
opt.do_levmarq(s, s.params)
pos = addsub.feature_guess(s, feature_rad, trim_edge=trim_edge, **kwargs)[0]
return pos |
def get_initial_featuring(statemaker, feature_rad, actual_rad=None,
im_name=None, tile=None, invert=True, desc='', use_full_path=False,
featuring_params={}, statemaker_kwargs={}, **kwargs):
"""
Completely optimizes a state from an image of roughly monodisperse
particles.
The user can interactively select the image. The state is periodically
saved during optimization, with different filename for different stages
of the optimization.
Parameters
----------
statemaker : Function
A statemaker function. Given arguments `im` (a
:class:`~peri.util.Image`), `pos` (numpy.ndarray), `rad` (ndarray),
and any additional `statemaker_kwargs`, must return a
:class:`~peri.states.ImageState`. There is an example function in
scripts/statemaker_example.py
feature_rad : Int, odd
The particle radius for featuring, as passed to locate_spheres.
actual_rad : Float, optional
The actual radius of the particles. Default is feature_rad
im_name : string, optional
The file name of the image to load. If not set, it is selected
interactively through Tk.
tile : :class:`peri.util.Tile`, optional
The tile of the raw image to be analyzed. Default is None, the
entire image.
invert : Bool, optional
Whether to invert the image for featuring, as passed to trackpy.
Default is True.
desc : String, optional
A description to be inserted in saved state. The save name will
be, e.g., '0.tif-peri-' + desc + 'initial-burn.pkl'. Default is ''
use_full_path : Bool, optional
Set to True to use the full path name for the image. Default
is False.
featuring_params : Dict, optional
kwargs-like dict of any additional keyword arguments to pass to
``get_initial_featuring``, such as ``'use_tp'`` or ``'minmass'``.
Default is ``{}``.
statemaker_kwargs : Dict, optional
kwargs-like dict of any additional keyword arguments to pass to
the statemaker function. Default is ``{}``.
Other Parameters
----------------
max_mem : Numeric
The maximum additional memory to use for the optimizers, as
passed to optimize.burn. Default is 1e9.
min_rad : Float, optional
The minimum particle radius, as passed to addsubtract.add_subtract.
Particles with a fitted radius smaller than this are identified
as fake and removed. Default is 0.5 * actual_rad.
max_rad : Float, optional
The maximum particle radius, as passed to addsubtract.add_subtract.
Particles with a fitted radius larger than this are identified
as fake and removed. Default is 1.5 * actual_rad, however you
may find better results if you make this more stringent.
rz_order : int, optional
If nonzero, the order of an additional augmented rscl(z)
parameter for optimization. Default is 0; i.e. no rscl(z)
optimization.
zscale : Float, optional
The zscale of the image. Default is 1.0
Returns
-------
s : :class:`peri.states.ImageState`
The optimized state.
See Also
--------
feature_from_pos_rad : Using a previous state's globals and
user-provided positions and radii as an initial guess,
completely optimizes a state.
get_particle_featuring : Using a previous state's globals and
positions as an initial guess, completely optimizes a state.
translate_featuring : Use a previous state's globals and
centroids methods for an initial particle guess, completely
optimizes a state.
Notes
-----
Proceeds by centroid-featuring the image for an initial guess of
particle positions, then optimizing the globals + positions until
termination as called in _optimize_from_centroid.
The ``Other Parameters`` are passed to _optimize_from_centroid.
"""
if actual_rad is None:
actual_rad = feature_rad
_, im_name = _pick_state_im_name('', im_name, use_full_path=use_full_path)
im = util.RawImage(im_name, tile=tile)
pos = locate_spheres(im, feature_rad, invert=invert, **featuring_params)
if np.size(pos) == 0:
msg = 'No particles found. Try using a smaller `feature_rad`.'
raise ValueError(msg)
rad = np.ones(pos.shape[0], dtype='float') * actual_rad
s = statemaker(im, pos, rad, **statemaker_kwargs)
RLOG.info('State Created.')
if desc is not None:
states.save(s, desc=desc+'initial')
optimize_from_initial(s, invert=invert, desc=desc, **kwargs)
return s |
def feature_from_pos_rad(statemaker, pos, rad, im_name=None, tile=None,
desc='', use_full_path=False, statemaker_kwargs={}, **kwargs):
"""
Gets a completely-optimized state from an image and an initial guess of
particle positions and radii.
The state is periodically saved during optimization, with different
filename for different stages of the optimization. The user can select
the image.
Parameters
----------
statemaker : Function
A statemaker function. Given arguments `im` (a
:class:`~peri.util.Image`), `pos` (numpy.ndarray), `rad` (ndarray),
and any additional `statemaker_kwargs`, must return a
:class:`~peri.states.ImageState`. There is an example function in
scripts/statemaker_example.py
pos : [N,3] element numpy.ndarray.
The initial guess for the N particle positions.
rad : N element numpy.ndarray.
The initial guess for the N particle radii.
im_name : string or None, optional
The filename of the image to feature. Default is None, in which
the user selects the image.
tile : :class:`peri.util.Tile`, optional
A tile of the sub-region of the image to feature. Default is
None, i.e. entire image.
desc : String, optional
A description to be inserted in saved state. The save name will
be, e.g., '0.tif-peri-' + desc + 'initial-burn.pkl'. Default is ''
use_full_path : Bool, optional
Set to True to use the full path name for the image. Default
is False.
statemaker_kwargs : Dict, optional
kwargs-like dict of any additional keyword arguments to pass to
the statemaker function. Default is ``{}``.
Other Parameters
----------------
max_mem : Numeric
The maximum additional memory to use for the optimizers, as
passed to optimize.burn. Default is 1e9.
min_rad : Float, optional
The minimum particle radius, as passed to addsubtract.add_subtract.
Particles with a fitted radius smaller than this are identified
as fake and removed. Default is 0.5 * actual_rad.
max_rad : Float, optional
The maximum particle radius, as passed to addsubtract.add_subtract.
Particles with a fitted radius larger than this are identified
as fake and removed. Default is 1.5 * actual_rad, however you
may find better results if you make this more stringent.
invert : {'guess', True, False}
Whether to invert the image for featuring, as passed to
addsubtract.add_subtract. Default is to guess from the
current state's particle positions.
rz_order : int, optional
If nonzero, the order of an additional augmented rscl(z)
parameter for optimization. Default is 0; i.e. no rscl(z)
optimization.
zscale : Float, optional
The zscale of the image. Default is 1.0
Returns
-------
s : :class:`peri.states.ImageState`
The optimized state.
See Also
--------
get_initial_featuring : Features an image from scratch, using
centroid methods as initial particle locations.
get_particle_featuring : Using a previous state's globals and
positions as an initial guess, completely optimizes a state.
translate_featuring : Use a previous state's globals and
centroids methods for an initial particle guess, completely
optimizes a state.
Notes
-----
The ``Other Parameters`` are passed to _optimize_from_centroid.
Proceeds by centroid-featuring the image for an initial guess of
particle positions, then optimizing the globals + positions until
termination as called in _optimize_from_centroid.
"""
if np.size(pos) == 0:
raise ValueError('`pos` is an empty array.')
elif np.shape(pos)[1] != 3:
raise ValueError('`pos` must be an [N,3] element numpy.ndarray.')
_, im_name = _pick_state_im_name('', im_name, use_full_path=use_full_path)
im = util.RawImage(im_name, tile=tile)
s = statemaker(im, pos, rad, **statemaker_kwargs)
RLOG.info('State Created.')
if desc is not None:
states.save(s, desc=desc+'initial')
optimize_from_initial(s, desc=desc, **kwargs)
return s |
def optimize_from_initial(s, max_mem=1e9, invert='guess', desc='', rz_order=3,
min_rad=None, max_rad=None):
"""
Optimizes a state from an initial set of positions and radii, without
any known microscope parameters.
Parameters
----------
s : :class:`peri.states.ImageState`
The state to optimize. It is modified internally and returned.
max_mem : Numeric, optional
The maximum memory for the optimizer to use. Default is 1e9 (bytes)
invert : Bool or `'guess'`, optional
Set to True if the image is dark particles on a bright
background, False otherwise. Used for add-subtract. The
default is to guess from the state's current particles.
desc : String, optional
An additional description to infix for periodic saving along the
way. Default is the null string ``''``.
rz_order : int, optional
``rz_order`` as passed to opt.burn. Default is 3
min_rad : Float or None, optional
The minimum radius to identify a particles as bad, as passed to
add-subtract. Default is None, which picks half the median radii.
If your sample is not monodisperse you should pick a different
value.
max_rad : Float or None, optional
The maximum radius to identify a particles as bad, as passed to
add-subtract. Default is None, which picks 1.5x the median radii.
If your sample is not monodisperse you should pick a different
value.
Returns
-------
s : :class:`peri.states.ImageState`
The optimized state, which is the same as the input ``s`` but
modified in-place.
"""
RLOG.info('Initial burn:')
if desc is not None:
desc_burn = desc + 'initial-burn'
desc_polish = desc + 'addsub-polish'
else:
desc_burn, desc_polish = [None] * 2
opt.burn(s, mode='burn', n_loop=3, fractol=0.1, desc=desc_burn,
max_mem=max_mem, include_rad=False, dowarn=False)
opt.burn(s, mode='burn', n_loop=3, fractol=0.1, desc=desc_burn,
max_mem=max_mem, include_rad=True, dowarn=False)
RLOG.info('Start add-subtract')
rad = s.obj_get_radii()
if min_rad is None:
min_rad = 0.5 * np.median(rad)
if max_rad is None:
max_rad = 1.5 * np.median(rad)
addsub.add_subtract(s, tries=30, min_rad=min_rad, max_rad=max_rad,
invert=invert)
if desc is not None:
states.save(s, desc=desc + 'initial-addsub')
RLOG.info('Final polish:')
d = opt.burn(s, mode='polish', n_loop=8, fractol=3e-4, desc=desc_polish,
max_mem=max_mem, rz_order=rz_order, dowarn=False)
if not d['converged']:
RLOG.warn('Optimization did not converge; consider re-running')
return s |
def translate_featuring(state_name=None, im_name=None, use_full_path=False,
**kwargs):
"""
Translates one optimized state into another image where the particles
have moved by a small amount (~1 particle radius).
