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/Flask-CKEditor-0.4.6.tar.gz/Flask-CKEditor-0.4.6/flask_ckeditor/static/full/lang/ms.js | /*
Copyright (c) 2003-2020, CKSource - Frederico Knabben. All rights reserved.
For licensing, see LICENSE.md or https://ckeditor.com/license
*/
CKEDITOR.lang['ms']={"editor":"Rich Text Editor","editorPanel":"Rich Text Editor panel","common":{"editorHelp":"Press ALT 0 for help","browseServer":"Browse Server","url":"URL","protocol":"Protokol","upload":"Muat Naik","uploadSubmit":"Hantar ke Server","image":"Gambar","flash":"Flash","form":"Borang","checkbox":"Checkbox","radio":"Butang Radio","textField":"Text Field","textarea":"Textarea","hiddenField":"Field Tersembunyi","button":"Butang","select":"Field Pilihan","imageButton":"Butang Bergambar","notSet":"<tidak di set>","id":"Id","name":"Nama","langDir":"Arah Tulisan","langDirLtr":"Kiri ke Kanan (LTR)","langDirRtl":"Kanan ke Kiri (RTL)","langCode":"Kod Bahasa","longDescr":"Butiran Panjang URL","cssClass":"Kelas-kelas Stylesheet","advisoryTitle":"Tajuk Makluman","cssStyle":"Stail","ok":"OK","cancel":"Batal","close":"Tutup","preview":"Prebiu","resize":"Resize","generalTab":"Umum","advancedTab":"Advanced","validateNumberFailed":"This value is not a number.","confirmNewPage":"Any unsaved changes to this content will be lost. Are you sure you want to load new page?","confirmCancel":"You have changed some options. Are you sure you want to close the dialog window?","options":"Options","target":"Sasaran","targetNew":"New Window (_blank)","targetTop":"Topmost Window (_top)","targetSelf":"Same Window (_self)","targetParent":"Parent Window (_parent)","langDirLTR":"Kiri ke Kanan (LTR)","langDirRTL":"Kanan ke Kiri (RTL)","styles":"Stail","cssClasses":"Kelas-kelas Stylesheet","width":"Lebar","height":"Tinggi","align":"Jajaran","left":"Kiri","right":"Kanan","center":"Tengah","justify":"Jajaran Blok","alignLeft":"Jajaran Kiri","alignRight":"Jajaran Kanan","alignCenter":"Align Center","alignTop":"Atas","alignMiddle":"Pertengahan","alignBottom":"Bawah","alignNone":"None","invalidValue":"Nilai tidak sah.","invalidHeight":"Height must be a number.","invalidWidth":"Width must be a number.","invalidLength":"Value specified for the \"%1\" field must be a positive number with or without a valid measurement unit (%2).","invalidCssLength":"Value specified for the \"%1\" field must be a positive number with or without a valid CSS measurement unit (px, %, in, cm, mm, em, ex, pt, or pc).","invalidHtmlLength":"Value specified for the \"%1\" field must be a positive number with or without a valid HTML measurement unit (px or %).","invalidInlineStyle":"Value specified for the inline style must consist of one or more tuples with the format of \"name : value\", separated by semi-colons.","cssLengthTooltip":"Enter a number for a value in pixels or a number with a valid CSS unit (px, %, in, cm, mm, em, ex, pt, or pc).","unavailable":"%1<span class=\"cke_accessibility\">, unavailable</span>","keyboard":{"8":"Backspace","13":"Enter","16":"Shift","17":"Ctrl","18":"Alt","32":"Space","35":"End","36":"Home","46":"Delete","112":"F1","113":"F2","114":"F3","115":"F4","116":"F5","117":"F6","118":"F7","119":"F8","120":"F9","121":"F10","122":"F11","123":"F12","124":"F13","125":"F14","126":"F15","127":"F16","128":"F17","129":"F18","130":"F19","131":"F20","132":"F21","133":"F22","134":"F23","135":"F24","224":"Command"},"keyboardShortcut":"Keyboard shortcut","optionDefault":"Default"},"about":{"copy":"Copyright © $1. All rights reserved.","dlgTitle":"About CKEditor 4","moreInfo":"For licensing information please visit our web site:"},"basicstyles":{"bold":"Bold","italic":"Italic","strike":"Strike Through","subscript":"Subscript","superscript":"Superscript","underline":"Underline"},"bidi":{"ltr":"Text direction from left to right","rtl":"Text direction from right to left"},"blockquote":{"toolbar":"Block Quote"},"notification":{"closed":"Notification closed."},"toolbar":{"toolbarCollapse":"Collapse Toolbar","toolbarExpand":"Expand Toolbar","toolbarGroups":{"document":"Document","clipboard":"Clipboard/Undo","editing":"Editing","forms":"Forms","basicstyles":"Basic Styles","paragraph":"Paragraph","links":"Links","insert":"Insert","styles":"Styles","colors":"Colors","tools":"Tools"},"toolbars":"Editor toolbars"},"clipboard":{"copy":"Salin","copyError":"Keselamatan perisian browser anda tidak membenarkan operasi salinan text/imej. Sila gunakan papan kekunci (Ctrl/Cmd+C).","cut":"Potong","cutError":"Keselamatan perisian browser anda tidak membenarkan operasi suntingan text/imej. Sila gunakan papan kekunci (Ctrl/Cmd+X).","paste":"Tampal","pasteNotification":"Press %1 to paste. Your browser doesn‘t support pasting with the toolbar button or context menu option.","pasteArea":"Paste Area","pasteMsg":"Paste your content inside the area below and press OK."},"colorbutton":{"auto":"Otomatik","bgColorTitle":"Warna Latarbelakang","colors":{"000":"Black","800000":"Maroon","8B4513":"Saddle Brown","2F4F4F":"Dark Slate Gray","008080":"Teal","000080":"Navy","4B0082":"Indigo","696969":"Dark Gray","B22222":"Fire Brick","A52A2A":"Brown","DAA520":"Golden Rod","006400":"Dark Green","40E0D0":"Turquoise","0000CD":"Medium Blue","800080":"Purple","808080":"Gray","F00":"Red","FF8C00":"Dark Orange","FFD700":"Gold","008000":"Green","0FF":"Cyan","00F":"Blue","EE82EE":"Violet","A9A9A9":"Dim Gray","FFA07A":"Light Salmon","FFA500":"Orange","FFFF00":"Yellow","00FF00":"Lime","AFEEEE":"Pale Turquoise","ADD8E6":"Light Blue","DDA0DD":"Plum","D3D3D3":"Light Grey","FFF0F5":"Lavender Blush","FAEBD7":"Antique White","FFFFE0":"Light Yellow","F0FFF0":"Honeydew","F0FFFF":"Azure","F0F8FF":"Alice Blue","E6E6FA":"Lavender","FFF":"White","1ABC9C":"Strong Cyan","2ECC71":"Emerald","3498DB":"Bright Blue","9B59B6":"Amethyst","4E5F70":"Grayish Blue","F1C40F":"Vivid Yellow","16A085":"Dark Cyan","27AE60":"Dark Emerald","2980B9":"Strong Blue","8E44AD":"Dark Violet","2C3E50":"Desaturated Blue","F39C12":"Orange","E67E22":"Carrot","E74C3C":"Pale Red","ECF0F1":"Bright Silver","95A5A6":"Light Grayish Cyan","DDD":"Light Gray","D35400":"Pumpkin","C0392B":"Strong Red","BDC3C7":"Silver","7F8C8D":"Grayish Cyan","999":"Dark Gray"},"more":"Warna lain-lain...","panelTitle":"Colors","textColorTitle":"Warna Text"},"colordialog":{"clear":"Clear","highlight":"Highlight","options":"Color Options","selected":"Selected Color","title":"Select color"},"templates":{"button":"Templat","emptyListMsg":"(Tiada Templat Disimpan)","insertOption":"Replace actual contents","options":"Template Options","selectPromptMsg":"Sila pilih templat untuk dibuka oleh editor<br>(kandungan sebenar akan hilang):","title":"Templat Kandungan"},"contextmenu":{"options":"Context Menu Options"},"copyformatting":{"label":"Copy Formatting","notification":{"copied":"Formatting copied","applied":"Formatting applied","canceled":"Formatting canceled","failed":"Formatting failed. You cannot apply styles without copying them first."}},"div":{"IdInputLabel":"Id","advisoryTitleInputLabel":"Advisory Title","cssClassInputLabel":"Stylesheet Classes","edit":"Edit Div","inlineStyleInputLabel":"Inline Style","langDirLTRLabel":"Left to Right (LTR)","langDirLabel":"Language Direction","langDirRTLLabel":"Right to Left (RTL)","languageCodeInputLabel":" Language Code","remove":"Remove Div","styleSelectLabel":"Style","title":"Create Div Container","toolbar":"Create Div Container"},"elementspath":{"eleLabel":"Elements path","eleTitle":"%1 element"},"filetools":{"loadError":"Error occurred during file read.","networkError":"Network error occurred during file upload.","httpError404":"HTTP error occurred during file upload (404: File not found).","httpError403":"HTTP error occurred during file upload (403: Forbidden).","httpError":"HTTP error occurred during file upload (error status: %1).","noUrlError":"Upload URL is not defined.","responseError":"Incorrect server response."},"find":{"find":"Cari","findOptions":"Find Options","findWhat":"Perkataan yang dicari:","matchCase":"Padanan case huruf","matchCyclic":"Match cyclic","matchWord":"Padana Keseluruhan perkataan","notFoundMsg":"Text yang dicari tidak dijumpai.","replace":"Ganti","replaceAll":"Ganti semua","replaceSuccessMsg":"%1 occurrence(s) replaced.","replaceWith":"Diganti dengan:","title":"Find and Replace"},"fakeobjects":{"anchor":"Anchor","flash":"Flash Animation","hiddenfield":"Hidden Field","iframe":"IFrame","unknown":"Unknown Object"},"flash":{"access":"Script Access","accessAlways":"Always","accessNever":"Never","accessSameDomain":"Same domain","alignAbsBottom":"Bawah Mutlak","alignAbsMiddle":"Pertengahan Mutlak","alignBaseline":"Garis Dasar","alignTextTop":"Atas Text","bgcolor":"Warna Latarbelakang","chkFull":"Allow Fullscreen","chkLoop":"Loop","chkMenu":"Enable Flash Menu","chkPlay":"Auto Play","flashvars":"Variables for Flash","hSpace":"Ruang Melintang","properties":"Flash Properties","propertiesTab":"Properties","quality":"Quality","qualityAutoHigh":"Auto High","qualityAutoLow":"Auto Low","qualityBest":"Best","qualityHigh":"High","qualityLow":"Low","qualityMedium":"Medium","scale":"Scale","scaleAll":"Show all","scaleFit":"Exact Fit","scaleNoBorder":"No Border","title":"Flash Properties","vSpace":"Ruang Menegak","validateHSpace":"HSpace must be a number.","validateSrc":"Sila taip sambungan URL","validateVSpace":"VSpace must be a number.","windowMode":"Window mode","windowModeOpaque":"Opaque","windowModeTransparent":"Transparent","windowModeWindow":"Window"},"font":{"fontSize":{"label":"Saiz","voiceLabel":"Font Size","panelTitle":"Saiz"},"label":"Font","panelTitle":"Font","voiceLabel":"Font"},"forms":{"button":{"title":"Ciri-ciri Butang","text":"Teks (Nilai)","type":"Jenis","typeBtn":"Button","typeSbm":"Submit","typeRst":"Reset"},"checkboxAndRadio":{"checkboxTitle":"Ciri-ciri Checkbox","radioTitle":"Ciri-ciri Butang Radio","value":"Nilai","selected":"Dipilih","required":"Required"},"form":{"title":"Ciri-ciri Borang","menu":"Ciri-ciri Borang","action":"Tindakan borang","method":"Cara borang dihantar","encoding":"Encoding"},"hidden":{"title":"Ciri-ciri Field Tersembunyi","name":"Nama","value":"Nilai"},"select":{"title":"Ciri-ciri Selection Field","selectInfo":"Select Info","opAvail":"Pilihan sediada","value":"Nilai","size":"Saiz","lines":"garisan","chkMulti":"Benarkan pilihan pelbagai","required":"Required","opText":"Teks","opValue":"Nilai","btnAdd":"Tambah Pilihan","btnModify":"Ubah Pilihan","btnUp":"Naik ke atas","btnDown":"Turun ke bawah","btnSetValue":"Set sebagai nilai terpilih","btnDelete":"Padam"},"textarea":{"title":"Ciri-ciri Textarea","cols":"Lajur","rows":"Baris"},"textfield":{"title":"Ciri-ciri Text Field","name":"Nama","value":"Nilai","charWidth":"Lebar isian","maxChars":"Isian Maksimum","required":"Required","type":"Jenis","typeText":"Teks","typePass":"Kata Laluan","typeEmail":"Email","typeSearch":"Search","typeTel":"Telephone Number","typeUrl":"URL"}},"format":{"label":"Format","panelTitle":"Format","tag_address":"Alamat","tag_div":"Perenggan (DIV)","tag_h1":"Heading 1","tag_h2":"Heading 2","tag_h3":"Heading 3","tag_h4":"Heading 4","tag_h5":"Heading 5","tag_h6":"Heading 6","tag_p":"Normal","tag_pre":"Telah Diformat"},"horizontalrule":{"toolbar":"Masukkan Garisan Membujur"},"iframe":{"border":"Show frame border","noUrl":"Please type the iframe URL","scrolling":"Enable scrollbars","title":"IFrame Properties","toolbar":"IFrame"},"image":{"alt":"Text Alternatif","border":"Border","btnUpload":"Hantar ke Server","button2Img":"Do you want to transform the selected image button on a simple image?","hSpace":"Ruang Melintang","img2Button":"Do you want to transform the selected image on a image button?","infoTab":"Info Imej","linkTab":"Sambungan","lockRatio":"Tetapkan Nisbah","menu":"Ciri-ciri Imej","resetSize":"Saiz Set Semula","title":"Ciri-ciri Imej","titleButton":"Ciri-ciri Butang Bergambar","upload":"Muat Naik","urlMissing":"Image source URL is missing.","vSpace":"Ruang Menegak","validateBorder":"Border must be a whole number.","validateHSpace":"HSpace must be a whole number.","validateVSpace":"VSpace must be a whole number."},"indent":{"indent":"Tambahkan Inden","outdent":"Kurangkan Inden"},"smiley":{"options":"Smiley Options","title":"Masukkan Smiley","toolbar":"Smiley"},"language":{"button":"Set language","remove":"Remove language"},"link":{"acccessKey":"Kunci Akses","advanced":"Advanced","advisoryContentType":"Jenis Kandungan Makluman","advisoryTitle":"Tajuk Makluman","anchor":{"toolbar":"Masukkan/Sunting Pautan","menu":"Ciri-ciri Pautan","title":"Ciri-ciri Pautan","name":"Nama Pautan","errorName":"Sila taip nama pautan","remove":"Remove Anchor"},"anchorId":"dengan menggunakan ID elemen","anchorName":"dengan menggunakan nama pautan","charset":"Linked Resource Charset","cssClasses":"Kelas-kelas Stylesheet","download":"Force Download","displayText":"Display Text","emailAddress":"Alamat E-Mail","emailBody":"Isi Kandungan Mesej","emailSubject":"Subjek Mesej","id":"Id","info":"Butiran Sambungan","langCode":"Arah Tulisan","langDir":"Arah Tulisan","langDirLTR":"Kiri ke Kanan (LTR)","langDirRTL":"Kanan ke Kiri (RTL)","menu":"Sunting Sambungan","name":"Nama","noAnchors":"(Tiada pautan terdapat dalam dokumen ini)","noEmail":"Sila taip alamat e-mail","noUrl":"Sila taip sambungan URL","noTel":"Please type the phone number","other":"<lain>","phoneNumber":"Phone number","popupDependent":"Bergantungan (Netscape)","popupFeatures":"Ciri Tetingkap Popup","popupFullScreen":"Skrin Penuh (IE)","popupLeft":"Posisi Kiri","popupLocationBar":"Bar Lokasi","popupMenuBar":"Bar Menu","popupResizable":"Resizable","popupScrollBars":"Bar-bar skrol","popupStatusBar":"Bar Status","popupToolbar":"Toolbar","popupTop":"Posisi Atas","rel":"Relationship","selectAnchor":"Sila pilih pautan","styles":"Stail","tabIndex":"Indeks Tab ","target":"Sasaran","targetFrame":"<bingkai>","targetFrameName":"Nama Bingkai Sasaran","targetPopup":"<tetingkap popup>","targetPopupName":"Nama Tetingkap Popup","title":"Sambungan","toAnchor":"Pautan dalam muka surat ini","toEmail":"E-Mail","toUrl":"URL","toPhone":"Phone","toolbar":"Masukkan/Sunting Sambungan","type":"Jenis Sambungan","unlink":"Buang Sambungan","upload":"Muat Naik"},"list":{"bulletedlist":"Senarai tidak bernombor","numberedlist":"Senarai bernombor"},"liststyle":{"bulletedTitle":"Bulleted List Properties","circle":"Circle","decimal":"Decimal (1, 2, 3, etc.)","disc":"Disc","lowerAlpha":"Lower Alpha (a, b, c, d, e, etc.)","lowerRoman":"Lower Roman (i, ii, iii, iv, v, etc.)","none":"None","notset":"<not set>","numberedTitle":"Numbered List Properties","square":"Square","start":"Start","type":"Type","upperAlpha":"Upper Alpha (A, B, C, D, E, etc.)","upperRoman":"Upper Roman (I, II, III, IV, V, etc.)","validateStartNumber":"List start number must be a whole number."},"magicline":{"title":"Insert paragraph here"},"maximize":{"maximize":"Maximize","minimize":"Minimize"},"newpage":{"toolbar":"Helaian Baru"},"pagebreak":{"alt":"Page Break","toolbar":"Insert Page Break for Printing"},"pastetext":{"button":"Tampal sebagai text biasa","pasteNotification":"Press %1 to paste. Your browser doesn‘t support pasting with the toolbar button or context menu option.","title":"Tampal sebagai text biasa"},"pastefromword":{"confirmCleanup":"The text you want to paste seems to be copied from Word. Do you want to clean it before pasting?","error":"It was not possible to clean up the pasted data due to an internal error","title":"Tampal dari Word","toolbar":"Tampal dari Word"},"preview":{"preview":"Prebiu"},"print":{"toolbar":"Cetak"},"removeformat":{"toolbar":"Buang Format"},"save":{"toolbar":"Simpan"},"selectall":{"toolbar":"Pilih Semua"},"showblocks":{"toolbar":"Show Blocks"},"sourcearea":{"toolbar":"Sumber"},"specialchar":{"options":"Special Character Options","title":"Sila pilih huruf istimewa","toolbar":"Masukkan Huruf Istimewa"},"scayt":{"btn_about":"About SCAYT","btn_dictionaries":"Dictionaries","btn_disable":"Disable SCAYT","btn_enable":"Enable SCAYT","btn_langs":"Languages","btn_options":"Options","text_title":"Spell Check As You Type"},"stylescombo":{"label":"Stail","panelTitle":"Formatting Styles","panelTitle1":"Block Styles","panelTitle2":"Inline Styles","panelTitle3":"Object Styles"},"table":{"border":"Saiz Border","caption":"Keterangan","cell":{"menu":"Cell","insertBefore":"Insert Cell Before","insertAfter":"Insert Cell After","deleteCell":"Buangkan Sel-sel","merge":"Cantumkan Sel-sel","mergeRight":"Merge Right","mergeDown":"Merge Down","splitHorizontal":"Split Cell Horizontally","splitVertical":"Split Cell Vertically","title":"Cell Properties","cellType":"Cell Type","rowSpan":"Rows Span","colSpan":"Columns Span","wordWrap":"Word Wrap","hAlign":"Horizontal Alignment","vAlign":"Vertical Alignment","alignBaseline":"Baseline","bgColor":"Background Color","borderColor":"Border Color","data":"Data","header":"Header","yes":"Yes","no":"No","invalidWidth":"Cell width must be a number.","invalidHeight":"Cell height must be a number.","invalidRowSpan":"Rows span must be a whole number.","invalidColSpan":"Columns span must be a whole number.","chooseColor":"Choose"},"cellPad":"Tambahan Ruang Sel","cellSpace":"Ruangan Antara Sel","column":{"menu":"Column","insertBefore":"Insert Column Before","insertAfter":"Insert Column After","deleteColumn":"Buangkan Lajur"},"columns":"Jaluran","deleteTable":"Delete Table","headers":"Headers","headersBoth":"Both","headersColumn":"First column","headersNone":"None","headersRow":"First Row","heightUnit":"height unit","invalidBorder":"Border size must be a number.","invalidCellPadding":"Cell padding must be a positive number.","invalidCellSpacing":"Cell spacing must be a positive number.","invalidCols":"Number of columns must be a number greater than 0.","invalidHeight":"Table height must be a number.","invalidRows":"Number of rows must be a number greater than 0.","invalidWidth":"Table width must be a number.","menu":"Ciri-ciri Jadual","row":{"menu":"Row","insertBefore":"Insert Row Before","insertAfter":"Insert Row After","deleteRow":"Buangkan Baris"},"rows":"Barisan","summary":"Summary","title":"Ciri-ciri Jadual","toolbar":"Jadual","widthPc":"peratus","widthPx":"piksel-piksel","widthUnit":"width unit"},"undo":{"redo":"Ulangkan","undo":"Batalkan"},"widget":{"move":"Click and drag to move","label":"%1 widget"},"uploadwidget":{"abort":"Upload aborted by the user.","doneOne":"File successfully uploaded.","doneMany":"Successfully uploaded %1 files.","uploadOne":"Uploading file ({percentage}%)...","uploadMany":"Uploading files, {current} of {max} done ({percentage}%)..."},"wsc":{"btnIgnore":"Biar","btnIgnoreAll":"Biarkan semua","btnReplace":"Ganti","btnReplaceAll":"Gantikan Semua","btnUndo":"Batalkan","changeTo":"Tukarkan kepada","errorLoading":"Error loading application service host: %s.","ieSpellDownload":"Pemeriksa ejaan tidak dipasang. Adakah anda mahu muat turun sekarang?","manyChanges":"Pemeriksaan ejaan siap: %1 perkataan diubah","noChanges":"Pemeriksaan ejaan siap: Tiada perkataan diubah","noMispell":"Pemeriksaan ejaan siap: Tiada salah ejaan","noSuggestions":"- Tiada cadangan -","notAvailable":"Sorry, but service is unavailable now.","notInDic":"Tidak terdapat didalam kamus","oneChange":"Pemeriksaan ejaan siap: Satu perkataan telah diubah","progress":"Pemeriksaan ejaan sedang diproses...","title":"Spell Checker","toolbar":"Semak Ejaan"}}; | PypiClean |
/K_AIKO-0.5.2-py3-none-any.whl/kaiko/tui/inputs.py | import functools
import contextlib
import re
import queue
import threading
from typing import Optional, List, Tuple, Dict, Callable
from pathlib import Path
import dataclasses
from ..utils import datanodes as dn
from ..utils import commands as cmd
from ..utils import config as cfg
from ..utils import markups as mu
from ..devices import engines
from . import sheditors
from .textboxes import Caret, TextBox, TextBoxWidgetSettings
# hint
class Hint:
pass
@dataclasses.dataclass(frozen=True)
class DescHint(Hint):
message: str
@dataclasses.dataclass(frozen=True)
class InfoHint(Hint):
message: str
@dataclasses.dataclass
class HintState:
hint: Hint
index: Optional[int]
tokens: Optional[List[str]]
class HintManager:
def __init__(self, editor, preview_handler):
self.editor = editor
self.preview_handler = preview_handler
self.popup_queue = queue.Queue()
self.hint_state = None
def get_hint(self):
return None if self.hint_state is None else self.hint_state.hint
def get_hint_location(self):
return None if self.hint_state is None else self.hint_state.index
def add_popup(self, hint):
self.popup_queue.put(hint)
def popup_hint(self):
hint = self.hint_state.hint
if not hint.message:
return False
self.add_popup(hint)
return True
def set_hint(self, hint, index=None):
if isinstance(hint, DescHint):
msg_tokens = (
[token.string for token in self.editor.tokens[:index]]
if index is not None
else None
)
elif isinstance(hint, InfoHint):
msg_tokens = (
[token.string for token in self.editor.tokens[: index + 1]]
if index is not None
else None
)
else:
assert False
self.hint_state = HintState(hint=hint, index=index, tokens=msg_tokens)
self.update_preview()
return True
def cancel_hint(self):
if self.hint_state is None:
return False
self.hint_state = None
self.update_preview()
return True
def update_hint(self):
if self.hint_state is None:
return False
if self.hint_state.tokens is None:
return self.cancel_hint()
if self.hint_state.index is not None and self.hint_state.index >= len(
self.editor.tokens
):
return self.cancel_hint()
if len(self.hint_state.tokens) > len(self.editor.tokens):
return self.cancel_hint()
for token_string, token in zip(self.hint_state.tokens, self.editor.tokens):
if token_string != token.string:
return self.cancel_hint()
if (
isinstance(self.hint_state.hint, DescHint)
and self.editor.tokens[len(self.hint_state.tokens) - 1].type is not None
):
return self.cancel_hint()
return False
def update_preview(self):
if self.hint_state is None:
self.preview_handler(None)
elif not isinstance(self.hint_state.hint, InfoHint):
self.preview_handler(None)
elif self.hint_state.tokens is None:
self.preview_handler(None)
elif len(self.hint_state.tokens) != 2:
self.preview_handler(None)
elif self.hint_state.tokens[0] != "play":
self.preview_handler(None)
else:
self.preview_handler(self.hint_state.tokens[1])
def ask_for_hint(self, index, type="all"):
if index not in range(len(self.editor.tokens)):
return False
target_type = self.editor.tokens[index].type
if target_type is None:
if type not in ("all", "desc"):
self.cancel_hint()
return False
msg = self.editor.desc(index)
if msg is None:
self.cancel_hint()
return False
hint = DescHint(msg)
self.set_hint(hint, index)
return True
else:
if type not in ("all", "info"):
self.cancel_hint()
return False
msg = self.editor.info(index + 1)
if msg is None:
self.cancel_hint()
return False
hint = InfoHint(msg)
self.set_hint(hint, index)
return True
# autocomplete
@dataclasses.dataclass
class TabState:
suggestions: List[str]
sugg_index: int
token_index: int
original_token: List[str]
original_pos: int
selection: slice
class AutocompleteManager:
def __init__(self, editor):
self.editor = editor
self.tab_state = None
def get_suggestions_list(self):
if self.tab_state is None:
return None
else:
return self.tab_state.suggestions
def get_suggestions_index(self):
if self.tab_state is None:
return None
else:
return self.tab_state.sugg_index
def is_in_cycle(self):
return self.tab_state is not None
def prepare_tab_state(self, action=+1):
# find the token to autocomplete
index, token = self.editor.find_token_before(self.editor.pos)
if token is None:
token_index = 0
target = ""
selection = slice(self.editor.pos, self.editor.pos)
elif token.mask.stop < self.editor.pos:
token_index = index + 1
target = ""
selection = slice(self.editor.pos, self.editor.pos)
else:
token_index = index
target = token.string
selection = token.mask
# generate suggestions
suggestions = [
sheditors.quoting(sugg) for sugg in self.editor.suggest(token_index, target)
]
sugg_index = len(suggestions) if action == -1 else -1
# tab state
original_pos = self.editor.pos
original_token = self.editor.buffer[selection]
return TabState(
suggestions=suggestions,
sugg_index=sugg_index,
token_index=token_index,
original_token=original_token,
original_pos=original_pos,
selection=selection,
)
def autocomplete(self, action=+1):
if self.tab_state is None:
tab_state = self.prepare_tab_state(action)
if len(tab_state.suggestions) == 0:
# no suggestion
return None
if len(tab_state.suggestions) == 1:
# one suggestion -> complete directly
self.editor.replace(tab_state.selection, tab_state.suggestions[0])
return tab_state.token_index
self.tab_state = tab_state
if action == +1:
self.tab_state.sugg_index += 1
elif action == -1:
self.tab_state.sugg_index -= 1
else:
raise ValueError(f"invalid action: {action}")
if self.tab_state.sugg_index not in range(len(self.tab_state.suggestions)):
self.cancel_autocomplete()
return None
# fill in selected token
self.tab_state.selection = self.editor.replace(
self.tab_state.selection,
self.tab_state.suggestions[self.tab_state.sugg_index],
)
return self.tab_state.token_index
def cancel_autocomplete(self):
if self.tab_state is None:
return
self.editor.replace(self.tab_state.selection, self.tab_state.original_token)
self.editor.move_to(self.tab_state.original_pos)
self.tab_state = None
def finish_autocomplete(self):
if self.tab_state is None:
return None
index = self.tab_state.token_index
self.tab_state = None
return index
# input
class Result:
pass
@dataclasses.dataclass(frozen=True)
class EmptyResult(Result):
pass
@dataclasses.dataclass(frozen=True)
class ErrorResult(Result):
command_str: str
index: Optional[int]
error: Exception
@dataclasses.dataclass(frozen=True)
class CompleteResult(Result):
command_group: str
command_str: str
command: Callable
class ShellSyntaxError(Exception):
pass
class HistoryManager:
r"""
Fields
------
history_path : Path
latest_command : tuple of str and str, optional
lastest group and command.
buffers : list of list of str
The buffers of editor.
buffer_index : int
The index of current buffer.
"""
TRIM_LEN = 10
PATTERN = re.compile(r"\[(\w+)\] (.+)")
def __init__(self, history_path, latest_command=None):
self.history_path = history_path
self.latest_command = latest_command
self.buffers = [[]]
self.buffer_index = -1
@property
def buffer(self):
return self.buffers[self.buffer_index]
def prev(self):
if self.buffer_index == -len(self.buffers):
return False
self.buffer_index -= 1
return True
def next(self):
if self.buffer_index == -1:
return False
self.buffer_index += 1
return True
def write_history(self, command_group, command):
self.history_path.touch()
command = command.strip()
if (
command
and command_group
and (command_group, command) != self.latest_command
):
open(self.history_path, "a").write(f"\n[{command_group}] {command}")
self.latest_command = (command_group, command)
def read_history(self, command_groups, read_size):
buffers = []
self.history_path.touch()
self.latest_command = None
for command in open(self.history_path):
command = command.strip()
match = self.PATTERN.fullmatch(command)
if match:
self.latest_command = (match.group(1), match.group(2))
if match.group(1) in command_groups and (
not buffers or buffers[-1] != match.group(2)
):
buffers.append(match.group(2))
if len(buffers) - read_size > self.TRIM_LEN:
del buffers[: self.TRIM_LEN]
self.buffers = [list(command) for command in buffers[-read_size:]]
self.buffers.append([])
self.buffer_index = -1
class InputSettings(cfg.Configurable):
r"""
Fields
------
preview_song : bool
Whether to preview the song when selected.
history_size : int
The maximum history size.
"""
preview_song: bool = True
history_size: int = 500
@cfg.subconfig
class control(cfg.Configurable):
r"""
Fields
------
confirm_key : str
The key for confirming input.
help_key : str
The key for help.
autocomplete_keys : tuple of str and str and str
The keys for finding the next, previous and canceling suggestions.
keymap : dict from str to str
The keymap of input. The key of dict is the keystroke, and the
value of dict is the action to activate. The format of action is
just like a normal python code: `input.insert_typeahead() or
input.move_right()`. The syntax is::
<function> ::= "input." /(?!_)\w+/ "()"
<operator> ::= " | " | " & " | " and " | " or "
<action> ::= (<function> <operator>)* <function>
"""
confirm_key: str = "Enter"
help_key: str = "Alt_Enter"
autocomplete_keys: Tuple[str, str, str] = ("Tab", "Shift_Tab", "Esc")
keymap: Dict[str, str] = {
"Backspace": "input.backspace()",
"Delete": "input.delete()",
"Left": "input.move_left()",
"Right": "input.insert_typeahead() or input.move_right()",
"Up": "input.prev()",
"Down": "input.next()",
"Home": "input.move_to_start()",
"End": "input.move_to_end()",
"Ctrl_Left": "input.move_to_word_start()",
"Ctrl_Right": "input.move_to_word_end()",
"Ctrl_Backspace": "input.delete_to_word_start()",
"Ctrl_Delete": "input.delete_to_word_end()",
"Alt_Left": "input.move_to_token_start()",
"Alt_Right": "input.move_to_token_end()",
"Alt_Backspace": "input.delete_backward_token()",
"Alt_Delete": "input.delete_forward_token()",
"Esc": "input.cancel_typeahead() | input.cancel_hint()",
"'\\x04'": "input.delete() or input.exit_if_empty()",
}
@cfg.subconfig
class hint(cfg.Configurable):
r"""
Fields
------
typeahead : str
The markup template for the type-ahead.
highlight : str
The markup template for the highlighted token.
desc_message : str
The markup template for the desc message.
info_message : str
The markup template for the info message.
message_max_lines : int
The maximum number of lines of the message.
message_overflow_ellipsis : str
Texts to display when overflowing.
suggestions_lines : int
The maximum number of lines of the suggestions.
suggestion_items : tuple of str and str
The markup templates for the unselected/selected suggestion.
suggestion_overflow_ellipses : tuple of str and str
Texts to display when overflowing top/bottom.
"""
typeahead: str = "[weight=dim][slot/][/]"
highlight: str = "[underline][slot/][/]"
desc_message: str = "[weight=dim][slot/][/]"
info_message: str = f"{'─'*80}\n[slot/]\n{'─'*80}"
message_max_lines: int = 16
message_overflow_ellipsis: str = "[weight=dim]…[/]"
suggestions_lines: int = 8
suggestion_items: Tuple[str, str] = ("• [slot/]", "• [invert][slot/][/]")
suggestion_overflow_ellipses: Tuple[str, str] = (
"[weight=dim]ⵗ [slot/][/]",
"[weight=dim]ⵗ [slot/][/]",
)
@cfg.subconfig
class textbox(cfg.Configurable, TextBoxWidgetSettings):
__doc__ = TextBoxWidgetSettings.__doc__
def __init__(self):
pass
class ContextDispatcher:
def __init__(self):
self.lock = threading.RLock()
self.isin = False
self.before_callbacks = []
self.after_callbacks = []
self.onerror_callbacks = []
def before(self, callback):
with self.lock:
self.before_callbacks.append(callback)
def after(self, callback):
with self.lock:
self.after_callbacks.append(callback)
def onerror(self, callback):
with self.lock:
self.onerror_callbacks.append(callback)
@contextlib.contextmanager
def on(self):
with self.lock:
isin = self.isin
if isin:
for callback in self.before_callbacks:
callback()
self.isin = False
try:
yield
except:
self.isin = isin
if isin:
for callback in self.onerror_callbacks:
callback()
raise
finally:
self.isin = isin
if isin:
for callback in self.after_callbacks:
callback()
def onstate(*states):
def onstate_dec(func):
@functools.wraps(func)
def onstate_func(self, *args, **kwargs):
if self.state not in states:
return False
return func(self, *args, **kwargs)
return onstate_func
return onstate_dec
def locked(func):
@functools.wraps(func)
def locked_func(self, *args, **kwargs):
with self.edit_ctxt.on():
return func(self, *args, **kwargs)
return locked_func
class Input:
r"""Input editor.
Attributes
----------
settings : InputSettings
The input settings.
history : HistoryManager
The input history manager.
editor : sheditors.Editor
The editor of command.
typeahead : str
The type ahead of input.
hint_manager : HintManager
autocomplete_manager : AutocompleteManager
result : Result or None
The result of input.
state : str
The input state.
buffer_modified_counter : int
The event counter for modifying buffer.
key_pressed_counter : int
The event counter for key pressing.