Returns a completely-optimized state. The user can interactively
selects the initial state and the second raw image. The state is
periodically saved during optimization, with different filename for
different stages of the optimization.
Parameters
----------
state_name : String or None, optional
The name of the initially-optimized state. Default is None,
which prompts the user to select the name interactively
through a Tk window.
im_name : String or None, optional
The name of the new image to optimize. Default is None,
which prompts the user to select the name interactively
through a Tk window.
use_full_path : Bool, optional
Set to True to use the full path of the state instead of
partial path names (e.g. /full/path/name/state.pkl vs
state.pkl). Default is False
Other Parameters
----------------
max_mem : Numeric
The maximum additional memory to use for the optimizers, as
passed to optimize.burn. Default is 1e9.
desc : String, optional
A description to be inserted in saved state. The save name will
be, e.g., '0.tif-peri-' + desc + 'initial-burn.pkl'. Default is ''
min_rad : Float, optional
The minimum particle radius, as passed to addsubtract.add_subtract.
Particles with a fitted radius smaller than this are identified
as fake and removed. Default is 0.5 * actual_rad.
max_rad : Float, optional
The maximum particle radius, as passed to addsubtract.add_subtract.
Particles with a fitted radius larger than this are identified
as fake and removed. Default is 1.5 * actual_rad, however you
may find better results if you make this more stringent.
invert : {True, False, 'guess'}
Whether to invert the image for featuring, as passed to
addsubtract.add_subtract. Default is to guess from the
state's current particles.
rz_order : int, optional
If nonzero, the order of an additional augmented rscl(z)
parameter for optimization. Default is 0; i.e. no rscl(z)
optimization.
do_polish : Bool, optional
Set to False to only optimize the particles and add-subtract.
Default is True, which then runs a polish afterwards.
Returns
-------
s : :class:`peri.states.ImageState`
The optimized state.
See Also
--------
get_initial_featuring : Features an image from scratch, using
centroid methods as initial particle locations.
feature_from_pos_rad : Using a previous state's globals and
user-provided positions and radii as an initial guess,
completely optimizes a state.
get_particle_featuring : Using a previous state's globals and
positions as an initial guess, completely optimizes a state.
Notes
-----
The ``Other Parameters`` are passed to _translate_particles.
Proceeds by:
1. Optimize particle positions only.
2. Optimize particle positions and radii only.
3. Add-subtract missing and bad particles.
4. If polish, optimize the illumination, background, and particles.
5. If polish, optimize everything.
"""
state_name, im_name = _pick_state_im_name(
state_name, im_name, use_full_path=use_full_path)
s = states.load(state_name)
im = util.RawImage(im_name, tile=s.image.tile)
s.set_image(im)
_translate_particles(s, **kwargs)
return s |
def get_particles_featuring(feature_rad, state_name=None, im_name=None,
use_full_path=False, actual_rad=None, invert=True, featuring_params={},
**kwargs):
"""
Combines centroid featuring with the globals from a previous state.
Runs trackpy.locate on an image, sets the globals from a previous state,
calls _translate_particles
Parameters
----------
feature_rad : Int, odd
The particle radius for featuring, as passed to locate_spheres.
state_name : String or None, optional
The name of the initially-optimized state. Default is None,
which prompts the user to select the name interactively
through a Tk window.
im_name : String or None, optional
The name of the new image to optimize. Default is None,
which prompts the user to select the name interactively
through a Tk window.
use_full_path : Bool, optional
Set to True to use the full path of the state instead of
partial path names (e.g. /full/path/name/state.pkl vs
state.pkl). Default is False
actual_rad : Float or None, optional
The initial guess for the particle radii. Default is the median
of the previous state.
invert : Bool
Whether to invert the image for featuring, as passed to
addsubtract.add_subtract and locate_spheres. Set to False
if the image is bright particles on a dark background.
Default is True (dark particles on bright background).
featuring_params : Dict, optional
kwargs-like dict of any additional keyword arguments to pass to
``get_initial_featuring``, such as ``'use_tp'`` or ``'minmass'``.
Default is ``{}``.
Other Parameters
----------------
max_mem : Numeric
The maximum additional memory to use for the optimizers, as
passed to optimize.burn. Default is 1e9.
desc : String, optional
A description to be inserted in saved state. The save name will
be, e.g., '0.tif-peri-' + desc + 'initial-burn.pkl'. Default is ''
min_rad : Float, optional
The minimum particle radius, as passed to addsubtract.add_subtract.
Particles with a fitted radius smaller than this are identified
as fake and removed. Default is 0.5 * actual_rad.
max_rad : Float, optional
The maximum particle radius, as passed to addsubtract.add_subtract.
Particles with a fitted radius larger than this are identified
as fake and removed. Default is 1.5 * actual_rad, however you
may find better results if you make this more stringent.
rz_order : int, optional
If nonzero, the order of an additional augmented rscl(z)
parameter for optimization. Default is 0; i.e. no rscl(z)
optimization.
do_polish : Bool, optional
Set to False to only optimize the particles and add-subtract.
Default is True, which then runs a polish afterwards.
Returns
-------
s : :class:`peri.states.ImageState`
The optimized state.
See Also
--------
get_initial_featuring : Features an image from scratch, using
centroid methods as initial particle locations.
feature_from_pos_rad : Using a previous state's globals and
user-provided positions and radii as an initial guess,
completely optimizes a state.
translate_featuring : Use a previous state's globals and
centroids methods for an initial particle guess, completely
optimizes a state.
Notes
-----
The ``Other Parameters`` are passed to _translate_particles.
Proceeds by:
1. Find a guess of the particle positions through centroid methods.
2. Optimize particle positions only.
3. Optimize particle positions and radii only.
4. Add-subtract missing and bad particles.
5. If polish, optimize the illumination, background, and particles.
6. If polish, optimize everything.
"""
state_name, im_name = _pick_state_im_name(
state_name, im_name, use_full_path=use_full_path)
s = states.load(state_name)
if actual_rad is None:
actual_rad = np.median(s.obj_get_radii())
im = util.RawImage(im_name, tile=s.image.tile)
pos = locate_spheres(im, feature_rad, invert=invert, **featuring_params)
_ = s.obj_remove_particle(np.arange(s.obj_get_radii().size))
s.obj_add_particle(pos, np.ones(pos.shape[0])*actual_rad)
s.set_image(im)
_translate_particles(s, invert=invert, **kwargs)
return s |
def _pick_state_im_name(state_name, im_name, use_full_path=False):
"""
If state_name or im_name is None, picks them interactively through Tk,
and then sets with or without the full path.
Parameters
----------
state_name : {string, None}
The name of the state. If None, selected through Tk.
im_name : {string, None}
The name of the image. If None, selected through Tk.
use_full_path : Bool, optional
Set to True to return the names as full paths rather than
relative paths. Default is False (relative path).
"""
initial_dir = os.getcwd()
if (state_name is None) or (im_name is None):
wid = tk.Tk()
wid.withdraw()
if state_name is None:
state_name = tkfd.askopenfilename(
initialdir=initial_dir, title='Select pre-featured state')
os.chdir(os.path.dirname(state_name))
if im_name is None:
im_name = tkfd.askopenfilename(
initialdir=initial_dir, title='Select new image')
if (not use_full_path) and (os.path.dirname(im_name) != ''):
im_path = os.path.dirname(im_name)
os.chdir(im_path)
im_name = os.path.basename(im_name)
else:
os.chdir(initial_dir)
return state_name, im_name |
def _translate_particles(s, max_mem=1e9, desc='', min_rad='calc',
max_rad='calc', invert='guess', rz_order=0, do_polish=True):
"""
Workhorse for translating particles. See get_particles_featuring for docs.
"""
if desc is not None:
desc_trans = desc + 'translate-particles'
desc_burn = desc + 'addsub_burn'
desc_polish = desc + 'addsub_polish'
else:
desc_trans, desc_burn, desc_polish = [None]*3
RLOG.info('Translate Particles:')
opt.burn(s, mode='do-particles', n_loop=4, fractol=0.1, desc=desc_trans,
max_mem=max_mem, include_rad=False, dowarn=False)
opt.burn(s, mode='do-particles', n_loop=4, fractol=0.05, desc=desc_trans,
max_mem=max_mem, include_rad=True, dowarn=False)
RLOG.info('Start add-subtract')
addsub.add_subtract(s, tries=30, min_rad=min_rad, max_rad=max_rad,
invert=invert)
if desc is not None:
states.save(s, desc=desc + 'translate-addsub')
if do_polish:
RLOG.info('Final Burn:')
opt.burn(s, mode='burn', n_loop=3, fractol=3e-4, desc=desc_burn,
max_mem=max_mem, rz_order=rz_order,dowarn=False)
RLOG.info('Final Polish:')
d = opt.burn(s, mode='polish', n_loop=4, fractol=3e-4, desc=desc_polish,
max_mem=max_mem, rz_order=rz_order, dowarn=False)
if not d['converged']:
RLOG.warn('Optimization did not converge; consider re-running') |
def link_zscale(st):
"""Links the state ``st`` psf zscale with the global zscale"""
# FIXME should be made more generic to other parameters and categories
psf = st.get('psf')
psf.param_dict['zscale'] = psf.param_dict['psf-zscale']
psf.params[psf.params.index('psf-zscale')] = 'zscale'
psf.global_zscale = True
psf.param_dict.pop('psf-zscale')
st.trigger_parameter_change()
st.reset() |
def finish_state(st, desc='finish-state', invert='guess'):
"""
Final optimization for the best-possible state.