"""
def __init__(
self,
preview_handler,
history_path,
settings,
):
r"""Constructor.
Parameters
----------
preview_handler : function
history_path : Path
The path of command history.
settings : InputSettings
The settings of input.
"""
self.settings = settings
self.history = HistoryManager(history_path)
self.editor = sheditors.Editor(None, self.history.buffer)
self.typeahead = ""
self.hint_manager = HintManager(
self.editor,
lambda song: preview_handler(song) if self.settings.preview_song else None,
)
self.autocomplete_manager = AutocompleteManager(self.editor)
self.state = "FIN"
self.result = None
self.edit_ctxt = ContextDispatcher()
self.key_pressed_counter = 0
self.buffer_modified_counter = 0
def _set_settings(self, settings):
self.settings = settings
def _register(self, fin_event, provider):
rich = provider.get(mu.RichParser)
renderer = provider.get(engines.Renderer)
controller = provider.get(engines.Controller)
stroke = InputStroke(self, self.settings.control)
stroke.register(controller)
state = InputView(self)
text_renderer = TextRenderer(rich, self.settings.hint)
msg_renderer = MsgRenderer(rich, self.settings.hint)
renderer.add_drawer(state.load(fin_event), zindex=())
renderer.add_drawer(msg_renderer.render_msg(state), zindex=(1,))
textbox = TextBox(
text_renderer.render_text(state),
self.settings.textbox,
).load(provider)
return textbox
def _record_command(self):
command = "".join(self.editor.buffer).strip()
self.history.write_history(self.editor.group, command)
@locked
@onstate("EDIT")
def _finish_session(self, res):
r"""Finish this session of input.
Parameters
----------
res : Result
The result.
"""
self.result = res
self.state = "FIN"
@locked
@onstate("FIN")
def _new_session(self, command_parser, clear=True):
r"""Start a new session of input.
Parameters
----------
command_parser : cmd.CommandParser
clear : bool, optional
"""
self.editor.update_parser(command_parser)
if clear:
groups = self.editor.get_all_groups()
history_size = self.settings.history_size
self.history.read_history(groups, history_size)
self.editor.init(self.history.buffer)
self.update_buffer(clear=True)
self.start()
@locked
@onstate("FIN")
def start(self):
"""Start a session of input.
Returns
-------
succ : bool
"""
self.result = None
self.state = "EDIT"
return True
@locked
@onstate("EDIT")
def prev(self):
"""Previous buffer.
Returns
-------
succ : bool
"""
succ = self.history.prev()
if not succ:
return False
self.editor.init(self.history.buffer)
self.update_buffer(clear=True)
return True
@locked
@onstate("EDIT")
def next(self):
"""Next buffer.
Returns
-------
succ : bool
"""
succ = self.history.next()
if not succ:
return False
self.editor.init(self.history.buffer)
self.update_buffer(clear=True)
return True
@locked
def show_typeahead(self):
"""Make typeahead.
Show the possible command you want to type. Only work if the caret is
at the end of buffer.
Returns
-------
succ : bool
`False` if unable to complete or the caret is not at the end of
buffer.
"""
if self.editor.pos != len(self.editor.buffer):
self.typeahead = ""
return False
# search history
pos = self.editor.pos
for buffer in reversed(self.history.buffers):
if len(buffer) > pos and buffer[:pos] == self.editor.buffer:
self.typeahead = "".join(buffer[pos:])
return True
self.typeahead = ""
return False
@locked
def cancel_typeahead(self):
"""Cancel typeahead.
Returns
-------
succ : bool
"""
self.typeahead = ""
return True
@locked
@onstate("EDIT")
def insert_typeahead(self):
"""Insert typeahead.
Insert the typeahead if the caret is at the end of buffer.
Returns
-------
succ : bool
`False` if there is no typeahead or the caret is not at the end of
buffer.
"""
if self.typeahead == "" or self.editor.pos != len(self.editor.buffer):
return False
self.editor.insert(self.typeahead)
self.update_buffer()
self.ask_for_hint()
return True
@locked
def add_popup(self, msg):
"""Add popup.
Show hint above the prompt.
Parameters
----------
msg : str
The message of hint.
Returns
-------
succ : bool
"""
self.hint_manager.add_popup(DescHint(msg))
return True
@locked
def set_hint(self, msg, index=None):
"""Set hint.
Show hint below the prompt.
Parameters
----------
msg : str
The message of hint.
index : int or None
Index of the token to which the hint is directed, or `None` for
nothing.
Returns
-------
succ : bool
"""
return self.hint_manager.set_hint(DescHint(msg), index=index)
@locked
def cancel_hint(self):
"""Cancel hint.
Remove the hint below the prompt.
Returns
-------
succ : bool
"""
return self.hint_manager.cancel_hint()
@locked
def update_hint(self):
"""Update hint.
Remove hint if the target is updated.
Returns
-------
succ : bool
`False` if there is no hint or the hint isn't removed.
"""
return self.hint_manager.update_hint()
@locked
@onstate("EDIT")
def ask_for_hint(self, index=None, type="all"):
"""Ask some hint for command.
Provide some hint for the command on the caret.
Parameters
----------
index : int, optional
type : one of "info", "desc", "all", optional
The type of hint to ask.
Returns
-------
succ : bool
"""
if index is None:
index, token = self.editor.find_token_before(self.editor.pos)
return self.hint_manager.ask_for_hint(index, type=type)
@locked
def update_buffer(self, clear=False):
"""Update buffer.
Parameters
----------
clear : bool, optional
Returns
-------
succ : bool
"""
self.editor.parse()
self.buffer_modified_counter += 1
self.cancel_typeahead()
if clear:
self.cancel_hint()
else:
self.update_hint()
return True
@locked
@onstate("EDIT")
def insert(self, text):
"""Input.
Insert some text into the buffer.
Parameters
----------
text : str
The text to insert. It shouldn't contain any nongraphic character,
except for prefix `\\b` which indicate deleting.
Returns
-------
succ : bool
`False` if buffer isn't changed.
"""
succ = self.editor.insert(text)
if not succ:
return False
self.update_buffer()
self.show_typeahead()
self.ask_for_hint()
return True
@locked
@onstate("EDIT")
def backspace(self):
"""Backspace.
Delete one character before the caret if exists.
Returns
-------
succ : bool
"""
succ = self.editor.backspace()
if not succ:
return False
self.update_buffer()
self.ask_for_hint()
return True
@locked
@onstate("EDIT")
def delete(self):
"""Delete.
Delete one character after the caret if exists.
Returns
-------
succ : bool
"""
succ = self.editor.delete()
if not succ:
return False
self.update_buffer()
self.ask_for_hint()
return True
@locked
@onstate("EDIT")
def delete_all(self):
"""Delete All.
Returns
-------
succ : bool
"""
succ = self.editor.delete_all()
if not succ:
return False
self.update_buffer()
self.ask_for_hint()
return True
@locked
@onstate("EDIT")
def delete_range(self, start, end):
"""Delete range.
Parameters
----------
start : int or None
end : int or None
Returns
-------
succ : bool
"""
self.editor.replace(slice(start, end), "")
self.update_buffer()
self.ask_for_hint()
return True
@locked
@onstate("EDIT")
def delete_to_word_start(self):
"""Delete to the word start.
The word is defined as `\\w+|\\W+`.
Returns
-------
succ : bool
"""
mask = self.editor.to_word_start()
return self.delete_range(mask.start, mask.stop)
@locked
@onstate("EDIT")
def delete_to_word_end(self):
"""Delete to the word end.
The word is defined as `\\w+|\\W+`.
Returns
-------
succ : bool
"""
mask = self.editor.to_word_end()
return self.delete_range(mask.start, mask.stop)
@locked
@onstate("EDIT")
def delete_token(self, index):
"""Delete current token.
Parameters
----------
index : int
Returns
-------
succ : bool
"""
token = self.editor.tokens[index]
return self.delete_range(token.mask.start, token.mask.stop)
@locked
@onstate("EDIT")
def delete_backward_token(self):
"""Delete backward token.
Returns
-------
succ : bool
"""
_, token = self.editor.find_token_before(self.editor.pos)
if token is None:
return self.delete_range(0, self.editor.pos)
else:
return self.delete_range(
token.mask.start, max(self.editor.pos, token.mask.stop)
)
@locked
@onstate("EDIT")
def delete_forward_token(self):
"""Delete forward token.
Returns
-------
succ : bool
"""
_, token = self.editor.find_token_after(self.editor.pos)
if token is None:
return self.delete_range(self.editor.pos, None)
else:
return self.delete_range(
min(self.editor.pos, token.mask.start), token.mask.stop
)
@locked
@onstate("EDIT")
def move_to(self, pos):
"""Move caret to the specific position.
Regardless of success or failure, typeahead will be cancelled.
Parameters
----------
pos : int or None
Index of buffer, which will be clamped to 0 and length of buffer, or
`None` for the end of buffer.
Returns
-------
succ : bool
"""
succ = self.editor.move_to(pos)
self.cancel_typeahead()
return succ
@locked
@onstate("EDIT")
def move(self, offset):
"""Move caret.
Parameters
----------
offset : int
Returns
-------
succ : bool
"""
return self.move_to(self.editor.pos + offset)
@locked
@onstate("EDIT")
def move_left(self):
"""Move caret one character to the left.
Returns
-------
succ : bool
"""
return self.move(-1)
@locked
@onstate("EDIT")
def move_right(self):
"""Move caret one character to the right.
Returns
-------
succ : bool
"""
return self.move(+1)
@locked
@onstate("EDIT")
def move_to_start(self):
"""Move caret to the start of buffer.
Returns
-------
succ : bool
"""
return self.move_to(0)
@locked
@onstate("EDIT")
def move_to_end(self):
"""Move caret to the end of buffer.
Returns
-------
succ : bool
"""
return self.move_to(None)
@locked
@onstate("EDIT")
def move_to_word_start(self):
"""Move caret to the start of the word.
Returns
-------
succ : bool
"""
mask = self.editor.to_word_start()
return self.move_to(mask.start)
@locked
@onstate("EDIT")
def move_to_word_end(self):
"""Move caret to the end of the word.
Returns
-------
succ : bool
"""
mask = self.editor.to_word_end()
return self.move_to(mask.stop)
@locked
@onstate("EDIT")
def move_to_token_start(self):
"""Move caret to the start of the token.
Returns
-------
succ : bool
"""
_, token = self.editor.find_token_before(self.editor.pos)
if token is None:
return self.move_to(0)
else:
return self.move_to(token.mask.start)
@locked
@onstate("EDIT")
def move_to_token_end(self):
"""Move caret to the end of the word.
Returns
-------
succ : bool
"""
_, token = self.editor.find_token_after(self.editor.pos)
if token is None:
return self.move_to(None)
else:
return self.move_to(token.mask.stop)
@locked
@onstate("EDIT")
def help(self):
"""Help for command.
Print some hint for the command before the caret.
Returns
-------
succ : bool
"""
# find the token before the caret
index, token = self.editor.find_token_before(self.editor.pos)
if token is None:
return False
if self.hint_manager.get_hint_location() != index:
self.ask_for_hint(index)
return False
return self.hint_manager.popup_hint()
@locked
@onstate("EDIT")
def confirm(self):
"""Finish the command.
Returns
-------
succ : bool
`False` if the command is wrong.
"""
self.cancel_hint()
if not self.editor.tokens:
self._finish_session(EmptyResult())
return True
command_str = "".join(self.editor.buffer).strip()
if self.editor.lex_state == sheditors.SHLEXER_STATE.BACKSLASHED:
res, index = (
ShellSyntaxError("No escaped character"),
len(self.editor.tokens) - 1,
)
elif self.editor.lex_state == sheditors.SHLEXER_STATE.QUOTED:
res, index = (
ShellSyntaxError("No closing quotation"),
len(self.editor.tokens) - 1,
)
else:
res, index = self.editor.result, self.editor.length
if isinstance(res, cmd.CommandUnfinishError):
self._finish_session(ErrorResult(command_str, None, res))
return False
elif isinstance(res, (cmd.CommandParseError, ShellSyntaxError)):
self._finish_session(ErrorResult(command_str, index, res))
return False
else:
self._finish_session(
CompleteResult(str(self.editor.group), command_str, res)
)
return True
@locked
@onstate("EDIT")
def exit_if_empty(self):
"""Finish the command.
Returns
-------
succ : bool
`False` if unfinished or the command is wrong.
"""
if self.editor.buffer:
return False
self.insert("bye")
return self.confirm()
@locked
@onstate("EDIT")
def forward_autocomplete(self):
"""Autocomplete forwardly.
Complete the token on the caret, or fill in suggestions if caret is
located in between.
Returns
-------
succ : bool
`True` if is in autocompletion cycle. Note that it will be `False`
for no suggestion or one suggestion case.
"""
index = self.autocomplete_manager.autocomplete(action=+1)
is_in_cycle = self.autocomplete_manager.is_in_cycle()
self.update_buffer(clear=True)
if index is not None:
self.ask_for_hint(index, type="info")
return is_in_cycle
@locked
@onstate("EDIT")
def backward_autocomplete(self):
"""Autocomplete backwardly.
Complete the token on the caret backwardly, or fill in suggestions if
caret is located in between.
Returns
-------
succ : bool
`True` if is in autocompletion cycle. Note that it will be `False`
for no suggestion or one suggestion case.
"""
index = self.autocomplete_manager.autocomplete(action=-1)
is_in_cycle = self.autocomplete_manager.is_in_cycle()
self.update_buffer(clear=True)
if index is not None:
self.ask_for_hint(index, type="info")
return is_in_cycle
@locked
@onstate("EDIT")
def finish_autocomplete(self):
r"""Finish autocompletion.
Returns
-------
succ : bool
"""
index = self.autocomplete_manager.finish_autocomplete()
if index is not None:
self.ask_for_hint(index, type="info")
return True
@locked
@onstate("EDIT")
def cancel_autocomplete(self):
r"""Cancel autocompletion.
Returns
-------
succ : bool
"""
self.autocomplete_manager.cancel_autocomplete()
self.update_buffer(clear=True)
return True
@locked
def unknown_key(self, key):
self.cancel_hint()
command_str = "".join(self.editor.buffer).strip()
self._finish_session(
ErrorResult(command_str, None, ValueError(f"Unknown key: " + key))
)
class InputStroke:
r"""Keyboard controller."""
def __init__(self, input, settings):
self.input = input
self.settings = settings
@staticmethod
def _parse_action(func):
ACTION_REGEX = "({fn}{op})*{fn}".format(
fn=r"input\.(?!_)\w+\(\)",
op=r"( \| | \& | and | or )",
)
if not re.match(ACTION_REGEX, func):
raise ValueError(f"invalid action: {repr(func)}")
def action(input):
with input.edit_ctxt.on():
eval(func, {}, {"input": input})
return action
def register(self, controller):
r"""Register handler to the given controller.
Parameters
----------
controller : engines.Controller
"""
controller.add_handler(self.keypress_handler())
controller.add_handler(
self.autocomplete_handler(
self.settings.autocomplete_keys, self.settings.help_key
)
)
controller.add_handler(self.printable_handler())
for key, func in self.settings.keymap.items():
action = self._parse_action(func)
action_handler = lambda _, action=action: action(self.input)
controller.add_handler(action_handler, key)
controller.add_handler(self.help_handler(), self.settings.help_key)
controller.add_handler(self.confirm_handler(), self.settings.confirm_key)
controller.add_handler(self.unknown_handler(self.settings))
def keypress_handler(self):
def keypress(_):
self.input.key_pressed_counter += 1
return keypress
def confirm_handler(self):
return lambda _: self.input.confirm()
def help_handler(self):
return lambda _: self.input.help()
def autocomplete_handler(self, keys, help_key):
next_key, prev_key, cancel_key = keys
def handler(args):
_, time, keyname, keycode = args
if keyname == next_key:
self.input.forward_autocomplete()
elif keyname == prev_key:
self.input.backward_autocomplete()
elif keyname == cancel_key:
self.input.cancel_autocomplete()
elif keyname != help_key:
self.input.finish_autocomplete()
return handler
def printable_handler(self):
def handler(args):
_, time, keyname, keycode = args
if keycode.isprintable():
self.input.insert(keycode)
return handler
def unknown_handler(self, settings):
keys = list(settings.keymap.keys())
keys.append(settings.confirm_key)
keys.append(settings.help_key)
keys.extend(settings.autocomplete_keys)
def handler(args):
_, _, key, code = args
if key not in keys and not code.isprintable():
self.input.unknown_key(key)
return handler
class InputView:
def __init__(self, input):
self.input = input
self.key_pressed = False
self.buffer = []
self.tokens = []
self.pos = 0
self.highlighted = None
self.typeahead = ""
self.clean = False
self.hint = None
self.popup = []
self.suggestions = None
self.state = "EDIT"
@dn.datanode
def load(self, fin_event):
buffer_modified_counter = None
key_pressed_counter = None
res, time, width = yield
while True:
with self.input.edit_ctxt.lock:
if self.input.buffer_modified_counter != buffer_modified_counter:
buffer_modified_counter = self.input.buffer_modified_counter
self.buffer = list(self.input.editor.buffer)
self.tokens = list(self.input.editor.tokens)
self.pos = self.input.editor.pos
self.typeahead = self.input.typeahead
self.clean = self.input.result is not None
self.hint = self.input.hint_manager.get_hint()
self.suggestions = (
self.input.autocomplete_manager.get_suggestions_list(),
self.input.autocomplete_manager.get_suggestions_index(),
)
self.popup = []
while True:
try:
hint = self.input.hint_manager.popup_queue.get(False)
except queue.Empty:
break
self.popup.append(hint)
if isinstance(self.input.result, ErrorResult):
self.highlighted = self.input.result.index
else:
self.highlighted = self.input.hint_manager.get_hint_location()
self.state = self.input.state
self.key_pressed = self.input.key_pressed_counter != key_pressed_counter
key_pressed_counter = self.input.key_pressed_counter
res, time, width = yield res
# fin
if self.state == "FIN" and not fin_event.is_set():
fin_event.set()
@dataclasses.dataclass(frozen=True)
class ByAddress:
value: object
def __eq__(self, other):
if not isinstance(other, ByAddress):
return False
return self.value is other.value
class TextRenderer:
def __init__(self, rich, settings):
self.rich = rich
self.settings = settings
@staticmethod
def _render_grammar_key(buffer, tokens, typeahead, pos, highlighted, clean):
return (
ByAddress(buffer),
typeahead,
pos,
highlighted,
clean,
)
def render_grammar(
self,
buffer,
tokens,
typeahead,
pos,
highlighted,
clean,
caret_markup,
typeahead_template,
highlight_template,
):
length = len(buffer)
buffer = list(buffer)
for token in tokens:
# markup whitespace
for index in range(token.mask.start, token.mask.stop):
if buffer[index] == " ":
buffer[index] = self.rich.tags["ws"]()
# markup escape
for index in token.quotes:
if buffer[index] == "'":
buffer[index] = self.rich.tags["qt"]()
elif buffer[index] == "\\":
buffer[index] = self.rich.tags["bs"]()
else:
assert False
# markup caret, typeahead
if clean:
typeahead = ""
if pos == length and not typeahead:
buffer.append(" ")
if not clean:
if pos < len(buffer):
buffer[pos] = caret_markup(mu.join([buffer[pos]]).children)
else:
typeahead = caret_markup(mu.join(typeahead[:1]).children), typeahead[1:]
typeahead_markup = typeahead_template(mu.join(typeahead))
res = []
prev_index = 0
for n, token in enumerate(tokens):
# markup delimiter
delimiter_markup = mu.join(buffer[prev_index : token.mask.start])
res.append(delimiter_markup)
prev_index = token.mask.stop
# markup token
token_markup = mu.join(buffer[token.mask])
if token.type is None:
if clean or token.mask.stop != length:
token_markup = self.rich.tags["unk"](token_markup.children)
elif token.type is cmd.TOKEN_TYPE.COMMAND:
token_markup = self.rich.tags["cmd"](token_markup.children)
elif token.type is cmd.TOKEN_TYPE.KEYWORD:
token_markup = self.rich.tags["kw"](token_markup.children)
elif token.type is cmd.TOKEN_TYPE.ARGUMENT:
token_markup = self.rich.tags["arg"](token_markup.children)
else:
assert False
# markup highlight
if n == highlighted:
token_markup = highlight_template(token_markup)
res.append(token_markup)
else:
delimiter_markup = mu.join(buffer[prev_index:])
res.append(delimiter_markup)
markup = mu.Group((*res, typeahead_markup))
markup = markup.expand()
return markup
@dn.datanode
def render_text(self, state):
typeahead_template = self.rich.parse(self.settings.typeahead, slotted=True)
highlight_template = self.rich.parse(self.settings.highlight, slotted=True)
render_grammar = dn.starcachemap(
self.render_grammar,
key=self._render_grammar_key,
caret_markup=Caret,
typeahead_template=typeahead_template,
highlight_template=highlight_template,
)
with render_grammar:
yield
while True:
markup = render_grammar.send(
(
state.buffer,
state.tokens,
state.typeahead,
state.pos,
state.highlighted,
state.clean,
)
)
yield markup, state.key_pressed
class MsgRenderer:
def __init__(self, rich, settings):
self.rich = rich
self.settings = settings
@dn.datanode
def render_msg(self, state):
message_max_lines = self.settings.message_max_lines
sugg_lines = self.settings.suggestions_lines
sugg_items = self.settings.suggestion_items
message_overflow_ellipsis = self.settings.message_overflow_ellipsis
suggestion_overflow_ellipses = self.settings.suggestion_overflow_ellipses
msg_ellipsis = self.rich.parse(message_overflow_ellipsis)
msg_ellipsis_width = self.rich.widthof(msg_ellipsis)
if msg_ellipsis_width == -1:
raise ValueError(f"invalid ellipsis: {message_overflow_ellipsis!r}")
sugg_top_ellipsis = self.rich.parse(
suggestion_overflow_ellipses[0], slotted=True
)
sugg_bottom_ellipsis = self.rich.parse(
suggestion_overflow_ellipses[1], slotted=True
)
sugg_items_templates = (
self.rich.parse(sugg_items[0], slotted=True),
self.rich.parse(sugg_items[1], slotted=True),
)
desc_template = self.rich.parse(self.settings.desc_message, slotted=True)
info_template = self.rich.parse(self.settings.info_message, slotted=True)
render_hint = dn.starcachemap(
self.render_hint,
message_max_lines=message_max_lines,
msg_ellipsis=msg_ellipsis,
sugg_lines=sugg_lines,
sugg_items_templates=sugg_items_templates,
sugg_ellipses=(sugg_top_ellipsis, sugg_bottom_ellipsis),
desc_template=desc_template,
info_template=info_template,
)
with render_hint:
(view, msgs, logs), time, width = yield
while True:
msg = render_hint.send((state.hint, state.suggestions))
if msg is None:
if len(msgs) != 0:
msgs.clear()
else:
if len(msgs) != 1 or msgs[0] is not msg:
msgs.clear()
msgs.append(msg)
logs.extend(
self.render_popup(
state.popup,
desc_template=desc_template,
info_template=info_template,
)
)
(view, msgs, logs), time, width = yield (view, msgs, logs)
def render_hint(
self,
hint,
suggestions,
*,
message_max_lines,
msg_ellipsis,
sugg_lines,
sugg_items_templates,
sugg_ellipses,
desc_template,
info_template,
):
msgs = []
# draw hint
msg = None
if hint is not None and hint.message:
msg = self.rich.parse(hint.message, root_tag=True)
lines = 0
def trim_lines(text):
nonlocal lines
if lines >= message_max_lines:
return mu.Text("")
if isinstance(text, mu.Newline):
lines += 1
if lines == message_max_lines:
return mu.Group((text, msg_ellipsis))
else:
for i, ch in enumerate(text.string):
if ch == "\n":
lines += 1
if lines == message_max_lines:
return mu.Group(
(mu.Text(text.string[: i + 1]), msg_ellipsis)
)
return text
msg = msg.traverse((mu.Text, mu.Newline), trim_lines)
if isinstance(hint, DescHint):
msg = desc_template(msg)
elif isinstance(hint, InfoHint):
msg = info_template(msg)
else:
assert False
msg = msg.expand()
if suggestions[0] is not None:
suggs_list, sugg_index = suggestions
sugg_start = sugg_index // sugg_lines * sugg_lines
sugg_end = sugg_start + sugg_lines
suggs = suggs_list[sugg_start:sugg_end]
res = []
for i, sugg in enumerate(suggs):
sugg = mu.Text(sugg)
item_template = (
sugg_items_templates[1]
if i == sugg_index - sugg_start
else sugg_items_templates[0]
)
sugg = item_template(sugg)
res.append(sugg)
if i == sugg_index - sugg_start and msg is not None:
res.append(msg)
if sugg_start > 0:
res.insert(0, sugg_ellipses[0](mu.Text(f"{sugg_start} more")))
if sugg_end < len(suggs_list):
res.append(
sugg_ellipses[1](mu.Text(f"{len(suggs_list) - sugg_end} more"))
)
nl = mu.Text("\n")
is_fst = True
for block in res:
if not is_fst:
msgs.append(nl)
msgs.append(block)
is_fst = False
else:
if msg is not None:
msgs.append(msg)
return mu.Group(tuple(msgs)) if msgs else None
def render_popup(self, popup, *, desc_template, info_template):
logs = []
# draw popup
for hint in popup:
msg = None
if hint.message:
msg = self.rich.parse(hint.message, root_tag=True)
if isinstance(hint, DescHint):
msg = desc_template(msg)
elif isinstance(hint, InfoHint):
msg = info_template(msg)
else:
assert False
msg = mu.Group((msg, mu.Text("\n")))
msg = msg.expand()
if msg is not None:
logs.append(msg)
return logs | PypiClean |
/Draugr-1.0.9.tar.gz/Draugr-1.0.9/draugr/visualisation/matplotlib_utilities/signal_data/3d_spectrum.py |
__author__ = "Christian Heider Nielsen"
__doc__ = r"""
Created on 06-01-2021
"""
from typing import Sequence
import mpl_toolkits.mplot3d.axes3d as p3
import numpy
from matplotlib import animation, cm, pyplot
from mpl_toolkits.mplot3d import axes3d
from scipy.signal import chirp, spectrogram
from warg import next_pow_2
__all__ = ["spectral_plot3d", "spectrum_plot3d"]
# TODO: ANIMATED VARIANT, maybe as a drawer!
def spectral_plot3d(
time: numpy.ndarray, frequencies: numpy.ndarray, fxt: numpy.ndarray
) -> pyplot.Figure:
"""
return new figure
of a 3d plot of the spectrogram of the signal
"""
assert fxt.shape == (*frequencies.shape, *time.shape)
assert fxt.dtype == numpy.complex
fig = pyplot.figure()
ax = p3.Axes3D(fig)
x, y = numpy.meshgrid(time, frequencies)
# colors=cm.jet(norm(colorfunction))
colors = numpy.empty(x.shape, dtype=numpy.float)
z = numpy.empty(x.shape, dtype=numpy.float)
for y_i in range(len(time)):
for x_i in range(len(frequencies)):
com = fxt[x_i, y_i]
z[x_i, y_i] = com.real
colors[x_i, y_i] = com.imag * 0.5 + 0.5
colors = colors / colors.max()
surf = ax.plot_surface(
x,
y,
z,
facecolors=cm.jet(colors),
# linewidth=0
# color='0.75',
# rstride=1,
# cstride=1
# rcount=50
# #ccount=50
)
ax.set_ylabel("Frequency [kHz]")
ax.set_xlabel("Time [s]")
ax.set_zlabel("Magnitude")
return fig
def spectrum_plot3d(
signal: Sequence, sampling_rate: int, window_length_ms=(20 / 1000)
) -> pyplot.Figure:
"""return new figure of a 3d plot of the spectrum of the signal"""
n_per_seg = next_pow_2(
sampling_rate * window_length_ms
) # 20 ms, next_pow_2 per seg == n_fft
f, t, fxt = spectrogram(
signal,
fs=sampling_rate,
window="hanning",
nperseg=n_per_seg,
scaling="spectrum",
mode="complex",
)
return spectral_plot3d(t, f, fxt)
if __name__ == "__main__":
def asdijaisd() -> None:
"""
:rtype: None
"""
sr = 1000
t = numpy.arange(sr * 4) / sr
# noise = numpy.random.rand(sr * 2) * 0.001
w = chirp(t, f0=100, f1=500, t1=4, method="linear")
signal = numpy.sin(200 * 2 * numpy.pi * t) + w # + noise
spectrum_plot3d(signal, sr)
pyplot.show()
def aisjd() -> None:
"""
:rtype: None
"""
fig = pyplot.figure()
ax = axes3d.Axes3D(fig)
def gen(n):
"""description"""
phi = 0
while phi < 2 * numpy.pi:
yield numpy.array([numpy.cos(phi), numpy.sin(phi), phi])
phi += 2 * numpy.pi / n
def update(num, data, line):
"""description"""
line.set_data(data[:2, :num])
line.set_3d_properties(data[2, :num])
def asudh():
"""description"""
N = 100
data = numpy.array(list(gen(N))).T
(line,) = ax.plot(data[0, 0:1], data[1, 0:1], data[2, 0:1])
# Setting the axes properties
ax.set_xlim3d([-1.0, 1.0])
ax.set_xlabel("X")
ax.set_ylim3d([-1.0, 1.0])
ax.set_ylabel("Y")
ax.set_zlim3d([0.0, 10.0])
ax.set_zlabel("Z")
ani = animation.FuncAnimation(
fig, update, N, fargs=(data, line), interval=10000 / N, blit=False
)
# ani.save('matplot003.gif', writer='imagemagick')
pyplot.show()
asudh()
# aisjd()
asdijaisd() | PypiClean |
/Audit-Alembic-0.1.0.tar.gz/Audit-Alembic-0.1.0/ci/appveyor-download.py | from __future__ import unicode_literals
import argparse
import os
import zipfile
import requests
def make_auth_headers():
"""Make the authentication headers needed to use the Appveyor API."""
path = os.path.expanduser("~/.appveyor.token")
if not os.path.exists(path):
raise RuntimeError(
"Please create a file named `.appveyor.token` in your home directory. "
"You can get the token from https://ci.appveyor.com/api-token"
)
with open(path) as f:
token = f.read().strip()
headers = {
'Authorization': 'Bearer {}'.format(token),
}
return headers
def download_latest_artifacts(account_project, build_id):
"""Download all the artifacts from the latest build."""
if build_id is None:
url = "https://ci.appveyor.com/api/projects/{}".format(account_project)
else:
url = "https://ci.appveyor.com/api/projects/{}/build/{}".format(account_project, build_id)
build = requests.get(url, headers=make_auth_headers()).json()
jobs = build['build']['jobs']
print(u"Build {0[build][version]}, {1} jobs: {0[build][message]}".format(build, len(jobs)))
for job in jobs:
name = job['name']
print(u" {0}: {1[status]}, {1[artifactsCount]} artifacts".format(name, job))
url = "https://ci.appveyor.com/api/buildjobs/{}/artifacts".format(job['jobId'])
response = requests.get(url, headers=make_auth_headers())
artifacts = response.json()
for artifact in artifacts:
is_zip = artifact['type'] == "Zip"
filename = artifact['fileName']
print(u" {0}, {1} bytes".format(filename, artifact['size']))
url = "https://ci.appveyor.com/api/buildjobs/{}/artifacts/{}".format(job['jobId'], filename)
download_url(url, filename, make_auth_headers())
if is_zip:
unpack_zipfile(filename)
os.remove(filename)
def ensure_dirs(filename):
"""Make sure the directories exist for `filename`."""
dirname = os.path.dirname(filename)
if dirname and not os.path.exists(dirname):
os.makedirs(dirname)
def download_url(url, filename, headers):
"""Download a file from `url` to `filename`."""
ensure_dirs(filename)
response = requests.get(url, headers=headers, stream=True)
if response.status_code == 200:
with open(filename, 'wb') as f:
for chunk in response.iter_content(16 * 1024):
f.write(chunk)
else:
print(u" Error downloading {}: {}".format(url, response))
def unpack_zipfile(filename):
"""Unpack a zipfile, using the names in the zip."""
with open(filename, 'rb') as fzip:
z = zipfile.ZipFile(fzip)
for name in z.namelist():
print(u" extracting {}".format(name))
ensure_dirs(name)
z.extract(name)
parser = argparse.ArgumentParser(description='Download artifacts from AppVeyor.')
parser.add_argument('--id',
metavar='PROJECT_ID',
default='jpassaro/Audit-Alembic',
help='Project ID in AppVeyor.')
parser.add_argument('build',
nargs='?',
metavar='BUILD_ID',
help='Build ID in AppVeyor. Eg: master-123')
if __name__ == "__main__":
# import logging
# logging.basicConfig(level="DEBUG")
args = parser.parse_args()
download_latest_artifacts(args.id, args.build) | PypiClean |
/ElasticTabstops-1.0.1.tar.gz/ElasticTabstops-1.0.1/elastictabstops/convert.py |
# This file tries to follow the Style Guide for Python Code (PEP 8) *EXCEPT*
# * it uses tabs for indenting (like Guido used to recommend)
# * it doesn't follow the Maximum Line Length rule
# use pylint as following: pylint --indent-string='\t' --max-line-length=1000 elastictabstops
from collections import namedtuple
import math
import re
# This code can be used to convert large amounts of text, so performance matters.
# For this reason we use namedtuples and __slots__ to create readable but well-performing data structures.
PositionedText = namedtuple('PositionedText', ['text', 'position'])
class SizedText(object):
"""Class used to store text and the width of the cell it's in."""
__slots__ = ['text', 'size']
def __init__(self, text, tab_width, multiples_of_tab_width):
self.text = text
# size initially stores the minimum width of the cell
# we add two to provide padding - one is not enough as it could be confused for a non-aligning space
if multiples_of_tab_width:
self.size = int((math.ceil((len(self.text) + 2) / float(tab_width)))) * tab_width
else:
self.size = max(len(self.text) + 2, tab_width)
def get_padded_text(self):
"""Returns self.text plus spaces to match the number of characters in self.size."""
nof_spaces = self.size - len(self.text)
return self.text + (' ' * nof_spaces)
def _cell_exists(list_of_lists, line_num, cell_num):
"""Check that an item exists in a list of lists."""
return line_num < len(list_of_lists) and cell_num < len(list_of_lists[line_num])
def _sub_tabs(line, tab_width, repl_char):
"""Return a line of text where tab characters have been substituted with the correct number of replacement characters."""
str_list = []
pos = 0
for char in line:
if char == '\t':
expand = tab_width - (pos % tab_width)
str_list.append(expand * repl_char)
pos += expand
else:
str_list.append(char)
pos += 1
return ''.join(str_list)
def _get_positions_contents(text, tab_width):
"""Given a piece of text and how long tabs should be, return a list of lists of PositionedText named tuples."""
repl_char = '\x1a' # the 'substitute character' in unicode
text = '\n'.join([_sub_tabs(line, tab_width, repl_char) for line in text.split('\n')])
# Look for a char that is (not a space or \x1a) followed by any number of chars that are either (not a space or \x1a) or a space followed by (not a space or \x1a)
# This allows the substrings to have spaces, but only if that space is followed by a non-space char
compiled = re.compile(r'[^%(repl_char)s\s](?:[^%(repl_char)s\s]|\s(?=[^%(repl_char)s\s]))*' % {'repl_char': repl_char})
return [[PositionedText(match.group(), match.start()) for match in compiled.finditer(line)] for line in text.split('\n')]
def _from_spaces(text, tab_width):
"""Convert spaces aligned text to table."""
if not isinstance(text, str):
raise TypeError("The first parameter of _from_spaces ('text') should be a string.")
if not isinstance(tab_width, int):
raise TypeError("The second parameter of _from_spaces ('tab_width') should be an integer.")
if tab_width < 2:
raise ValueError("The second parameter of _from_spaces ('tab_width') should be 2 or greater.")
# '\r's before '\n's are just left at the end of lines
# solitary '\r's aren't dealt with as these days no one uses CRs on their own for new lines
lines = _get_positions_contents(text, tab_width)
max_cells = max([len(line) for line in lines])
nof_lines = len(lines)
# not a "for cell_num in (range(max_cells)):" loop because max_cells may increase
cell_num = 0
while cell_num < max_cells:
starting_new_block = True
start_range = 0
end_range = 0
for line_num in range(nof_lines + 1):
if _cell_exists(lines, line_num, cell_num):
# if we're at the start of a block remember what line we're on
if starting_new_block:
start_range = line_num
starting_new_block = False
end_range = line_num
# if there's no cell and we're not starting a block then we're at the end of a column block
elif not starting_new_block:
block_positions = [lines[block_line_num][cell_num].position for block_line_num in range(start_range, end_range + 1)]
min_indent = min(block_positions)
for block_line_offset, block_position in enumerate(block_positions):
block_line_num = start_range + block_line_offset
# if the current block is to the right we need to insert an empty cell
if block_position > min_indent:
# insert an empty cell to shift existing cells across
lines[block_line_num].insert(cell_num, PositionedText('', 0))
max_cells = max(max_cells, len(lines[block_line_num]))
# otherwise if we're in the first column we need to insert empty cells for every line in this block
elif cell_num == 0:
nof_cells_missing = int(block_position / tab_width)
for _ in range(nof_cells_missing):
# insert empty indentation cells
lines[block_line_num].insert(cell_num, PositionedText('', 0))
max_cells = max(max_cells, len(lines[block_line_num]))
starting_new_block = True
cell_num += 1
return [([cell.text for cell in line] or ['']) for line in lines]
def _to_elastic_tabstops(table):
"""Convert table to elastic tabstops aligned text."""
if not isinstance(table, list):
raise TypeError("The first parameter of _to_elastic_tabstops ('table') should be a list.")
return '\n'.join(['\t'.join(row) for row in table])
def _to_fixed_tabstops(table, tab_width):
"""Convert table to fixed tabstops aligned text."""
if not isinstance(table, list):
raise TypeError("The first parameter of _to_fixed_tabstops ('table') should be a list.")
if not isinstance(tab_width, int):
raise TypeError("The second parameter of _to_fixed_tabstops ('tab_width') should be an integer .")
if tab_width < 2:
raise ValueError("The second parameter of _to_fixed_tabstops ('tab_width') should be 2 or greater.")
spaced_text = _to_spaces(table, tab_width, multiples_of_tab_width=True)
lines = _get_positions_contents(spaced_text, tab_width)
tabbed_text = []
for line in lines:
pos = 0
tabbed_line = ''
for cell in line:
gap = cell.position - pos
num_tabs = int(math.floor((gap + (tab_width - 1))/ tab_width))
num_spaces = cell.position % tab_width
tabbed_line += ('\t' * num_tabs) + (' ' * num_spaces) + cell.text
pos = cell.position + len(cell.text)
tabbed_text.append(tabbed_line)
return '\n'.join(tabbed_text)
def _from_fixed_tabstops(text, tab_width):
"""Convert fixed tabstops aligned text to table."""
if not isinstance(text, str):
raise TypeError("The first parameter of _from_fixed_tabstops ('text') should be a string.")
if not isinstance(tab_width, int):
raise TypeError("The second parameter of _from_fixed_tabstops ('tab_width') should be an integer.")
if tab_width < 2:
raise ValueError("The second parameter of _from_fixed_tabstops ('tab_width') should be 2 or greater.")
expanded = text.expandtabs(tab_width)
return _from_spaces(expanded, tab_width)
def _from_elastic_tabstops(text):
"""Convert elastic tabstops aligned text to table."""
if not isinstance(text, str):
raise TypeError("The first parameter of _from_elastic_tabstops ('text') should be a string.")
# '\r's before '\n's are just left at the end of lines
# solitary '\r's aren't dealt with as these days no one uses CRs on their own for new lines
return [line.split('\t') for line in text.split('\n')]
def _to_spaces(table, tab_width, multiples_of_tab_width=False):
"""Convert table to spaces aligned text."""
if not isinstance(table, list):
raise TypeError("The first parameter of _to_spaces ('table') should be a list.")
if not isinstance(tab_width, int):
raise TypeError("The second parameter of _to_spaces ('tab_width') should be an integer .")
if tab_width < 2:
raise ValueError("The second parameter of _to_spaces ('tab_width') should be 2 or greater.")
lines = [[SizedText(cell, tab_width, multiples_of_tab_width) for cell in row] for row in table]
max_cells = max([len(line) for line in lines])
nof_lines = len(lines)
for cell_num in range(max_cells):
starting_new_block = True
start_range = 0
end_range = 0
max_width = 0
for line_num in range(nof_lines):
# check if there's a cell to the right of this column (which means this cell ends in a tab) - we only care about terminated cells
if _cell_exists(lines, line_num, cell_num + 1):
# if we're at the start of a block remember what line we're on
if starting_new_block:
start_range = line_num
starting_new_block = False
# record the max width of the block so far
max_width = max(max_width, lines[line_num][cell_num].size)
end_range = line_num
# if the cell has not been terminated and we're not starting a block then we're at the end of a column block
elif not starting_new_block:
# iterate over all cells in the block and set their width to the max width
for block_line_num in range(start_range, end_range + 1):
lines[block_line_num][cell_num].size = max_width
starting_new_block = True
max_width = 0
# if we got to the last line without setting the size of the current block, do that now
if not starting_new_block:
for block_line_num in range(start_range, end_range + 1):
lines[block_line_num][cell_num].size = max_width
# append text and spaces to new_text
new_text = [''] * nof_lines
for line_num in range(nof_lines):
if len(lines[line_num]) > 0:
for cell_num in range(len(lines[line_num]) - 1):
new_text[line_num] += lines[line_num][cell_num].get_padded_text()
last_cell_num = len(lines[line_num]) - 1
new_text[line_num] += lines[line_num][last_cell_num].text
return '\n'.join(new_text) | PypiClean |
/Kamaelia-0.6.0.tar.gz/Kamaelia-0.6.0/Tools/Whiteboard/Whiteboard.py |
import os
import sys
import Axon
import pygame
from Axon.Component import component
from Axon.Ipc import WaitComplete, producerFinished, shutdownMicroprocess
from Kamaelia.Chassis.Graphline import Graphline
from Kamaelia.Chassis.Pipeline import Pipeline
from Kamaelia.Chassis.ConnectedServer import SimpleServer
from Kamaelia.Internet.TCPClient import TCPClient
from Kamaelia.Util.Console import ConsoleEchoer
from Kamaelia.Visualisation.PhysicsGraph.chunks_to_lines import chunks_to_lines
from Kamaelia.Visualisation.PhysicsGraph.lines_to_tokenlists import lines_to_tokenlists as text_to_tokenlists
from Kamaelia.Util.NullSink import nullSinkComponent
from Kamaelia.Util.Backplane import Backplane, PublishTo, SubscribeTo
from Kamaelia.Util.Detuple import SimpleDetupler
from Kamaelia.Util.Console import ConsoleEchoer
#
# The following application specific components will probably be rolled
# back into the repository.
#
from Kamaelia.Apps.Whiteboard.TagFiltering import TagAndFilterWrapper, FilterAndTagWrapper
from Kamaelia.Apps.Whiteboard.TagFiltering import TagAndFilterWrapperKeepingTag, FilterAndTagWrapperKeepingTag
from Kamaelia.Apps.Whiteboard.Tokenisation import tokenlists_to_lines, lines_to_tokenlists
from Kamaelia.Apps.Whiteboard.Canvas import Canvas
from Kamaelia.Apps.Whiteboard.Painter import Painter
from Kamaelia.Apps.Whiteboard.SingleShot import OneShot
from Kamaelia.Apps.Whiteboard.CheckpointSequencer import CheckpointSequencer
from Kamaelia.Apps.Whiteboard.Entuple import Entuple
from Kamaelia.Apps.Whiteboard.Routers import Router, TwoWaySplitter, ConditionalSplitter
from Kamaelia.Apps.Whiteboard.Palette import buildPalette, colours
from Kamaelia.Apps.Whiteboard.Options import parseOptions
from Kamaelia.Apps.Whiteboard.UI import PagingControls, LocalPagingControls, Eraser, ClearPage
from Kamaelia.Apps.Whiteboard.CommandConsole import CommandConsole
try:
from Kamaelia.Codec.Speex import SpeexEncode,SpeexDecode
except Exception, e:
print "Speex not available, using null components instead"
SpeexEncode = nullSinkComponent
SpeexDecode = nullSinkComponent
try:
from Kamaelia.Apps.Whiteboard.Audio import SoundInput
except ImportError:
print "SoundInput not available, using NullSink instead"
SoundInput = nullSinkComponent
try:
from Kamaelia.Apps.Whiteboard.Audio import SoundOutput
except ImportError:
print "SoundOutput not available, using NullSink instead"
SoundOutput = nullSinkComponent
try:
from Kamaelia.Apps.Whiteboard.Audio import RawAudioMixer
except ImportError:
print "RawAudioMixer not available, using NullSink instead"
RawAudioMixer = nullSinkComponent
notepad = None
if len(sys.argv) >1:
if os.path.exists(sys.argv[1]):
if os.path.isdir(sys.argv[1]):
notepad = sys.argv[1]
if (notepad is None) and os.path.exists("Scribbles"):
if os.path.isdir("Scribbles"):
notepad = "Scribbles"
if (notepad is None):
N = os.path.join(os.path.expanduser("~"),"Scribbles")
if not os.path.exists(N):
os.makedirs(N)
if os.path.isdir(N):
notepad = N
if (notepad is None):
print "Can't figure out what to do with piccies. Exitting"
sys.exit(0)
#
# Misplaced encapsulation --> Kamaelia.Apps.Whiteboard.Palette
#
colours_order = [ "black", "red", "orange", "yellow", "green", "turquoise", "blue", "purple", "darkgrey", "lightgrey" ]
num_pages = len(os.listdir(notepad))
def FilteringPubsubBackplane(backplaneID,**FilterTagWrapperOptions):
"""Sends tagged events to a backplane. Emits events not tagged by this pubsub."""
return FilterAndTagWrapper(
Pipeline(
PublishTo(backplaneID),
# well, should be to separate pipelines, this is lazier!
SubscribeTo(backplaneID),
),
**FilterTagWrapperOptions
)
def clientconnector(whiteboardBackplane="WHITEBOARD", audioBackplane="AUDIO", port=1500):
return Pipeline(
chunks_to_lines(),
lines_to_tokenlists(),
Graphline(
ROUTER = Router( ((lambda T : T[0]=="SOUND"), "audio"),
((lambda T : T[0]!="SOUND"), "whiteboard"),
),
WHITEBOARD = FilteringPubsubBackplane(whiteboardBackplane),
AUDIO = Pipeline(
SimpleDetupler(1), # remove 'SOUND' tag
SpeexDecode(3),
FilteringPubsubBackplane(audioBackplane, dontRemoveTag=True),
RawAudioMixer(),
SpeexEncode(3),
Entuple(prefix=["SOUND"],postfix=[]),
),
linkages = {
# incoming messages go to a router
("", "inbox") : ("ROUTER", "inbox"),
# distribute messages to appropriate destinations
("ROUTER", "audio") : ("AUDIO", "inbox"),
("ROUTER", "whiteboard") : ("WHITEBOARD", "inbox"),
# aggregate all output
("AUDIO", "outbox") : ("", "outbox"),
("WHITEBOARD", "outbox") : ("", "outbox"),
# shutdown routing, not sure if this will actually work, but hey!
("", "control") : ("ROUTER", "control"),
("ROUTER", "signal") : ("AUDIO", "control"),
("AUDIO", "signal") : ("WHITEBOARD", "control"),
("WHITEBOARD", "signal") : ("", "signal")
},
),
tokenlists_to_lines(),
)
#/-------------------------------------------------------------------------
# Server side of the system
#
def LocalEventServer(whiteboardBackplane="WHITEBOARD", audioBackplane="AUDIO", port=1500):
def configuredClientConnector():
return clientconnector(whiteboardBackplane=whiteboardBackplane,
audioBackplane=audioBackplane,
port=port)
return SimpleServer(protocol=clientconnector, port=port)
#/-------------------------------------------------------------------------
# Client side of the system
#
def EventServerClients(rhost, rport,
whiteboardBackplane="WHITEBOARD",
audioBackplane="AUDIO"):
# plug a TCPClient into the backplane
loadingmsg = "Fetching sketch from server..."
return Graphline(
# initial messages sent to the server, and the local whiteboard
GETIMG = Pipeline(
OneShot(msg=[["GETIMG"]]),
tokenlists_to_lines()
),
BLACKOUT = OneShot(msg="CLEAR 0 0 0\r\n"
"WRITE 100 100 24 255 255 255 "+loadingmsg+"\r\n"),
NETWORK = TCPClient(host=rhost,port=rport),
APPCOMMS = clientconnector(whiteboardBackplane=whiteboardBackplane,
audioBackplane=audioBackplane),
linkages = {
("GETIMG", "outbox") : ("NETWORK", "inbox"), # Single shot out
("APPCOMMS", "outbox") : ("NETWORK", "inbox"), # Continuous out
("BLACKOUT", "outbox") : ("APPCOMMS", "inbox"), # Single shot in
("NETWORK", "outbox") : ("APPCOMMS", "inbox"), # Continuous in
}
)
#/-------------------------------------------------------------------------
class LocalPageEventsFilter(ConditionalSplitter): # This is a data tap/siphon/demuxer
def condition(self, data):
return (data == [["prev"]]) or (data == [["next"]])
def true(self,data):
self.send((data[0][0], "local"), "true")
SLIDESPEC = notepad+"/slide.%d.png"
def makeBasicSketcher(left=0,top=0,width=1024,height=768):
return Graphline( CANVAS = Canvas( position=(left,top+32),size=(width,height-32) ),
PAINTER = Painter(),
PALETTE = buildPalette( cols=colours, order=colours_order, topleft=(left+64,top), size=32 ),
ERASER = Eraser(left,top),
CLEAR = ClearPage(left+(64*5)+32*len(colours),top),
PAGINGCONTROLS = PagingControls(left+64+32*len(colours),top),
LOCALPAGINGCONTROLS = LocalPagingControls(left+(64*6)+32*len(colours),top),
LOCALPAGEEVENTS = LocalPageEventsFilter(),
HISTORY = CheckpointSequencer(lambda X: [["LOAD", SLIDESPEC % (X,)]],
lambda X: [["SAVE", SLIDESPEC % (X,)]],
lambda X: [["CLEAR"]],
initial = 1,
highest = num_pages,
),
PAINT_SPLITTER = TwoWaySplitter(),
LOCALEVENT_SPLITTER = TwoWaySplitter(),
DEBUG = ConsoleEchoer(),
linkages = {
("CANVAS", "eventsOut") : ("PAINTER", "inbox"),
("PALETTE", "outbox") : ("PAINTER", "colour"),
("ERASER", "outbox") : ("PAINTER", "erase"),
("PAINTER", "outbox") : ("PAINT_SPLITTER", "inbox"),
("CLEAR","outbox") : ("PAINT_SPLITTER", "inbox"),
("PAINT_SPLITTER", "outbox") : ("CANVAS", "inbox"),
("PAINT_SPLITTER", "outbox2") : ("", "outbox"), # send to network
("LOCALPAGINGCONTROLS","outbox") : ("LOCALEVENT_SPLITTER", "inbox"),
("LOCALEVENT_SPLITTER", "outbox2"): ("", "outbox"), # send to network
("LOCALEVENT_SPLITTER", "outbox") : ("LOCALPAGEEVENTS", "inbox"),
("", "inbox") : ("LOCALPAGEEVENTS", "inbox"),
("LOCALPAGEEVENTS", "false") : ("CANVAS", "inbox"),
("LOCALPAGEEVENTS", "true") : ("HISTORY", "inbox"),
("PAGINGCONTROLS","outbox") : ("HISTORY", "inbox"),
("HISTORY","outbox") : ("CANVAS", "inbox"),
("CANVAS", "outbox") : ("", "outbox"),
("CANVAS","surfacechanged") : ("HISTORY", "inbox"),
},
)
if __name__=="__main__":
mainsketcher = \
Graphline( SKETCHER = makeBasicSketcher(width=1024,height=768),
CONSOLE = CommandConsole(),
linkages = { ('','inbox'):('SKETCHER','inbox'),
('SKETCHER','outbox'):('','outbox'),
('CONSOLE','outbox'):('SKETCHER','inbox'),
}
)
# primary whiteboard
Pipeline( SubscribeTo("WHITEBOARD"),
TagAndFilterWrapper(mainsketcher),
PublishTo("WHITEBOARD")
).activate()
# primary sound IO - tagged and filtered, so can't hear self
Pipeline( SubscribeTo("AUDIO"),
TagAndFilterWrapperKeepingTag(
Pipeline(
RawAudioMixer(),
SoundOutput(),
######
SoundInput(),
),
),
PublishTo("AUDIO"),
).activate()
rhost, rport, serveport = parseOptions()
# setup a server, if requested
if serveport:
LocalEventServer("WHITEBOARD", "AUDIO", port=serveport).activate()
# connect to remote host & port, if requested
if rhost and rport:
EventServerClients(rhost, rport, "WHITEBOARD", "AUDIO").activate()
# sys.path.append("../Introspection")
# from Profiling import FormattedProfiler
#
# Pipeline(FormattedProfiler( 20.0, 1.0),
# ConsoleEchoer()
# ).activate()
Backplane("WHITEBOARD").activate()
Backplane("AUDIO").run() | PypiClean |
/AutoMonkey-0.2.1.tar.gz/AutoMonkey-0.2.1/automonkey/app_funcs.py | from time import sleep
from sys import platform
if platform == "win32":
from os import startfile # It is used
elif platform == "linux":
from subprocess import call
def startfile(file):
call(["xdg-open", file])
from os import system
from os.path import isfile
from re import search
from subprocess import Popen
from win32con import WM_CLOSE
from win32con import SW_RESTORE
from win32con import SW_MINIMIZE
from win32con import SW_MAXIMIZE
from win32gui import IsIconic
from win32gui import ShowWindow
from win32gui import FindWindow
from win32gui import PostMessage
from win32gui import EnumWindows
from win32gui import GetWindowText
from win32gui import SetForegroundWindow
from pyautogui import keyUp
from pyautogui import keyDown
from pyautogui import hotkey as keys2 # this is best solution, pass list to be unpacked with *list
from .utils import copy
def msoffice_replace(replace_this: str, with_this: str, match_case: bool = True, whole_words: bool = True, delay_factor: float = 1):
"""Search and replace in all MS Office Software. No Guarantees.
Args:
replace_this (str): string to be replaced
with_this (str): new string
delay_factor (float, optional): Delay factor in case
the default sleep times for waiting that the replacement
is finished are too fast. Defaults to 1.
"""
copy(replace_this)
sleep(0.2 * delay_factor)
keys2('ctrl', 'h')
sleep(0.2 * delay_factor)
if match_case or whole_words:
keys2('alt', 'm')
sleep(0.2 * delay_factor)
if match_case:
keys2('alt', 'h')
sleep(0.2 * delay_factor)
if whole_words:
keys2('alt', 'y')
sleep(0.2 * delay_factor)
keys2('alt', 'n')
sleep(0.2 * delay_factor)
keys2('ctrl', 'v')
sleep(0.2 * delay_factor)
copy(with_this)
sleep(0.2 * delay_factor)
keys2('alt', 'i')
sleep(0.2 * delay_factor)
keys2('ctrl', 'v')
sleep(0.2 * delay_factor)
keys2('alt', 'a')
sleep(0.2 * delay_factor)
keys2('enter')
sleep(0.2 * delay_factor)
keys2('enter')
sleep(0.2 * delay_factor)
keys2('esc')
sleep(0.2 * delay_factor)
keys2('esc')
sleep(0.2 * delay_factor)
class WindowManager:
"""Window Manager
"""
def __init__(self):
self._handle = None
def get_window_by_class(self, class_name, window_name=None):
"""Find a window by the class name
"""
self._handle = FindWindow(class_name, window_name)
def _parse_windows(self, hwnd, pattern):
"""Pass to EnumWindows() to check all opened windows
"""
if search(pattern, str(GetWindowText(hwnd))) is not None:
self._handle = hwnd
def get_window_by_title(self, pattern):
"""Find a window whose title matches the given regex pattern
"""
self._handle = None
EnumWindows(self._parse_windows, pattern)
def focus(self):
"""Bring focus to the selected window
"""
# SetForegroundWindow works well only after pressing alt
keyDown('alt')
SetForegroundWindow(self._handle)
self.restore()
keyUp('alt')
def minimize(self):
if not IsIconic(self._handle):
ShowWindow(self._handle, SW_MINIMIZE)
def restore(self):
if IsIconic(self._handle):
ShowWindow(self._handle, SW_RESTORE)
def maximize(self):
ShowWindow(self._handle, SW_MAXIMIZE)
def close(self):
PostMessage(self._handle, WM_CLOSE, 0, 0)
def close(title: str):
"""Close a window
"""
win_man = WindowManager()
win_man.get_window_by_title(f".*?{title}.*?")
win_man.close()
def minimize(title: str):
"""Minimize a window
"""
win_man = WindowManager()
win_man.get_window_by_title(f".*?{title}.*?")
win_man.minimize()
def maximize(title: str):
"""Minimize a window
"""
win_man = WindowManager()
win_man.get_window_by_title(f".*?{title}.*?")
win_man.maximize()
def restore(title: str):
"""Restore a window
"""
win_man = WindowManager()
win_man.get_window_by_title(f".*?{title}.*?")
win_man.restore()
def focus(title: str):
"""Bring Focus to a window
"""
win_man = WindowManager()
win_man.get_window_by_title(f".*?{title}.*?")
win_man.focus()
def open_app(app: str):
"""Open an application
Args:
app_path (str): path to the application
"""
if isfile(app):
Popen(app)
else:
try:
system(f"start {app}")
except Exception as err:
raise Exception(f"Could not open {app} because of {err}") from err | PypiClean |
/BlueWhale3-3.31.3.tar.gz/BlueWhale3-3.31.3/doc/visual-programming/build/htmlhelp/_static/searchtools.js | if (!Scorer) {
/**
* Simple result scoring code.
*/
var Scorer = {
// Implement the following function to further tweak the score for each result
// The function takes a result array [filename, title, anchor, descr, score]
// and returns the new score.
/*
score: function(result) {
return result[4];
},
*/
// query matches the full name of an object
objNameMatch: 11,
// or matches in the last dotted part of the object name
objPartialMatch: 6,
// Additive scores depending on the priority of the object
objPrio: {0: 15, // used to be importantResults
1: 5, // used to be objectResults
2: -5}, // used to be unimportantResults
// Used when the priority is not in the mapping.
objPrioDefault: 0,
// query found in title
title: 15,
partialTitle: 7,
// query found in terms
term: 5,
partialTerm: 2
};
}
if (!splitQuery) {
function splitQuery(query) {
return query.split(/\s+/);
}
}
/**
* Search Module
*/
var Search = {
_index : null,
_queued_query : null,
_pulse_status : -1,
htmlToText : function(htmlString) {
var virtualDocument = document.implementation.createHTMLDocument('virtual');
var htmlElement = $(htmlString, virtualDocument);
htmlElement.find('.headerlink').remove();
docContent = htmlElement.find('[role=main]')[0];
if(docContent === undefined) {
console.warn("Content block not found. Sphinx search tries to obtain it " +
"via '[role=main]'. Could you check your theme or template.");
return "";
}
return docContent.textContent || docContent.innerText;
},
init : function() {
var params = $.getQueryParameters();
if (params.q) {
var query = params.q[0];
$('input[name="q"]')[0].value = query;
this.performSearch(query);
}
},
loadIndex : function(url) {
$.ajax({type: "GET", url: url, data: null,
dataType: "script", cache: true,
complete: function(jqxhr, textstatus) {
if (textstatus != "success") {
document.getElementById("searchindexloader").src = url;
}
}});
},
setIndex : function(index) {
var q;
this._index = index;
if ((q = this._queued_query) !== null) {
this._queued_query = null;
Search.query(q);
}
},
hasIndex : function() {
return this._index !== null;
},
deferQuery : function(query) {
this._queued_query = query;
},
stopPulse : function() {
this._pulse_status = 0;
},
startPulse : function() {
if (this._pulse_status >= 0)
return;
function pulse() {
var i;
Search._pulse_status = (Search._pulse_status + 1) % 4;
var dotString = '';
for (i = 0; i < Search._pulse_status; i++)
dotString += '.';
Search.dots.text(dotString);
if (Search._pulse_status > -1)
window.setTimeout(pulse, 500);
}
pulse();
},
/**
* perform a search for something (or wait until index is loaded)
*/
performSearch : function(query) {
// create the required interface elements
this.out = $('#search-results');
this.title = $('<h2>' + _('Searching') + '</h2>').appendTo(this.out);
this.dots = $('<span></span>').appendTo(this.title);
this.status = $('<p class="search-summary"> </p>').appendTo(this.out);
this.output = $('<ul class="search"/>').appendTo(this.out);
$('#search-progress').text(_('Preparing search...'));
this.startPulse();
// index already loaded, the browser was quick!
if (this.hasIndex())
this.query(query);
else
this.deferQuery(query);
},
/**
* execute search (requires search index to be loaded)
*/
query : function(query) {
var i;
// stem the searchterms and add them to the correct list
var stemmer = new Stemmer();
var searchterms = [];
var excluded = [];
var hlterms = [];
var tmp = splitQuery(query);
var objectterms = [];
for (i = 0; i < tmp.length; i++) {
if (tmp[i] !== "") {
objectterms.push(tmp[i].toLowerCase());
}
if ($u.indexOf(stopwords, tmp[i].toLowerCase()) != -1 || tmp[i] === "") {
// skip this "word"
continue;
}
// stem the word
var word = stemmer.stemWord(tmp[i].toLowerCase());
// prevent stemmer from cutting word smaller than two chars
if(word.length < 3 && tmp[i].length >= 3) {
word = tmp[i];
}
var toAppend;
// select the correct list
if (word[0] == '-') {
toAppend = excluded;
word = word.substr(1);
}
else {
toAppend = searchterms;
hlterms.push(tmp[i].toLowerCase());
}
// only add if not already in the list
if (!$u.contains(toAppend, word))
toAppend.push(word);
}
var highlightstring = '?highlight=' + $.urlencode(hlterms.join(" "));
// console.debug('SEARCH: searching for:');
// console.info('required: ', searchterms);
// console.info('excluded: ', excluded);
// prepare search
var terms = this._index.terms;
var titleterms = this._index.titleterms;
// array of [filename, title, anchor, descr, score]
var results = [];
$('#search-progress').empty();
// lookup as object
for (i = 0; i < objectterms.length; i++) {
var others = [].concat(objectterms.slice(0, i),
objectterms.slice(i+1, objectterms.length));
results = results.concat(this.performObjectSearch(objectterms[i], others));
}
// lookup as search terms in fulltext
results = results.concat(this.performTermsSearch(searchterms, excluded, terms, titleterms));
// let the scorer override scores with a custom scoring function
if (Scorer.score) {
for (i = 0; i < results.length; i++)
results[i][4] = Scorer.score(results[i]);
}
// now sort the results by score (in opposite order of appearance, since the
// display function below uses pop() to retrieve items) and then
// alphabetically
results.sort(function(a, b) {
var left = a[4];
var right = b[4];
if (left > right) {
return 1;
} else if (left < right) {
return -1;
} else {
// same score: sort alphabetically
left = a[1].toLowerCase();
right = b[1].toLowerCase();
return (left > right) ? -1 : ((left < right) ? 1 : 0);
}
});
// for debugging
//Search.lastresults = results.slice(); // a copy
//console.info('search results:', Search.lastresults);
// print the results
var resultCount = results.length;
function displayNextItem() {
// results left, load the summary and display it
if (results.length) {
var item = results.pop();
var listItem = $('<li></li>');
var requestUrl = "";
var linkUrl = "";
if (DOCUMENTATION_OPTIONS.BUILDER === 'dirhtml') {
// dirhtml builder
var dirname = item[0] + '/';
if (dirname.match(/\/index\/$/)) {
dirname = dirname.substring(0, dirname.length-6);
} else if (dirname == 'index/') {
dirname = '';
}
requestUrl = DOCUMENTATION_OPTIONS.URL_ROOT + dirname;
linkUrl = requestUrl;
} else {
// normal html builders
requestUrl = DOCUMENTATION_OPTIONS.URL_ROOT + item[0] + DOCUMENTATION_OPTIONS.FILE_SUFFIX;
linkUrl = item[0] + DOCUMENTATION_OPTIONS.LINK_SUFFIX;
}
listItem.append($('<a/>').attr('href',
linkUrl +
highlightstring + item[2]).html(item[1]));
if (item[3]) {
listItem.append($('<span> (' + item[3] + ')</span>'));
Search.output.append(listItem);
setTimeout(function() {
displayNextItem();
}, 5);
} else if (DOCUMENTATION_OPTIONS.HAS_SOURCE) {
$.ajax({url: requestUrl,
dataType: "text",
complete: function(jqxhr, textstatus) {
var data = jqxhr.responseText;
if (data !== '' && data !== undefined) {
var summary = Search.makeSearchSummary(data, searchterms, hlterms);
if (summary) {
listItem.append(summary);
}
}
Search.output.append(listItem);
setTimeout(function() {
displayNextItem();
}, 5);
}});
} else {
// no source available, just display title
Search.output.append(listItem);
setTimeout(function() {
displayNextItem();
}, 5);
}
}
// search finished, update title and status message
else {
Search.stopPulse();
Search.title.text(_('Search Results'));
if (!resultCount)
Search.status.text(_('Your search did not match any documents. Please make sure that all words are spelled correctly and that you\'ve selected enough categories.'));
else
Search.status.text(_('Search finished, found %s page(s) matching the search query.').replace('%s', resultCount));
Search.status.fadeIn(500);
}
}
displayNextItem();
},
/**
* search for object names
*/
performObjectSearch : function(object, otherterms) {
var filenames = this._index.filenames;
var docnames = this._index.docnames;
var objects = this._index.objects;
var objnames = this._index.objnames;
var titles = this._index.titles;
var i;
var results = [];
for (var prefix in objects) {
for (var iMatch = 0; iMatch != objects[prefix].length; ++iMatch) {
var match = objects[prefix][iMatch];
var name = match[4];
var fullname = (prefix ? prefix + '.' : '') + name;
var fullnameLower = fullname.toLowerCase()
if (fullnameLower.indexOf(object) > -1) {
var score = 0;
var parts = fullnameLower.split('.');
// check for different match types: exact matches of full name or
// "last name" (i.e. last dotted part)
if (fullnameLower == object || parts[parts.length - 1] == object) {
score += Scorer.objNameMatch;
// matches in last name
} else if (parts[parts.length - 1].indexOf(object) > -1) {
score += Scorer.objPartialMatch;
}
var objname = objnames[match[1]][2];
var title = titles[match[0]];
// If more than one term searched for, we require other words to be
// found in the name/title/description
if (otherterms.length > 0) {
var haystack = (prefix + ' ' + name + ' ' +
objname + ' ' + title).toLowerCase();
var allfound = true;
for (i = 0; i < otherterms.length; i++) {
if (haystack.indexOf(otherterms[i]) == -1) {
allfound = false;
break;
}
}
if (!allfound) {
continue;
}
}
var descr = objname + _(', in ') + title;
var anchor = match[3];
if (anchor === '')
anchor = fullname;
else if (anchor == '-')
anchor = objnames[match[1]][1] + '-' + fullname;
// add custom score for some objects according to scorer
if (Scorer.objPrio.hasOwnProperty(match[2])) {
score += Scorer.objPrio[match[2]];
} else {
score += Scorer.objPrioDefault;
}
results.push([docnames[match[0]], fullname, '#'+anchor, descr, score, filenames[match[0]]]);
}
}
}
return results;
},
/**
* See https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Regular_Expressions
*/
escapeRegExp : function(string) {
return string.replace(/[.*+\-?^${}()|[\]\\]/g, '\\$&'); // $& means the whole matched string
},
/**
* search for full-text terms in the index
*/
performTermsSearch : function(searchterms, excluded, terms, titleterms) {
var docnames = this._index.docnames;
var filenames = this._index.filenames;
var titles = this._index.titles;
var i, j, file;
var fileMap = {};
var scoreMap = {};
var results = [];
// perform the search on the required terms
for (i = 0; i < searchterms.length; i++) {
var word = searchterms[i];
var files = [];
var _o = [
{files: terms[word], score: Scorer.term},
{files: titleterms[word], score: Scorer.title}
];
// add support for partial matches
if (word.length > 2) {
var word_regex = this.escapeRegExp(word);
for (var w in terms) {
if (w.match(word_regex) && !terms[word]) {
_o.push({files: terms[w], score: Scorer.partialTerm})
}
}
for (var w in titleterms) {
if (w.match(word_regex) && !titleterms[word]) {
_o.push({files: titleterms[w], score: Scorer.partialTitle})
}
}
}
// no match but word was a required one
if ($u.every(_o, function(o){return o.files === undefined;})) {
break;
}
// found search word in contents
$u.each(_o, function(o) {
var _files = o.files;
if (_files === undefined)
return
if (_files.length === undefined)
_files = [_files];
files = files.concat(_files);
// set score for the word in each file to Scorer.term
for (j = 0; j < _files.length; j++) {
file = _files[j];
if (!(file in scoreMap))
scoreMap[file] = {};
scoreMap[file][word] = o.score;
}
});
// create the mapping
for (j = 0; j < files.length; j++) {
file = files[j];
if (file in fileMap && fileMap[file].indexOf(word) === -1)
fileMap[file].push(word);
else
fileMap[file] = [word];
}
}
// now check if the files don't contain excluded terms
for (file in fileMap) {
var valid = true;
// check if all requirements are matched
var filteredTermCount = // as search terms with length < 3 are discarded: ignore
searchterms.filter(function(term){return term.length > 2}).length
if (
fileMap[file].length != searchterms.length &&
fileMap[file].length != filteredTermCount
) continue;
// ensure that none of the excluded terms is in the search result
for (i = 0; i < excluded.length; i++) {
if (terms[excluded[i]] == file ||
titleterms[excluded[i]] == file ||
$u.contains(terms[excluded[i]] || [], file) ||
$u.contains(titleterms[excluded[i]] || [], file)) {
valid = false;
break;
}
}
// if we have still a valid result we can add it to the result list
if (valid) {
// select one (max) score for the file.
// for better ranking, we should calculate ranking by using words statistics like basic tf-idf...
var score = $u.max($u.map(fileMap[file], function(w){return scoreMap[file][w]}));
results.push([docnames[file], titles[file], '', null, score, filenames[file]]);
}
}
return results;
},
/**
* helper function to return a node containing the
* search summary for a given text. keywords is a list
* of stemmed words, hlwords is the list of normal, unstemmed
* words. the first one is used to find the occurrence, the
* latter for highlighting it.