Runs a local add-subtract to capture any difficult-to-feature particles,
then does another set of optimization designed to get to the best
possible fit.
Parameters
----------
st : :class:`peri.states.ImageState`
The state to finish
desc : String, optional
Description to intermittently save the state as, as passed to
state.save. Default is `'finish-state'`.
invert : {'guess', True, False}
Whether to invert the image for featuring, as passed to
addsubtract.add_subtract. Default is to guess from the
state's current particles.
See Also
--------
`peri.opt.addsubtract.add_subtract_locally`
`peri.opt.optimize.finish`
"""
for minmass in [None, 0]:
for _ in range(3):
npart, poses = addsub.add_subtract_locally(st, region_depth=7,
minmass=minmass, invert=invert)
if npart == 0:
break
opt.finish(st, n_loop=1, separate_psf=True, desc=desc, dowarn=False)
opt.burn(st, mode='polish', desc=desc, n_loop=2, dowarn=False)
d = opt.finish(st, desc=desc, n_loop=4, dowarn=False)
if not d['converged']:
RLOG.warn('Optimization did not converge; consider re-running') |
def optimize_particle(state, index, method='gn', doradius=True):
"""
Methods available are
gn : Gauss-Newton with JTJ (recommended)
nr : Newton-Rhaphson with hessian
if doradius, also optimize the radius.
"""
blocks = state.param_particle(index)
if not doradius:
blocks = blocks[:-1]
g = state.gradloglikelihood(blocks=blocks)
if method == 'gn':
h = state.jtj(blocks=blocks)
if method == 'nr':
h = state.hessloglikelihood(blocks=blocks)
step = np.linalg.solve(h, g)
h = np.zeros_like(g)
for i in range(len(g)):
state.update(blocks[i], state.state[blocks[i]] - step[i])
return g,h |
def makestate(im, pos, rad, slab=None, mem_level='hi'):
"""
Workhorse for creating & optimizing states with an initial centroid
guess.
This is an example function that works for a particular microscope. For
your own microscope, you'll need to change particulars such as the psf
type and the orders of the background and illumination.
Parameters
----------
im : :class:`~peri.util.RawImage`
A RawImage of the data.
pos : [N,3] element numpy.ndarray.
The initial guess for the N particle positions.
rad : N element numpy.ndarray.
The initial guess for the N particle radii.
slab : :class:`peri.comp.objs.Slab` or None, optional
If not None, a slab corresponding to that in the image. Default
is None.
mem_level : {'lo', 'med-lo', 'med', 'med-hi', 'hi'}, optional
A valid memory level for the state to control the memory overhead
at the expense of accuracy. Default is `'hi'`
Returns
-------
:class:`~peri.states.ImageState`
An ImageState with a linked z-scale, a ConfocalImageModel, and
all the necessary components with orders at which are useful for
my particular test case.
"""
if slab is not None:
o = comp.ComponentCollection(
[
objs.PlatonicSpheresCollection(pos, rad, zscale=zscale),
slab
],
category='obj'
)
else:
o = objs.PlatonicSpheresCollection(pos, rad, zscale=zscale)
p = exactpsf.FixedSSChebLinePSF()
npts, iorder = _calc_ilm_order(im.get_image().shape)
i = ilms.BarnesStreakLegPoly2P1D(npts=npts, zorder=iorder)
b = ilms.LegendrePoly2P1D(order=(9 ,3, 5), category='bkg')
c = comp.GlobalScalar('offset', 0.0)
s = states.ImageState(im, [o, i, b, c, p])
runner.link_zscale(s)
if mem_level != 'hi':
s.set_mem_level(mem_level)
opt.do_levmarq(s, ['ilm-scale'], max_iter=1, run_length=6, max_mem=1e4)
return s |
def _calc_ilm_order(imshape):
"""
Calculates an ilm order based on the shape of an image. This is based on
something that works for our particular images. Your mileage will vary.
Parameters
----------
imshape : 3-element list-like
The shape of the image.
Returns
-------
npts : tuple
The number of points to use for the ilm.
zorder : int
The order of the z-polynomial.
"""
zorder = int(imshape[0] / 6.25) + 1
l_npts = int(imshape[1] / 42.5)+1
npts = ()
for a in range(l_npts):
if a < 5:
npts += (int(imshape[2] * [59, 39, 29, 19, 14][a]/512.) + 1,)
else:
npts += (int(imshape[2] * 11/512.) + 1,)
return npts, zorder |
def _check_for_inception(self, root_dict):
'''
Used to check if there is a dict in a dict
'''
for key in root_dict:
if isinstance(root_dict[key], dict):
root_dict[key] = ResponseObject(root_dict[key])
return root_dict |
def randomize_parameters(self, ptp=0.2, fourier=False, vmin=None, vmax=None):
"""
Create random parameters for this ILM that mimic experiments
as closely as possible without real assumptions.
"""
if vmin is not None and vmax is not None:
ptp = vmax - vmin
elif vmax is not None and vmin is None:
vmin = vmax - ptp
elif vmin is not None and vmax is None:
vmax = vmin + ptp
else:
vmax = 1.0
vmin = vmax - ptp
self.set_values(self.category+'-scale', 1.0)
self.set_values(self.category+'-off', 0.0)
for k, v in iteritems(self.poly_params):
norm = (self.zorder + 1.0)*2
self.set_values(k, ptp*(np.random.rand() - 0.5) / norm)
for i, p in enumerate(self.barnes_params):
N = len(p)
if fourier:
t = ((np.random.rand(N)-0.5) + 1.j*(np.random.rand(N)-0.5))/(np.arange(N)+1)
q = np.real(np.fft.ifftn(t)) / (i+1)
else:
t = ptp*np.sqrt(N)*(np.random.rand(N)-0.5)
q = np.cumsum(t) / (i+1)
q = ptp * q / q.ptp() / len(self.barnes_params)
q -= q.mean()
self.set_values(p, q)
self._norm_stat = [ptp, vmin]
if self.shape:
self.initialize()
if self._parent:
param = self.category+'-scale'
self.trigger_update(param, self.get_values(param)) |
def _barnes(self, pos):
"""Creates a barnes interpolant & calculates its values"""
b_in = self.b_in
dist = lambda x: np.sqrt(np.dot(x,x))
#we take a filter size as the max distance between the grids along
#x or y:
sz = self.npts[1]
coeffs = self.get_values(self.barnes_params)
b = BarnesInterpolationND(
b_in, coeffs, filter_size=self.filtsize, damp=0.9, iterations=3,
clip=self.local_updates, clipsize=self.barnes_clip_size,
blocksize=100 # FIXME magic blocksize
)
return b(pos) |
def schedules(self):
'''
Returns details of the posting schedules associated with a social media
profile.
'''
url = PATHS['GET_SCHEDULES'] % self.id
self.__schedules = self.api.get(url=url)
return self.__schedules |
def schedules(self, schedules):
'''
Set the posting schedules for the specified social media profile.
'''
url = PATHS['UPDATE_SCHEDULES'] % self.id
data_format = "schedules[0][%s][]=%s&"
post_data = ""
for format_type, values in schedules.iteritems():
for value in values:
post_data += data_format % (format_type, value)
self.api.post(url=url, data=post_data) |
def moment(p, v, order=1):
""" Calculates the moments of the probability distribution p with vector v """
if order == 1:
return (v*p).sum()
elif order == 2:
return np.sqrt( ((v**2)*p).sum() - (v*p).sum()**2 ) |
def psf_slice(self, zint, size=11, zoffset=0., getextent=False):
"""
Calculates the 3D psf at a particular z pixel height
Parameters
----------
zint : float
z pixel height in image coordinates , converted to 1/k by the
function using the slab position as well
size : int, list, tuple
The size over which to calculate the psf, can be 1 or 3 elements
for the different axes in image pixel coordinates
zoffset : float
Offset in pixel units to use in the calculation of the psf
cutval : float
If not None, the psf will be cut along a curve corresponding to
p(r) == 0 with exponential damping exp(-d^4)
getextent : boolean
If True, also return the extent of the psf in pixels for example
to get the support size. Can only be used with cutval.
"""
# calculate the current pixel value in 1/k, making sure we are above the slab
zint = max(self._p2k(self._tz(zint)), 0)
offset = np.array([zoffset*(zint>0), 0, 0])
scale = [self.param_dict[self.zscale], 1.0, 1.0]
# create the coordinate vectors for where to actually calculate the
tile = util.Tile(left=0, size=size, centered=True)
vecs = tile.coords(form='flat')
vecs = [self._p2k(s*i+o) for i,s,o in zip(vecs, scale, offset)]
psf = self.psffunc(*vecs[::-1], zint=zint, **self.pack_args()).T
vec = tile.coords(form='meshed')
# create a smoothly varying point spread function by cutting off the psf
# at a certain value and smoothly taking it to zero
if self.cutoffval is not None and not self.cutbyval:
# find the edges of the PSF
edge = psf > psf.max() * self.cutoffval
dd = nd.morphology.distance_transform_edt(~edge)
# calculate the new PSF and normalize it to the new support
psf = psf * np.exp(-dd**4)
psf /= psf.sum()
if getextent:
# the size is determined by the edge plus a 2 pad for the
# exponential damping to zero at the edge
size = np.array([
(vec*edge).min(axis=(1,2,3))-2,
(vec*edge).max(axis=(1,2,3))+2,
]).T
return psf, vec, size
return psf, vec
# perform a cut by value instead
if self.cutoffval is not None and self.cutbyval:
cutval = self.cutoffval * psf.max()
dd = (psf - cutval) / cutval
dd[dd > 0] = 0.
# calculate the new PSF and normalize it to the new support
psf = psf * np.exp(-(dd / self.cutfallrate)**4)
psf /= psf.sum()
# let the small values determine the edges
edge = psf > cutval * self.cutedgeval
if getextent:
# the size is determined by the edge plus a 2 pad for the
# exponential damping to zero at the edge
size = np.array([
(vec*edge).min(axis=(1,2,3))-2,
(vec*edge).max(axis=(1,2,3))+2,
]).T
return psf, vec, size
return psf, vec
return psf, vec |
def _p2k(self, v):
""" Convert from pixel to 1/k_incoming (laser_wavelength/(2\pi)) units """
return 2*np.pi*self.pxsize*v/self.param_dict['psf-laser-wavelength'] |
def _tz(self, z):
""" Transform z to real-space coordinates from tile coordinates """
return (z-self.param_dict['psf-zslab'])*self.param_dict[self.zscale] |
def measure_size_drift(self, z, size=31, zoffset=0.):
""" Returns the 'size' of the psf in each direction a particular z (px) """
drift = 0.0
for i in range(self.measurement_iterations):
psf, vec = self.psf_slice(z, size=size, zoffset=zoffset+drift)
psf = psf / psf.sum()
drift += moment(psf, vec[0], order=1)
psize = [moment(psf, j, order=2) for j in vec]
return np.array(psize), drift |
def characterize_psf(self):
""" Get support size and drift polynomial for current set of params """
# there may be an issue with the support and characterization--
# it might be best to do the characterization with the same support
# as the calculated psf.
l,u = max(self.zrange[0], self.param_dict['psf-zslab']), self.zrange[1]
size_l, drift_l = self.measure_size_drift(l)
size_u, drift_u = self.measure_size_drift(u)
# must be odd for now or have a better system for getting the center
self.support = util.oddify(2*self.support_factor*size_u.astype('int'))
self.drift_poly = np.polyfit([l, u], [drift_l, drift_u], 1)
if self.cutoffval is not None:
psf, vec, size_l = self.psf_slice(l, size=51, zoffset=drift_l, getextent=True)
psf, vec, size_u = self.psf_slice(u, size=51, zoffset=drift_u, getextent=True)
ss = [np.abs(i).sum(axis=-1) for i in [size_l, size_u]]
self.support = util.oddify(util.amax(*ss)) |
def _kpad(self, field, finalshape, zpad=False, norm=True):
"""
fftshift and pad the field with zeros until it has size finalshape.
if zpad is off, then no padding is put on the z direction. returns
the fourier transform of the field
"""
currshape = np.array(field.shape)
if any(finalshape < currshape):
raise IndexError("PSF tile size is less than minimum support size")
d = finalshape - currshape
# fix off-by-one issues when going odd to even tile sizes
o = d % 2
d = np.floor_divide(d, 2)
if not zpad:
o[0] = 0
axes = None
pad = tuple((d[i]+o[i],d[i]) for i in [0,1,2])
rpsf = np.pad(field, pad, mode='constant', constant_values=0)
rpsf = np.fft.ifftshift(rpsf, axes=axes)
kpsf = fft.rfftn(rpsf, **fftkwargs)
if norm:
kpsf /= kpsf[0,0,0]
return kpsf |
def pack_args(self):
"""
Pack the parameters into the form necessary for the integration
routines above. For example, packs for calculate_linescan_psf
"""
mapper = {
'psf-kfki': 'kfki',
'psf-alpha': 'alpha',
'psf-n2n1': 'n2n1',
'psf-sigkf': 'sigkf',
'psf-sph6-ab': 'sph6_ab',
'psf-laser-wavelength': 'laser_wavelength',
'psf-pinhole-width': 'pinhole_width'
}
bads = [self.zscale, 'psf-zslab']
d = {}
for k,v in iteritems(mapper):
if k in self.param_dict:
d[v] = self.param_dict[k]
d.update({
'polar_angle': self.polar_angle,
'normalize': self.normalize,
'include_K3_det':self.use_J1
})
if self.polychromatic:
d.update({'nkpts': self.nkpts})
d.update({'k_dist': self.k_dist})
if self.do_pinhole:
d.update({'nlpts': self.num_line_pts})
d.update({'use_laggauss': True})
return d |
def psffunc(self, *args, **kwargs):
"""Calculates a linescan psf"""
if self.polychromatic:
func = psfcalc.calculate_polychrome_linescan_psf
else:
func = psfcalc.calculate_linescan_psf
return func(*args, **kwargs) |
def psffunc(self, x, y, z, **kwargs):
"""Calculates a pinhole psf"""
#do_pinhole?? FIXME
if self.polychromatic:
func = psfcalc.calculate_polychrome_pinhole_psf
else:
func = psfcalc.calculate_pinhole_psf
x0, y0 = [psfcalc.vec_to_halfvec(v) for v in [x,y]]
vls = psfcalc.wrap_and_calc_psf(x0, y0, z, func, **kwargs)
return vls / vls.sum() |
def characterize_psf(self):
""" Get support size and drift polynomial for current set of params """
l,u = max(self.zrange[0], self.param_dict['psf-zslab']), self.zrange[1]
size_l, drift_l = self.measure_size_drift(l, size=self.support)
size_u, drift_u = self.measure_size_drift(u, size=self.support)
self.drift_poly = np.polyfit([l, u], [drift_l, drift_u], 1) |
def _req(self, url, method='GET', **kw):
'''Make request and convert JSON response to python objects'''
send = requests.post if method == 'POST' else requests.get
try:
r = send(
url,
headers=self._token_header(),
timeout=self.settings['timeout'],
**kw)
except requests.exceptions.Timeout:
raise ApiError('Request timed out (%s seconds)' % self.settings['timeout'])
try:
json = r.json()
except ValueError:
raise ApiError('Received not JSON response from API')
if json.get('status') != 'ok':
raise ApiError('API error: received unexpected json from API: %s' % json)
return json |
def get_active_bets(self, project_id=None):
'''Returns all active bets'''
url = urljoin(
self.settings['bets_url'],
'bets?state=fresh,active,accept_end&page=1&page_size=100')
if project_id is not None:
url += '&kava_project_id={}'.format(project_id)
bets = []
has_next_page = True
while has_next_page:
res = self._req(url)
bets.extend(res['bets']['results'])
url = res['bets'].get('next')
has_next_page = bool(url)
return bets |
def get_bets(self, type=None, order_by=None, state=None, project_id=None,
page=None, page_size=None):
"""Return bets with given filters and ordering.
:param type: return bets only with this type.
Use None to include all (default).
:param order_by: '-last_stake' or 'last_stake' to sort by stake's
created date or None for default ordering.
:param state: one of 'active', 'closed', 'all' (default 'active').
:param project_id: return bets associated with given project id in kava
:param page: default 1.
:param page_site: page size (default 100).
"""
if page is None:
page = 1
if page_size is None:
page_size = 100
if state == 'all':
_states = [] # all states == no filter
elif state == 'closed':
_states = self.CLOSED_STATES
else:
_states = self.ACTIVE_STATES
url = urljoin(
self.settings['bets_url'],
'bets?page={}&page_size={}'.format(page, page_size))
url += '&state={}'.format(','.join(_states))
if type is not None:
url += '&type={}'.format(type)
if order_by in ['-last_stake', 'last_stake']:
url += '&order_by={}'.format(order_by)
if project_id is not None:
url += '&kava_project_id={}'.format(project_id)
res = self._req(url)
return res['bets']['results'] |
def get_project_slug(self, bet):
'''Return slug of a project that given bet is associated with
or None if bet is not associated with any project.
'''
if bet.get('form_params'):
params = json.loads(bet['form_params'])
return params.get('project')
return None |
def subscribe(self, event, bet_ids):
'''Subscribe to event for given bet ids.'''
if not self._subscriptions.get(event):
self._subscriptions[event] = set()
self._subscriptions[event] = self._subscriptions[event].union(bet_ids) |
def preview(context):
"""Opens local preview of your blog website"""
config = context.obj
pelican(config, '--verbose', '--ignore-cache')
server_proc = None
os.chdir(config['OUTPUT_DIR'])
try:
try:
command = 'python -m http.server ' + str(PORT)
server_proc = run(command, bg=True)
time.sleep(3)
click.launch('http://localhost:8000')
time.sleep(5)
pelican(config, '--autoreload')
except Exception:
if server_proc is not None:
server_proc.kill()
raise
except KeyboardInterrupt:
abort(context) |
def get_collection_endpoint(cls):
"""
Get the relative path to the API resource collection
If self.collection_endpoint is not set, it will default to the lowercase name of the resource class plus an "s" and the terminating "/"
:param cls: Resource class
:return: Relative path to the resource collection
"""
return cls.Meta.collection_endpoint if cls.Meta.collection_endpoint is not None else cls.__name__.lower() + "s/" |
def send(self, url, http_method, **client_args):
"""
Make the actual request to the API
:param url: URL
:param http_method: The method used to make the request to the API
:param client_args: Arguments to be sent to the auth client
:return: requests' response object
"""
return self.client.send(url, http_method, **client_args) |
def get(self, resource_id):
"""
Get one single resource from the API
:param resource_id: Id of the resource to be retrieved
:return: Retrieved resource
"""
response = self.send(self.get_resource_endpoint(resource_id), "get")
try:
resource = self.resource_class(self.client)
except (ValueError, TypeError):
return None
else:
resource.update_from_dict(self.client.get_response_data(response, self.Meta.parse_json))
return resource |
def filter(self, **search_args):
"""
Get a filtered list of resources
:param search_args: To be translated into ?arg1=value1&arg2=value2...