*/
makeSearchSummary : function(htmlText, keywords, hlwords) {
var text = Search.htmlToText(htmlText);
if (text == "") {
return null;
}
var textLower = text.toLowerCase();
var start = 0;
$.each(keywords, function() {
var i = textLower.indexOf(this.toLowerCase());
if (i > -1)
start = i;
});
start = Math.max(start - 120, 0);
var excerpt = ((start > 0) ? '...' : '') +
$.trim(text.substr(start, 240)) +
((start + 240 - text.length) ? '...' : '');
var rv = $('<p class="context"></p>').text(excerpt);
$.each(hlwords, function() {
rv = rv.highlightText(this, 'highlighted');
});
return rv;
}
};
$(document).ready(function() {
Search.init();
}); | PypiClean |
/Flask%20of%20Cinema-1.0.0.tar.gz/Flask of Cinema-1.0.0/static/js/waves.js | ;(function(window) {
'use strict';
var Waves = Waves || {};
var $$ = document.querySelectorAll.bind(document);
// Find exact position of element
function isWindow(obj) {
return obj !== null && obj === obj.window;
}
function getWindow(elem) {
return isWindow(elem) ? elem : elem.nodeType === 9 && elem.defaultView;
}
function offset(elem) {
var docElem, win,
box = {top: 0, left: 0},
doc = elem && elem.ownerDocument;
docElem = doc.documentElement;
if (typeof elem.getBoundingClientRect !== typeof undefined) {
box = elem.getBoundingClientRect();
}
win = getWindow(doc);
return {
top: box.top + win.pageYOffset - docElem.clientTop,
left: box.left + win.pageXOffset - docElem.clientLeft
};
}
function convertStyle(obj) {
var style = '';
for (var a in obj) {
if (obj.hasOwnProperty(a)) {
style += (a + ':' + obj[a] + ';');
}
}
return style;
}
var Effect = {
// Effect delay
duration: 750,
show: function(e, element) {
// Disable right click
if (e.button === 2) {
return false;
}
var el = element || this;
// Create ripple
var ripple = document.createElement('div');
ripple.className = 'waves-ripple';
el.appendChild(ripple);
// Get click coordinate and element witdh
var pos = offset(el);
var relativeY = (e.pageY - pos.top);
var relativeX = (e.pageX - pos.left);
var scale = 'scale('+((el.clientWidth / 100) * 10)+')';
// Support for touch devices
if ('touches' in e) {
relativeY = (e.touches[0].pageY - pos.top);
relativeX = (e.touches[0].pageX - pos.left);
}
// Attach data to element
ripple.setAttribute('data-hold', Date.now());
ripple.setAttribute('data-scale', scale);
ripple.setAttribute('data-x', relativeX);
ripple.setAttribute('data-y', relativeY);
// Set ripple position
var rippleStyle = {
'top': relativeY+'px',
'left': relativeX+'px'
};
ripple.className = ripple.className + ' waves-notransition';
ripple.setAttribute('style', convertStyle(rippleStyle));
ripple.className = ripple.className.replace('waves-notransition', '');
// Scale the ripple
rippleStyle['-webkit-transform'] = scale;
rippleStyle['-moz-transform'] = scale;
rippleStyle['-ms-transform'] = scale;
rippleStyle['-o-transform'] = scale;
rippleStyle.transform = scale;
rippleStyle.opacity = '1';
rippleStyle['-webkit-transition-duration'] = Effect.duration + 'ms';
rippleStyle['-moz-transition-duration'] = Effect.duration + 'ms';
rippleStyle['-o-transition-duration'] = Effect.duration + 'ms';
rippleStyle['transition-duration'] = Effect.duration + 'ms';
rippleStyle['-webkit-transition-timing-function'] = 'cubic-bezier(0.250, 0.460, 0.450, 0.940)';
rippleStyle['-moz-transition-timing-function'] = 'cubic-bezier(0.250, 0.460, 0.450, 0.940)';
rippleStyle['-o-transition-timing-function'] = 'cubic-bezier(0.250, 0.460, 0.450, 0.940)';
rippleStyle['transition-timing-function'] = 'cubic-bezier(0.250, 0.460, 0.450, 0.940)';
ripple.setAttribute('style', convertStyle(rippleStyle));
},
hide: function(e) {
TouchHandler.touchup(e);
var el = this;
var width = el.clientWidth * 1.4;
// Get first ripple
var ripple = null;
var ripples = el.getElementsByClassName('waves-ripple');
if (ripples.length > 0) {
ripple = ripples[ripples.length - 1];
} else {
return false;
}
var relativeX = ripple.getAttribute('data-x');
var relativeY = ripple.getAttribute('data-y');
var scale = ripple.getAttribute('data-scale');
// Get delay beetween mousedown and mouse leave
var diff = Date.now() - Number(ripple.getAttribute('data-hold'));
var delay = 350 - diff;
if (delay < 0) {
delay = 0;
}
// Fade out ripple after delay
setTimeout(function() {
var style = {
'top': relativeY+'px',
'left': relativeX+'px',
'opacity': '0',
// Duration
'-webkit-transition-duration': Effect.duration + 'ms',
'-moz-transition-duration': Effect.duration + 'ms',
'-o-transition-duration': Effect.duration + 'ms',
'transition-duration': Effect.duration + 'ms',
'-webkit-transform': scale,
'-moz-transform': scale,
'-ms-transform': scale,
'-o-transform': scale,
'transform': scale,
};
ripple.setAttribute('style', convertStyle(style));
setTimeout(function() {
try {
el.removeChild(ripple);
} catch(e) {
return false;
}
}, Effect.duration);
}, delay);
},
// Little hack to make <input> can perform waves effect
wrapInput: function(elements) {
for (var a = 0; a < elements.length; a++) {
var el = elements[a];
if (el.tagName.toLowerCase() === 'input') {
var parent = el.parentNode;
// If input already have parent just pass through
if (parent.tagName.toLowerCase() === 'i' && parent.className.indexOf('waves-effect') !== -1) {
continue;
}
// Put element class and style to the specified parent
var wrapper = document.createElement('i');
wrapper.className = el.className + ' waves-input-wrapper';
var elementStyle = el.getAttribute('style');
if (!elementStyle) {
elementStyle = '';
}
wrapper.setAttribute('style', elementStyle);
el.className = 'waves-button-input';
el.removeAttribute('style');
// Put element as child
parent.replaceChild(wrapper, el);
wrapper.appendChild(el);
}
}
}
};
/**
* Disable mousedown event for 500ms during and after touch
*/
var TouchHandler = {
/* uses an integer rather than bool so there's no issues with
* needing to clear timeouts if another touch event occurred
* within the 500ms. Cannot mouseup between touchstart and
* touchend, nor in the 500ms after touchend. */
touches: 0,
allowEvent: function(e) {
var allow = true;
if (e.type === 'touchstart') {
TouchHandler.touches += 1; //push
} else if (e.type === 'touchend' || e.type === 'touchcancel') {
setTimeout(function() {
if (TouchHandler.touches > 0) {
TouchHandler.touches -= 1; //pop after 500ms
}
}, 500);
} else if (e.type === 'mousedown' && TouchHandler.touches > 0) {
allow = false;
}
return allow;
},
touchup: function(e) {
TouchHandler.allowEvent(e);
}
};
/**
* Delegated click handler for .waves-effect element.
* returns null when .waves-effect element not in "click tree"
*/
function getWavesEffectElement(e) {
if (TouchHandler.allowEvent(e) === false) {
return null;
}
var element = null;
var target = e.target || e.srcElement;
while (target.parentNode !== null) {
if (!(target instanceof SVGElement) && target.className.indexOf('waves-effect') !== -1) {
element = target;
break;
}
target = target.parentNode;
}
return element;
}
/**
* Bubble the click and show effect if .waves-effect elem was found
*/
function showEffect(e) {
var element = getWavesEffectElement(e);
if (element !== null) {
Effect.show(e, element);
if ('ontouchstart' in window) {
element.addEventListener('touchend', Effect.hide, false);
element.addEventListener('touchcancel', Effect.hide, false);
}
element.addEventListener('mouseup', Effect.hide, false);
element.addEventListener('mouseleave', Effect.hide, false);
element.addEventListener('dragend', Effect.hide, false);
}
}
Waves.displayEffect = function(options) {
options = options || {};
if ('duration' in options) {
Effect.duration = options.duration;
}
//Wrap input inside <i> tag
Effect.wrapInput($$('.waves-effect'));
if ('ontouchstart' in window) {
document.body.addEventListener('touchstart', showEffect, false);
}
document.body.addEventListener('mousedown', showEffect, false);
};
/**
* Attach Waves to an input element (or any element which doesn't
* bubble mouseup/mousedown events).
* Intended to be used with dynamically loaded forms/inputs, or
* where the user doesn't want a delegated click handler.
*/
Waves.attach = function(element) {
//FUTURE: automatically add waves classes and allow users
// to specify them with an options param? Eg. light/classic/button
if (element.tagName.toLowerCase() === 'input') {
Effect.wrapInput([element]);
element = element.parentNode;
}
if ('ontouchstart' in window) {
element.addEventListener('touchstart', showEffect, false);
}
element.addEventListener('mousedown', showEffect, false);
};
window.Waves = Waves;
document.addEventListener('DOMContentLoaded', function() {
Waves.displayEffect();
}, false);
})(window); | PypiClean |
/Newcalls-0.0.1-cp37-cp37m-win_amd64.whl/newcalls/node_modules/minizlib/constants.js | const realZlibConstants = require('zlib').constants ||
/* istanbul ignore next */ { ZLIB_VERNUM: 4736 }
module.exports = Object.freeze(Object.assign(Object.create(null), {
Z_NO_FLUSH: 0,
Z_PARTIAL_FLUSH: 1,
Z_SYNC_FLUSH: 2,
Z_FULL_FLUSH: 3,
Z_FINISH: 4,
Z_BLOCK: 5,
Z_OK: 0,
Z_STREAM_END: 1,
Z_NEED_DICT: 2,
Z_ERRNO: -1,
Z_STREAM_ERROR: -2,
Z_DATA_ERROR: -3,
Z_MEM_ERROR: -4,
Z_BUF_ERROR: -5,
Z_VERSION_ERROR: -6,
Z_NO_COMPRESSION: 0,
Z_BEST_SPEED: 1,
Z_BEST_COMPRESSION: 9,
Z_DEFAULT_COMPRESSION: -1,
Z_FILTERED: 1,
Z_HUFFMAN_ONLY: 2,
Z_RLE: 3,
Z_FIXED: 4,
Z_DEFAULT_STRATEGY: 0,
DEFLATE: 1,
INFLATE: 2,
GZIP: 3,
GUNZIP: 4,
DEFLATERAW: 5,
INFLATERAW: 6,
UNZIP: 7,
BROTLI_DECODE: 8,
BROTLI_ENCODE: 9,
Z_MIN_WINDOWBITS: 8,
Z_MAX_WINDOWBITS: 15,
Z_DEFAULT_WINDOWBITS: 15,
Z_MIN_CHUNK: 64,
Z_MAX_CHUNK: Infinity,
Z_DEFAULT_CHUNK: 16384,
Z_MIN_MEMLEVEL: 1,
Z_MAX_MEMLEVEL: 9,
Z_DEFAULT_MEMLEVEL: 8,
Z_MIN_LEVEL: -1,
Z_MAX_LEVEL: 9,
Z_DEFAULT_LEVEL: -1,
BROTLI_OPERATION_PROCESS: 0,
BROTLI_OPERATION_FLUSH: 1,
BROTLI_OPERATION_FINISH: 2,
BROTLI_OPERATION_EMIT_METADATA: 3,
BROTLI_MODE_GENERIC: 0,
BROTLI_MODE_TEXT: 1,
BROTLI_MODE_FONT: 2,
BROTLI_DEFAULT_MODE: 0,
BROTLI_MIN_QUALITY: 0,
BROTLI_MAX_QUALITY: 11,
BROTLI_DEFAULT_QUALITY: 11,
BROTLI_MIN_WINDOW_BITS: 10,
BROTLI_MAX_WINDOW_BITS: 24,
BROTLI_LARGE_MAX_WINDOW_BITS: 30,
BROTLI_DEFAULT_WINDOW: 22,
BROTLI_MIN_INPUT_BLOCK_BITS: 16,
BROTLI_MAX_INPUT_BLOCK_BITS: 24,
BROTLI_PARAM_MODE: 0,
BROTLI_PARAM_QUALITY: 1,
BROTLI_PARAM_LGWIN: 2,
BROTLI_PARAM_LGBLOCK: 3,
BROTLI_PARAM_DISABLE_LITERAL_CONTEXT_MODELING: 4,
BROTLI_PARAM_SIZE_HINT: 5,
BROTLI_PARAM_LARGE_WINDOW: 6,
BROTLI_PARAM_NPOSTFIX: 7,
BROTLI_PARAM_NDIRECT: 8,
BROTLI_DECODER_RESULT_ERROR: 0,
BROTLI_DECODER_RESULT_SUCCESS: 1,
BROTLI_DECODER_RESULT_NEEDS_MORE_INPUT: 2,
BROTLI_DECODER_RESULT_NEEDS_MORE_OUTPUT: 3,
BROTLI_DECODER_PARAM_DISABLE_RING_BUFFER_REALLOCATION: 0,
BROTLI_DECODER_PARAM_LARGE_WINDOW: 1,
BROTLI_DECODER_NO_ERROR: 0,
BROTLI_DECODER_SUCCESS: 1,
BROTLI_DECODER_NEEDS_MORE_INPUT: 2,
BROTLI_DECODER_NEEDS_MORE_OUTPUT: 3,
BROTLI_DECODER_ERROR_FORMAT_EXUBERANT_NIBBLE: -1,
BROTLI_DECODER_ERROR_FORMAT_RESERVED: -2,
BROTLI_DECODER_ERROR_FORMAT_EXUBERANT_META_NIBBLE: -3,
BROTLI_DECODER_ERROR_FORMAT_SIMPLE_HUFFMAN_ALPHABET: -4,
BROTLI_DECODER_ERROR_FORMAT_SIMPLE_HUFFMAN_SAME: -5,
BROTLI_DECODER_ERROR_FORMAT_CL_SPACE: -6,
BROTLI_DECODER_ERROR_FORMAT_HUFFMAN_SPACE: -7,
BROTLI_DECODER_ERROR_FORMAT_CONTEXT_MAP_REPEAT: -8,
BROTLI_DECODER_ERROR_FORMAT_BLOCK_LENGTH_1: -9,
BROTLI_DECODER_ERROR_FORMAT_BLOCK_LENGTH_2: -10,
BROTLI_DECODER_ERROR_FORMAT_TRANSFORM: -11,
BROTLI_DECODER_ERROR_FORMAT_DICTIONARY: -12,
BROTLI_DECODER_ERROR_FORMAT_WINDOW_BITS: -13,
BROTLI_DECODER_ERROR_FORMAT_PADDING_1: -14,
BROTLI_DECODER_ERROR_FORMAT_PADDING_2: -15,
BROTLI_DECODER_ERROR_FORMAT_DISTANCE: -16,
BROTLI_DECODER_ERROR_DICTIONARY_NOT_SET: -19,
BROTLI_DECODER_ERROR_INVALID_ARGUMENTS: -20,
BROTLI_DECODER_ERROR_ALLOC_CONTEXT_MODES: -21,
BROTLI_DECODER_ERROR_ALLOC_TREE_GROUPS: -22,
BROTLI_DECODER_ERROR_ALLOC_CONTEXT_MAP: -25,
BROTLI_DECODER_ERROR_ALLOC_RING_BUFFER_1: -26,
BROTLI_DECODER_ERROR_ALLOC_RING_BUFFER_2: -27,
BROTLI_DECODER_ERROR_ALLOC_BLOCK_TYPE_TREES: -30,
BROTLI_DECODER_ERROR_UNREACHABLE: -31,
}, realZlibConstants)) | PypiClean |
/KD_Lib-0.0.32.tar.gz/KD_Lib-0.0.32/docs/usage/tutorials/VirtualTeacher.rst | ===========================================
Virtual Teacher using KD_Lib
===========================================
`Paper <https://arxiv.org/abs/1909.11723>`_
* A teacher is designed with 100% accuracy using label smoothening regularization
* The teacher model which outputs distribution for classes as the following -
.. image:: ../../assets/VT.png
:width: 400
where K is the total number of classes, c is the correct label and a is the correct probability for the
correct class
To use the virtual teacher algorithm with the correct classes assigned probabilities of 0.9 -
.. code-block:: python
import torch
import torch.nn as nn
import torch.optim as optim
from torchvision import datasets, transforms
from KD_Lib.KD import VirtualTeacher
# Define datasets, dataloaders, models and optimizers
train_loader = torch.utils.data.DataLoader(
datasets.MNIST(
"mnist_data",
train=True,
download=True,
transform=transforms.Compose(
[transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))]
),
),
batch_size=32,
shuffle=True,
)
test_loader = torch.utils.data.DataLoader(
datasets.MNIST(
"mnist_data",
train=False,
transform=transforms.Compose(
[transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))]
),
),
batch_size=32,
shuffle=True,
)
# Set device to be trained on
device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
# Define student and teacher models
student_model = <your model>
# Define optimizer
student_optimizer = optim.SGD(student_model.parameters(), lr=0.01)
# Train using KD_Lib
distiller = VirtualTeacher(student_model, train_loader, test_loader, student_optimizer,
correct_prob=0.9, device=device)
distiller.train_student(epochs=5) # Train the student model
distiller.evaluate() # Evaluate the student model
| PypiClean |
/LiDAR_Lite-0.1.0-py3-none-any.whl/LiDAR_Lite.py | import smbus2 as smbus
class LiDAR_Lite():
def __init__(self, addr=0x62):
"""Creates the LiDAR_Lite object
Args:
addr (int, optional): the I2C address of the LiDAR-Lite
"""
self.reg = {
"ACQ_COMMAND": 0x00, # Device command
"STATUS": 0x01, # System status
"SIG_COUNT_VAL": 0x02, # Maximum acquisition count
"ACQ_CONFIG_REG": 0x04, # Acquisition mode control
"VELOCITY": 0x09, # Velocity measurement output
"PEAK_CORR": 0x0c, # Peak value in correlation record
"NOISE_PEAK": 0x0d, # Correlation record noise floor
"SIGNAL_STRENGTH": 0x0e, # Received signal strength
"FULL_DELAY_HIGH": 0x0f, # Distance measurement high byte
"FULL_DELAY_LOW": 0x10, # Distance measurement low byte
"OUTER_LOOP_COUNT": 0x11, # Burst measurement count control
"REF_COUNT_VAL": 0x12, # Reference acquisition count
"LAST_DELAY_HIGH": 0x14, # Previous distance measurement high byte
"LAST_DELAY_LOW": 0x15, # Previous distance measurement low byte
"UNIT_ID_HIGH": 0x16, # Serial number high byte
"UNIT_ID_LOW": 0x17, # Serial number low byte
"I2C_ID_HIGH": 0x18, # Write serial number high byte for I2C address unlock
"I2C_ID_LOW": 0x19, # Write serial number low byte for I2C address unlock
"I2C_SEC_ADDR": 0x1a, # Write new I2C address after unlock
"THRESHOLD_BYPASS": 0x1c, # Peak detection threshold bypass
"I2C_CONFIG": 0x1e, # Default address response control
"COMMAND": 0x40, # State command
"MEASURE_DELAY": 0x45, # Delay between automatic measurements
"PEAK_BCK": 0x4c, # Second largest peak value in correlation record
"CORR_DATA": 0x52, # Correlation record data low byte
"CORR_DATA_SIGN": 0x53, # Correlation record data high byte
"ACQ_SETTINGS": 0x5d, # Correlation record memory bank select
"POWER_CONTROL": 0x65, # Power state control
"FULL_DELAY": 0x0f,
"LAST_DELAY": 0x14,
"UNIT_ID": 0x16,
"I2C_ID": 0x18,
}
self.addr = addr
self.count = 0
def connect(self, bus):
"""Connects the internal SMBus instance to an I2C bus
Args:
bus (int): I2C bus number (i.e. 1 corresponds to /dev/i2c-1)
"""
self.bus = smbus.SMBus(bus)
def wait_until_not_busy(self):
"""Waits until the LiDAR-Lite is ready for a new command
"""
status = 1
while status != 0:
status = self.read_reg("STATUS") & 0b1
def get_distance(self):
"""Gets the current LiDAR distance
Returns:
int: distance (in cm)
"""
self.write_reg("ACQ_COMMAND", 0x04)
self.wait_until_not_busy()
return self.read_reg2("FULL_DELAY")
def set_maximum_acquisition_count(self, mac=0x80):
"""The maximum acquisition count limits the number of times the device
will integrate acquisitions to find a correlation record peak (from a
returned signal), which occurs at long range or with low target
reflectivity. This controls the minimum measurement rate and maximum
range. The unit-less relationship is roughly as follows: rate = 1/n and
range = n^(1/4), where n is the number of acquisitions.
Args:
mac (int, optional): maximum acquisition count
"""
self.write_reg("SIG_COUNT_VAL", mac)
def set_measurement_quick_termination_detection(self, mqtd=False):
"""If set, the device will terminate a distance measurement early if it
anticipates that the signal peak in the correlation record will reach
maximum value. This allows for faster and slightly less accurate
operation at strong signal strengths without sacrificing long range
performance.
Args:
mqtd (bool, optional): measurement quick termination detection
"""
self.set_ACR_bit(3, not mqtd)
def set_detection_sensitivity(self, ds=0x00):
"""The default valid measurement detection algorithm is based on the
peak value, signal strength, and noise in the correlation record. This
can be overridden to become a simple threshold criterion by setting a
non-zero value. Recommended non-default values are 0x20 for higher
sensitivity with more frequent erroneous measurements, and 0x60 for
reduced sensitivity and fewer erroneous measurements.
Args:
ds (int, optional): detection sensitivity
"""
self.write_reg("THRESHOLD_BYPASS", ds)
def set_bm_repetition_count(self, rc=0x00):
"""This controls the number of times the device will retrigger itself.
Values 0x00 or 0x01 result in the default one measurement per command.
Values 0x02 to 0xfe directly set the repetition count. Value 0xff will
enable free running mode after the host device sends an initial
measurement command.
Args:
rc (int, optional): repetition count
Raises:
ValueError: if the repetition count is out of range
"""
if rc < 0x00 or rc > 0xff:
raise ValueError("Repetition count out of range 0x00 - 0xff")
self.write_reg("OUTER_LOOP_COUNT", rc)
def set_bm_delay(self, delay=0x14):
"""This sets the default delay between automatic measurements. The
default delay (0xc8) corresponds to a 10 Hz repetition rate. A delay
value of 0x14 roughly corresponds to 100Hz.
Args:
delay (int, optional): delay between automatic measurements
"""
self.set_ACR_bit(5, True)
self.write_reg("MEASURE_DELAY", delay)
def reset_bm_delay(self):
"""This resets the delay between automatic measurements to the default
delay of 10 Hz (0xc8).
"""
self.set_bm_delay()
self.set_ACR_bit(5, False)
def get_velocity(self):
"""The velocity measurement is the difference between the current
measurement and the previous one, resulting in a signed (2’s complement)
8-bit number in cm. Positive velocity is away from the device. This can
be combined with free running mode for a constant measurement frequency.
The default free running frequency of 10 Hz therefore results in a
velocity measurement in .1 m/s.
Returns:
int: velocity
"""
vel = self.read_reg("VELOCITY")
return signed(vel)
def change_I2C_address(self, addr=0x62):
"""The I2C address can be changed from its default value. Available
addresses are 7-bit values with a ‘0’ in the least significant bit (even
hexadecimal numbers).
Args:
addr (int, optional): new I2C address
Raises:
ValueError: if I2C address is invalid
"""
if addr & 0b1 != 0:
raise ValueError("Least significant bit is not 0")
if addr >> 7 != 0:
raise ValueError("Address is greater than 7 bits")
sn = self.read_reg2("UNIT_ID")
self.write_reg2("I2C_ID", sn)
self.write_reg("I2C_SEC_ADDR", addr)
self.addr = addr
self.write_reg("I2C_CONFIG", 0x08)
def set_power_control(self, disable_rc=False, device_sleep=False):
"""Disabling the receiver circuit saves roughly 40mA. After being
re-enabled, the receiver circuit stabilizes by the time a measurement
can be performed. Putting the device in sleep mode until the next I2C
transaction saves 20mA. Wake-up time is only around 2 m/s shorter than
the full power-on time. Both will reset all registers.
Args:
disable_rc (bool, optional): disable receiver circuit
device_sleep (bool, optional): put the device in sleep mode
"""
pc = 0
if disable_rc:
pc |= 0b001
if device_sleep:
pc |= 0b100
self.write_reg("POWER_CONTROL", pc)
def set_ACR_bit(self, bit, val=True):
"""Sets the specified bit in ACQ_CONFIG_REG to the specified value.
Args:
bit (int): the bit to set
val (bool, optional): the value to set the bit to
"""
acr = self.read_reg("ACQ_CONFIG_REG")
if val:
acr |= 1 << bit
else:
acr &= 0b1111111 - (1 << bit)
self.write_reg("ACQ_CONFIG_REG", acr)
def read_reg(self, reg):
"""Reads a specified register from the LiDAR
Args:
reg (string): the name of the register (contained in self.reg)
Returns:
byte: the value of the register (8 bits)
"""
return self.bus.read_byte_data(self.addr, self.reg[reg])
def read_reg2(self, reg):
"""Reads 2 registers from the LiDAR
Args:
reg (string): the name of the first register (contained in self.reg)
Returns:
byte: the value of both registers (16 bits)
"""
high_byte = self.bus.read_byte_data(self.addr, self.reg[reg])
low_byte = self.bus.read_byte_data(self.addr, self.reg[reg] + 1)
return (high_byte << 8) + low_byte
def write_reg(self, reg, val):
"""Writes a specified value into a specified register
Args:
reg (string): the name of the register (contained in self.reg)
val (byte): the value to write to the register (8 bits)
"""
self.bus.write_byte_data(self.addr, self.reg[reg], val)
def write_reg2(self, reg, val):
"""Writes a specified value into 2 registers
Args:
reg (string): the name of the first register (contained in self.reg)
val (byte): the value to write into both registers (16 bits)
"""
self.bus.write_byte_data(self.addr, self.reg[reg], val >> 8)
self.bus.write_byte_data(self.addr, self.reg[reg] + 1, val & 0b11111111)
def signed(self, val):
"""Converts a signed 8 bit value into a signed number
Args:
val (byte): 8-bit signed value
Returns:
int: signed number
"""
if val > 0b01111111:
return (0b100000000 - val) * (-1)
else:
return val | PypiClean |
/observations-0.1.4.tar.gz/observations-0.1.4/observations/r/cbpp.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import numpy as np
import os
import sys
from observations.util import maybe_download_and_extract
def cbpp(path):
"""Contagious bovine pleuropneumonia
Contagious bovine pleuropneumonia (CBPP) is a major disease of cattle in
Africa, caused by a mycoplasma. This dataset describes the serological
incidence of CBPP in zebu cattle during a follow-up survey implemented
in 15 commercial herds located in the Boji district of Ethiopia. The
goal of the survey was to study the within-herd spread of CBPP in newly
infected herds. Blood samples were quarterly collected from all animals
of these herds to determine their CBPP status. These data were used to
compute the serological incidence of CBPP (new cases occurring during a
given time period). Some data are missing (lost to follow-up).
A data frame with 56 observations on the following 4 variables.
`herd`
A factor identifying the herd (1 to 15).
`incidence`
The number of new serological cases for a given herd and time
period.
`size`
A numeric vector describing herd size at the beginning of a given
time period.
`period`
A factor with levels `1` to `4`.
Lesnoff, M., Laval, G., Bonnet, P., Abdicho, S., Workalemahu, A., Kifle,
D., Peyraud, A., Lancelot, R., Thiaucourt, F. (2004) Within-herd spread
of contagious bovine pleuropneumonia in Ethiopian highlands. *Preventive
Veterinary Medicine* **64**, 27–40.
Args:
path: str.
Path to directory which either stores file or otherwise file will
be downloaded and extracted there.
Filename is `cbpp.csv`.
Returns:
Tuple of np.ndarray `x_train` with 56 rows and 4 columns and
dictionary `metadata` of column headers (feature names).
"""
import pandas as pd
path = os.path.expanduser(path)
filename = 'cbpp.csv'
if not os.path.exists(os.path.join(path, filename)):
url = 'http://dustintran.com/data/r/lme4/cbpp.csv'
maybe_download_and_extract(path, url,
save_file_name='cbpp.csv',
resume=False)
data = pd.read_csv(os.path.join(path, filename), index_col=0,
parse_dates=True)
x_train = data.values
metadata = {'columns': data.columns}
return x_train, metadata | PypiClean |
/FreePyBX-1.0-RC1.tar.gz/FreePyBX-1.0-RC1/freepybx/public/js/dojox/grid/enhanced/plugins/GridSource.js.uncompressed.js | define("dojox/grid/enhanced/plugins/GridSource", [
"dojo/_base/declare",
"dojo/_base/array",
"dojo/_base/lang",
"dojo/dnd/Source",
"./DnD"
], function(declare, array, lang, Source, DnD){
var _joinToArray = function(arrays){
var a = arrays[0];
for(var i = 1; i < arrays.length; ++i){
a = a.concat(arrays[i]);
}
return a;
};
var GridDnDSource = lang.getObject("dojox.grid.enhanced.plugins.GridDnDSource");
return declare("dojox.grid.enhanced.plugins.GridSource", Source, {
// summary:
// A special source that can accept grid contents.
// Only for non-grid widgets or domNodes.
accept: ["grid/cells", "grid/rows", "grid/cols", "text"],
// insertNodesForGrid:
// If you'd like to insert some sort of nodes into your dnd source, turn this on,
// and override getCellContent/getRowContent/getColumnContent
// to populate the dnd data in your desired format.
insertNodesForGrid: false,
markupFactory: function(params, node){
cls = lang.getObject("dojox.grid.enhanced.plugins.GridSource");
return new cls(node, params);
},
checkAcceptance: function(source, nodes){
if(source instanceof GridDnDSource){
if(nodes[0]){
var item = source.getItem(nodes[0].id);
if(item && (array.indexOf(item.type, "grid/rows") >= 0 || array.indexOf(item.type, "grid/cells") >= 0) &&
!source.dndPlugin._allDnDItemsLoaded()){
return false;
}
}
this.sourcePlugin = source.dndPlugin;
}
return this.inherited(arguments);
},
onDraggingOver: function(){
if(this.sourcePlugin){
this.sourcePlugin._isSource = true;
}
},
onDraggingOut: function(){
if(this.sourcePlugin){
this.sourcePlugin._isSource = false;
}
},
onDropExternal: function(source, nodes, copy){
if(source instanceof GridDnDSource){
var ranges = array.map(nodes, function(node){
return source.getItem(node.id).data;
});
var item = source.getItem(nodes[0].id);
var grid = item.dndPlugin.grid;
var type = item.type[0];
var range;
try{
switch(type){
case "grid/cells":
nodes[0].innerHTML = this.getCellContent(grid, ranges[0].min, ranges[0].max) || "";
this.onDropGridCells(grid, ranges[0].min, ranges[0].max);
break;
case "grid/rows":
range = _joinToArray(ranges);
nodes[0].innerHTML = this.getRowContent(grid, range) || "";
this.onDropGridRows(grid, range);
break;
case "grid/cols":
range = _joinToArray(ranges);
nodes[0].innerHTML = this.getColumnContent(grid, range) || "";
this.onDropGridColumns(grid, range);
break;
}
if(this.insertNodesForGrid){
this.selectNone();
this.insertNodes(true, [nodes[0]], this.before, this.current);
}
item.dndPlugin.onDragOut(!copy);
}catch(e){
console.warn("GridSource.onDropExternal() error:",e);
}
}else{
this.inherited(arguments);
}
},
getCellContent: function(grid, leftTopCell, rightBottomCell){
// summary:
// Fill node innerHTML for dnd grid cells.
// sample code:
// var cells = grid.layout.cells;
// var store = grid.store;
// var cache = grid._by_idx;
// var res = "Grid Cells from " + grid.id + ":<br/>";
// for(var r = leftTopCell.row; r <= rightBottomCell.row; ++r){
// for(var c = leftTopCell.col; c <= rightBottomCell.col; ++c){
// res += store.getValue(cache[r].item, cells[c].field) + ", ";
// }
// res = res.substring(0, res.length - 2) + ";<br/>";
// }
// return res;
},
getRowContent: function(grid, rowIndexes){
// summary:
// Fill node innerHTML for dnd grid rows.
// sample code:
// var cells = grid.layout.cells;
// var store = grid.store;
// var cache = grid._by_idx;
// var res = "Grid Rows from " + grid.id + ":<br/>";
// for(var i = 0; i < rowIndexes.length; ++i){
// var r = rowIndexes[i];
// res += "Row " + r + ": ";
// for(var j = 0; j < cells.length; ++j){
// if(!cells[j].hidden){
// res += store.getValue(cache[r].item, cells[j].field) + ", ";
// }
// }
// res = res.substring(0, res.length - 2) + ";<br/>";
// }
// return res;
},
getColumnContent: function(grid, colIndexes){
// summary:
// Fill node innerHTML for dnd grid columns.