:return: A list of resources
"""
search_args = search_args or {}
raw_resources = []
for url, paginator_params in self.paginator.get_urls(self.get_collection_endpoint()):
search_args.update(paginator_params)
response = self.paginator.process_response(self.send(url, "get", params=search_args))
raw_resources += self.client.get_response_data(response, self.Meta.parse_json)[self.json_collection_attribute] if self.json_collection_attribute is not None else self.client.get_response_data(response, self.Meta.parse_json)
resources = []
for raw_resource in raw_resources:
try:
resource = self.resource_class(self.client)
except (ValueError, TypeError):
continue
else:
resource.update_from_dict(raw_resource)
resources.append(resource)
return resources |
def create(self, **kwargs):
"""
Create a resource on the server
:params kwargs: Attributes (field names and values) of the new resource
"""
resource = self.resource_class(self.client)
resource.update_from_dict(kwargs)
resource.save(force_create=True)
return resource |
def send(self, relative_path, http_method, **requests_args):
"""
Subclasses must implement this method, that will be used to send API requests with proper auth
:param relative_path: URL path relative to self.base_url
:param http_method: HTTP method
:param requests_args: kargs to be sent to requests
:return:
"""
url = urljoin(self.base_url, relative_path)
return self.session.request(http_method, url, **requests_args) |
def get_response_data(self, response, parse_json=True):
"""
Get response data or throw an appropiate exception
:param response: requests response object
:param parse_json: if True, response will be parsed as JSON
:return: response data, either as json or as a regular response.content object
"""
if response.status_code in (requests.codes.ok, requests.codes.created):
if parse_json:
return response.json()
return response.content
elif response.status_code == requests.codes.bad_request:
response_json = response.json()
raise BadRequestException(response_json.get("error", False) or response_json.get("errors",
_("Bad Request: {text}").format(text=response.text)))
elif response.status_code == requests.codes.not_found:
raise NotFoundException(_("Resource not found: {url}").format(url=response.url))
elif response.status_code == requests.codes.internal_server_error:
raise ServerErrorException(_("Internal server error"))
elif response.status_code in (requests.codes.unauthorized, requests.codes.forbidden):
raise AuthErrorException(_("Access denied"))
elif response.status_code == requests.codes.too_many_requests:
raise RateLimitException(_(response.text))
else:
raise ServerErrorException(_("Unknown error occurred")) |
def send(self, relative_path, http_method, **requests_args):
"""
Make a unauthorized request
:param relative_path: URL path relative to self.base_url
:param http_method: HTTP method
:param requests_args: kargs to be sent to requests
:return: requests' response object
"""
if http_method != "get":
warnings.warn(_("You are using methods other than get with no authentication!!!"))
return super(NoAuthClient, self).send(relative_path, http_method, **requests_args) |
def write(context):
"""Starts a new article"""
config = context.obj
title = click.prompt('Title')
author = click.prompt('Author', default=config.get('DEFAULT_AUTHOR'))
slug = slugify(title)
creation_date = datetime.now()
basename = '{:%Y-%m-%d}_{}.md'.format(creation_date, slug)
meta = (
('Title', title),
('Date', '{:%Y-%m-%d %H:%M}:00'.format(creation_date)),
('Modified', '{:%Y-%m-%d %H:%M}:00'.format(creation_date)),
('Author', author),
)
file_content = ''
for key, value in meta:
file_content += '{}: {}\n'.format(key, value)
file_content += '\n\n'
file_content += 'Text...\n\n'
file_content += '\n\n'
file_content += 'Text...\n\n'
os.makedirs(config['CONTENT_DIR'], exist_ok=True)
path = os.path.join(config['CONTENT_DIR'], basename)
with click.open_file(path, 'w') as f:
f.write(file_content)
click.echo(path)
click.launch(path) |
def lint(context):
"""Looks for errors in source code of your blog"""
config = context.obj
try:
run('flake8 {dir} --exclude={exclude}'.format(
dir=config['CWD'],
exclude=','.join(EXCLUDE),
))
except SubprocessError:
context.exit(1) |
def set_real_value_class(self):
"""
value_class is initially a string with the import path to the resource class, but we need to get the actual class before doing any work
We do not expect the actual clas to be in value_class since the beginning to avoid nasty import egg-before-chicken errors
"""
if self.value_class is not None and isinstance(self.value_class, str):
module_name, dot, class_name = self.value_class.rpartition(".")
module = __import__(module_name, fromlist=[class_name])
self.value_class = getattr(module, class_name)
self._initialized = True |
def publish(context):
"""Saves changes and sends them to GitHub"""
header('Recording changes...')
run('git add -A')
header('Displaying changes...')
run('git -c color.status=always status')
if not click.confirm('\nContinue publishing'):
run('git reset HEAD --')
abort(context)
header('Saving changes...')
try:
run('git commit -m "{message}"'.format(
message='Publishing {}'.format(choose_commit_emoji())
), capture=True)
except subprocess.CalledProcessError as e:
if 'nothing to commit' not in e.stdout:
raise
else:
click.echo('Nothing to commit.')
header('Pushing to GitHub...')
branch = get_branch()
run('git push origin {branch}:{branch}'.format(branch=branch))
pr_link = get_pr_link(branch)
if pr_link:
click.launch(pr_link) |
def deploy(context):
"""Uploads new version of the blog website"""
config = context.obj
header('Generating HTML...')
pelican(config, '--verbose', production=True)
header('Removing unnecessary output...')
unnecessary_paths = [
'author', 'category', 'tag', 'feeds', 'tags.html',
'authors.html', 'categories.html', 'archives.html',
]
for path in unnecessary_paths:
remove_path(os.path.join(config['OUTPUT_DIR'], path))
if os.environ.get('TRAVIS'): # Travis CI
header('Setting up Git...')
run(
'git config user.name ' +
run('git show --format="%cN" -s', capture=True)
)
run(
'git config user.email ' +
run('git show --format="%cE" -s', capture=True)
)
github_token = os.environ.get('GITHUB_TOKEN')
repo_slug = os.environ.get('TRAVIS_REPO_SLUG')
origin = 'https://{}@github.com/{}.git'.format(github_token, repo_slug)
run('git remote set-url origin ' + origin)
header('Rewriting gh-pages branch...')
run('ghp-import -m "{message}" {dir}'.format(
message='Deploying {}'.format(choose_commit_emoji()),
dir=config['OUTPUT_DIR'],
))
header('Pushing to GitHub...')
run('git push origin gh-pages:gh-pages --force') |
def signed_number(number, precision=2):
"""
Return the given number as a string with a sign in front of it, ie. `+` if the number is positive, `-` otherwise.
"""
prefix = '' if number <= 0 else '+'
number_str = '{}{:.{precision}f}'.format(prefix, number, precision=precision)
return number_str |
def balance(ctx):
"""
Show Zebra balance.
Like the hours balance, vacation left, etc.
"""
backend = plugins_registry.get_backends_by_class(ZebraBackend)[0]
timesheet_collection = get_timesheet_collection_for_context(ctx, None)
hours_to_be_pushed = timesheet_collection.get_hours(pushed=False, ignored=False, unmapped=False)
today = datetime.date.today()
user_info = backend.get_user_info()
timesheets = backend.get_timesheets(get_first_dow(today), get_last_dow(today))
total_duration = sum([float(timesheet['time']) for timesheet in timesheets])
vacation = hours_to_days(user_info['vacation']['difference'])
vacation_balance = '{} days, {:.2f} hours'.format(*vacation)
hours_balance = user_info['hours']['hours']['balance']
click.echo("Hours balance: {}".format(signed_number(hours_balance)))
click.echo("Hours balance after push: {}".format(signed_number(hours_balance + hours_to_be_pushed)))
click.echo("Hours done this week: {:.2f}".format(total_duration))
click.echo("Vacation left: {}".format(vacation_balance)) |
def to_zebra_params(params):
"""
Transforms the given `params` dict to values that are understood by Zebra (eg. False is represented as 'false')
"""
def to_zebra_value(value):
transform_funcs = {
bool: lambda v: 'true' if v else 'false',
}
return transform_funcs.get(type(value), lambda v: v)(value)
return {param: to_zebra_value(value) for param, value in params.items()} |
def show_response_messages(response_json):
"""
Show all messages in the `messages` key of the given dict.
"""
message_type_kwargs = {
'warning': {'fg': 'yellow'},
'error': {'fg': 'red'},
}
for message in response_json.get('messages', []):
click.secho(message['text'], **message_type_kwargs.get(message['type'], {})) |
def update_alias_mapping(settings, alias, new_mapping):
"""
Override `alias` mapping in the user configuration file with the given `new_mapping`, which should be a tuple with
2 or 3 elements (in the form `(project_id, activity_id, role_id)`).
"""
mapping = aliases_database[alias]
new_mapping = Mapping(mapping=new_mapping, backend=mapping.backend)
aliases_database[alias] = new_mapping
settings.add_alias(alias, new_mapping)
settings.write_config() |
def photos(context, path):
"""Adds images to the last article"""
config = context.obj
header('Looking for the latest article...')
article_filename = find_last_article(config['CONTENT_DIR'])
if not article_filename:
return click.secho('No articles.', fg='red')
click.echo(os.path.basename(article_filename))
header('Looking for images...')
images = list(sorted(find_images(path)))
if not images:
return click.secho('Found no images.', fg='red')
for filename in images:
click.secho(filename, fg='green')
if not click.confirm('\nAdd these images to the latest article'):
abort(config)
url_prefix = os.path.join('{filename}', IMAGES_PATH)
images_dir = os.path.join(config['CONTENT_DIR'], IMAGES_PATH)
os.makedirs(images_dir, exist_ok=True)
header('Processing images...')
urls = []
for filename in images:
image_basename = os.path.basename(filename).replace(' ', '-').lower()
urls.append(os.path.join(url_prefix, image_basename))
image_filename = os.path.join(images_dir, image_basename)
print(filename, image_filename)
import_image(filename, image_filename)
content = '\n'
for url in urls:
url = url.replace('\\', '/')
content += '\n\n'.format(url)
header('Adding to article: {}'.format(article_filename))
with click.open_file(article_filename, 'a') as f:
f.write(content)
click.launch(article_filename) |
def _generate_circle(self):
"""Generates the circle.