// sample code:
// var cells = grid.layout.cells;
// var res = "Grid Columns from " + grid.id + ":";
// for(var i = 0; i < colIndexes.length; ++i){
// var c = colIndexes[i];
// res += (cells[c].name || cells[c].field) + ", ";
// }
// return res.substring(0, res.length - 2);
},
onDropGridCells: function(grid, leftTopCell, rightBottomCell){
},
onDropGridRows: function(grid, rowIndexes){
},
onDropGridColumns: function(grid, colIndexes){
}
});
}); | PypiClean |
/DFRobot_EC_PH_ADC-0.1.1.tar.gz/DFRobot_EC_PH_ADC-0.1.1/DFRobot/DFR_ADS1115.py | import smbus
import time
# Get I2C bus
bus = smbus.SMBus(1)
# I2C address of the device
ADS1115_IIC_ADDRESS0 = 0x48
ADS1115_IIC_ADDRESS1 = 0x49
# ADS1115 Register Map
ADS1115_REG_POINTER_CONVERT = 0x00 # Conversion register
ADS1115_REG_POINTER_CONFIG = 0x01 # Configuration register
ADS1115_REG_POINTER_LOWTHRESH = 0x02 # Lo_thresh register
ADS1115_REG_POINTER_HITHRESH = 0x03 # Hi_thresh register
# ADS1115 Configuration Register
ADS1115_REG_CONFIG_OS_NOEFFECT = 0x00 # No effect
ADS1115_REG_CONFIG_OS_SINGLE = 0x80 # Begin a single conversion
ADS1115_REG_CONFIG_MUX_DIFF_0_1 = 0x00 # Differential P = AIN0, N = AIN1 (default)
ADS1115_REG_CONFIG_MUX_DIFF_0_3 = 0x10 # Differential P = AIN0, N = AIN3
ADS1115_REG_CONFIG_MUX_DIFF_1_3 = 0x20 # Differential P = AIN1, N = AIN3
ADS1115_REG_CONFIG_MUX_DIFF_2_3 = 0x30 # Differential P = AIN2, N = AIN3
ADS1115_REG_CONFIG_MUX_SINGLE_0 = 0x40 # Single-ended P = AIN0, N = GND
ADS1115_REG_CONFIG_MUX_SINGLE_1 = 0x50 # Single-ended P = AIN1, N = GND
ADS1115_REG_CONFIG_MUX_SINGLE_2 = 0x60 # Single-ended P = AIN2, N = GND
ADS1115_REG_CONFIG_MUX_SINGLE_3 = 0x70 # Single-ended P = AIN3, N = GND
ADS1115_REG_CONFIG_PGA_6_144V = 0x00 # +/-6.144V range = Gain 2/3
ADS1115_REG_CONFIG_PGA_4_096V = 0x02 # +/-4.096V range = Gain 1
ADS1115_REG_CONFIG_PGA_2_048V = 0x04 # +/-2.048V range = Gain 2 (default)
ADS1115_REG_CONFIG_PGA_1_024V = 0x06 # +/-1.024V range = Gain 4
ADS1115_REG_CONFIG_PGA_0_512V = 0x08 # +/-0.512V range = Gain 8
ADS1115_REG_CONFIG_PGA_0_256V = 0x0A # +/-0.256V range = Gain 16
ADS1115_REG_CONFIG_MODE_CONTIN = 0x00 # Continuous conversion mode
ADS1115_REG_CONFIG_MODE_SINGLE = 0x01 # Power-down single-shot mode (default)
ADS1115_REG_CONFIG_DR_8SPS = 0x00 # 8 samples per second
ADS1115_REG_CONFIG_DR_16SPS = 0x20 # 16 samples per second
ADS1115_REG_CONFIG_DR_32SPS = 0x40 # 32 samples per second
ADS1115_REG_CONFIG_DR_64SPS = 0x60 # 64 samples per second
ADS1115_REG_CONFIG_DR_128SPS = 0x80 # 128 samples per second (default)
ADS1115_REG_CONFIG_DR_250SPS = 0xA0 # 250 samples per second
ADS1115_REG_CONFIG_DR_475SPS = 0xC0 # 475 samples per second
ADS1115_REG_CONFIG_DR_860SPS = 0xE0 # 860 samples per second
ADS1115_REG_CONFIG_CMODE_TRAD = 0x00 # Traditional comparator with hysteresis (default)
ADS1115_REG_CONFIG_CMODE_WINDOW = 0x10 # Window comparator
ADS1115_REG_CONFIG_CPOL_ACTVLOW = 0x00 # ALERT/RDY pin is low when active (default)
ADS1115_REG_CONFIG_CPOL_ACTVHI = 0x08 # ALERT/RDY pin is high when active
ADS1115_REG_CONFIG_CLAT_NONLAT = 0x00 # Non-latching comparator (default)
ADS1115_REG_CONFIG_CLAT_LATCH = 0x04 # Latching comparator
ADS1115_REG_CONFIG_CQUE_1CONV = 0x00 # Assert ALERT/RDY after one conversions
ADS1115_REG_CONFIG_CQUE_2CONV = 0x01 # Assert ALERT/RDY after two conversions
ADS1115_REG_CONFIG_CQUE_4CONV = 0x02 # Assert ALERT/RDY after four conversions
ADS1115_REG_CONFIG_CQUE_NONE = 0x03 # Disable the comparator and put ALERT/RDY in high state (default)
mygain=0x02
coefficient=0.125
addr_G=ADS1115_IIC_ADDRESS0
class ADS1115():
def setGain(self,gain):
global mygain
global coefficient
mygain=gain
if mygain == ADS1115_REG_CONFIG_PGA_6_144V:
coefficient = 0.1875
elif mygain == ADS1115_REG_CONFIG_PGA_4_096V:
coefficient = 0.125
elif mygain == ADS1115_REG_CONFIG_PGA_2_048V:
coefficient = 0.0625
elif mygain == ADS1115_REG_CONFIG_PGA_1_024V:
coefficient = 0.03125
elif mygain == ADS1115_REG_CONFIG_PGA_0_512V:
coefficient = 0.015625
elif mygain == ADS1115_REG_CONFIG_PGA_0_256V:
coefficient = 0.0078125
else:
coefficient = 0.125
def setAddr_ADS1115(self,addr):
global addr_G
addr_G=addr
def setChannel(self,channel):
global mygain
"""Select the Channel user want to use from 0-3
For Single-ended Output
0 : AINP = AIN0 and AINN = GND
1 : AINP = AIN1 and AINN = GND
2 : AINP = AIN2 and AINN = GND
3 : AINP = AIN3 and AINN = GND
For Differential Output
0 : AINP = AIN0 and AINN = AIN1
1 : AINP = AIN0 and AINN = AIN3
2 : AINP = AIN1 and AINN = AIN3
3 : AINP = AIN2 and AINN = AIN3"""
self.channel = channel
while self.channel > 3 :
self.channel = 0
return self.channel
def setSingle(self):
global addr_G
if self.channel == 0:
CONFIG_REG = [ADS1115_REG_CONFIG_OS_SINGLE | ADS1115_REG_CONFIG_MUX_SINGLE_0 | mygain | ADS1115_REG_CONFIG_MODE_CONTIN, ADS1115_REG_CONFIG_DR_128SPS | ADS1115_REG_CONFIG_CQUE_NONE]
elif self.channel == 1:
CONFIG_REG = [ADS1115_REG_CONFIG_OS_SINGLE | ADS1115_REG_CONFIG_MUX_SINGLE_1 | mygain | ADS1115_REG_CONFIG_MODE_CONTIN, ADS1115_REG_CONFIG_DR_128SPS | ADS1115_REG_CONFIG_CQUE_NONE]
elif self.channel == 2:
CONFIG_REG = [ADS1115_REG_CONFIG_OS_SINGLE | ADS1115_REG_CONFIG_MUX_SINGLE_2 | mygain | ADS1115_REG_CONFIG_MODE_CONTIN, ADS1115_REG_CONFIG_DR_128SPS | ADS1115_REG_CONFIG_CQUE_NONE]
elif self.channel == 3:
CONFIG_REG = [ADS1115_REG_CONFIG_OS_SINGLE | ADS1115_REG_CONFIG_MUX_SINGLE_3 | mygain | ADS1115_REG_CONFIG_MODE_CONTIN, ADS1115_REG_CONFIG_DR_128SPS | ADS1115_REG_CONFIG_CQUE_NONE]
bus.write_i2c_block_data(addr_G, ADS1115_REG_POINTER_CONFIG, CONFIG_REG)
def setDifferential(self):
global addr_G
if self.channel == 0:
CONFIG_REG = [ADS1115_REG_CONFIG_OS_SINGLE | ADS1115_REG_CONFIG_MUX_DIFF_0_1 | mygain | ADS1115_REG_CONFIG_MODE_CONTIN, ADS1115_REG_CONFIG_DR_128SPS | ADS1115_REG_CONFIG_CQUE_NONE]
elif self.channel == 1:
CONFIG_REG = [ADS1115_REG_CONFIG_OS_SINGLE | ADS1115_REG_CONFIG_MUX_DIFF_0_3 | mygain | ADS1115_REG_CONFIG_MODE_CONTIN, ADS1115_REG_CONFIG_DR_128SPS | ADS1115_REG_CONFIG_CQUE_NONE]
elif self.channel == 2:
CONFIG_REG = [ADS1115_REG_CONFIG_OS_SINGLE | ADS1115_REG_CONFIG_MUX_DIFF_1_3 | mygain | ADS1115_REG_CONFIG_MODE_CONTIN, ADS1115_REG_CONFIG_DR_128SPS | ADS1115_REG_CONFIG_CQUE_NONE]
elif self.channel == 3:
CONFIG_REG = [ADS1115_REG_CONFIG_OS_SINGLE | ADS1115_REG_CONFIG_MUX_DIFF_2_3 | mygain | ADS1115_REG_CONFIG_MODE_CONTIN, ADS1115_REG_CONFIG_DR_128SPS | ADS1115_REG_CONFIG_CQUE_NONE]
bus.write_i2c_block_data(addr_G, ADS1115_REG_POINTER_CONFIG, CONFIG_REG)
def readValue(self):
"""Read data back from ADS1115_REG_POINTER_CONVERT(0x00), 2 bytes
raw_adc MSB, raw_adc LSB"""
global coefficient
global addr_G
data = bus.read_i2c_block_data(addr_G, ADS1115_REG_POINTER_CONVERT, 2)
# Convert the data
raw_adc = data[0] * 256 + data[1]
if raw_adc > 32767:
raw_adc -= 65535
raw_adc = int(float(raw_adc)*coefficient)
return {'r' : raw_adc}
def readVoltage(self,channel):
self.setChannel(channel)
self.setSingle()
time.sleep(0.1)
return self.readValue()
def ComparatorVoltage(self,channel):
self.setChannel(channel)
self.setDifferential()
time.sleep(0.1)
return self.readValue() | PypiClean |
/EasyAdls-0.1.3.tar.gz/EasyAdls-0.1.3/README.md | ## EasyAdls
Wrapper around the Azure Storage Blobs SDK to make life a bit easier.
### Install
`pip install EasyAdls`
### Examples
Get a client with either a key or sas token:
```
from EasyAdls import EasyBlob
client = EasyBlob(account_name='mystorageaccount',
container='some-container',
credential='key_or_sas_token')
```
Retrieve properties of a blob:
```
# return properties
client.get_properties('blob.jpg')
```
Copy a blob. You can specify another container if needed, default is same container:
```
# copy a blob
client.copy_blob('blob.jpg', 'copy_of_blob.jpg')
client.copy_blob(source_path='blob.jpg',
destination_path='copy_of_blob.jpg',
destination_container='anothercontainer')
```
Move-, or rename a blob. You can specify another container if needed, default is same container
```
client.move_or_rename_blob('blob.jpg', 'renamed_blob.jpg')
client.move_or_rename_blob(source_path='/path/to/blob.jpg',
destination_path='/another/path/to/blob.jpg',
destination_container='anothercontainer')
```
Read / write a csv directly into a pandas dataframe. You can pass-down
all arguments of `pandas.read_csv()` and `pandas.to_csv()`:
```
# read csv
df = client.read_csv_to_pandas('some.csv', header=None, sep=',')
# write csv
client.write_pandas_to_csv(df, 'another.csv', overwrite=False, index=True)
```
Get a string of bytestring back from a blob:
```
# returns string
client.read_blob_to_string('some.csv')
# returns bytes
client.read_blob_to_bytes('blob.jpg')
```
Write any content into a blob, can be both string or bytestring:
```
# directly write to file
client.write_content_to_blob('some.txt', 'some random test string', overwrite=True)
```
Read a text blob into a StringIO object, so you can read it in with e.g., Pandas
as if it was on disk:
```
# get StringIO
csv_as_string = client.read_textfile_to_io('some.csv')
# turn it into a pandas df
pd.read_csv(csv_as_string)
```
Read a (binary) blob into a BytesIO object, so you can read it in with e.g., Pandas
as if it was on disk
```
# get BytesIO
csv_as_bytes = client.read_binary_to_io('some.csv')
# turn it into a pandas df
pd.read_csv(csv_as_bytes)
```
Upload a local file to blob or vice versa
```
# upload a file
client.upload_blob('./some_local.jpg', 'blob.jpg', overwrite=True)
# download a file
client.download_blob('blob.jpg', './some_local.jpg')
```
### License
None whatsoever
### Author
D. Koops | PypiClean |
/Newgram-0.0.5.tar.gz/Newgram-0.0.5/newgram/methods/utilities/run.py |
import asyncio
import inspect
import newgram
from newgram.methods.utilities.idle import idle
class Run:
def run(
self: "newgram.Client",
coroutine=None
):
"""Start the client, idle the main script and finally stop the client.
When calling this method without any argument it acts as a convenience method that calls
:meth:`~newgram.Client.start`, :meth:`~newgram.idle` and :meth:`~newgram.Client.stop` in sequence.
It makes running a single client less verbose.
In case a coroutine is passed as argument, runs the coroutine until it's completed and doesn't do any client
operation. This is almost the same as :py:obj:`asyncio.run` except for the fact that Newgram's ``run`` uses the
current event loop instead of a new one.
If you want to run multiple clients at once, see :meth:`newgram.compose`.
Parameters:
coroutine (``Coroutine``, *optional*):
Pass a coroutine to run it until it completes.
Raises:
ConnectionError: In case you try to run an already started client.
Example:
.. code-block:: python
from newgram import Client
app = Client("my_account")
... # Set handlers up
app.run()
.. code-block:: python
from newgram import Client
app = Client("my_account")
async def main():
async with app:
print(await app.get_me())
app.run(main())
"""
loop = asyncio.get_event_loop()
run = loop.run_until_complete
if coroutine is not None:
run(coroutine)
else:
if inspect.iscoroutinefunction(self.start):
run(self.start())
run(idle())
run(self.stop())
else:
self.start()
run(idle())
self.stop() | PypiClean |
/MDSuite-0.2.0-py3-none-any.whl/mdsuite/time_series/base.py | from __future__ import annotations
from typing import TYPE_CHECKING
import matplotlib.pyplot as plt
import numpy as np
import tensorflow as tf
from mdsuite.database.simulation_database import Database
if TYPE_CHECKING:
from mdsuite import Experiment
def running_mean(x, N):
"""Perform a rolling window mean"""
cumsum = np.cumsum(np.insert(x, 0, 0))
return (cumsum[N:] - cumsum[:-N]) / float(N)
class TimeSeries:
def __init__(self, experiment: Experiment):
"""
Parameters
----------
experiment: Experiment
The parent experiment class to perform the time series operation on
"""
self.experiment = experiment
self.loaded_property = None
self.fig_labels = {"x": None, "y": None}
self.species = experiment.species
self.rolling_window = 0
self.reduce_sum = True
# Properties
self._database = None
self._data = None
def __call__(self, species: list = None, rolling_window: int = 0):
if species is not None:
self.species = species
self.rolling_window = rolling_window
self.plot()
@property
def database(self):
"""Get the database"""
if self._database is None:
self._database = Database(self.experiment.database_path / "database.hdf5")
return self._database
@property
def data(self):
"""Get the data for all species and timesteps for the loaded_property"""
if self._data is None:
self._data = tf.concat(
[
self.database.load_data([f"{species}/{self.loaded_property}"])
for species in self.species
],
axis=0,
)
return self._data
@property
def preprocess_data(self):
"""Perform some data preprocessing before plotting it"""
data = self.data
if self.reduce_sum:
data = tf.einsum("atx -> t", data)
# perform a reduce sum over atoms "a" and property dimension "x" to
# yield time steps "t"
if self.rolling_window > 0:
data = running_mean(data, self.rolling_window)
return data
def plot(self):
"""Plot the data over timesteps"""
fig, ax = plt.subplots()
ax.plot(self.preprocess_data)
ax.set_xlabel(self.fig_labels["x"])
ax.set_ylabel(self.fig_labels["y"])
fig.show() | PypiClean |
/BatteryHorse-1.0.0.tar.gz/BatteryHorse-1.0.0/batteryhorse/encoder.py | import os
import sys
import argparse
from functools import lru_cache
import nltk
from nltk.corpus import wordnet
from .version import __version__
try:
from secrets import choice
except ImportError:
from random import SystemRandom
choice = SystemRandom().choice
def _filter_words(word):
return word.isalpha() and len(word) > 1
@lru_cache()
def _get_words():
nltk_path = os.path.join(os.path.dirname(__file__), 'nltk_data')
if nltk_path not in nltk.data.path:
nltk.data.path.insert(0, nltk_path)
verbs = sorted({word.lower() for word in filter(
_filter_words, wordnet.all_lemma_names(wordnet.VERB))})
verb_size = len(verbs)
nouns = sorted({word.lower() for word in filter(
_filter_words, wordnet.all_lemma_names(wordnet.NOUN))})
noun_size = len(nouns)
adjs = sorted({word.lower() for word in filter(
_filter_words, wordnet.all_lemma_names(wordnet.ADJ))})
adj_size = len(adjs)
conjs = sorted(['and', 'or', 'lest', 'till', 'nor',
'but', 'yet', 'so', 'unless', 'when'])
conj_size = len(conjs)
return (verbs, verb_size, nouns, noun_size, adjs, adj_size, conjs, conj_size)
def encode_data(data: bytes) -> str:
"""Creates a sentence encoding the hashed data given above. The output is one or more
sentences with the format Verb Noun Adjective Conjunction Adjective."""
VERBS, VERB_SIZE, NOUNS, NOUN_SIZE, ADJS, ADJ_SIZE, CONJS, CONJ_SIZE = _get_words()
sentences = []
sentence = []
value = int.from_bytes(data, byteorder='big', signed=False)
while value > 0:
if len(sentence) == 0: # Verb
value, offset = divmod(value, VERB_SIZE)
sentence.append(VERBS[offset].capitalize())
elif len(sentence) == 1: # Noun
value, offset = divmod(value, NOUN_SIZE)
sentence.append(NOUNS[offset])
elif len(sentence) == 3: # Conjunction
value, offset = divmod(value, CONJ_SIZE)
sentence.append(CONJS[offset])
elif len(sentence) in (2, 4): # Adjective
value, offset = divmod(value, ADJ_SIZE)
sentence.append(ADJS[offset])
elif len(sentence) == 5: # Sentence break
sentences.append(' '.join(sentence))
sentence = []
sentences.append(' '.join(sentence))
return '. '.join(sentences).strip()
def decode_data(string: str, length: int) -> bytes:
"""Extract the hash of the encoded data from the given string of sentences created
with encode_data."""
VERBS, VERB_SIZE, NOUNS, NOUN_SIZE, ADJS, ADJ_SIZE, CONJS, CONJ_SIZE = _get_words()
parts = [
(ADJS, ADJ_SIZE),
(CONJS, CONJ_SIZE),
(ADJS, ADJ_SIZE),
(NOUNS, NOUN_SIZE),
(VERBS, VERB_SIZE)
]
sentences = string.lower().split('.')
sentences.reverse()
value = 0
for sentence in sentences:
words = sentence.split()
words.reverse()
# Start at an offset if necessary if we do not have a full sentence (ie: partial block)
max_parts = len(parts) - len(words)
for n, word in enumerate(words, start=max_parts):
word = word.strip()
dictionary, size = parts[n]
index = dictionary.index(word)
value = index + (value * size)
return value.to_bytes(length=length, byteorder='big', signed=False)
def create_secret(size=3):
"""Creates a random sentence that can be used as a passphrase"""
VERBS, VERB_SIZE, NOUNS, NOUN_SIZE, ADJS, ADJ_SIZE, CONJS, CONJ_SIZE = _get_words()
words = []
for _ in range(size):
words.append(choice(NOUNS + VERBS))
return ' '.join(words).capitalize()
def main():
"""Run Batteryhorse in the terminal"""
parser = argparse.ArgumentParser(
prog="batteryhorse", description="Encode and decode data as sentences")
parser.add_argument('--encode', action='store_true',
help='Accept data to be encoded from STDIN')
parser.add_argument('--decode', action='store_true',
help='Accept data to be decoded from STDIN')
parser.add_argument('--generate', action='store_true',
help='Generate a random secret')
parser.add_argument(
'--length',
help='Specify the length of secret or data to be decoded',
default=20,
type=int
)
parser.add_argument('--version', action='version',
version='%(prog)s ' + __version__)
args = parser.parse_args()
if args.encode:
data = sys.stdin.read()
print(encode_data(data.encode('ascii')))
elif args.decode:
data = sys.stdin.read()
print(decode_data(data, args.length).decode('ascii'))
elif args.generate:
print(create_secret(args.length))
else:
print(parser.print_usage())
if __name__ == '__main__':
main() | PypiClean |
/HOPP-0.0.5-py3-none-any.whl/tools/optimization/optimizer/ask_tell_optimizer.py | from abc import abstractmethod
from typing import (
Optional,
Tuple,
)
from ..data_logging.data_recorder import DataRecorder
class AskTellOptimizer:
"""
An Ask-Tell structured optimizer, following the recommendations from
Collette, Y., N. Hansen, G. Pujol, D. Salazar Aponte and R. Le Riche (2010).
On Object-Oriented Programming of Optimizers - Examples in Scilab.
In P. Breitkopf and R. F. Coelho, eds.: Multidisciplinary Design Optimization in Computational Mechanics, Wiley,
pp. 527-565;
http://www.cmap.polytechnique.fr/~nikolaus.hansen/collette2010Chap14.pdf
Example usage:
while not opt.stop():
x = opt.ask()
y = f(x)
opt.tell(x, y)
return opt.best()
"""
@abstractmethod
def setup(self, dimensions: [any], recorder: DataRecorder) -> None:
"""
Setup parameters given initial conditions of the candidate
:param dimensions: list of search dimensions
:param recorder: data recorder
"""
pass
@abstractmethod
def stop(self) -> bool:
"""
:return: True when the optimizer thinks it has reached a stopping point
"""
pass
@abstractmethod
def ask(self, num: Optional[int] = None) -> [any]:
"""
:param num: the number of search points to return. If undefined, the optimizer will choose how many to return.
:return: a list of search points generated by the optimizer
"""
pass
@abstractmethod
def tell(self, evaluations: [Tuple[float, float, any]]) -> None:
"""
Updates the optimizer with the objective evaluations of a list of search points
:param evaluations: a list of tuples of (evaluation, search point)
"""
pass
@abstractmethod
def best_solution(self) -> Optional[Tuple[float, float, any]]:
"""
:return: the current best solution and (estimated) score
"""
pass
@abstractmethod
def central_solution(self) -> (Optional[float], Optional[float], any):
"""
:return: the current central solution and (estimated) score
"""
pass
def get_num_candidates(self) -> Optional[int]:
"""
:return: Suggested number of candidates to ask for (for parallel asking), or None for no suggestion
"""
return None
def get_candidate_block_size(self) -> int:
"""
:return: number of candidates requested should be a multiple of this quantity
"""
return 1
def get_num_dimensions(self) -> Optional[int]:
"""
:return: number of dimensions being optimized over, or None if not implemented or applicable
"""
return None | PypiClean |
/ApiLogicServer-9.2.18-py3-none-any.whl/api_logic_server_cli/create_from_model/safrs-react-admin-npm-build/static/js/6304.ce792f5f.chunk.js | "use strict";(self.webpackChunkreact_admin_upgrade=self.webpackChunkreact_admin_upgrade||[]).push([[6304],{86304:function(e,t,o){o.r(t),o.d(t,{conf:function(){return n},language:function(){return i}});var 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//# sourceMappingURL=6304.ce792f5f.chunk.js.map | PypiClean |
/FHIR%20Parser-0.1.5.tar.gz/FHIR Parser-0.1.5/fhir_parser/observation.py | import datetime
from typing import List, Union, Optional
class ObservationComponent:
"""An observation component object containing the details of a part of the observation"""
def __init__(self, system: str, code: str, display: str, value: Optional[Union[str, float]], unit: Optional[str]):
self.system: str = system
self.code: str = code
self.display: str = display
self.value: float = value
self.unit: str = unit
def quantity(self) -> str:
""" Pretty print of the value and unit for an observation
Returns: Value and unit, '76.0 mm[Hg]'
"""
return str(self.value if self.value is not None else 'N/A') + (self.unit if self.unit is not None else '')
def __eq__(self, o: object) -> bool:
if type(o) != ObservationComponent:
return False
return self.__dict__ == o.__dict__
def __str__(self) -> str:
return self.display + ': ' + str(self.value if self.value is not None else 'N/A') + (self.unit if self.unit is not None else '')
class Observation:
"""An observation object holding either one or more observation components"""
def __init__(self, uuid: str, type: str, status: str, patient_uuid: str, encounter_uuid: str,
effective_datetime: datetime.datetime, issued_datetime: datetime.datetime,
components: List[ObservationComponent]):
self.uuid: str = uuid
self.type: str = type
self.status: str = status
self.patient_uuid: str = patient_uuid
self.encounter_uuid: str = encounter_uuid
self.effective_datetime: datetime.datetime = effective_datetime
self.issued_datetime: datetime.datetime = issued_datetime
self.components: List[ObservationComponent] = components
def __str__(self) -> str:
return ' | '.join(map(str, [self.uuid, self.type, self.status, self.effective_datetime, self.issued_datetime, '[' + ', '.join(map(str, self.components)) + ']'])) | PypiClean |
/MezzanineFor1.7-3.1.10.tar.gz/MezzanineFor1.7-3.1.10/mezzanine/core/models.py | from __future__ import unicode_literals
from future.builtins import str
from future.utils import with_metaclass
from json import loads
try:
from urllib.request import urlopen
from urllib.parse import urlencode
except ImportError:
from urllib import urlopen, urlencode
from django.contrib.contenttypes.generic import GenericForeignKey
from django.db import models
from django.db.models.base import ModelBase
from django.db.models.signals import post_save
from django.template.defaultfilters import truncatewords_html
from django.utils.encoding import python_2_unicode_compatible
from django.utils.html import strip_tags
from django.utils.timesince import timesince
from django.utils.timezone import now
from django.utils.translation import ugettext, ugettext_lazy as _
from mezzanine.core.fields import RichTextField, OrderField
from mezzanine.core.managers import DisplayableManager, CurrentSiteManager
from mezzanine.generic.fields import KeywordsField
from mezzanine.utils.html import TagCloser
from mezzanine.utils.models import base_concrete_model, get_user_model_name
from mezzanine.utils.sites import current_site_id, current_request
from mezzanine.utils.urls import admin_url, slugify, unique_slug
user_model_name = get_user_model_name()
class SiteRelated(models.Model):
"""
Abstract model for all things site-related. Adds a foreignkey to
Django's ``Site`` model, and filters by site with all querysets.
See ``mezzanine.utils.sites.current_site_id`` for implementation
details.
"""
objects = CurrentSiteManager()
class Meta:
abstract = True
site = models.ForeignKey("sites.Site", editable=False)
def save(self, update_site=False, *args, **kwargs):
"""
Set the site to the current site when the record is first
created, or the ``update_site`` argument is explicitly set
to ``True``.
"""
if update_site or (self.id is None and self.site_id is None):
self.site_id = current_site_id()
super(SiteRelated, self).save(*args, **kwargs)
@python_2_unicode_compatible
class Slugged(SiteRelated):
"""
Abstract model that handles auto-generating slugs. Each slugged
object is also affiliated with a specific site object.
"""
title = models.CharField(_("Title"), max_length=500)
slug = models.CharField(_("URL"), max_length=2000, blank=True, null=True,
help_text=_("Leave blank to have the URL auto-generated from "
"the title."))
class Meta:
abstract = True
def __str__(self):
return self.title
def save(self, *args, **kwargs):
"""
If no slug is provided, generates one before saving.
"""
if not self.slug:
self.slug = self.generate_unique_slug()
super(Slugged, self).save(*args, **kwargs)
def generate_unique_slug(self):
"""
Create a unique slug by passing the result of get_slug() to
utils.urls.unique_slug, which appends an index if necessary.
"""
# For custom content types, use the ``Page`` instance for
# slug lookup.
concrete_model = base_concrete_model(Slugged, self)
slug_qs = concrete_model.objects.exclude(id=self.id)
return unique_slug(slug_qs, "slug", self.get_slug())
def get_slug(self):
"""
Allows subclasses to implement their own slug creation logic.
"""
return slugify(self.title)
def admin_link(self):
return "<a href='%s'>%s</a>" % (self.get_absolute_url(),
ugettext("View on site"))
admin_link.allow_tags = True
admin_link.short_description = ""
class MetaData(models.Model):
"""
Abstract model that provides meta data for content.
"""
_meta_title = models.CharField(_("Title"), null=True, blank=True,
max_length=500,
help_text=_("Optional title to be used in the HTML title tag. "
"If left blank, the main title field will be used."))
description = models.TextField(_("Description"), blank=True)
gen_description = models.BooleanField(_("Generate description"),
help_text=_("If checked, the description will be automatically "
"generated from content. Uncheck if you want to manually "
"set a custom description."), default=True)
keywords = KeywordsField(verbose_name=_("Keywords"))
class Meta:
abstract = True
def save(self, *args, **kwargs):
"""
Set the description field on save.
"""
if self.gen_description:
self.description = strip_tags(self.description_from_content())
super(MetaData, self).save(*args, **kwargs)
def meta_title(self):
"""
Accessor for the optional ``_meta_title`` field, which returns
the string version of the instance if not provided.
"""
return self._meta_title or str(self)
def description_from_content(self):
"""
Returns the first block or sentence of the first content-like
field.
"""
description = ""
# Use the first RichTextField, or TextField if none found.
for field_type in (RichTextField, models.TextField):
if not description:
for field in self._meta.fields:
if (isinstance(field, field_type) and
field.name != "description"):
description = getattr(self, field.name)
if description:
from mezzanine.core.templatetags.mezzanine_tags \
import richtext_filters
description = richtext_filters(description)
break
# Fall back to the title if description couldn't be determined.
if not description:
description = str(self)
# Strip everything after the first block or sentence.
ends = ("</p>", "<br />", "<br/>", "<br>", "</ul>",
"\n", ". ", "! ", "? ")
for end in ends:
pos = description.lower().find(end)
if pos > -1:
description = TagCloser(description[:pos]).html
break
else:
description = truncatewords_html(description, 100)
return description
class TimeStamped(models.Model):
"""
Provides created and updated timestamps on models.
"""
class Meta:
abstract = True
created = models.DateTimeField(null=True, editable=False)
updated = models.DateTimeField(null=True, editable=False)
def save(self, *args, **kwargs):
_now = now()
self.updated = _now
if not self.id:
self.created = _now
super(TimeStamped, self).save(*args, **kwargs)
CONTENT_STATUS_DRAFT = 1
CONTENT_STATUS_PUBLISHED = 2
CONTENT_STATUS_CHOICES = (
(CONTENT_STATUS_DRAFT, _("Draft")),
(CONTENT_STATUS_PUBLISHED, _("Published")),
)
SHORT_URL_UNSET = "unset"
class Displayable(Slugged, MetaData, TimeStamped):
"""
Abstract model that provides features of a visible page on the
website such as publishing fields. Basis of Mezzanine pages,
blog posts, and Cartridge products.
"""
status = models.IntegerField(_("Status"),
choices=CONTENT_STATUS_CHOICES, default=CONTENT_STATUS_PUBLISHED,
help_text=_("With Draft chosen, will only be shown for admin users "
"on the site."))
publish_date = models.DateTimeField(_("Published from"),
help_text=_("With Published chosen, won't be shown until this time"),
blank=True, null=True)
expiry_date = models.DateTimeField(_("Expires on"),
help_text=_("With Published chosen, won't be shown after this time"),
blank=True, null=True)
short_url = models.URLField(blank=True, null=True)
in_sitemap = models.BooleanField(_("Show in sitemap"), default=True)
objects = DisplayableManager()
search_fields = {"keywords": 10, "title": 5}
class Meta:
abstract = True
def save(self, *args, **kwargs):
"""
Set default for ``publish_date``. We can't use ``auto_now_add`` on
the field as it will be blank when a blog post is created from
the quick blog form in the admin dashboard.
"""
if self.publish_date is None:
self.publish_date = now()
super(Displayable, self).save(*args, **kwargs)
def get_admin_url(self):
return admin_url(self, "change", self.id)
def publish_date_since(self):
"""
Returns the time since ``publish_date``.
"""
return timesince(self.publish_date)
publish_date_since.short_description = _("Published from")
def get_absolute_url(self):
"""
Raise an error if called on a subclass without
``get_absolute_url`` defined, to ensure all search results
contains a URL.
"""
name = self.__class__.__name__
raise NotImplementedError("The model %s does not have "
"get_absolute_url defined" % name)
def get_absolute_url_with_host(self):
"""
Returns host + ``get_absolute_url`` - used by the various
``short_url`` mechanics below.
Technically we should use ``self.site.domain``, here, however
if we were to invoke the ``short_url`` mechanics on a list of
data (eg blog post list view), we'd trigger a db query per
item. Using ``current_request`` should provide the same
result, since site related data should only be loaded based
on the current host anyway.
"""
return current_request().build_absolute_uri(self.get_absolute_url())
def set_short_url(self):
"""
Generates the ``short_url`` attribute if the model does not
already have one. Used by the ``set_short_url_for`` template
tag and ``TweetableAdmin``.
If no sharing service is defined (bitly is the one implemented,
but others could be by overriding ``generate_short_url``), the
``SHORT_URL_UNSET`` marker gets stored in the DB. In this case,
``short_url`` is temporarily (eg not persisted) set to
host + ``get_absolute_url`` - this is so that we don't
permanently store ``get_absolute_url``, since it may change
over time.
"""
if self.short_url == SHORT_URL_UNSET:
self.short_url = self.get_absolute_url_with_host()
elif not self.short_url:
self.short_url = self.generate_short_url()
self.save()
def generate_short_url(self):
"""
Returns a new short URL generated using bit.ly if credentials for the
service have been specified.
"""
from mezzanine.conf import settings
settings.use_editable()
if settings.BITLY_ACCESS_TOKEN:
url = "https://api-ssl.bit.ly/v3/shorten?%s" % urlencode({
"access_token": settings.BITLY_ACCESS_TOKEN,
"uri": self.get_absolute_url_with_host(),
})
response = loads(urlopen(url).read().decode("utf-8"))
if response["status_code"] == 200:
return response["data"]["url"]
return SHORT_URL_UNSET
def _get_next_or_previous_by_publish_date(self, is_next, **kwargs):
"""
Retrieves next or previous object by publish date. We implement
our own version instead of Django's so we can hook into the
published manager and concrete subclasses.
"""
arg = "publish_date__gt" if is_next else "publish_date__lt"
order = "publish_date" if is_next else "-publish_date"
lookup = {arg: self.publish_date}
concrete_model = base_concrete_model(Displayable, self)
try:
queryset = concrete_model.objects.published
except AttributeError:
queryset = concrete_model.objects.all
try:
return queryset(**kwargs).filter(**lookup).order_by(order)[0]
except IndexError:
pass
def get_next_by_publish_date(self, **kwargs):
"""
Retrieves next object by publish date.
"""
return self._get_next_or_previous_by_publish_date(True, **kwargs)
def get_previous_by_publish_date(self, **kwargs):
"""
Retrieves previous object by publish date.
"""
return self._get_next_or_previous_by_publish_date(False, **kwargs)
class RichText(models.Model):
"""
Provides a Rich Text field for managing general content and making
it searchable.
"""
content = RichTextField(_("Content"))
search_fields = ("content",)
class Meta:
abstract = True
class OrderableBase(ModelBase):
"""
Checks for ``order_with_respect_to`` on the model's inner ``Meta``
class and if found, copies it to a custom attribute and deletes it
since it will cause errors when used with ``ForeignKey("self")``.
Also creates the ``ordering`` attribute on the ``Meta`` class if
not yet provided.
"""
def __new__(cls, name, bases, attrs):
if "Meta" not in attrs:
class Meta:
pass
attrs["Meta"] = Meta
if hasattr(attrs["Meta"], "order_with_respect_to"):
order_field = attrs["Meta"].order_with_respect_to
attrs["order_with_respect_to"] = order_field
del attrs["Meta"].order_with_respect_to
if not hasattr(attrs["Meta"], "ordering"):
setattr(attrs["Meta"], "ordering", ("_order",))
return super(OrderableBase, cls).__new__(cls, name, bases, attrs)
class Orderable(with_metaclass(OrderableBase, models.Model)):
"""
Abstract model that provides a custom ordering integer field
similar to using Meta's ``order_with_respect_to``, since to
date (Django 1.2) this doesn't work with ``ForeignKey("self")``,
or with Generic Relations. We may also want this feature for
models that aren't ordered with respect to a particular field.
"""
_order = OrderField(_("Order"), null=True)
class Meta:
abstract = True
def with_respect_to(self):
"""
Returns a dict to use as a filter for ordering operations
containing the original ``Meta.order_with_respect_to`` value
if provided. If the field is a Generic Relation, the dict
returned contains names and values for looking up the
relation's ``ct_field`` and ``fk_field`` attributes.
"""
try:
name = self.order_with_respect_to
value = getattr(self, name)
except AttributeError:
# No ``order_with_respect_to`` specified on the model.
return {}
# Support for generic relations.
field = getattr(self.__class__, name)
if isinstance(field, GenericForeignKey):
names = (field.ct_field, field.fk_field)
return dict([(n, getattr(self, n)) for n in names])
return {name: value}
def save(self, *args, **kwargs):
"""
Set the initial ordering value.
"""
if self._order is None:
lookup = self.with_respect_to()
lookup["_order__isnull"] = False
concrete_model = base_concrete_model(Orderable, self)
self._order = concrete_model.objects.filter(**lookup).count()
super(Orderable, self).save(*args, **kwargs)
def delete(self, *args, **kwargs):
"""
Update the ordering values for siblings.