"""
total_weight = 0
for node in self.nodes:
total_weight += self.weights.get(node, 1)
for node in self.nodes:
weight = 1
if node in self.weights:
weight = self.weights.get(node)
factor = math.floor((40 * len(self.nodes) * weight) / total_weight)
for j in range(0, int(factor)):
b_key = bytearray(self._hash_digest('%s-%s' % (node, j)))
for i in range(0, 3):
key = self._hash_val(b_key, lambda x: x + i * 4)
self.ring[key] = node
self._sorted_keys.append(key)
self._sorted_keys.sort() |
def get_node(self, string_key):
"""Given a string key a corresponding node in the hash ring is returned.
If the hash ring is empty, `None` is returned.
"""
pos = self.get_node_pos(string_key)
if pos is None:
return None
return self.ring[self._sorted_keys[pos]] |
def get_node_pos(self, string_key):
"""Given a string key a corresponding node in the hash ring is returned
along with it's position in the ring.
If the hash ring is empty, (`None`, `None`) is returned.
"""
if not self.ring:
return None
key = self.gen_key(string_key)
nodes = self._sorted_keys
pos = bisect(nodes, key)
if pos == len(nodes):
return 0
else:
return pos |
def iterate_nodes(self, string_key, distinct=True):
"""Given a string key it returns the nodes as a generator that can hold the key.
The generator iterates one time through the ring
starting at the correct position.
if `distinct` is set, then the nodes returned will be unique,
i.e. no virtual copies will be returned.
"""
if not self.ring:
yield None, None
returned_values = set()
def distinct_filter(value):
if str(value) not in returned_values:
returned_values.add(str(value))
return value
pos = self.get_node_pos(string_key)
for key in self._sorted_keys[pos:]:
val = distinct_filter(self.ring[key])
if val:
yield val
for i, key in enumerate(self._sorted_keys):
if i < pos:
val = distinct_filter(self.ring[key])
if val:
yield val |
def gen_key(self, key):
"""Given a string key it returns a long value,
this long value represents a place on the hash ring.
md5 is currently used because it mixes well.
"""
b_key = self._hash_digest(key)
return self._hash_val(b_key, lambda x: x) |
def get_number_of_app_ports(app):
"""
Get the number of ports for the given app JSON. This roughly follows the
logic in marathon-lb for finding app IPs/ports, although we are only
interested in the quantity of ports an app should have and don't consider
the specific IPs/ports of individual tasks:
https://github.com/mesosphere/marathon-lb/blob/v1.10.3/utils.py#L393-L415
:param app: The app JSON from the Marathon API.
:return: The number of ports for the app.
"""
mode = _get_networking_mode(app)
ports_list = None
if mode == 'host':
ports_list = _get_port_definitions(app)
elif mode == 'container/bridge':
ports_list = _get_port_definitions(app)
if ports_list is None:
ports_list = _get_container_port_mappings(app)
elif mode == 'container':
ports_list = _get_ip_address_discovery_ports(app)
# Marathon 1.5+: the ipAddress field is missing -> ports_list is None
# Marathon <1.5: the ipAddress field can be present, but ports_list can
# still be empty while the container port mapping is not :-/
if not ports_list:
ports_list = _get_container_port_mappings(app)
else:
raise RuntimeError(
"Unknown Marathon networking mode '{}'".format(mode))
return len(ports_list) |
def _get_networking_mode(app):
"""
Get the Marathon networking mode for the app.
"""
# Marathon 1.5+: there is a `networks` field
networks = app.get('networks')
if networks:
# Modes cannot be mixed, so assigning the last mode is fine
return networks[-1].get('mode', 'container')
# Older Marathon: determine equivalent network mode
container = app.get('container')
if container is not None and 'docker' in container:
docker_network = container['docker'].get('network')
if docker_network == 'USER':
return 'container'
elif docker_network == 'BRIDGE':
return 'container/bridge'
return 'container' if _is_legacy_ip_per_task(app) else 'host' |
def _get_container_port_mappings(app):
"""
Get the ``portMappings`` field for the app container.
"""
container = app['container']
# Marathon 1.5+: container.portMappings field
port_mappings = container.get('portMappings')
# Older Marathon: container.docker.portMappings field
if port_mappings is None and 'docker' in container:
port_mappings = container['docker'].get('portMappings')
return port_mappings |
def sort_pem_objects(pem_objects):
"""
Given a list of pem objects, sort the objects into the private key, leaf
certificate, and list of CA certificates in the trust chain. This function
assumes that the list of pem objects will contain exactly one private key
and exactly one leaf certificate and that only key and certificate type
objects are provided.
"""
keys, certs, ca_certs = [], [], []
for pem_object in pem_objects:
if isinstance(pem_object, pem.Key):
keys.append(pem_object)
else:
# This assumes all pem objects provided are either of type pem.Key
# or pem.Certificate. Technically, there are CSR and CRL types, but
# we should never be passed those.
if _is_ca(pem_object):
ca_certs.append(pem_object)
else:
certs.append(pem_object)
[key], [cert] = keys, certs
return key, cert, ca_certs |
def _cert_data_to_pem_objects(cert_data):
"""
Given a non-None response from the Vault key/value store, convert the
key/values into a list of PEM objects.
"""
pem_objects = []
for key in ['privkey', 'cert', 'chain']:
pem_objects.extend(pem.parse(cert_data[key].encode('utf-8')))
return pem_objects |
def raise_for_not_ok_status(response):
"""
Raises a `requests.exceptions.HTTPError` if the response has a non-200
status code.
"""
if response.code != OK:
raise HTTPError('Non-200 response code (%s) for url: %s' % (
response.code, uridecode(response.request.absoluteURI)))
return response |
def _sse_content_with_protocol(response, handler, **sse_kwargs):
"""
Sometimes we need the protocol object so that we can manipulate the
underlying transport in tests.
"""
protocol = SseProtocol(handler, **sse_kwargs)
finished = protocol.when_finished()
response.deliverBody(protocol)
return finished, protocol |
def sse_content(response, handler, **sse_kwargs):
"""
Callback to collect the Server-Sent Events content of a response. Callbacks
passed will receive event data.
:param response:
The response from the SSE request.
:param handler:
The handler for the SSE protocol.
"""
# An SSE response must be 200/OK and have content-type 'text/event-stream'
raise_for_not_ok_status(response)
raise_for_header(response, 'Content-Type', 'text/event-stream')
finished, _ = _sse_content_with_protocol(response, handler, **sse_kwargs)
return finished |
def _request(self, failure, endpoints, *args, **kwargs):
"""
Recursively make requests to each endpoint in ``endpoints``.
"""
# We've run out of endpoints, fail
if not endpoints:
return failure
endpoint = endpoints.pop(0)
d = super(MarathonClient, self).request(*args, url=endpoint, **kwargs)
# If something goes wrong, call ourselves again with the remaining
# endpoints
d.addErrback(self._request, endpoints, *args, **kwargs)
return d |
def get_json_field(self, field, **kwargs):
"""
Perform a GET request and get the contents of the JSON response.
Marathon's JSON responses tend to contain an object with a single key
which points to the actual data of the response. For example /v2/apps
returns something like {"apps": [ {"app1"}, {"app2"} ]}. We're
interested in the contents of "apps".
This method will raise an error if:
* There is an error response code
* The field with the given name cannot be found
"""
d = self.request(
'GET', headers={'Accept': 'application/json'}, **kwargs)
d.addCallback(raise_for_status)
d.addCallback(raise_for_header, 'Content-Type', 'application/json')
d.addCallback(json_content)
d.addCallback(self._get_json_field, field)
return d |
def _get_json_field(self, response_json, field_name):
"""
Get a JSON field from the response JSON.
:param: response_json:
The parsed JSON content of the response.
:param: field_name:
The name of the field in the JSON to get.
"""
if field_name not in response_json:
raise KeyError('Unable to get value for "%s" from Marathon '
'response: "%s"' % (
field_name, json.dumps(response_json),))
return response_json[field_name] |
def get_events(self, callbacks):
"""
Attach to Marathon's event stream using Server-Sent Events (SSE).
:param callbacks:
A dict mapping event types to functions that handle the event data
"""
d = self.request(
'GET', path='/v2/events', unbuffered=True,
# The event_type parameter was added in Marathon 1.3.7. It can be
# used to specify which event types we are interested in. On older
# versions of Marathon it is ignored, and we ignore events we're
# not interested in anyway.
params={'event_type': sorted(callbacks.keys())},
headers={
'Accept': 'text/event-stream',
'Cache-Control': 'no-store'
})
def handler(event, data):
callback = callbacks.get(event)
# Deserialize JSON if a callback is present
if callback is not None:
callback(json.loads(data))
return d.addCallback(
sse_content, handler, reactor=self._reactor, **self._sse_kwargs) |
def parse(
self,
value: str,
type_: typing.Type[typing.Any] = str,
subtype: typing.Type[typing.Any] = str,
) -> typing.Any:
"""
Parse value from string.
Convert :code:`value` to
.. code-block:: python
>>> parser = Config()
>>> parser.parse('12345', type_=int)
<<< 12345
>>>
>>> parser.parse('1,2,3,4', type_=list, subtype=int)
<<< [1, 2, 3, 4]
:param value: string
:param type\\_: the type to return
:param subtype: subtype for iterator types
:return: the parsed config value
"""
if type_ is bool:
return type_(value.lower() in self.TRUE_STRINGS)
try:
if isinstance(type_, type) and issubclass(
type_, (list, tuple, set, frozenset)
):
return type_(
self.parse(v.strip(" "), subtype)
for v in value.split(",")
if value.strip(" ")
)
return type_(value)
except ValueError as e:
raise ConfigError(*e.args) |
def get(
self,
key: str,
default: typing.Any = UNSET,
type_: typing.Type[typing.Any] = str,
subtype: typing.Type[typing.Any] = str,
mapper: typing.Optional[typing.Callable[[object], object]] = None,
) -> typing.Any:
"""
Parse a value from an environment variable.
.. code-block:: python
>>> os.environ['FOO']
<<< '12345'
>>>
>>> os.environ['BAR']
<<< '1,2,3,4'
>>>
>>> 'BAZ' in os.environ
<<< False
>>>
>>> parser = Config()
>>> parser.get('FOO', type_=int)
<<< 12345
>>>
>>> parser.get('BAR', type_=list, subtype=int)
<<< [1, 2, 3, 4]
>>>
>>> parser.get('BAZ', default='abc123')
<<< 'abc123'
>>>
>>> parser.get('FOO', type_=int, mapper=lambda x: x*10)
<<< 123450
:param key: the key to look up the value under
:param default: default value to return when when no value is present
:param type\\_: the type to return
:param subtype: subtype for iterator types
:param mapper: a function to post-process the value with
:return: the parsed config value
"""
value = self.environ.get(key, UNSET)
if value is UNSET and default is UNSET:
raise ConfigError("Unknown environment variable: {0}".format(key))
if value is UNSET:
value = default
else:
value = self.parse(typing.cast(str, value), type_, subtype)
if mapper:
value = mapper(value)
return value |
def _request(self, endpoint, *args, **kwargs):
"""
Perform a request to a specific endpoint. Raise an error if the status
code indicates a client or server error.
"""
kwargs['url'] = endpoint
return (super(MarathonLbClient, self).request(*args, **kwargs)
.addCallback(raise_for_status)) |
def _check_request_results(self, results):
"""
Check the result of each request that we made. If a failure occurred,
but some requests succeeded, log and count the failures. If all
requests failed, raise an error.
:return:
The list of responses, with a None value for any requests that
failed.
"""
responses = []
failed_endpoints = []
for index, result_tuple in enumerate(results):
success, result = result_tuple
if success:
responses.append(result)
else:
endpoint = self.endpoints[index]
self.log.failure(
'Failed to make a request to a marathon-lb instance: '
'{endpoint}', result, LogLevel.error, endpoint=endpoint)
responses.append(None)
failed_endpoints.append(endpoint)
if len(failed_endpoints) == len(self.endpoints):
raise RuntimeError(
'Failed to make a request to all marathon-lb instances')
if failed_endpoints:
self.log.error(
'Failed to make a request to {x}/{y} marathon-lb instances: '
'{endpoints}', x=len(failed_endpoints), y=len(self.endpoints),
endpoints=failed_endpoints)
return responses |
def maybe_key(pem_path):
"""
Set up a client key if one does not exist already.
https://gist.github.com/glyph/27867a478bb71d8b6046fbfb176e1a33#file-local-certs-py-L32-L50
:type pem_path: twisted.python.filepath.FilePath
:param pem_path:
The path to the certificate directory to use.
:rtype: twisted.internet.defer.Deferred
"""
acme_key_file = pem_path.child(u'client.key')
if acme_key_file.exists():
key = _load_pem_private_key_bytes(acme_key_file.getContent())
else:
key = generate_private_key(u'rsa')
acme_key_file.setContent(_dump_pem_private_key_bytes(key))
return succeed(JWKRSA(key=key)) |
def maybe_key_vault(client, mount_path):
"""
Set up a client key in Vault if one does not exist already.
:param client:
The Vault API client to use.
:param mount_path:
The Vault key/value mount path to use.
:rtype: twisted.internet.defer.Deferred
"""
d = client.read_kv2('client_key', mount_path=mount_path)
def get_or_create_key(client_key):
if client_key is not None:
key_data = client_key['data']['data']
key = _load_pem_private_key_bytes(key_data['key'].encode('utf-8'))
return JWKRSA(key=key)
else:
key = generate_private_key(u'rsa')
key_data = {
'key': _dump_pem_private_key_bytes(key).decode('utf-8')
}
d = client.create_or_update_kv2(
'client_key', key_data, mount_path=mount_path)
return d.addCallback(lambda _result: JWKRSA(key=key))
return d.addCallback(get_or_create_key) |
def create_txacme_client_creator(key, reactor, url, alg=RS256):
"""
Create a creator for txacme clients to provide to the txacme service. See
``txacme.client.Client.from_url()``. We create the underlying JWSClient
with a non-persistent pool to avoid
https://github.com/mithrandi/txacme/issues/86.
:return: a callable that returns a deffered that returns the client
"""
# Creating an Agent without specifying a pool gives us the default pool
# which is non-persistent.
jws_client = JWSClient(HTTPClient(agent=Agent(reactor)), key, alg)
return partial(txacme_Client.from_url, reactor, url, key, alg, jws_client) |
def generate_wildcard_pem_bytes():
"""
Generate a wildcard (subject name '*') self-signed certificate valid for
10 years.
https://cryptography.io/en/latest/x509/tutorial/#creating-a-self-signed-certificate
:return: Bytes representation of the PEM certificate data
"""
key = generate_private_key(u'rsa')
name = x509.Name([x509.NameAttribute(NameOID.COMMON_NAME, u'*')])
cert = (
x509.CertificateBuilder()
.issuer_name(name)
.subject_name(name)
.not_valid_before(datetime.today() - timedelta(days=1))
.not_valid_after(datetime.now() + timedelta(days=3650))
.serial_number(int(uuid.uuid4()))
.public_key(key.public_key())
.sign(
private_key=key,
algorithm=hashes.SHA256(),
backend=default_backend())
)
return b''.join((
key.private_bytes(
encoding=serialization.Encoding.PEM,
format=serialization.PrivateFormat.TraditionalOpenSSL,
encryption_algorithm=serialization.NoEncryption()),
cert.public_bytes(serialization.Encoding.PEM)
)) |
def from_env(cls, reactor=None, env=os.environ):
"""
Create a Vault client with configuration from the environment. Supports
a limited number of the available config options:
https://www.vaultproject.io/docs/commands/index.html#environment-variables
https://github.com/hashicorp/vault/blob/v0.11.3/api/client.go#L28-L40
Supported:
- ``VAULT_ADDR``
- ``VAULT_CACERT``
- ``VAULT_CLIENT_CERT``
- ``VAULT_CLIENT_KEY``
- ``VAULT_TLS_SERVER_NAME``
- ``VAULT_TOKEN``
Not currently supported:
- ``VAULT_CAPATH``
- ``VAULT_CLIENT_TIMEOUT``
- ``VAULT_MAX_RETRIES``
- ``VAULT_MFA``
- ``VAULT_RATE_LIMIT``
- ``VAULT_SKIP_VERIFY``
- ``VAULT_WRAP_TTL``
"""
address = env.get('VAULT_ADDR', 'https://127.0.0.1:8200')
# This seems to be what the Vault CLI defaults to
token = env.get('VAULT_TOKEN', 'TEST')
ca_cert = env.get('VAULT_CACERT')
tls_server_name = env.get('VAULT_TLS_SERVER_NAME')
client_cert = env.get('VAULT_CLIENT_CERT')
client_key = env.get('VAULT_CLIENT_KEY')
cf = ClientPolicyForHTTPS.from_pem_files(
caKey=ca_cert, privateKey=client_key, certKey=client_cert,
tls_server_name=tls_server_name
)
client, reactor = default_client(reactor, contextFactory=cf)
return cls(address, token, client=client, reactor=reactor) |
def read(self, path, **params):
"""
Read data from Vault. Returns the JSON-decoded response.
"""
d = self.request('GET', '/v1/' + path, params=params)
return d.addCallback(self._handle_response) |
def write(self, path, **data):
"""
Write data to Vault. Returns the JSON-decoded response.
"""
d = self.request('PUT', '/v1/' + path, json=data)
return d.addCallback(self._handle_response, check_cas=True) |
def read_kv2(self, path, version=None, mount_path='secret'):
"""
Read some data from a key/value version 2 secret engine.
"""
params = {}
if version is not None:
params['version'] = version
read_path = '{}/data/{}'.format(mount_path, path)
return self.read(read_path, **params) |
def create_or_update_kv2(self, path, data, cas=None, mount_path='secret'):
"""
Create or update some data in a key/value version 2 secret engine.
:raises CasError:
Raises an error if the ``cas`` value, when provided, doesn't match
Vault's version for the key.
"""
params = {
'options': {},
'data': data
}
if cas is not None:
params['options']['cas'] = cas
write_path = '{}/data/{}'.format(mount_path, path)
return self.write(write_path, **params) |
def get_single_header(headers, key):
"""
Get a single value for the given key out of the given set of headers.
:param twisted.web.http_headers.Headers headers:
The set of headers in which to look for the header value
:param str key:
The header key
"""
raw_headers = headers.getRawHeaders(key)
if raw_headers is None:
return None
# Take the final header as the authorative
header, _ = cgi.parse_header(raw_headers[-1])
return header |
def raise_for_status(response):
"""
Raises a `requests.exceptions.HTTPError` if the response did not succeed.
Adapted from the Requests library:
https://github.com/kennethreitz/requests/blob/v2.8.1/requests/models.py#L825-L837
"""
http_error_msg = ''
if 400 <= response.code < 500:
http_error_msg = '%s Client Error for url: %s' % (
response.code, uridecode(response.request.absoluteURI))
elif 500 <= response.code < 600:
http_error_msg = '%s Server Error for url: %s' % (
response.code, uridecode(response.request.absoluteURI))
if http_error_msg:
raise HTTPError(http_error_msg, response=response)
return response |
def _compose_url(self, url, kwargs):
"""
Compose a URL starting with the given URL (or self.url if that URL is
None) and using the values in kwargs.
:param str url:
The base URL to use. If None, ``self.url`` will be used instead.