"""
lookup = self.with_respect_to()
lookup["_order__gte"] = self._order
concrete_model = base_concrete_model(Orderable, self)
after = concrete_model.objects.filter(**lookup)
after.update(_order=models.F("_order") - 1)
super(Orderable, self).delete(*args, **kwargs)
def _get_next_or_previous_by_order(self, is_next, **kwargs):
"""
Retrieves next or previous object by order. We implement our
own version instead of Django's so we can hook into the
published manager, concrete subclasses and our custom
``with_respect_to`` method.
"""
lookup = self.with_respect_to()
lookup["_order"] = self._order + (1 if is_next else -1)
concrete_model = base_concrete_model(Orderable, self)
try:
queryset = concrete_model.objects.published
except AttributeError:
queryset = concrete_model.objects.filter
try:
return queryset(**kwargs).get(**lookup)
except concrete_model.DoesNotExist:
pass
def get_next_by_order(self, **kwargs):
"""
Retrieves next object by order.
"""
return self._get_next_or_previous_by_order(True, **kwargs)
def get_previous_by_order(self, **kwargs):
"""
Retrieves previous object by order.
"""
return self._get_next_or_previous_by_order(False, **kwargs)
class Ownable(models.Model):
"""
Abstract model that provides ownership of an object for a user.
"""
user = models.ForeignKey(user_model_name, verbose_name=_("Author"),
related_name="%(class)ss")
class Meta:
abstract = True
def is_editable(self, request):
"""
Restrict in-line editing to the objects's owner and superusers.
"""
return request.user.is_superuser or request.user.id == self.user_id
class SitePermission(models.Model):
"""
Permission relationship between a user and a site that's
used instead of ``User.is_staff``, for admin and inline-editing
access.
"""
user = models.ForeignKey(user_model_name, verbose_name=_("Author"),
related_name="%(class)ss", unique=True)
sites = models.ManyToManyField("sites.Site", blank=True,
verbose_name=_("Sites"))
class Meta:
verbose_name = _("Site permission")
verbose_name_plural = _("Site permissions")
def create_site_permission(sender, **kw):
sender_name = "%s.%s" % (sender._meta.app_label, sender._meta.object_name)
if sender_name.lower() != user_model_name.lower():
return
user = kw["instance"]
if user.is_staff and not user.is_superuser:
perm, created = SitePermission.objects.get_or_create(user=user)
if created or perm.sites.count() < 1:
perm.sites.add(current_site_id())
# We don't specify the user model here, because with 1.5's custom
# user models, everything explodes. So we check the name of it in
# the signal.
post_save.connect(create_site_permission) | PypiClean |
/ArticutAPI_Taigi-0.94-py3-none-any.whl/ArticutAPI_Taigi/defaultDict/moe_dict/ACTION_verb.py | moe_ActionVerb = 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| PypiClean |
/CAuthomatic-0.1.5.tar.gz/CAuthomatic-0.1.5/authomatic/extras/gae/openid.py |
# We need absolute import to import from openid library which has the same
# name as this module
from __future__ import absolute_import
import logging
import datetime
from google.appengine.ext import ndb
import openid.store.interface
class NDBOpenIDStore(ndb.Expando, openid.store.interface.OpenIDStore):
"""
|gae| `NDB <https://developers.google.com/appengine/docs/python/ndb/>`_
based implementation of the :class:`openid.store.interface.OpenIDStore`
interface of the `python-openid`_ library.
"""
serialized = ndb.StringProperty()
expiration_date = ndb.DateTimeProperty()
# we need issued to sort by most recently issued
issued = ndb.IntegerProperty()
@staticmethod
def _log(*args, **kwargs):
pass
@classmethod
def storeAssociation(cls, server_url, association):
# store an entity with key = server_url
issued = datetime.datetime.fromtimestamp(association.issued)
lifetime = datetime.timedelta(0, association.lifetime)
expiration_date = issued + lifetime
entity = cls.get_or_insert(
association.handle, parent=ndb.Key(
'ServerUrl', server_url))
entity.serialized = association.serialize()
entity.expiration_date = expiration_date
entity.issued = association.issued
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Putting OpenID association to datastore.')
entity.put()
@classmethod
def cleanupAssociations(cls):
# query for all expired
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Querying datastore for OpenID associations.')
query = cls.query(cls.expiration_date <= datetime.datetime.now())
# fetch keys only
expired = query.fetch(keys_only=True)
# delete all expired
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Deleting expired OpenID associations from datastore.')
ndb.delete_multi(expired)
return len(expired)
@classmethod
def getAssociation(cls, server_url, handle=None):
cls.cleanupAssociations()
if handle:
key = ndb.Key('ServerUrl', server_url, cls, handle)
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Getting OpenID association from datastore by key.')
entity = key.get()
else:
# return most recently issued association
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Querying datastore for OpenID associations by ancestor.')
entity = cls.query(ancestor=ndb.Key(
'ServerUrl', server_url)).order(-cls.issued).get()
if entity and entity.serialized:
return openid.association.Association.deserialize(
entity.serialized)
@classmethod
def removeAssociation(cls, server_url, handle):
key = ndb.Key('ServerUrl', server_url, cls, handle)
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Getting OpenID association from datastore by key.')
if key.get():
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Deleting OpenID association from datastore.')
key.delete()
return True
@classmethod
def useNonce(cls, server_url, timestamp, salt):
# check whether there is already an entity with the same ancestor path
# in the datastore
key = ndb.Key(
'ServerUrl',
str(server_url) or 'x',
'TimeStamp',
str(timestamp),
cls,
str(salt))
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Getting OpenID nonce from datastore by key.')
result = key.get()
if result:
# if so, the nonce is not valid so return False
cls._log(
logging.WARNING,
u'NDBOpenIDStore: Nonce was already used!')
return False
else:
# if not, store the key to datastore and return True
nonce = cls(key=key)
nonce.expiration_date = datetime.datetime.fromtimestamp(
timestamp) + datetime.timedelta(0, openid.store.nonce.SKEW)
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Putting new nonce to datastore.')
nonce.put()
return True
@classmethod
def cleanupNonces(cls):
# get all expired nonces
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Querying datastore for OpenID nonces ordered by expiration date.')
expired = cls.query().filter(
cls.expiration_date <= datetime.datetime.now()).fetch(
keys_only=True)
# delete all expired
cls._log(
logging.DEBUG,
u'NDBOpenIDStore: Deleting expired OpenID nonces from datastore.')
ndb.delete_multi(expired)
return len(expired) | PypiClean |
/DSRE-0.2.tar.gz/DSRE-0.2/HATT/hatt/data_loader/data_loader.py | import torch
import random
import torch.utils.data as data
import numpy as np
import pandas as pd
from collections import Counter
import sklearn.metrics
import utils
np.seterr(divide='ignore', invalid='ignore')
class BagREDataset(data.Dataset):
"""
Bag-level relation extraction dataset. Note that relation of NA should be named as 'NA'.
"""
def __init__(self, path, rel2id, tokenizer, entpair_as_bag=False, bag_size=0, mode=None):
"""
Args:
path: path of the input file
rel2id: dictionary of relation->id mapping
tokenizer: function of tokenizing
entpair_as_bag: if True, bags are constructed based on same
entity pairs instead of same relation facts (ignoring
relation labels)
bag_size: bag size
mode: training model. Defaults to multi-instance (bag) training
"""
super().__init__()
self.tokenizer = tokenizer
self.rel2id = rel2id
self.entpair_as_bag = entpair_as_bag
self.bag_size = bag_size
if "NYT-10" in path:
self.data = pd.read_json(path, encoding='utf8')
self.data = self.data.to_dict('records')
# Construct bag-level dataset
if mode == None:
self.weight = np.zeros((len(self.rel2id)), dtype=np.float32)
self.bag_scope = []
self.name2id = {}
self.bag_name = []
self.facts = {}
for idx, item in enumerate(self.data):
rel_fact = (item['h_id'], item['t_id'], item['relation'])
if item['relation'] != 'NA':
self.facts[rel_fact] = 1
if entpair_as_bag:
name = (item['h_id'], item['t_id'])
else:
name = rel_fact
if name not in self.name2id:
self.name2id[name] = len(self.name2id)
self.bag_scope.append([])
self.bag_name.append(name)
self.bag_scope[self.name2id[name]].append(idx)
self.weight[self.rel2id[item['relation']]] += 1.0
self.weight = np.float32(1.0 / (self.weight ** 0.05))
self.weight = torch.from_numpy(self.weight)
else:
pass
elif "GDS" in path:
self.data = pd.read_csv(path, sep='\t', encoding='utf-8')
self.data = self.data.to_dict('records')
# Construct bag-level dataset
if mode == None:
self.weight = np.zeros((len(self.rel2id)), dtype=np.float32)
self.bag_scope = []
self.name2id = {}
self.bag_name = []
self.facts = {}
for idx, item in enumerate(self.data):
rel_fact = (item['h_FB_ID'], item['t_FB_ID'], item['relation'])
if item['relation'] != "no_relation": #
self.facts[rel_fact] = 1
if entpair_as_bag:
name = (item['h_FB_ID'], item['t_FB_ID'])
else:
name = rel_fact
if name not in self.name2id:
self.name2id[name] = len(self.name2id)
self.bag_scope.append([])
self.bag_name.append(name)
self.bag_scope[self.name2id[name]].append(idx)
self.weight[self.rel2id[item['relation']]] += 1.0
self.weight = np.float32(1.0 / (self.weight ** 0.05))
self.weight = torch.from_numpy(self.weight)
else:
pass
def __len__(self):
return len(self.bag_scope)
def __getitem__(self, index):
bag = self.bag_scope[index]
if self.bag_size > 0:
if self.bag_size <= len(bag):
resize_bag = random.sample(bag, self.bag_size)
else:
resize_bag = bag + list(np.random.choice(bag, self.bag_size - len(bag)))
bag = resize_bag
seqs = None
rel = self.rel2id[self.data[bag[0]]['relation']]
for sent_id in bag:
item = self.data[sent_id]
seq = list(self.tokenizer(item))
if seqs is None:
seqs = []
for i in range(len(seq)):
seqs.append([])
for i in range(len(seq)):
seqs[i].append(seq[i])
for i in range(len(seqs)):
seqs[i] = torch.cat(seqs[i], 0) # (bag_size, L)
return [rel, self.bag_name[index], len(bag)] + seqs
def collate_fn(data):
data = list(zip(*data))
label, bag_name, count = data[:3]
seqs = data[3:]
for i in range(len(seqs)):
seqs[i] = torch.cat(seqs[i], 0) # (sumn, L)
seqs[i] = seqs[i].expand((torch.cuda.device_count(),) + seqs[i].size())
scope = []
start = 0
for c in count:
scope.append((start, start + c))
start += c
assert (start == seqs[0].size(1))
scope = torch.tensor(scope).long()
label = torch.tensor(label).long()
return [label, bag_name, scope] + seqs
def collate_bag_size_fn(data):
data = list(zip(*data))
label, bag_name, count = data[:3]
seqs = data[3:]
for i in range(len(seqs)):
seqs[i] = torch.stack(seqs[i], 0)
scope = []
start = 0
for c in count:
scope.append((start, start + c))
start += c
label = torch.tensor(label).long()
return [label, bag_name, scope] + seqs
def eval(self, pred_result, model_name, save_eval_metrics=False):
"""
Args:
pred_result: a list with dict {'entpair': (head_id, tail_id), 'relation': rel, 'score': score}.
Note that relation of NA should be excluded.
model_name: name of the model
save_eval_metrics: declares whether to store evaluation metrics or not
Return:
{'prec': narray[...], 'rec': narray[...], 'auc': xx, 'p@all': xx, 'p@100': xx, 'p@200': xx, 'p@300': xx,
'p@500': xx, 'p@1000': xx, 'p@2000': xx, 'rel_dist_at_300': dict{...}, 'rel_facts': narray[...],
'sorted_pred_results': narray[...], 'rel_pos_dist_at_300':dict{...}}
prec (precision) and rec (recall) are in micro style.
prec (precision) and rec (recall) are sorted in the decreasing order of the score.
"""
sorted_pred_result = sorted(pred_result, key=lambda x: x['score'], reverse=True)
prec = []
rec = []
correct = 0
total = len(self.facts)
for i, item in enumerate(sorted_pred_result):
if (item['entpair'][0], item['entpair'][1], item['relation']) in self.facts:
correct += 1
prec.append(float(correct) / float(i + 1))
rec.append(float(correct) / float(total))
auc = np.around(sklearn.metrics.auc(x=rec, y=prec), 4)
np_prec = np.array(prec)
np_rec = np.array(rec)
def prec_at_n(n):
correct = 0
for i, item in enumerate(sorted_pred_result[:n]):
if (item['entpair'][0], item['entpair'][1], item['relation']) in self.facts:
correct += 1
return (correct / n)
prec_at_all = prec_at_n(len(sorted_pred_result))
prec_at_100 = prec_at_n(100)
prec_at_200 = prec_at_n(200)
prec_at_300 = prec_at_n(300)
prec_at_500 = prec_at_n(500)
prec_at_1000 = prec_at_n(1000)
prec_at_2000 = prec_at_n(2000)
rel_at_300 = [x['relation'] for x in sorted_pred_result[0:300]]
rel_dist_at_300 = dict(Counter(rel_at_300))
rel_pos_dist_at_300 = dict(Counter([x['relation'] for x in sorted_pred_result[0:300] if x['score'] > 0.5]))
# Return the eval metrics
if save_eval_metrics:
print("Saving eval metrics for testing set")
utils.plot_precision_recall_curve(np_prec, np_rec, auc, model_name)
utils.save_precision_recall_values(np_prec, np_rec, model_name)
utils.save_eval_metrics(prec_at_100, prec_at_200, prec_at_300, prec_at_500, prec_at_1000, prec_at_2000,
prec_at_all, auc, model_name)
utils.save_labels_distribution_at_top_300_predictions(rel_dist_at_300, model_name)
utils.save_relational_facts(self.facts, model_name)
utils.save_sorted_pred_results(sorted_pred_result, model_name)
return {'prec': np_prec, 'rec': np_rec, 'auc': auc, 'p@all': prec_at_all, 'p@100': prec_at_100,
'p@200': prec_at_200, 'p@300': prec_at_300, 'p@500': prec_at_500, 'p@1000': prec_at_1000,
'p@2000': prec_at_2000, 'rel_dist_at_300': rel_dist_at_300, 'relfacts': self.facts,
'sorted_pred_results': sorted_pred_result, 'rel_pos_dist_at_300': rel_pos_dist_at_300}
def BagRELoader(path, rel2id, tokenizer, batch_size, shuffle, entpair_as_bag=False, bag_size=0, num_workers=0,
collate_fn=BagREDataset.collate_fn):
if bag_size == 0:
collate_fn = BagREDataset.collate_fn
else:
collate_fn = BagREDataset.collate_bag_size_fn
dataset = BagREDataset(path, rel2id, tokenizer, entpair_as_bag=entpair_as_bag, bag_size=bag_size)
data_loader = data.DataLoader(dataset=dataset, batch_size=batch_size, shuffle=shuffle, pin_memory=True,
num_workers=num_workers, collate_fn=collate_fn)
return data_loader | PypiClean |
/CmonCrawl-1.0.3.tar.gz/CmonCrawl-1.0.3/cmoncrawl/middleware/stompware.py | from datetime import datetime
import json
from typing import List
from cmoncrawl.aggregator.index_query import IndexAggregator
from cmoncrawl.common.loggers import all_purpose_logger
import asyncio
from dataclasses import dataclass
from datetime import datetime, timedelta
from typing import Dict, List, Set, Tuple
from cmoncrawl.aggregator.utils.helpers import unify_url_id
from stomp import Connection, ConnectionListener
from stomp.utils import Frame
from stomp.exception import StompException
from cmoncrawl.common.types import DomainRecord
from cmoncrawl.processor.pipeline.pipeline import ProcessorPipeline
DUPL_ID_HEADER = "_AMQ_DUPL_ID"
@dataclass
class Message:
dr: DomainRecord
headers: Dict[str, str]
@dataclass
class ListnerStats:
messages: int = 0
last_message_time: datetime = datetime.now()
class ArtemisAggregator:
"""
Aggregator that listens queries the common crawl index and sends the results to a queue
using the stomp protocol. It the creates a queue
with name `queue.{url}` and sends the results to it.
It also creates a topic with name `topic.poisson_pill.{url}`
and sends a message with type `poisson_pill` to it when it finishes.
Args:
queue_host (str): The host of the queue
queue_port (int): The port of the queue
url (str): The url of the queue
index_agg (IndexAggregator): The index aggregator
heartbeat (int, optional): The heartbeat of the connection. Defaults to 10000.
"""
def __init__(
self,
queue_host: str,
queue_port: int,
url: str,
index_agg: IndexAggregator,
heartbeat: int = 10000,
):
self.queue_host = queue_host
self.queue_port = queue_port
self.index_agg = index_agg
self.url = url
self.heartbeat = heartbeat
def _init_connection(self):
conn = Connection(
[(self.queue_host, self.queue_port)],
heartbeats=(self.heartbeat, self.heartbeat),
)
conn.connect(login="producer", passcode="producer", wait=True) # type: ignore
all_purpose_logger.info(f"Connected to queue")
return conn
async def aggregate(self, filter_duplicates: bool = True):
"""
Aggregates the results of the index aggregator and sends them to the queue.
If `filter_duplicates` is True, it will use the `DUPL_ID_HEADER` header,
which Artemis uses to filter duplicates.
"""
while True:
try:
conn = self._init_connection()
break
except StompException as e:
all_purpose_logger.error(e, exc_info=True)
await asyncio.sleep(5)
continue
i = 0
async with self.index_agg as aggregator:
async for domain_record in aggregator:
try:
while not conn.is_connected():
conn = self._init_connection()
json_str = json.dumps(domain_record.__dict__, default=str)
headers = {}
id = unify_url_id(domain_record.url or "")
if filter_duplicates:
headers[DUPL_ID_HEADER] = id
conn.send( # type: ignore
f"queue.{self.url}",
json_str,
headers=headers,
)
all_purpose_logger.debug(
f"Sent url: {domain_record.url} with id: {id}"
)
i += 1
except (StompException, OSError) as e:
all_purpose_logger.error(e, exc_info=True)
continue
except Exception as e:
all_purpose_logger.error(e, exc_info=True)
break
all_purpose_logger.info(f"Sent {i} messages")
conn.send( # type: ignore
f"topic.poisson_pill.{self.url}", "", headers={"type": "poisson_pill"}
)
conn.disconnect() # type: ignore
class ArtemisProcessor:
"""
Processor that listens to a queues and processes the messages using a pipeline.
When it receives a message with type enough `poisson_pill` messages, it will
stop listening if it doesn't receive any messages for `timeout` minutes.
Args:
queue_host (str): The host of the queue
queue_port (int): The port of the queue
pills_to_die (int, optional): The number of `poisson_pill` messages to receive before dying. Defaults to None.
queue_size (int): The size of the queue
timeout (int): The timeout in minutes
addresses (List[str]): The addresses of the queues
pipeline (ProcessorPipeline): The pipeline to use for processing
heartbeat (int, optional): The heartbeat of the connection. Defaults to 10000.
"""
def __init__(
self,
queue_host: str,
queue_port: int,
pills_to_die: int | None,
queue_size: int,
timeout: int,
addresses: List[str],
pipeline: ProcessorPipeline,
heartbeat: int = 10000,
):
self.queue_host = queue_host
self.queue_port = queue_port
self.pills_to_die = pills_to_die
self.queue_size = queue_size
self.timeout = timeout
self.pipeline = pipeline
self.addresses = addresses
self.heartbeat = heartbeat
class Listener(ConnectionListener):
def __init__(
self,
messages: asyncio.Queue[Message],
listener_stats: ListnerStats,
):
self.messages = messages
self.pills = 0
self.listener_stats = listener_stats
def on_message(self, frame: Frame):
if frame.headers.get("type") == "poisson_pill": # type: ignore
self.pills += 1
else:
msg_json = json.loads(frame.body) # type: ignore
try:
msg_json["timestamp"] = datetime.fromisoformat(
msg_json.get("timestamp")
)
domain_record = DomainRecord(**msg_json)
self.messages.put_nowait(Message(domain_record, frame.headers)) # type: ignore
self.listener_stats.messages += 1
self.listener_stats.last_message_time = datetime.now()
except ValueError:
pass
def _init_connection(self, addresses: List[str]):
conn = Connection(
[(self.queue_host, self.queue_port)],
reconnect_attempts_max=-1,
heartbeats=(self.heartbeat, self.heartbeat),
)
conn.connect(login="consumer", passcode="consumer", wait=True) # type: ignore
for address in addresses:
conn.subscribe(address, id=address, ack="client-individual") # type: ignore
conn.subscribe("topic.poisson_pill.#", id="poisson_pill", ack="auto") # type: ignore
listener_stats = ListnerStats()
listener = self.Listener(asyncio.Queue(0), listener_stats)
conn.set_listener("", listener) # type: ignore
all_purpose_logger.info("Connected to queue")
return conn, listener
async def _call_pipeline_with_ack(
self,
pipeline: ProcessorPipeline,
msg: Message,
client: Connection,
):
# Make sure no exception is thrown from this function
# So that we can nack it if needed
paths = []
try:
paths = await pipeline.process_domain_record(msg.dr, {})
# Ack at any result
client.ack(msg.headers.get("message-id"), msg.headers.get("subscription"))
except KeyboardInterrupt:
raise KeyboardInterrupt
except Exception as e:
client.nack(msg.headers.get("message-id"), msg.headers.get("subscription"))
all_purpose_logger.error(f"Error in pipeline: {e}", exc_info=True)
return (msg, paths)
async def process(self):
timeout_delta = timedelta(minutes=self.timeout)
# Set's extractor path based on config
pending_extracts: Set[asyncio.Task[Tuple[Message, List[str]]]] = set()
while True:
try:
conn, listener = self._init_connection(self.addresses)
break
except StompException as e:
all_purpose_logger.error(e, exc_info=True)
await asyncio.sleep(5)
continue
all_purpose_logger.debug("Connecting to queue")
extracted_num = 0
try:
if hasattr(self.pipeline.downloader, "__aenter__"):
await self.pipeline.downloader.__aenter__() # type: ignore
while True:
if (
listener.messages.empty()
and (
self.pills_to_die is None or listener.pills >= self.pills_to_die
)
and datetime.now() - listener.listener_stats.last_message_time
>= timeout_delta
):
all_purpose_logger.info(
f"No new messages in {self.timeout} minutes, exiting"
)
break
try:
# Auto reconnect if queue disconnects
if not conn.is_connected():
conn, listener = self._init_connection(self.addresses)
if len(pending_extracts) > 0:
done, pending_extracts = await asyncio.wait(
pending_extracts, return_when="FIRST_COMPLETED"
)
for task in done:
message, paths = task.result()
if len(paths) > 0:
for path in paths:
all_purpose_logger.info(
f"Downloaded {message.dr.url} to {path}"
)
extracted_num += 1
else:
all_purpose_logger.info(
f"Failed to extract {message.dr.url}"
)
while (
len(pending_extracts) < self.queue_size
and not listener.messages.empty()
):
pending_extracts.add(
asyncio.create_task(
self._call_pipeline_with_ack(
self.pipeline, listener.messages.get_nowait(), conn
)
)
)
except StompException as e:
all_purpose_logger.error(e, exc_info=True)
continue
except Exception as e:
all_purpose_logger.error(e, exc_info=True)
break
# Process reamining stuff in queue
gathered = await asyncio.gather(*pending_extracts, return_exceptions=True)
for task in gathered:
if isinstance(task, Exception):
continue
message, paths = task
if len(paths) > 0:
for path in paths:
all_purpose_logger.info(
f"Downloaded {message.dr.url} to {path}"
)
extracted_num += 1
else:
all_purpose_logger.info(f"Failed to extract {message.dr.url}")
except Exception as e:
pass
finally:
if hasattr(self.pipeline.downloader, "__aexit__"):
await self.pipeline.downloader.__aexit__(None, None, None) # type: ignore
all_purpose_logger.info(
f"Extracted {extracted_num}/{listener.listener_stats.messages} articles"
)
conn.disconnect() # type: ignore | PypiClean |
/BIDSHandler-0.2.1-py3-none-any.whl/bidshandler/session.py | import os
import os.path as op
from collections import OrderedDict
import xml.etree.ElementTree as ET
import pandas as pd
from .utils import _get_bids_params, _copyfiles, _realize_paths, _combine_tsv
from .bidserrors import MappingError, NoScanError, AssociationError
from .scan import Scan
from .querymixin import QueryMixin
_RAW_FILETYPES = ('.nii', '.bdf', '.con', '.sqd') # TODO: add more...
class Session(QueryMixin):
"""Session-level object.
Parameters
----------
id_ : str
Id of the session. This is the sequence of characters after `'ses-'`.
subject : :class:`bidshandler.Subject`
Parent Subject object containing this Session.
initialize : bool, optional
Whether to parse the folder and load any child structures.
no_folder : bool, optional
Whether or not the session is contained within a `ses-XX` folder.
For experiments with multiple sessions each folder will correspond to
a Session object, however if there is only a single session this can
be omitted and the Subject folder is in fact the Session folder.
"""
def __init__(self, id_, subject, initialize=True, no_folder=False):
super(Session, self).__init__()
self._id = id_
self.subject = subject
self._scans_tsv = None
self._scans = []
self.recording_types = []
self._queryable_types = ('session', 'scan')
self.has_no_folder = no_folder
if initialize:
self._add_scans()
self._check()
#region public methods
def add(self, other, copier=_copyfiles):
""".. # noqa
Add another Scan or Session to this object.
Parameters
----------
other : Instance of :class:`bidshandler.Scan` or :class:`bidshandler.Session`
Object to be added to this Session.
The added object must already exist in the same context as this
object.
copier : function, optional
A function to facilitate the copying of any applicable data.
This function must have the call signature
`function(src_files: list, dst_files: list)`
Where src_files is the list of files to be moved and dst_files is
the list of corresponding destinations.
This will default to using utils._copyfiles which simply implements
:py:func:`shutil.copy` and creates any directories that do not
already exist.
"""
if isinstance(other, Session):
if self._id == other._id:
for scan in other.scans:
self.add(scan, copier)
else:
raise ValueError("Added session must have same ID.")
elif isinstance(other, Scan):
# TODO-LT: handle other modalities
# We need to make sure that the scan is of the same person/session:
if (self._id == other.session._id and
self.subject._id == other.subject._id and
self.project._id == other.project._id):
# Handle merging the scans.tsv file.
if other in self:
# We don't want to add it if it is already in this session.
# TODO: add overwrite argument to allow it to still be
# added.
return
other_scan_df = pd.DataFrame(
OrderedDict([
('filename', [other.raw_file_relative]),
('acq_time', [other.acq_time])]),
columns=['filename', 'acq_time'])
# Combine the new data into the original tsv.
_combine_tsv(self.scans_tsv, other_scan_df, 'filename')
# Assign as a set to avoid any potential doubling of the raw
# file path.
files = set(other.associated_files.values())
files.add(other._sidecar)
files.add(other._raw_file)
# Copy the files over.
fl_left = _realize_paths(other, files)
fl_right = []
for fpath in files:
fl_right.append(op.join(self.path, other._path, fpath))
copier(fl_left, fl_right)
# Add the scan object to our scans list.
scan = Scan(other.raw_file_relative, self,
acq_time=other.acq_time)
self._scans.append(scan)
else:
raise AssociationError("scan", "project, subject and session")
else:
raise TypeError("Cannot add a {0} object to a Subject".format(
type(other).__name__))
def contained_files(self):
"""Get the list of contained files.
Returns
-------
file_list : list
List with paths to all contained files relating to the BIDS
structure.
"""
file_list = set()
file_list.add(_realize_paths(self, self._scans_tsv))
for scan in self.scans:
file_list.update(scan.contained_files())
return file_list
def scan(self, task=None, acq=None, run=None):
# TODO: Allow this to return a list if mutliple scans match.
# Consider None a wildcard.
"""Return the contained Scan corresponding to the provided values
Parameters
----------
task : str
Value of `task` in the BIDS filename.
acq : str
Value of `acq` in the BIDS filename.
run : str
Value of `run` in the BIDS filename.
Returns
-------
scan : :class:`bidshandler.Scan`
Scan object.
"""
for scan in self.scans:
if (scan.task == task and scan.acq == acq and scan.run == run):
return scan
raise NoScanError
#region private methods
def _add_scans(self):
"""Parse the session folder to find what recordings are included."""
for fname in os.listdir(self.path):
full_path = op.join(self.path, fname)
# Each sub-directory is considered a separate type of recording.
if op.isdir(full_path):
self.recording_types.append(fname)
# The only other non-folder should be the scans tsv.
else:
filename_data = _get_bids_params(fname)
if filename_data.get('file', None) == 'scans':
# Store the path and extract the paths of the scans.
self._scans_tsv = fname
scans = pd.read_csv(_realize_paths(self, self._scans_tsv),
sep='\t')
column_names = set(scans.columns.values)
if 'filename' not in column_names:
raise MappingError(
"{0} contains no 'filename' column".format(
self.scans_tsv))
column_names.remove('filename')
for i in range(len(scans)):
row = scans.iloc[i]
fname = row.pop('filename')
self._scans.append(
Scan(fname, self, **dict(row)))
# if we haven't found a scans.tsv file then we need to add all the
# scans in a different way.
if self._scans_tsv is None:
# for now do just MRI stuff which is any .nii.gz file I think?
#TODO: have a switch for each folder name?
for rec_type in self.recording_types:
if rec_type not in ('anat', 'dwi'):
rec_path = _realize_paths(self, rec_type)
if rec_type == 'fmap':
# fieldmap sequence
# The files with `file` = `magnitude1` are not raw
# scans.
filename_data = _get_bids_params(fname)
if ((filename_data['file'] not in ('magnitude1',
'magnitude2')) and
'nii' in fname):
self._scans.append(
Scan(op.join(rec_type, fname), self))
for fname in os.listdir(rec_path):
for ext in _RAW_FILETYPES:
if ext in fname:
self._scans.append(
Scan(op.join(rec_type, fname), self))
def _check(self):
"""Check that there is at least one included scan."""
if len(self._scans) == 0:
raise MappingError("No scans found in {0}/{1}/{2}.".format(
self.project.ID, self.subject.ID, self.ID))
@staticmethod
def _clone_into_subject(subject, other):
"""Create a copy of the Session with a new parent Subject.
Parameters
----------
subject : :class:`bidshandler.Subject`
New parent Subject.
other : :class:`BIDSHandler.Session`
Original Session instance to clone.
Returns
-------
new_session : :class:`bidshandler.Session`
New uninitialized Session cloned from `other` to be a child of
`subject`.
"""
os.makedirs(_realize_paths(subject, other.ID), exist_ok=True)
# Create a new empty session object.
new_session = Session(other._id, subject, initialize=False)
new_session._create_empty_scan_tsv()
return new_session
def _create_empty_scan_tsv(self):
"""Create an empty scans.tsv file for this session."""
self._scans_tsv = '{0}_{1}_scans.tsv'.format(self.subject.ID, self.ID)
full_path = _realize_paths(self, self._scans_tsv)
if not op.exists(full_path):
df = pd.DataFrame(OrderedDict([('filename', [])]),
columns=['filename'])
df.to_csv(full_path, sep='\t', index=False, na_rep='n/a',
encoding='utf-8')
def _generate_map(self):
"""Generate a map of the Session.
Returns
-------
root : :py:class:`xml.etree.ElementTree.Element`
Xml element containing session information.
"""
root = ET.Element('Session', attrib={'ID': str(self._id)})
for scan in self.scans:
root.append(scan._generate_map())
return root
#region properties
@property
def bids_tree(self):
"""Parent :class:`bidshandler.BIDSTree` object."""
return self.project.bids_tree
@property
def ID(self):
"""ID with 'ses' prefix."""
return 'ses-{0}'.format(self._id)
@property
def inheritable_files(self):
"""List of files that are able to be inherited by child objects."""
files = self.subject.inheritable_files
for fname in os.listdir(self.path):
abs_path = _realize_paths(self, fname)
if op.isfile(abs_path):
files.append(abs_path)
return files
@property
def path(self):
"""Determine path location based on parent paths."""
if self.has_no_folder:
return self.subject.path
return op.join(self.subject.path, self.ID)
@property
def project(self):
"""Parent :class:`bidshandler.Project` object."""
return self.subject.project
@property
def scans(self):
"""List of contained Scans."""
return self._scans
@property
def scans_tsv(self):
"""Absolute path of associated scans.tsv file."""
return _realize_paths(self, self._scans_tsv)
#region class methods
def __contains__(self, other):
"""Determine whether the Session object contains a scan.
Parameters
----------
other : :class:`bidshandler.Scan`
Object to test whether it is contained in this Session.
Returns
-------
bool
Returns True if the object is contained within this Session.
"""
if isinstance(other, Scan):
for scan in self._scans:
if scan == other:
return True
return False
raise TypeError("Can only determine if a Scan is contained.")
def __iter__(self):
return iter(self._scans)
def __repr__(self):
return '<Session, ID: {0}, {1} scan{2}, @ {3}>'.format(
self.ID,
len(self.scans),
('s' if len(self.scans) > 1 else ''),
self.path)
def __str__(self):
output = []
output.append('ID: {0}'.format(self.ID))
output.append('Number of scans: {0}'.format(len(self.scans)))
return '\n'.join(output) | PypiClean |
/FreePyBX-1.0-RC1.tar.gz/FreePyBX-1.0-RC1/freepybx/public/js/dojox/editor/README | -------------------------------------------------------------------------------
dojox.editor
-------------------------------------------------------------------------------
Version 0.9
Release date: 9/14/2009
-------------------------------------------------------------------------------
Project state:
experimental, beta, stable
-------------------------------------------------------------------------------
Credits
Mike Wilcox - Author
Jared Jurkiewicz - Author (PrettyPrint, PageBreak, ShowBlockNodes,
Preview, Save, ToolbarLineBreak, InsertEntity,
NormalizeIndentOutdent, Breadcrumb, FindReplace,
CollapsibleToolbar, Blockquote, PasteFromWord, InsertAnchor,
TextColor, NormalizeStyle, StatusBar, SafePaste)
Dustin Machi - Technical Assistance
David Schwartz and Gu Yi He (IBM) - Contributed enhancements to the
look and feel of FindReplace, as well as behavioral
improvements.
Eldon (IBM, CCLA) - LocalImage, AutoUrlLink, TablePluginsColorCell -
dojox.widget.ColorPicker, ResizeTableColumn, AutoSave, SpellCheck
-------------------------------------------------------------------------------
Project description
Space for extensions and additional plugins for dijit.Editor. The project
currently contains the following plugins:
dojox.editor.plugins.TablePlugins:
Status: Experimental.
The Table Plugins provide a mechanism for editing tables withing the
dijit.Editor. This plugin is experimental and does not work correctly
in all dojo supported browsers.
dojox.editor.plugins.UploadImage:
Status: Experimental.
The UploadImage plugin makes use of the dojox upload widgets to provide
a mechanism to upload images to your server for use in the editor.
dojox.editor.plugins.PrettyPrint:
Status: Supported (stable).
The PrettyPrint plugin provides a mechanism by which the output from
editor.getValue()/editor.attr("value") is nicely formatted. Optional
format parameters are how many spaces to indent by (default is tab),
the maximum text line length (not including indent), and what
characters in text strings should be encoded to their &<enc>;
representation.
dojox.editor.plugins.PageBreak:
Status: Supported (stable).
A simple plugin that allows you to insert 'page breaks' into the doc
being edited. These page break styles will then cause the document
to break to another page when printed.
dojox.editor.plugins.ShowBlockNodes:
Status: Supported (stable).
A simple plugin that allows you to toggle on and off a CSS 'view' of
how the page is laid out in terms of the block nodes used for its
formatting.
dojox.editor.plugins.Save:
Status: Supported (beta).
A simple plugin that allows you to POST the content of the editor back
to a URL.
dojox.editor.plugins.Preview:
Status: Supported (beta).
A simple plugin that allows you to display the content of the editor
in a new window and apply a set of styles to it so you can see how
content will look with various styles applied. It is likely this
plugin will still evolve a bit.
dojox.editor.plugins.ToolbarLineBreak:
Status: Supported (stable).
An extremely simple plugin that allows you to 'linebreak' the dijit toolbar so that really long
toolbars for editor (lots of plugins enabled), can be broken up into multiple rows.
dojox.editor.plugins.InsertEntity:
Status: Experimental (unsupported).
A plugin that enables the ability to insert HTML/XML entity characters
into a page. These are often called 'symbols'. The set it provides are the
basic latin (8859) set and a portion of greek symbols common to mathematics.
It has been marked experimental as it is likely this plugin will evolve a bit.
dojox.editor.plugins.NormalizeIndentOutdent:
Status: Experimental (unsupported).
A plugin that normalizes the behavior of indent/outdent to use margin styles instead
of <blockquote> tags. Also fixes indent/outdent of lists to work properly. This is new
and has been tested, but not extensively. Therefore it is currently classed as experimental.
dojox.editor.plugins.Breadcrumb:
Status: Experimental (unsupported).
A plugin that adds a breadcrumb toolbar to the bottom of the editor. Useful for seeing
where you aren and what operations you can perform. This is new and has been tested, but not
extensively. Therefore it is currently classed as experimental.
dojox.editor.plugins.FindReplace:
Status: Experimental (unsupported).
A plugin that adds a togglable Find/Replace toolbar to the editor. Useful for searching
and replacing text strings in the editor content. Only works on FF, IE, and WebKit. No Opera
support. This is new and has been tested, but not extensively. Therefore it is currently
classed as experimental.
dojox.editor.plugins.CollapsibleToolbar:
Status: Supported (Stable).
A plugin that modified the header node of the editor so that it is 'collapsible'. Meaning that
it can be closed (reduced), and reopened. Useful for increasing editor real-estate.
dojox.editor.plugins.Blockquote:
Status: Supported (Stable).
A plugin that puts a button on the toolbar that allows users to select text for a semantic
'blockquote' tag-wrap action. It toggles on and off during state changes to determine if
the current section is contained within a blockquote.
dojox.editor.plugins.PasteFromWord:
Status: Beta (unsupported).
A plugin that puts a button that opens a dialog to paste in content from Word and similar
programs like wordpad. It will then filter out extraneous and bad html from the content
before injecting it into the RTE. Experimental as the filter list may not be complete yet.
Feedback is welcome and appreciated. Filters will be updated based on it.
dojox.editor.plugins.InsertAnchor:
Status: Stable (supported).
A plugin that allows anchor points to be inserted into the document being edited.
The anchors are styled in the doc to make them easily visible/editable in the document.
dojox.editor.plugins.TextColor:
Status: Experimental (unsupported).
A plugin that makes use of the dojox.widget.ColorPicker widget in lieu of the
dijit.ColorPalette.
dojox.editor.plugins.NormalizeStyle:
Status: Experimental (unsupported).
A plugin that tries to normalize the output from the editor as either CSS styled or semantic (<b>, <i>, etc)
style.
dojox.editor.plugins.StatusBar:
Status: Experimental (unsupported).
A plugin that adds a status bar and an optional resize handle to the footer of the editor.
dojox.editor.plugins.LocalImage
Status: Beta
A plugin that adds local image upload and edit capability to the editor.
dojox.editor.plugins.AutoUrlLink
Status: Experimental (Unsupported)
A plugin that adds auto url link creation capability as a headless plugin to the editor
dojox.editor.plugins.ResizeColumnPlugin
Status: Experimental (Unsupported)
A plugin that adds column resize to the editor table plugins.
dojox.editor.plugins.AutoSave
Status: Experimental (Unsupported)
A plugin that provides 'auto-save' capablity, eg, post back to some url at an interval.
dojox.editor.plugins.SpellCheck
Status: Experimental (Unsupported)
A plugin that provides server-side spell-check support.
dojox.editor.plugins.SafePaste
Status: Beta (Supported)
A plugin that provides a safer paste function to the editor. It strips out script tags,
tries to fix up odd input from Word, Wordpad, etc. Very similar to PasteFromWord except that
it takes complete control of paste in dijit.Editor instead of being an alternate paste icon.
-------------------------------------------------------------------------------
Dependencies:
dijit
dojox.form
dojox.html.format
dojox.widget.ColorPicker
dojox.layout.ResizeHandle
-------------------------------------------------------------------------------
Documentation
The plugins directory contains extensions which work with dijit.Editor.
See also:
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/TablePlugins.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/PrettyPrint.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/PageBreak.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/ShowBlockNodes.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/Preview.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/Save.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/ToolbarLineBreak.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/InsertEntity.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/NormalizeIndentOutdent.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/Breadcrumb.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/FindReplace.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/CollapsibleToolbar.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/Blockquote.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/PasteFromWord.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/InsertAnchor.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/TextColor.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/NormalizeStyle.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/StatusBar.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/LocalImage.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/AutoUrlLink.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/ResizeTableColumn.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/AutoSave.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/SpellCheck.html
http://dojotoolkit.org/reference-guide/dojox/editor/plugins/SafePaste.html
.html
-------------------------------------------------------------------------------
Plugin Installation instructions
Get dojo and dijit from svn. Include the Editor and plugins in your page:
dojo.require("dijit.Editor");
For the TablePlugins:
dojo.require("dojox.editor.plugins.TablePlugins");
and CSS:
<link href="[path]dojox/editor/plugins/resources/editorPlugins.css" type="text/css" rel="stylesheet" />
For the UploadImage plugin:
dojo.require("dojox.editor.plugins.UploadImage");
and CSS:
<link href="[path]dojox/editor/plugins/resources/editorPlugins.css" type="text/css" rel="stylesheet" />
<link href="[path]dojox/form/resources/FileInput.css" type="text/css" rel="stylesheet" />
For the PrettyPrint plugin:
dojo.require("dojox.editor.plugins.PrettyPrint");
and CSS:
No CSS required.
For the PageBreak plugin:
dojo.require("dojox.editor.plugins.PageBreak");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/PageBreak.css" type="text/css" rel="stylesheet" />
For the ShowBlockNodes plugin:
dojo.require("dojox.editor.plugins.ShowBockNodes");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/ShowBlockNodes.css" type="text/css" rel="stylesheet" />
For the Preview plugin:
dojo.require("dojox.editor.plugins.Preview");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/Preview.css" type="text/css" rel="stylesheet" />
For the Save plugin:
dojo.require("dojox.editor.plugins.Save");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/Save.css" type="text/css" rel="stylesheet" />
For the ToolbarLineBreak plugin:
dojo.require("dojox.editor.plugins.ToolbarLineBreak");
and CSS:
No CSS required.
For the InsertEntity plugin:
dojo.require("dojox.editor.plugins.InsertEntity");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/InsertEntity.css" type="text/css" rel="stylesheet" />
For the NormalizeIndentOutdent plugin:
dojo.require("dojox.editor.plugins.NormalizeIndentOutdent");
and CSS:
No CSS required.
For the Breadcrumb plugin:
dojo.require("dojox.editor.plugins.Breadcrumb");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/Breadcrumb.css" type="text/css" rel="stylesheet" />
For the FindReplace plugin:
dojo.require("dojox.editor.plugins.FindReplace");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/FindReplace.css" type="text/css" rel="stylesheet" />
For the CollapsibleToolbar plugin:
dojo.require("dojox.editor.plugins.CollapsibleToolbar");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/CollapsibleToolbar.css" type="text/css" rel="stylesheet" />
For the Blockquote plugin:
dojo.require("dojox.editor.plugins.Blockquote");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/Blockquote.css" type="text/css" rel="stylesheet" />
For the PasteFromWord plugin:
dojo.require("dojox.editor.plugins.PasteFromWord");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/PasteFromWord.css" type="text/css" rel="stylesheet" />
For the InsertAnchor plugin:
dojo.require("dojox.editor.plugins.InsertAnchor");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/InsertAnchor.css" type="text/css" rel="stylesheet" />
For the TextColor plugin:
dojo.require("dojox.editor.plugins.TextColor");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/TextColor.css" type="text/css" rel="stylesheet" />
For the NormalizeStyle plugin:
dojo.require("dojox.editor.plugins.NormalizeStyle");
and CSS:
No CSS required.
For the StatusBar plugin:
dojo.require("dojox.editor.plugins.StatusBar");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/StatusBar.css" type="text/css" rel="stylesheet" />
For the LocalImage plugin:
dojo.require("dojox.editor.plugins.LocalImage");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/LocalImage.css" type="text/css" rel="stylesheet" />
For the AutoUrlLink plugin:
dojo.require("dojox.editor.plugins.AutoUrlLink");
and CSS:
No CSS required.
For the ResizeTableColumn plugin:
dojo.require("dojox.editor.plugins.ResizeTableColumn");
and CSS:
No CSS required in addition to the table plugins css.
For the AutoSave plugin:
dojo.require("dojox.editor.plugins.AutoSave");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/AutoSave.css" type="text/css" rel="stylesheet" />
For the SpellCheck plugin:
dojo.require("dojox.editor.plugins.SpellCheck");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/SpellCheck.css" type="text/css" rel="stylesheet" />
For the SafePaste plugin:
dojo.require("dojox.editor.plugins.SafePaste");
and CSS:
<link href="[path]dojox/editor/plugins/resources/css/SafePaste.css" type="text/css" rel="stylesheet" />
See tests for examples:
dojox/editor/tests/editorTablePlugs.html
dojox/editor/tests/editorUploadPlug.html
dojox/editor/tests/editorPrettyPrint.html
dojox/editor/tests/editorPageBreak.html
dojox/editor/tests/editorShowBlockNodes.html
dojox/editor/tests/editorPreview.html
dojox/editor/tests/editorSave.html
dojox/editor/tests/editorToolbarLineBreak.html
dojox/editor/tests/editorInsertEntity.html
dojox/editor/tests/editorNormalizeIndentOutdent.html
dojox/editor/tests/editorBreadcrumb.html
dojox/editor/tests/editorFindReplace.html
dojox/editor/tests/editorCollapsibleToolbar.html
dojox/editor/tests/editorBlockquote.html
dojox/editor/tests/editorPasteFromWord.html
dojox/editor/tests/editorInsertAnchor.html
dojox/editor/tests/editorTextColor.html
dojox/editor/tests/editorNormalizeStyle.html
dojox/editor/tests/editorStatusBar.html
dojox/editor/tests/editorLocalImage.html
dojox/editor/tests/editorAutoUrlLink.html
dojox/editor/tests/editorResizeTableColumn.html
dojox/editor/tests/editorAutoSave.html
dojox/editor/tests/editorSpellCheck.html
dojox/editor/tests/editorSafePaste.html
dojox/editor/tests/testPluginsAll.html | PypiClean |
/Dulcinea-0.11.tar.gz/Dulcinea-0.11/lib/user.py | from dulcinea.base import DulcineaPersistent
from dulcinea.sort import lexical_sort
from dulcinea.spec import add_getters_and_setters, sequence, string
from dulcinea.spec import spec, require, mapping, init, either
from durus.persistent import Persistent
from durus.persistent_dict import PersistentDict
from durus.persistent_set import PersistentSet
from quixote.util import randbytes
import re, sha, binascii
def hash_password(password):
"""Apply a one way hash function to a password and return the result."""
return sha.new(password).hexdigest()
class Permissions (PersistentDict):
data_is = {string:sequence(either(Persistent, True), PersistentSet)}
def grant(self, permission, granter):
require(permission, string)
require(granter, either(Persistent, True))
if permission not in self:
self[permission] = PersistentSet([granter])
else:
self[permission].add(granter)
def ungrant(self, permission, granter):
require(permission, string)
require(granter, either(Persistent, True))
if self.is_granted(permission, granter):
self.data[permission].remove(granter)
if len(self.data[permission]) == 0:
del self.data[permission]
def is_granted(self, permission, granter):
return granter in self.get(permission, [])
class DulcineaUser(DulcineaPersistent):
"""
a registered user.
"""
global_permissions = {
"act-as":
"Allow to act as another user.",
"create-users":
"Allow the creation of other users.",
"manage-permissions":
"Allow changing of permissions.",
"staff":
("Is a member of the staff, with all of the privileges and "
"responsibilities thereunto appertaining."),
"system":
"Allow to do things normally done by the software system.",
}
user_id_re = re.compile('^[-A-Za-z0-9_@.]*$')
id_is = spec(
string,
"unique identifier for this user")
password_hash_is = spec(
(string, None),
"the hashed version of the user's password, created using "
"the hash_password function")
email_is = (string, None)
permissions_is = Permissions
def __init__(self, user_id=None):
init(self, permissions=Permissions())
if user_id is not None:
self.set_id(user_id)
def __str__(self):
return self.id or "*no id*"
format = format_realname = __str__ # subclasses should override
def get_key(self):
""" used for forming component representing this user in URLs
"""
return self.get_id()
def set_id(self, user_id):
require(user_id, string)
assert self.id is None, "'id' may only be set once"
if not self.user_id_re.match(user_id):
raise ValueError(
'Invalid user ID %r: can only contain '
'letters, numbers, and "-_@."' % user_id)
self.id = user_id
def set_password(self, new_password, check=True):
"""Set the user's password to 'new_password'."""
if check and self.check_new_password(new_password) != "":
raise ValueError, 'invalid password'
self.password_hash = hash_password(new_password)
def valid_password(self, password):
"""Return true if the provided password is correct."""
return self.password_hash == hash_password(password)
def generate_password (self, length=6):
"""Set the password to a random value and return the new password."""
password = binascii.b2a_base64(binascii.unhexlify(randbytes(length)))
password = password[:length]
self.set_password(password)
return password
def check_new_password(self, new_password):
"""(string) -> string
Check if a new password is valid. Returns the empty string if the
password is okay otherwise returns a string that describes what is
wrong with the entered password.
"""
return ""
def format_realname(self):
return ''
def is_null(self):
return self.id == ''
def is_disabled(self):
return self.password_hash is None
def __nonzero__(self):
return not self.is_null()
def is_system(self):
return self.id == 'SYSTEM'
def is_admin(self):
return self.is_granted('staff')
def is_granted(self, permission, granter=True):
return self.get_permissions().is_granted(permission, granter)
def can_manage_permissions(self):
return self.is_granted('manage-permissions')
add_getters_and_setters(DulcineaUser)
class DulcineaUserDatabase(DulcineaPersistent):
"""
Class to hold all users in the system. User IDs are always looked
up in the user database, so you will generally not be able to use
a user until it has been added to the user database.
"""
users_is = spec(
mapping({string:DulcineaUser}, PersistentDict),
"all known users")
motd_is = spec(
string,
"message-of-the-day")
user_class = DulcineaUser
def __init__(self):
self.users = PersistentDict()
self.motd = ''
def get_all_users(self):
return self.users.values()
def __iter__(self):
return self.users.itervalues()
def get_users(self, sort=0):
users = [user for user in self.users.itervalues()
if not (user.is_null() or
user.is_system() or
user.is_disabled())]
if sort:
users = lexical_sort(users)
return users
def get_disabled_users(self, sort=0):
users = [user for user in self.users.itervalues()
if user.is_disabled() and not (user.is_null() or
user.is_system())]
if sort:
users = lexical_sort(users)
return users
def get_matching_user(self, identifier):
"""(identifier : string) -> DulcineaUser | None
Return a user with matching id or email address, or None
if no such user is found.
"""
user = self.get_user(identifier)
if user:
return user
elif '@' in identifier:
identifier = identifier.lower()
for user in self.users.itervalues():
if (user.get_email() or '').lower() == identifier:
return user
return None
def get_user(self, user_id):
"""Return the User object with id 'user_id', or None if no such user.
"""
return self.users.get(user_id)
def __getitem__(self, user_id):
return self.users[user_id]
def add_user(self, user):
"""Add User object 'user' to the user database.
"""
assert not self.users.has_key(user.get_id())
self.users[user.id] = user
def get_admin(self):
"""Subclasses should override to return a PermissionManager
"""
return None
def get_null_user(self):
user = self.users.get('')
if user is None:
user = self.user_class(user_id='')
self.add_user(user)
return user
def get_motd(self):
return self.motd
def set_motd(self, motd):
self.motd = motd or ''
def gen_users_granted(self, permission, granter=True):
for user in self:
if user.is_granted(permission, granter):
yield user | PypiClean |
/FlexGet-3.9.6-py3-none-any.whl/flexget/components/sites/sites/filelist.py | import datetime
import re
from loguru import logger
from sqlalchemy import Column, DateTime, Unicode
from flexget import db_schema, plugin
from flexget.entry import Entry
from flexget.event import event
from flexget.manager import Session
from flexget.utils.database import json_synonym
from flexget.utils.requests import RequestException, TimedLimiter
from flexget.utils.requests import Session as RequestSession
from flexget.utils.soup import get_soup
from flexget.utils.tools import parse_filesize
logger = logger.bind(name='filelist')
Base = db_schema.versioned_base('filelist', 0)
requests = RequestSession()
requests.add_domain_limiter(TimedLimiter('filelist.ro', '2 seconds'))
BASE_URL = 'https://filelist.ro/'
CATEGORIES = {
'all': 0,
'anime': 24,
'audio': 11,
'cartoons': 15,
'docs': 16,
'games console': 10,
'games pc': 9,
'linux': 17,
'misc': 18,
'mobile': 22,
'movies 3d': 25,
'movies 4k': 6,
'movies 4k blueray': 26,
'movies bluray': 20,
'movies dvd': 2,
'movies dvd-ro': 3,
'movies hd': 4,
'movies hd-ro': 19,
'movies sd': 1,
'series 4k': 27,
'series hd': 21,
'series sd': 23,
'software': 8,
'sport': 13,
'tv': 14,
'videoclip': 12,
'xxx': 7,
}
SORTING = {'hybrid': 0, 'relevance': 1, 'date': 2, 'size': 3, 'snatches': 4, 'peers': 5}
SEARCH_IN = {'both': 0, 'title': 1, 'description': 2}
class FileListCookie(Base):
__tablename__ = 'filelist_cookie'
username = Column(Unicode, primary_key=True)
_cookie = Column('cookie', Unicode)
cookie = json_synonym('_cookie')
expires = Column(DateTime)
class SearchFileList:
"""
FileList.ro search plugin.
"""
schema = {
'type': 'object',
'deprecated': 'plugin filelist is deprecated, please consider using plugin filelist_api',
'properties': {
'username': {'type': 'string'},
'password': {'type': 'string'},
'passkey': {'type': 'string'},
'category': {'type': 'string', 'enum': list(CATEGORIES.keys()), 'default': 'all'},
'order_by': {'type': 'string', 'enum': list(SORTING.keys()), 'default': 'hybrid'},
'order_ascending': {'type': 'boolean', 'default': False},
'search_in': {'type': 'string', 'enum': list(SEARCH_IN.keys()), 'default': 'both'},
'include_dead': {'type': 'boolean', 'default': False},
},
'required': ['username', 'password', 'passkey'],
'additionalProperties': False,
}
errors = False
def get(self, url, params, username, password, force=False):
"""
Wrapper to allow refreshing the cookie if it is invalid for some reason
:param str url:
:param list params:
:param str username:
:param str password:
:param bool force: flag used to refresh the cookie forcefully ie. forgo DB lookup
:return:
"""
cookies = self.get_login_cookie(username, password, force=force)
response = requests.get(url, params=params, cookies=cookies)
if 'login.php' in response.url:
if self.errors:
raise plugin.PluginError(
'FileList.ro login cookie is invalid. Login page received?'
)
self.errors = True
# try again
response = self.get(url, params, username, password, force=True)
else:
self.errors = False
return response
def get_login_cookie(self, username, password, force=False):
"""
Retrieves login cookie
:param str username:
:param str password:
:param bool force: if True, then retrieve a fresh cookie instead of looking in the DB
:return:
"""
if not force:
with Session() as session:
saved_cookie = (
session.query(FileListCookie)
.filter(FileListCookie.username == username.lower())
.first()
)
if (
saved_cookie
and saved_cookie.expires
and saved_cookie.expires >= datetime.datetime.now()
):
logger.debug('Found valid login cookie')
return saved_cookie.cookie
url = BASE_URL + 'takelogin.php'
try:
# get validator token
response = requests.get(BASE_URL + 'login.php')
soup = get_soup(response.content)
login_validator = soup.find("input", {"name": "validator"})
if not login_validator:
raise plugin.PluginError('FileList.ro could not get login validator')
logger.debug('Login Validator: {}'.format(login_validator.get('value')))
logger.debug('Attempting to retrieve FileList.ro cookie')
response = requests.post(
url,
data={
'username': username,
'password': password,
'validator': login_validator.get('value'),
'login': 'Log in',
'unlock': '1',
},
timeout=30,
)
except RequestException as e:
raise plugin.PluginError('FileList.ro login failed: %s' % e)
if 'https://filelist.ro/my.php' != response.url:
raise plugin.PluginError(
'FileList.ro login failed: Your username or password was incorrect.'
)
with Session() as session:
expires = None
for c in requests.cookies:
if c.name == 'pass':
expires = c.expires
if expires:
expires = datetime.datetime.fromtimestamp(expires)
logger.debug('Saving or updating FileList.ro cookie in db')
cookie = FileListCookie(
username=username.lower(), cookie=dict(requests.cookies), expires=expires
)
session.merge(cookie)
return cookie.cookie
@plugin.internet(logger)
def search(self, task, entry, config):
"""
Search for entries on FileList.ro
"""
entries = []
params = {
'cat': CATEGORIES[config['category']],
'incldead': int(config['include_dead']),
'order_by': SORTING[config['order_by']],
'searchin': SEARCH_IN[config['search_in']],
'asc': int(config['order_ascending']),
}
for search_string in entry.get('search_strings', [entry['title']]):
params['search'] = search_string
logger.debug('Using search params: {}', params)
try:
page = self.get(
BASE_URL + 'browse.php', params, config['username'], config['password']
)
logger.debug('requesting: {}', page.url)
except RequestException as e:
logger.error('FileList.ro request failed: {}', e)
continue
soup = get_soup(page.content)
for result in soup.findAll('div', attrs={'class': 'torrentrow'}):
e = Entry()
torrent_info = result.findAll('div', attrs={'class': 'torrenttable'})
# genres
genres = torrent_info[1].find('font')
if genres:
genres = genres.text.lstrip('[').rstrip(']').replace(' ', '')
genres = genres.split('|')
tags = torrent_info[1].findAll('img')
freeleech = False
internal = False
for tag in tags:
if tag.get('alt', '').lower() == 'freeleech':
freeleech = True
if tag.get('alt', '').lower() == 'internal':
internal = True
title = torrent_info[1].find('a').get('title')
# this is a dirty fix to get the full title since their developer is a moron
if re.match(r"\<img src=\'.*\'\>", title):
title = torrent_info[1].find('b').text
# if the title is shortened, then do a request to get the full one :(
if title.endswith('...'):
url = BASE_URL + torrent_info[1].find('a')['href']
try:
request = self.get(url, {}, config['username'], config['password'])
except RequestException as e:
logger.error('FileList.ro request failed: {}', e)
continue
title_soup = get_soup(request.content)
title = title_soup.find('div', attrs={'class': 'cblock-header'}).text
e['title'] = title
e['url'] = (
BASE_URL + torrent_info[3].find('a')['href'] + '&passkey=' + config['passkey']
)
e['content_size'] = parse_filesize(torrent_info[6].find('font').text)
e['torrent_snatches'] = int(
torrent_info[7]
.find('font')
.text.replace(' ', '')
.replace('times', '')
.replace(',', '')
)
e['torrent_seeds'] = int(torrent_info[8].find('span').text)
e['torrent_leeches'] = int(torrent_info[9].find('span').text)
e['torrent_internal'] = internal
e['torrent_freeleech'] = freeleech
if genres:
e['torrent_genres'] = genres
entries.append(e)
return entries
@event('plugin.register')
def register_plugin():
plugin.register(SearchFileList, 'filelist', interfaces=['search'], api_ver=2) | PypiClean |
/MXFusion-0.3.1.tar.gz/MXFusion-0.3.1/mxfusion/components/distributions/gp/kernels/rbf.py |
from .stationary import StationaryKernel
class RBF(StationaryKernel):
"""
Radial Basis Function kernel, aka squared-exponential, exponentiated quadratic or Gaussian kernel:
.. math::
k(r^2) = \\sigma^2 \\exp \\bigg(- \\frac{1}{2} r^2 \\bigg)
:param input_dim: the number of dimensions of the kernel. (The total number of active dimensions)
:type input_dim: int
:param ARD: a binary switch for Automatic Relevance Determination (ARD). If true, the squared distance is divided
by a lengthscale for individual dimensions.
:type ARD: boolean
:param variance: the initial value for the variance parameter (scalar), which scales the whole covariance matrix.
:type variance: float or MXNet NDArray
:param lengthscale: the initial value for the lengthscale parameter.
:type lengthscale: float or MXNet NDArray
:param name: the name of the kernel. The name is used to access kernel parameters.
:type name: str
:param active_dims: The dimensions of the inputs that are taken for the covariance matrix computation.
(default: None, taking all the dimensions).
:type active_dims: [int] or None
:param dtype: the data type for float point numbers.
:type dtype: numpy.float32 or numpy.float64
:param ctx: the mxnet context (default: None/current context).
:type ctx: None or mxnet.cpu or mxnet.gpu
"""
broadcastable = True
def __init__(self, input_dim, ARD=False, variance=1., lengthscale=1.,
name='rbf', active_dims=None, dtype=None, ctx=None):
super(RBF, self).__init__(
input_dim=input_dim, ARD=ARD, variance=variance,
lengthscale=lengthscale, name=name, active_dims=active_dims,
dtype=dtype, ctx=ctx)
def _compute_K(self, F, X, lengthscale, variance, X2=None):
"""
The internal interface for the actual covariance matrix computation.
:param F: MXNet computation type <mx.sym, mx.nd>.
:param X: the first set of inputs to the kernel.
:type X: MXNet NDArray or MXNet Symbol
:param X2: (optional) the second set of arguments to the kernel. If X2 is None, this computes a square
covariance matrix of X. In other words, X2 is internally treated as X.
:type X2: MXNet NDArray or MXNet Symbol
:param variance: the variance parameter (scalar), which scales the whole covariance matrix.
:type variance: MXNet NDArray or MXNet Symbol
:param lengthscale: the lengthscale parameter.
:type lengthscale: MXNet NDArray or MXNet Symbol
:return: The covariance matrix.
:rtype: MXNet NDArray or MXNet Symbol
"""
R2 = self._compute_R2(F, X, lengthscale, variance, X2=X2)
return F.exp(R2 / -2) * F.expand_dims(variance, axis=-1) | PypiClean |
/GxSphinx-1.0.0.tar.gz/GxSphinx-1.0.0/sphinx/builders/latex/constants.py | from typing import Any, Dict
PDFLATEX_DEFAULT_FONTPKG = r'''
\usepackage{times}
\expandafter\ifx\csname T@LGR\endcsname\relax
\else
% LGR was declared as font encoding
\substitutefont{LGR}{\rmdefault}{cmr}
\substitutefont{LGR}{\sfdefault}{cmss}
\substitutefont{LGR}{\ttdefault}{cmtt}
\fi
\expandafter\ifx\csname T@X2\endcsname\relax
\expandafter\ifx\csname T@T2A\endcsname\relax
\else
% T2A was declared as font encoding
\substitutefont{T2A}{\rmdefault}{cmr}
\substitutefont{T2A}{\sfdefault}{cmss}
\substitutefont{T2A}{\ttdefault}{cmtt}
\fi
\else
% X2 was declared as font encoding
\substitutefont{X2}{\rmdefault}{cmr}
\substitutefont{X2}{\sfdefault}{cmss}
\substitutefont{X2}{\ttdefault}{cmtt}
\fi
'''
XELATEX_DEFAULT_FONTPKG = r'''
\setmainfont{FreeSerif}[
Extension = .otf,
UprightFont = *,
ItalicFont = *Italic,
BoldFont = *Bold,
BoldItalicFont = *BoldItalic
]
\setsansfont{FreeSans}[
Extension = .otf,
UprightFont = *,
ItalicFont = *Oblique,
BoldFont = *Bold,
BoldItalicFont = *BoldOblique,
]
\setmonofont{FreeMono}[
Extension = .otf,
UprightFont = *,
ItalicFont = *Oblique,
BoldFont = *Bold,
BoldItalicFont = *BoldOblique,
]
'''
XELATEX_GREEK_DEFAULT_FONTPKG = (XELATEX_DEFAULT_FONTPKG +
'\n\\newfontfamily\\greekfont{FreeSerif}' +
'\n\\newfontfamily\\greekfontsf{FreeSans}' +
'\n\\newfontfamily\\greekfonttt{FreeMono}')
LUALATEX_DEFAULT_FONTPKG = XELATEX_DEFAULT_FONTPKG
DEFAULT_SETTINGS = {
'latex_engine': 'pdflatex',
'papersize': '',
'pointsize': '',
'pxunit': '.75bp',
'classoptions': '',
'extraclassoptions': '',
'maxlistdepth': '',
'sphinxpkgoptions': '',
'sphinxsetup': '',
'fvset': '\\fvset{fontsize=\\small}',
'passoptionstopackages': '',
'geometry': '\\usepackage{geometry}',
'inputenc': '',
'utf8extra': '',
'cmappkg': '\\usepackage{cmap}',
'fontenc': '\\usepackage[T1]{fontenc}',
'amsmath': '\\usepackage{amsmath,amssymb,amstext}',
'multilingual': '',
'babel': '\\usepackage{babel}',
'polyglossia': '',
'fontpkg': PDFLATEX_DEFAULT_FONTPKG,
'substitutefont': '',
'textcyrillic': '',
'textgreek': '\\usepackage{textalpha}',
'fncychap': '\\usepackage[Bjarne]{fncychap}',
'hyperref': ('% Include hyperref last.\n'
'\\usepackage{hyperref}\n'
'% Fix anchor placement for figures with captions.\n'
'\\usepackage{hypcap}% it must be loaded after hyperref.\n'
'% Set up styles of URL: it should be placed after hyperref.\n'
'\\urlstyle{same}'),
'contentsname': '',
'extrapackages': '',
'preamble': '',
'title': '',
'release': '',
'author': '',
'releasename': '',
'makeindex': '\\makeindex',
'shorthandoff': '',
'maketitle': '\\sphinxmaketitle',
'tableofcontents': '\\sphinxtableofcontents',
'atendofbody': '',
'printindex': '\\printindex',
'transition': '\n\n\\bigskip\\hrule\\bigskip\n\n',
'figure_align': 'htbp',
'tocdepth': '',
'secnumdepth': '',
} # type: Dict[str, Any]
ADDITIONAL_SETTINGS = {
'pdflatex': {
'inputenc': '\\usepackage[utf8]{inputenc}',
'utf8extra': ('\\ifdefined\\DeclareUnicodeCharacter\n'
'% support both utf8 and utf8x syntaxes\n'
' \\ifdefined\\DeclareUnicodeCharacterAsOptional\n'
' \\def\\sphinxDUC#1{\\DeclareUnicodeCharacter{"#1}}\n'
' \\else\n'
' \\let\\sphinxDUC\\DeclareUnicodeCharacter\n'
' \\fi\n'
' \\sphinxDUC{00A0}{\\nobreakspace}\n'
' \\sphinxDUC{2500}{\\sphinxunichar{2500}}\n'
' \\sphinxDUC{2502}{\\sphinxunichar{2502}}\n'
' \\sphinxDUC{2514}{\\sphinxunichar{2514}}\n'
' \\sphinxDUC{251C}{\\sphinxunichar{251C}}\n'
' \\sphinxDUC{2572}{\\textbackslash}\n'
'\\fi'),
},
'xelatex': {
'latex_engine': 'xelatex',
'polyglossia': '\\usepackage{polyglossia}',
'babel': '',
'fontenc': ('\\usepackage{fontspec}\n'
'\\defaultfontfeatures[\\rmfamily,\\sffamily,\\ttfamily]{}'),
'fontpkg': XELATEX_DEFAULT_FONTPKG,
'textgreek': '',
'utf8extra': ('\\catcode`^^^^00a0\\active\\protected\\def^^^^00a0'
'{\\leavevmode\\nobreak\\ }'),
},
'lualatex': {
'latex_engine': 'lualatex',
'polyglossia': '\\usepackage{polyglossia}',
'babel': '',
'fontenc': ('\\usepackage{fontspec}\n'
'\\defaultfontfeatures[\\rmfamily,\\sffamily,\\ttfamily]{}'),
'fontpkg': LUALATEX_DEFAULT_FONTPKG,
'textgreek': '',
'utf8extra': ('\\catcode`^^^^00a0\\active\\protected\\def^^^^00a0'
'{\\leavevmode\\nobreak\\ }'),
},
'platex': {
'latex_engine': 'platex',
'babel': '',
'classoptions': ',dvipdfmx',
'fontpkg': '\\usepackage{times}',
'textgreek': '',
'fncychap': '',
'geometry': '\\usepackage[dvipdfm]{geometry}',
},
'uplatex': {
'latex_engine': 'uplatex',
'babel': '',
'classoptions': ',dvipdfmx',
'fontpkg': '\\usepackage{times}',
'textgreek': '',
'fncychap': '',
'geometry': '\\usepackage[dvipdfm]{geometry}',
},
# special settings for latex_engine + language_code
('xelatex', 'fr'): {
# use babel instead of polyglossia by default
'polyglossia': '',
'babel': '\\usepackage{babel}',
},
('xelatex', 'zh'): {
'polyglossia': '',
'babel': '\\usepackage{babel}',
'fontenc': '\\usepackage{xeCJK}',
},
('xelatex', 'el'): {
'fontpkg': XELATEX_GREEK_DEFAULT_FONTPKG,
},
} # type: Dict[Any, Dict[str, Any]]
SHORTHANDOFF = r'''
\ifdefined\shorthandoff
\ifnum\catcode`\=\string=\active\shorthandoff{=}\fi
\ifnum\catcode`\"=\active\shorthandoff{"}\fi
\fi
''' | PypiClean |
/ANNOgesic-1.1.14.linux-x86_64.tar.gz/usr/local/lib/python3.10/dist-packages/annogesiclib/seq_editer.py | import os
import shutil
import sys
import csv
from Bio import SeqIO
from Bio.SeqRecord import SeqRecord
from Bio.Seq import Seq
from annogesiclib.seqmodifier import SeqModifier
class SeqEditer(object):
'''Edit the sequence if it is needed'''
def _row_to_location(self, row, out_name):
return({"ref_id": row[0], "target_id": "_".join([out_name, row[0]]),
"datas": [{"ref_nt": row[3],
"tar_nt": row[4], "position": row[1]}]})
def _import_data(self, mod_table_file, out_name):
datas = []
first = True
num_index = 0
fh = open(mod_table_file)
for row in csv.reader(fh, delimiter="\t"):
if row[0].startswith("#"):
continue
else:
if first:
datas.append(self._row_to_location(row, out_name))
pre_ref_id = row[0].strip()
first = False
else:
if (row[0] == pre_ref_id):
datas[num_index]["datas"].append(
{"ref_nt": row[3].strip(),
"tar_nt": row[4].strip(),
"position": row[1].strip()})
else:
datas.append(self._row_to_location(row, out_name))
num_index += 1
pre_ref_id = row[0].strip()
fh.close()
return datas
def modify_seq(self, fasta_folder, mod_table_file, output_folder, out_name):
datas = self._import_data(mod_table_file, out_name)
for data in datas:
seq = ""
if (data["ref_id"] + ".fa") in os.listdir(fasta_folder):
filename = os.path.join(fasta_folder, data["ref_id"] + ".fa")
with open(filename, "r") as fasta:
for line in fasta:
line = line.strip()
if len(line) != 0:
if line[0] != ">":
seq = seq + line
seq_modifier = SeqModifier(seq)
for change in data["datas"]:
if change["ref_nt"] == "-":
seq_modifier.insert(
int(change["position"]), change["tar_nt"])
elif change["tar_nt"] == "-":
seq_modifier.remove(int(change["position"]),
len(change["ref_nt"]))
else:
seq_modifier.replace(
int(change["position"]), change["tar_nt"])
record = SeqRecord(Seq(seq_modifier.seq()))
record.id = data["target_id"]
record.description = ""
SeqIO.write(record, os.path.join(
output_folder, record.id + ".fa"), "fasta")
def modify_header(self, input_file):
first = True
tmp_file_path = input_file + "_TMP"
output_fh = open(input_file + "_TMP", "w")
with open(input_file, "r") as s_h:
for line in s_h:
line = line.strip()
if first:
first = False
if (line[0] != ">"):
print("Error: No proper header!!")