:param dict kwargs:
A dictionary of values to override in the base URL. Relevant keys
will be popped from the dictionary.
"""
if url is None:
url = self.url
if url is None:
raise ValueError(
'url not provided and this client has no url attribute')
split_result = urisplit(url)
userinfo = split_result.userinfo
# Build up the kwargs to pass to uricompose
compose_kwargs = {}
for key in ['scheme', 'host', 'port', 'path', 'fragment']:
if key in kwargs:
compose_kwargs[key] = kwargs.pop(key)
else:
compose_kwargs[key] = getattr(split_result, key)
if 'params' in kwargs:
compose_kwargs['query'] = kwargs.pop('params')
else:
compose_kwargs['query'] = split_result.query
# Take the userinfo out of the URL and pass as 'auth' to treq so it can
# be used for HTTP basic auth headers
if 'auth' not in kwargs and userinfo is not None:
# treq expects a 2-tuple (username, password)
kwargs['auth'] = tuple(userinfo.split(':', 2))
return uricompose(**compose_kwargs) |
def request(self, method, url=None, **kwargs):
"""
Perform a request.
:param: method:
The HTTP method to use (example is `GET`).
:param: url:
The URL to use. The default value is the URL this client was
created with (`self.url`) (example is `http://localhost:8080`)
:param: kwargs:
Any other parameters that will be passed to `treq.request`, for
example headers. Or any URL parameters to override, for example
path, query or fragment.
"""
url = self._compose_url(url, kwargs)
kwargs.setdefault('timeout', self._timeout)
d = self._client.request(method, url, reactor=self._reactor, **kwargs)
d.addCallback(self._log_request_response, method, url, kwargs)
d.addErrback(self._log_request_error, url)
return d |
def listen(self, reactor, endpoint_description):
"""
Run the server, i.e. start listening for requests on the given host and
port.
:param reactor: The ``IReactorTCP`` to use.
:param endpoint_description:
The Twisted description for the endpoint to listen on.
:return:
A deferred that returns an object that provides ``IListeningPort``.
"""
endpoint = serverFromString(reactor, endpoint_description)
return endpoint.listen(Site(self.app.resource())) |
def health(self, request):
""" Listens to incoming health checks from Marathon on ``/health``. """
if self.health_handler is None:
return self._no_health_handler(request)
health = self.health_handler()
response_code = OK if health.healthy else SERVICE_UNAVAILABLE
request.setResponseCode(response_code)
write_request_json(request, health.json_message) |
def main(reactor, argv=sys.argv[1:], env=os.environ,
acme_url=LETSENCRYPT_DIRECTORY.asText()):
"""
A tool to automatically request, renew and distribute Let's Encrypt
certificates for apps running on Marathon and served by marathon-lb.
"""
parser = argparse.ArgumentParser(
description='Automatically manage ACME certificates for Marathon apps')
parser.add_argument('-a', '--acme',
help='The address for the ACME Directory Resource '
'(default: %(default)s)',
default=acme_url)
parser.add_argument('-e', '--email',
help='An email address to register with the ACME '
'service (optional)')
parser.add_argument('-m', '--marathon', metavar='MARATHON[,MARATHON,...]',
help='The addresses for the Marathon HTTP API '
'(default: %(default)s)',
default='http://marathon.mesos:8080')
parser.add_argument('-l', '--lb', metavar='LB[,LB,...]',
help='The addresses for the marathon-lb HTTP API '
'(default: %(default)s)',
default='http://marathon-lb.marathon.mesos:9090')
parser.add_argument('-g', '--group',
help='The marathon-lb group to issue certificates for '
'(default: %(default)s)',
default='external')
parser.add_argument('--allow-multiple-certs',
help=('Allow multiple certificates for a single app '
'port. This allows multiple domains for an app, '
'but is not recommended.'),
action='store_true')
parser.add_argument('--listen',
help='The address for the port to listen on (default: '
'%(default)s)',
default=':8000')
parser.add_argument('--marathon-timeout',
help=('Amount of time in seconds to wait for HTTP '
'response headers to be received for all '
'requests to Marathon. Set to 0 to disable. '
'(default: %(default)s)'),
type=float,
default=10)
parser.add_argument('--sse-timeout',
help=('Amount of time in seconds to wait for some '
'event data to be received from Marathon. Set '
'to 0 to disable. (default: %(default)s)'),
type=float,
default=60)
parser.add_argument('--log-level',
help='The minimum severity level to log messages at '
'(default: %(default)s)',
choices=['debug', 'info', 'warn', 'error', 'critical'],
default='info'),
parser.add_argument('--vault',
help=('Enable storage of certificates in Vault. This '
'can be further configured with VAULT_-style '
'environment variables.'),
action='store_true')
parser.add_argument('storage_path', metavar='storage-path',
help=('Path for storing certificates. If --vault is '
'used then this is the mount path for the '
'key/value engine in Vault. If not, this is the '
'path to a directory.'))
parser.add_argument('--version', action='version', version=__version__)
args = parser.parse_args(argv)
# Set up logging
init_logging(args.log_level)
# Set up marathon-acme
marathon_addrs = args.marathon.split(',')
mlb_addrs = args.lb.split(',')
sse_timeout = args.sse_timeout if args.sse_timeout > 0 else None
acme_url = URL.fromText(_to_unicode(args.acme))
endpoint_description = parse_listen_addr(args.listen)
log_args = [
('storage-path', args.storage_path),
('vault', args.vault),
('acme', acme_url),
('email', args.email),
('allow-multiple-certs', args.allow_multiple_certs),
('marathon', marathon_addrs),
('sse-timeout', sse_timeout),
('lb', mlb_addrs),
('group', args.group),
('endpoint-description', endpoint_description),
]
log_args = ['{}={!r}'.format(k, v) for k, v in log_args]
log.info('Starting marathon-acme {} with: {}'.format(
__version__, ', '.join(log_args)))
if args.vault:
key_d, cert_store = init_vault_storage(
reactor, env, args.storage_path)
else:
key_d, cert_store = init_file_storage(args.storage_path)
# Once we have the client key, create the txacme client creator
key_d.addCallback(create_txacme_client_creator, reactor, acme_url)
# Once we have the client creator, create the service
key_d.addCallback(
create_marathon_acme, cert_store, args.email,
args.allow_multiple_certs, marathon_addrs, args.marathon_timeout,
sse_timeout, mlb_addrs, args.group, reactor)
# Finally, run the thing
return key_d.addCallback(lambda ma: ma.run(endpoint_description)) |
def parse_listen_addr(listen_addr):
"""
Parse an address of the form [ipaddress]:port into a tcp or tcp6 Twisted
endpoint description string for use with
``twisted.internet.endpoints.serverFromString``.
"""
if ':' not in listen_addr:
raise ValueError(
"'%s' does not have the correct form for a listen address: "
'[ipaddress]:port' % (listen_addr,))
host, port = listen_addr.rsplit(':', 1)
# Validate the host
if host == '':
protocol = 'tcp'
interface = None
else:
if host.startswith('[') and host.endswith(']'): # IPv6 wrapped in []
host = host[1:-1]
ip_address = ipaddress.ip_address(_to_unicode(host))
protocol = 'tcp6' if ip_address.version == 6 else 'tcp'
interface = str(ip_address)
# Validate the port
if not port.isdigit() or int(port) < 1 or int(port) > 65535:
raise ValueError(
"'%s' does not appear to be a valid port number" % (port,))
args = [protocol, port]
kwargs = {'interface': interface} if interface is not None else {}
return _create_tx_endpoints_string(args, kwargs) |
def create_marathon_acme(
client_creator, cert_store, acme_email, allow_multiple_certs,
marathon_addrs, marathon_timeout, sse_timeout, mlb_addrs, group,
reactor):
"""
Create a marathon-acme instance.
:param client_creator:
The txacme client creator function.
:param cert_store:
The txacme certificate store instance.
:param acme_email:
Email address to use when registering with the ACME service.
:param allow_multiple_certs:
Whether to allow multiple certificates per app port.
:param marathon_addr:
Address for the Marathon instance to find app domains that require
certificates.
:param marathon_timeout:
Amount of time in seconds to wait for response headers to be received
from Marathon.
:param sse_timeout:
Amount of time in seconds to wait for some event data to be received
from Marathon.
:param mlb_addrs:
List of addresses for marathon-lb instances to reload when a new
certificate is issued.
:param group:
The marathon-lb group (``HAPROXY_GROUP``) to consider when finding
app domains.
:param reactor: The reactor to use.
"""
marathon_client = MarathonClient(marathon_addrs, timeout=marathon_timeout,
sse_kwargs={'timeout': sse_timeout},
reactor=reactor)
marathon_lb_client = MarathonLbClient(mlb_addrs, reactor=reactor)
return MarathonAcme(
marathon_client,
group,
cert_store,
marathon_lb_client,
client_creator,
reactor,
acme_email,
allow_multiple_certs
) |
def init_storage_dir(storage_dir):
"""
Initialise the storage directory with the certificates directory and a
default wildcard self-signed certificate for HAProxy.
:return: the storage path and certs path
"""
storage_path = FilePath(storage_dir)
# Create the default wildcard certificate if it doesn't already exist
default_cert_path = storage_path.child('default.pem')
if not default_cert_path.exists():
default_cert_path.setContent(generate_wildcard_pem_bytes())
# Create a directory for unmanaged certs. We don't touch this again, but it
# needs to be there and it makes sense to create it at the same time as
# everything else.
unmanaged_certs_path = storage_path.child('unmanaged-certs')
if not unmanaged_certs_path.exists():
unmanaged_certs_path.createDirectory()
# Store certificates in a directory inside the storage directory, so
# HAProxy will read just the certificates there.
certs_path = storage_path.child('certs')
if not certs_path.exists():
certs_path.createDirectory()
return storage_path, certs_path |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.