sys.exit()
if line.startswith(">"):
mod = line.split("|")
folder = input_file.split("/")
folder = "/".join(folder[:-1])
if (len(mod) == 5) and (line[0] == ">"):
new_header = ">%s" % (mod[3])
elif (len(mod) != 5) and (line[0] == ">"):
new_header = line.split(" ")[0]
elif (line[0] != ">"):
print("Error: No proper header!!")
sys.exit()
line = new_header
output_fh.write(line + "\n")
output_fh.close()
shutil.move(tmp_file_path, input_file) | PypiClean |
/BaculaFS-0.1.7.tar.gz/BaculaFS-0.1.7/baculafs/FileSystem.py |
__version__ = '0.1.7'
import os
import sys
import stat
import errno
import copy
import tempfile
import shutil
import threading
import traceback
import pexpect
import fcntl
import time
import re
import binascii
from LogFile import *
from Database import *
from Catalog import *
from SQL import *
# pull in some spaghetti to make this stuff work without fuse-py being installed
try:
import _find_fuse_parts
except ImportError:
pass
import fuse
from fuse import Fuse
if not hasattr(fuse, '__version__'):
raise RuntimeError, \
"your fuse-py doesn't know of fuse.__version__, probably it's too old."
fuse.fuse_python_api = (0, 2)
fuse.feature_assert('stateful_files', 'has_init')
def flag2mode(flags):
'''
taken from python-fuse xmp.py example
'''
md = {os.O_RDONLY: 'r', os.O_WRONLY: 'w', os.O_RDWR: 'w+'}
m = md[flags & (os.O_RDONLY | os.O_WRONLY | os.O_RDWR)]
if flags | os.O_APPEND:
m = m.replace('w', 'a', 1)
return m
def makedirs(path):
'''
create path like mkdir -p
taken from: http://stackoverflow.com/questions/600268/mkdir-p-functionality-in-python/600612#600612
'''
try:
os.makedirs(path)
except OSError, exc:
if exc.errno == errno.EEXIST:
pass
else:
raise
def touch(fname, times = None):
'''
touch file
adapted from: http://stackoverflow.com/questions/1158076/implement-touch-using-python/1160227#1160227
'''
fhandle = open(fname, 'a')
try:
os.utime(fname, times)
finally:
fhandle.close()
class FileSystem(Fuse) :
null_stat = fuse.Stat(st_mode=stat.S_IFDIR | 0755,
st_ino=0,
st_dev=0,
st_nlink=2,
st_uid=0,
st_gid=0,
st_size=0,
st_atime=0,
st_mtime=0,
st_ctime=0,
st_blksize=0,
st_rdev=0)
bacula_stat_fields = ['st_dev',
'st_ino',
'st_mode',
'st_nlink',
'st_uid',
'st_gid',
'st_rdev',
'st_size',
'st_blksize',
'st_blocks',
'st_atime',
'st_mtime',
'st_ctime',
'st_linkfi',
'st_flags',
'st_streamid']
fuse_stat_fields = [attr for attr in dir(null_stat) if attr.startswith('st_')]
xattr_prefix = 'user.baculafs.'
xattr_fields = ['FileIndex', 'JobId', 'LStat', 'MD5']
xattr_fields_root = ['client', 'fileset', 'datetime', 'joblist', 'cache_prefix']
xattr_fields_bextract = ['path', 'volume', 'retries', 'state', 'pending', 'failures']
bextract_done = {'path': None,
'volume': None,
'retries': 0,
'state': 'idle'}
def __init__(self, *args, **kw):
'''
Initialize filesystem
'''
self._extract_lock = threading.Lock()
self._getattr_lock = threading.Lock()
self._bextract_status_lock = threading.Lock()
self._bextract_user_intervention_event = threading.Event()
self._initialized = False
# default option values
self.logging = 'info'
self.syslog = False
self.driver = SQL.SQLITE3
self.database = None
self.host = 'localhost'
self.port = 0
self.username = 'bacula'
self.password = None
self.conf = '/etc/bacula/bacula-sd.conf'
self.client = ''
self.fileset = None
self.device = 'FileStorage'
self.datetime = None
self.recent_job = False
self.joblist = None
self.cache_prefix = None
self.user_cache_path = None
self.cleanup = False
self.move_root = False
self.prefetch_attrs = False
self.prefetch_regex = None
self.prefetch_symlinks = False
self.prefetch_recent = False
self.prefetch_diff = None
self.prefetch_difflist = None
self.prefetch_list = None
self.prefetch_everything = False
self.batch_mode = False
self.batch_list = False
self.batch_bsr = False
self.batch_extract = False
self.use_ino = False
self.max_ino = 0
self.dirs = { '/': { '': (FileSystem.null_stat,) } }
self._bextract_status = copy.deepcopy(FileSystem.bextract_done)
self._bextract_status['pending'] = 0
self._bextract_status['failures'] = 0
class File (FileSystem._File):
def __init__(self2, *a, **kw):
FileSystem._File.__init__(self2, self, *a, **kw)
self.file_class = File
Fuse.__init__(self, *args, **kw)
def _split(self, path) :
'''
os.path.split wrapper
'''
head, tail = os.path.split(path)
if head and not head.endswith('/') :
head += '/'
return head, tail
def _bacula_stat(self, base64) :
'''
Parse base64 encoded lstat info.
Returns fuse.Stat object with subset of decoded values,
and dictionary with full list of decoded values
'''
st = fuse.Stat()
lst = dict(zip(FileSystem.bacula_stat_fields, map(self.base64.decode, base64.split())))
for k in FileSystem.bacula_stat_fields :
if k in FileSystem.fuse_stat_fields :
setattr(st, k, lst[k])
return lst, st
def _add_parent_dirs(self, path) :
'''
add parent directories of path to dirs dictionary
'''
head, tail = self._split(path[:-1])
if not head or head == path:
return
if not head in self.dirs :
self.dirs[head] = { tail: (FileSystem.null_stat,) }
elif not tail in self.dirs[head] :
self.dirs[head][tail] = (FileSystem.null_stat,)
self._add_parent_dirs(head)
def _update_inodes(self, head) :
'''
generate unique st_ino for each missing st_ino
'''
for tail in self.dirs[head] :
if self.dirs[head][tail][-1].st_ino == 0 :
if len(self.dirs[head][tail]) == 1:
self.dirs[head][tail] = (copy.deepcopy(FileSystem.null_stat),)
self.max_ino += 1
self.dirs[head][tail][-1].st_ino = self.max_ino
subdir = '%s%s/' % (head, tail)
if subdir in self.dirs :
self._update_inodes(subdir)
def _extract(self, path_list) :
'''
extract path list from storage, returns path list of extracted files
'''
nitems = len(path_list)
self._bextract_increment_counter('pending', nitems)
# serialize extractions
self._extract_lock.acquire()
items = []
realpath_list = []
hardlink_targets = []
for path in path_list :
realpath, symlinkinfo, volumes = self._find_volumes(path)
realpath_list.append(realpath)
if volumes :
items.append((symlinkinfo, path, volumes))
# collect hard link targets
hardlink_target = self._hardlink_target(path)
if (hardlink_target and
hardlink_target not in path_list and
hardlink_target not in hardlink_targets) :
hardlink_targets.append(hardlink_target)
# add hardlink targets to list
# bextract will fail to extract the hardlink if its target does not exist
for path in hardlink_targets :
realpath, symlinkinfo, volumes = self._find_volumes(path)
if volumes :
items.append((symlinkinfo, path, volumes))
if len(items) > 0 :
rc, sig = self._bextract(items)
# it seems that bextract does not restore mtime for symlinks
# so we create a normal file with same mtime as stored symlink
if rc == 0 and not self.batch_mode :
for item in items :
if item[0] :
symlinkfile = item[0][0]
symlinktime = item[0][1:]
makedirs(os.path.dirname(symlinkfile))
touch(symlinkfile, symlinktime)
self._extract_lock.release()
self._bextract_increment_counter('pending', -nitems)
return realpath_list
def _hardlink_target(self, path) :
'''
return hard link target of path if it is a hard link
'''
head, tail = self._split(path)
bs = self.dirs[head][tail][-2]
jobid = self.dirs[head][tail][1]
if bs['st_nlink'] > 1 and bs['st_linkfi'] > 0 :
st_linkfi = bs['st_linkfi']
for file in self.catalog.files :
if jobid == file[3] and st_linkfi == file[2] :
hardlink_target = ('/' if not file[0].startswith('/') else '')+file[0]+file[1]
return hardlink_target
return None
def _find_volumes(self, path) :
'''
return list of volumes that contain path to be extracted,
if the path has not been extracted yet
'''
realpath = os.path.normpath(self.cache_path + path)
symlinkpath = os.path.normpath(self.cache_symlinks + path)
head, tail = self._split(path)
# sanity check: path should not be a directory
if tail == '':
raise RuntimeError, 'trying to extract a directory %s' % path
# check that path exists in catalog
if head not in self.dirs or tail not in self.dirs[head] :
return None, None, None
# sanity check: path entry is incomplete
if len(self.dirs[head][tail]) == 1 :
raise RuntimeError, 'incomplete entry for path %s' % path
# return if file has already been extracted
bs = self.getattr(path)
is_symlink = stat.S_ISLNK(bs.st_mode)
found = False
if os.path.exists(realpath) or os.path.lexists(realpath) :
# make sure that stat info of realpath matches path
s = os.lstat(realpath)
conds = [getattr(s, attr) == getattr(bs, attr)
for attr in ['st_mode', 'st_uid', 'st_gid', 'st_size', 'st_mtime']]
if is_symlink :
conds[-1] = (os.path.exists(symlinkpath) and
bs.st_mtime == os.stat(symlinkpath).st_mtime)
if all(conds) :
return realpath, None, None
# generate list of volumes for path
fileindex, jobid = self.dirs[head][tail][0:2]
jobs = [job for job in self.catalog.jobs
if job[0] == jobid]
volumes = [[volume[1], # 0-Volume
volume[2], # 1-MediaType
self.device, # 2-Device
jobs[0][0], # 3-JobId
jobs[0][1], # 4-VolSessionId
jobs[0][2], # 5-VolSessionTime
(volume[5] << 32) | volume[7], # 6-VolAddr: StartAddr
(volume[6] << 32) | volume[8], # 7-VolAddr: EndAddr
fileindex] # 8-FileIndex
for volume in self.catalog.volumes
if (volume[0] == jobid and
volume[3] <= fileindex and
fileindex <= volume[4])]
return realpath, (symlinkpath, bs.st_atime, bs.st_mtime) if is_symlink else None, volumes
def _bextract_set_status(self, status) :
'''
thread safe modification of bextract status dict
'''
self._bextract_status_lock.acquire()
for key in status :
self._bextract_status[key] = status[key]
self._bextract_status_lock.release()
def _bextract_increment_counter(self, counter, n) :
'''
thread safe modification of bextract counters
'''
self._bextract_status_lock.acquire()
self._bextract_status[counter] += n
self._bextract_status_lock.release()
def _bextract_get_status(self) :
'''
thread safe access to bextract status dict
'''
self._bextract_status_lock.acquire()
status = copy.deepcopy(self._bextract_status)
self._bextract_status_lock.release()
return status
def _bextract_flock(self) :
'''
lock the storage daemon configuration file
'''
# we allow locking to fail, so as to allow
# at least a single instance of baculafs,
# even if we can't lock the sd conf file
try :
f = open(self.conf, 'r')
fcntl.flock(f, fcntl.LOCK_EX)
return f
except :
self.logger.warning(traceback.format_exc())
return None
def _bextract_funlock(self, f) :
'''
unlock the file f
'''
if not f :
return
try :
fcntl.flock(f, fcntl.LOCK_UN)
f.close()
except :
self.logger.warning(traceback.format_exc())
def _bextract(self, items) :
'''
extract list of items from Bacula storage device
'''
if self.batch_list :
for item in items :
print item[1]
if (not self.batch_bsr and
not self.batch_extract) :
return (0, 0)
bsrpath = self._write_bsr(items)
if self.batch_bsr :
bsrfile = open(bsrpath, 'rt')
for line in bsrfile :
sys.stdout.write(line)
sys.stdout.flush()
bsrfile.close()
if not self.batch_extract :
return (0, 0)
if self.batch_extract :
makedirs(self.fuse_args.mountpoint)
cmd = 'bextract -b "%s" -c "%s" "%s" "%s"' % (bsrpath,
self.conf,
self.device,
self.cache_path if not self.batch_extract else self.fuse_args.mountpoint)
self.logger.debug(cmd)
self._bextract_set_status({'path': items[0][1],
'volume': items[0][-1][0][0],
'retries': 0,
'state': 'run'})
# we serialize calls to bextract across instances of baculafs
# by locking the storage daemon configuration file
# (note that this may not work over NFS)
f = self._bextract_flock()
child = pexpect.spawn(cmd)
child.logfile = self.logfile #sys.stdout
attempt = 0
missing = ''
while True :
# bextract either finishes or waits for a missing volume
i = child.expect([self.fail_pattern, pexpect.EOF],
timeout=None,
searchwindowsize=200)
self.logfile.flush(flush_tail = True)
if i == 0 :
# count retries
if missing == child.match.groups()[0] :
attempt += 1
self._bextract_set_status({'retries': attempt,
'state': '*user intervention required*'})
else :
attempt = 1
missing = child.match.groups()[0]
self._bextract_set_status({'volume': missing,
'retries': attempt,
'state': '*user intervention required*'})
# wait for user
if not self._initialized :
if self.loglevel != logging.DEBUG :
sys.stdout.write('Mount Volume "%s" on device "%s" %s and press return when ready: ' %
(missing, self.device, child.match.groups()[1]))
sys.stdout.flush()
sys.stdin.read(1)
else :
self.logger.error('Mount volume "%s" on device "%s" %s and run "attr -s baculafs.bextract.state -V run %s" when ready' %
(missing, self.device, child.match.groups()[1], self.fuse_args.mountpoint))
self._bextract_user_intervention_event.clear()
self._bextract_user_intervention_event.wait()
self._bextract_user_intervention_event.clear()
# retry
self._bextract_set_status({'state': 'run'})
child.sendline('')
else :
child.close()
break
# unlock the sd configuration file
self._bextract_funlock(f)
self._bextract_set_status(FileSystem.bextract_done)
if child.exitstatus or child.signalstatus :
self.logger.error('extraction failed (bsr file: %s)' % bsrpath)
self._bextract_increment_counter('failures', 1)
return (child.exitstatus, child.signalstatus)
def _group_by_volume(self, items) :
'''
return items grouped by volume
'''
# group volumes
volumes = []
for item in items :
for v in item[-1] :
found = False
findex = v[-1]
for vindex in xrange(0,len(volumes)) :
volume = volumes[vindex]
if not any(map(cmp, v[:-1], volume[:-1])) :
volume[-1].append(findex)
found = True
break
if not found :
volumes.append(v[:-1] + [[v[-1]]])
# compact list of file indices
for volume in volumes :
volume[-1] = list(set(volume[-1]))
volume[-1].sort()
l = len(volume[-1])
findex = volume[-1][0]
findices = [(findex, findex)]
for idx in volume[-1][1:] :
next_idx = findices[-1][-1] + 1
if idx == next_idx :
findices[-1] = (findices[-1][0], idx)
else :
findices.append((idx,idx))
volume[-1] = findices
volume.append(l)
# reorder volumes to ensure correct handling of
# files spanning multiple volumes
volumes.sort(cmp = lambda a,b : \
(cmp(a[3],b[3]) or
cmp(a[8][-1][-1], b[8][0][0])))
return volumes
def _write_bsr(self, items) :
'''
generate bsr for items to be extracted
'''
bsrfd, bsrpath = tempfile.mkstemp(suffix='.bsr', dir=self.cache_bsrpath, text=True)
volumes = self._group_by_volume(items)
for volume in volumes :
os.write(bsrfd, 'Volume="%s"\n' % volume[0])
os.write(bsrfd, 'MediaType="%s"\n' % volume[1])
os.write(bsrfd, 'Device="%s"\n' % volume[2])
os.write(bsrfd, 'VolSessionId=%d\n' % volume[4])
os.write(bsrfd, 'VolSessionTime=%d\n' % volume[5])
if not self.bsr_compat :
os.write(bsrfd, 'VolAddr=%d-%d\n' % (volume[6],volume[7]))
for findex in volume[8] :
if findex[0] == findex[1] :
os.write(bsrfd, 'FileIndex=%d\n' % findex[0])
else :
os.write(bsrfd, 'FileIndex=%d-%d\n' % findex)
os.write(bsrfd, 'Count=%d\n' % volume[9])
os.close(bsrfd)
return bsrpath
def _match_stat(self, path, bs) :
'''
determine if stat of path matches bs
'''
found = False
if os.path.exists(path) or os.path.lexists(path) :
s = os.lstat(path)
found = all([getattr(s, attr) == getattr(bs, attr)
for attr in ['st_mode', 'st_uid', 'st_gid', 'st_size', 'st_mtime']])
return found
def _setup_logging(self) :
'''
initialize logging facility
'''
# log messages are sent to both console and syslog
# use -o logging=level to set the log level
# use -o syslog to enable logging to syslog
self.logger = logging.getLogger('BaculaFS')
self.loglevel = LOGGING_LEVELS.get(self.logging, logging.NOTSET)
self.logger.setLevel(self.loglevel)
h = logging.StreamHandler()
h.setLevel(self.loglevel)
formatter = logging.Formatter("%(message)s")
h.setFormatter(formatter)
self.logger.addHandler(h)
if self.syslog :
try :
h = logging.handlers.SysLogHandler('/dev/log')
h.setLevel(self.loglevel)
formatter = logging.Formatter("%(name)s: %(levelname)-8s - %(message)s")
h.setFormatter(formatter)
self.logger.addHandler(h)
except :
self.logger.warning(traceback.format_exc())
self.logfile = LogFile(self.logger, logging.DEBUG)
def initialize(self, version) :
'''
initialize database, catalog
'''
self._setup_logging()
# batch mode
self.batch_mode = (self.batch_list or
self.batch_bsr or
self.batch_extract)
# disable INFO level logging in batch mode
if self.batch_mode and self.loglevel == logging.INFO :
self.loglevel = logging.WARNING
self.logger.setLevel(self.loglevel)
self.logger.info('Populating file system ... ')
# setup cache
if self.user_cache_path :
self.cache_prefix = self.user_cache_path
else :
self.cache_prefix = tempfile.mkdtemp(prefix='baculafs-')
self.cache_path = os.path.normpath(self.cache_prefix + '/files')
makedirs(self.cache_path)
self.cache_bsrpath = os.path.normpath(self.cache_prefix + '/bsr')
makedirs(self.cache_bsrpath)
self.cache_symlinks = os.path.normpath(self.cache_prefix + '/symlinks')
makedirs(self.cache_symlinks)
# test for old version (2.x) of bacula
self.bsr_compat = int(version[0]) < 3
if self.bsr_compat :
self.logger.debug('Detected old Bacula: %s' % version)
# test access to sd conf file
open(self.conf, 'r').close()
# init bextract failure pattren
self.fail_pattern = 'Mount Volume "([^"]+)" on device "%s" (.*) and press return when ready:' % self.device
# init database and catalog
self.db = Database(self.driver,
self.host,
self.port,
self.database,
self.username,
self.password,
self.logger)
self.catalog = Catalog(self.db)
self.base64 = Base64()
files = self.catalog.query(self.client, self.fileset, self.datetime, self.recent_job, self.joblist)
# validated values
self.client = self.catalog.client
self.fileset = self.catalog.fileset[1]
self.datetime = self.catalog.datetime
# we don't need the database anymore
self.db.close()
prefetches = []
difflist = {}
# validate prefetch conditions
if self.prefetch_everything :
self.prefetch_recent = False
self.prefetch_regex = None
self.prefetch_diff = None
self.prefetch_difflist = None
self.prefetch_list = None
self.prefetch_symlinks = True
if self.prefetch_regex :
try :
regex = re.compile(self.prefetch_regex)
self.prefetch_attrs = True
except :
# bad regex: show traceback and ignore
self.logger.warning(traceback.format_exc())
self.prefetch_regex = None
if self.prefetch_diff :
self.prefetch_diff = os.path.normpath(os.path.expanduser(self.prefetch_diff))
try :
if os.path.isdir(self.prefetch_diff) :
self.prefetch_symlinks = True
else :
self.prefetch_diff = None
except :
# can't access target directory: show traceback and ignore
self.logger.warning(traceback.format_exc())
self.prefetch_diff = None
if self.prefetch_difflist :
self.prefetch_difflist = os.path.normpath(os.path.expanduser(self.prefetch_difflist))
try :
difflistfile = sys.stdin if self.prefetch_difflist == '-' else open(self.prefetch_difflist, 'rt')
for line in difflistfile.readlines():
date = ' '.join(line.split()[:5])
difflist[line[(len(date) + 1):].strip()] = time.strptime(date, '%a %b %d %H:%M:%S %Y')
difflistfile.close()
self.prefetch_symlinks = True
except :
# can't access/parse difflist: show traceback and ignore
self.logger.warning(traceback.format_exc())
self.prefetch_difflist = None
if self.prefetch_list :
self.prefetch_list = os.path.normpath(os.path.expanduser(self.prefetch_list))
try :
listfile = sys.stdin if self.prefetch_list == '-' else open(self.prefetch_list, 'rt')
matchlist = [line.strip() for line in listfile.readlines()]
listfile.close()
self.prefetch_symlinks = True
except :
# can't access/parse list: show traceback and ignore
self.logger.warning(traceback.format_exc())
self.prefetch_list = None
if self.prefetch_recent :
self.prefetch_symlinks = True
if self.prefetch_symlinks :
self.prefetch_attrs = True
if 'use_ino' in self.fuse_args.optlist:
self.use_ino = True
self.prefetch_attrs = True # must figure out max st_ino
for file in files :
head = file[0]
tail = file[1]
# handle windows directories
if not head.startswith('/') :
head = '/'+head
# make file entry
if self.prefetch_attrs :
entry = file[2:] + self._bacula_stat(file[-2])
# find max st_ino
if self.use_ino:
if entry[-1].st_ino > self.max_ino :
self.max_ino = entry[-1].st_ino
# detemine if we need to prefetch this entry
filepath = head + tail
if (not stat.S_ISDIR(entry[-1].st_mode) and
(self.prefetch_everything or
(self.prefetch_recent and
file[3] == self.catalog.most_recent_jobid) or
(self.prefetch_regex and
regex.search(filepath)) or
(self.prefetch_diff and
not self._match_stat(self.prefetch_diff + filepath, entry[-1])) or
(self.prefetch_difflist and
(filepath[1:] not in difflist or
difflist[filepath[1:]][:-1] != time.localtime(entry[-1].st_mtime)[:-1])) or
(self.prefetch_list and
filepath in matchlist) or
(self.prefetch_symlinks and
stat.S_ISLNK(entry[-1].st_mode)))) :
prefetches.append(filepath)
else :
entry = file[2:] + (None,) # stat info placeholder
# new directory
if head not in self.dirs :
self.dirs[head] = {}
# add parent directories
self._add_parent_dirs(head)
# directories are added to their parents
if head != '/' and tail == '' :
head, tail = self._split(head[:-1])
# and finally
self.dirs[head][tail] = entry
# fix st_ino
if self.use_ino:
self._update_inodes('/')
npf = len(prefetches)
if npf > 0 :
self.logger.info('Prefetching %d objects ... ' % npf)
self._extract(prefetches)
self.logger.debug('Cache directory is: %s' % self.cache_prefix)
self.joblist = ' '.join([str(job[0]) for job in self.catalog.jobs])
self.logger.debug('Job ids in file system: %s' % self.joblist)
self.logger.info('BaculaFS ready (%d files).' % len(files))
self._initialized = True
def shutdown(self) :
'''
remove cache directory if required
'''
if self.cleanup and not self.user_cache_path and self.cache_prefix :
self.logger.info('removing cache directory: %s' % self.cache_prefix)
shutil.rmtree(self.cache_prefix, ignore_errors = True)
def setxattr(self, path, name, value, flags):
'''
set value of extended attribute
we allow only setting user.baculafs.bextract.state on the root directory
'''
if (path == '/' and
name == FileSystem.xattr_prefix + 'bextract.state' and
value == 'run') :
self._bextract_user_intervention_event.set()
else :
return -errno.EOPNOTSUPP
def getxattr(self, path, name, size):
'''
get value of extended attribute
baculafs exposes some filesystem attributes for the root directory
(e.g. joblist, cache_prefix - see FileSystem.xattr_fields_root)
and several other attributes for each file/directory that appears
in the catalog (e.g. MD5, JobId - see FileSystem.xattr_fields)
'''
head, tail = self._split(path)
val = None
n = name.replace(FileSystem.xattr_prefix, '')
if path == '/' :
if n in FileSystem.xattr_fields_root :
val = str(getattr(self, n))
elif n.startswith('bextract.') :
n = n.replace('bextract.', '')
if n in FileSystem.xattr_fields_bextract :
val = str(self._bextract_get_status()[n])
if (not val and head in self.dirs and tail in self.dirs[head] and
len(self.dirs[head][tail]) != 1 and
n in FileSystem.xattr_fields) :
val = str(self.dirs[head][tail][FileSystem.xattr_fields.index(n)])
if n == 'MD5' and val != '0':
l = len(val)
val = binascii.b2a_hex(binascii.a2b_base64(val+'='*((l*3+8)/3-l)+'\n')) # padding
# attribute not found
if val == None :
return -errno.ENODATA
# We are asked for size of the value.
if size == 0:
return len(val)
return val
def listxattr(self, path, size):
'''
list extended attributes
'''
head, tail = self._split(path)
xattrs = []
if path == '/' :
xattrs += [FileSystem.xattr_prefix + a for a in FileSystem.xattr_fields_root]
xattrs += [FileSystem.xattr_prefix + 'bextract.' + a for a in FileSystem.xattr_fields_bextract]
if (head in self.dirs and tail in self.dirs[head] and
len(self.dirs[head][tail]) != 1) :
xattrs += [FileSystem.xattr_prefix + a for a in FileSystem.xattr_fields]
# We are asked for size of the attr list, ie. joint size of attrs
# plus null separators.
if size == 0:
return len("".join(xattrs)) + len(xattrs)
return xattrs
def getattr(self, path):
'''
Retrieve file attributes.
Notes:
1) Bacula does not store attributes for parent directories
that are not being explicitly backed up, so we provide
a default set of attributes FileSystem.null_stat
2) file attributes are base64-encoded and stored by Bacula
in the catalog. These attributes are decoded when first
needed and then cached for subsequent requests.
3) python fuse expects atime/ctime/mtime to be positive
'''
head, tail = self._split(path)
if head in self.dirs and tail in self.dirs[head] :
self._getattr_lock.acquire()
attrs = self.dirs[head][tail][-1]
# decode and cache stat info
if not attrs :
self.dirs[head][tail] = self.dirs[head][tail][:-1] + self._bacula_stat(self.dirs[head][tail][-3])
attrs = self.dirs[head][tail][-1]
# zero negative timestamps
for a in ['st_atime','st_mtime','st_ctime'] :
t = getattr(attrs, a)
if t < 0 :
self.logger.warning('%s has negative timestamp %s=%d, will use 0' % (path, a, t))
setattr(attrs, a, 0)
self._getattr_lock.release()
return attrs
else:
return -errno.ENOENT
def readdir(self, path, offset):
'''
read directory entries
'''
path = path if path.endswith('/') else path+'/'
for key in ['.','..'] :
yield fuse.Direntry(key)
for key in self.dirs[path].keys() :
if len(key) > 0:
if self.use_ino:
bs = self.getattr(path + key)
ino = bs.st_ino
else :
ino = 0
yield fuse.Direntry(key, ino=ino)
def readlink(self, path):
'''
read link contents
'''
realpath = self._extract([path])[0]
if realpath :
link = os.readlink(realpath)
if self.move_root and link.startswith('/') :
link = os.path.normpath(self.fuse_args.mountpoint + link)
return link
return -errno.ENOENT
class _File(object) :
def __init__(self, fs, path, flags, *mode) :
self.fs = fs
accmode = os.O_RDONLY | os.O_WRONLY | os.O_RDWR
if (flags & accmode) != os.O_RDONLY:
raise IOError(errno.EACCES, '')
self.path = path
self.realpath = fs._extract([path])[0]
self.file = os.fdopen(os.open(self.realpath, flags, *mode), flag2mode(flags))
self.fd = self.file.fileno()
self.direct_io = False
self.keep_cache = True
def read(self, length, offset):
self.file.seek(offset)
return self.file.read(length)
def release(self, flags):
self.file.close()
def _bextract_version() :
'''
return version string of bextract,
return None if not runnable or version cannot be parsed
'''
version = None
try :
child = pexpect.spawn('bextract -?')
i = child.expect(['Version: ([^(]*) \(([^)]*)\)', pexpect.EOF])
if i == 0 :
version = '%s (%s)' % child.match.groups()
child.close()
except :
pass
return version
def main():
usage = """
BaculaFS: exposes the Bacula catalog and storage as a Filesystem in USErspace
""" + Fuse.fusage
bacula_version = _bextract_version()
server = FileSystem(version="BaculaFS version: %s\nbextract version: %s\nPython FUSE version: %s" %
(__version__, bacula_version, fuse.__version__), usage=usage)
server.multithreaded = True
server.parser.add_option(mountopt="driver", choices=Database.drivers, metavar='|'.join(Database.drivers), default=server.driver,
help="database driver [default: %default]")
server.parser.add_option(mountopt="host", metavar="HOST", default=server.host,
help="database server address [default: %default]")
server.parser.add_option(mountopt="port", metavar="PORT", default=server.port, type="int",
help="database server port")
server.parser.add_option(mountopt="database", metavar="PATH", default=server.database,
help="database name [default: bacula]")
server.parser.add_option(mountopt="username", metavar="USERNAME", default=server.username,
help="database user name [default: %default]")
server.parser.add_option(mountopt="password", metavar="PASSWORD", default=server.password,
help="database password (use '-o password= ' to get a password prompt; if not provided, the password is read from the DATABASE_PASSWORD environment variable)")
server.parser.add_option(mountopt="conf", metavar="PATH", default=server.conf,
help="storage daemon configuration file [default: %default]")
server.parser.add_option(mountopt="client", metavar="CLIENT", default=server.client,
help="file daemon name")
server.parser.add_option(mountopt="fileset", metavar="FILESET", default=server.fileset,
help="backup fileset")
server.parser.add_option(mountopt="device", metavar="DEVICE", default=server.device,
help="storage device name [default: %default]")
server.parser.add_option(mountopt="datetime", metavar="'YYYY-MM-DD hh:mm:ss'", default=server.datetime,
help="snapshot date/time [default: now]")
server.parser.add_option(mountopt="recent_job", action="store_true", default=server.recent_job,
help="select contents of most recent job only [default: %default]")
server.parser.add_option(mountopt="joblist", metavar="'JOBID1 JOBID2 ...'", default=server.joblist,
help="select contents of specified list of jobs")
server.parser.add_option(mountopt="cleanup", action="store_true", default=server.cleanup,
help="clean cache directory upon umount [default: %default]")
server.parser.add_option(mountopt="move_root", action="store_true", default=server.move_root,
help="make absolute path symlinks point to path under mount point [default: %default]")
server.parser.add_option(mountopt="prefetch_attrs", action="store_true", default=server.prefetch_symlinks,
help="read and parse attributes for all files upon filesystem initialization [default: %default]")
server.parser.add_option(mountopt="prefetch_symlinks", action="store_true", default=server.prefetch_symlinks,
help="extract all symbolic links upon filesystem initialization (implies prefetch_attrs) [default: %default]")
server.parser.add_option(mountopt="prefetch_regex", metavar="REGEX", default=server.prefetch_regex,
help="extract all objects that match REGEX upon filesystem initialization (implies prefetch_attrs)")
server.parser.add_option(mountopt="prefetch_recent", action="store_true", default=server.prefetch_recent,
help="extract contents of most recent non-full job upon filesystem initialization (implies prefetch_symlinks) [default: %default]")
server.parser.add_option(mountopt="prefetch_diff", metavar="PATH", default=server.prefetch_diff,
help="extract files that do not match files at PATH (hint: speeds up rsync; implies prefetch_symlinks)")
server.parser.add_option(mountopt="prefetch_difflist", metavar="DIFFLIST", default=server.prefetch_difflist,
help="extract files that do not match files in DIFFLIST (list line format: 'Day Mon DD hh:mm:ss YYYY PATH'; use '-' to read from standard input; hint: format matches output of 'duplicity list-current-files -v0 target_url'; implies prefetch_symlinks)")
server.parser.add_option(mountopt="prefetch_list", metavar="LIST", default=server.prefetch_list,
help="extract files that match files in LIST (list should contains one absolute file path per line; use '-' to read from standard input; implies prefetch_symlinks)")
server.parser.add_option(mountopt="prefetch_everything", action="store_true", default=server.prefetch_everything,
help="extract everything upon filesystem initialization (complete restore to cache) [default: %default]")
server.parser.add_option(mountopt="batch_list", action="store_true", default=server.batch_list,
help="list files to be prefetched and exit [default: %default]")
server.parser.add_option(mountopt="batch_bsr", action="store_true", default=server.batch_bsr,
help="dump contnets of bsr file for extracting prefetched files and exit [default: %default]")
server.parser.add_option(mountopt="batch_extract", action="store_true", default=server.batch_extract,
help="extract prefetched files to mount point and exit [default: %default]")
server.parser.add_option(mountopt="user_cache_path", metavar="PATH", default=server.user_cache_path,
help="user specified cache path (hint: combine this with one of the prefetch options) [default: %default]")
server.parser.add_option(mountopt="logging", choices=LOGGING_LEVELS.keys(), metavar='|'.join(LOGGING_LEVELS.keys()), default=server.logging,
help="logging level [default: %default]")
server.parser.add_option(mountopt="syslog", action="store_true", default=server.syslog,
help="log to both syslog and console [default: %default]")
server.parse(values=server, errex=1)
if server.fuse_args.mount_expected() :
if not bacula_version :
raise RuntimeError, 'cannot determine Bacula bextract version - is it installed?'
else :
# we initialize before main (i.e. not in fsinit) so that
# any failure here aborts the mount
try :
server.initialize(bacula_version)
except :
server.shutdown()
raise
if not server.batch_mode :
server.main()
# we shutdown after main, i.e. not in fsshutdown, because
# calling fsshutdown with multithreaded==True seems to cause
# the python fuse process to hang waiting for the python gil
if server.fuse_args.mount_expected() :
server.shutdown() | PypiClean |
/564bff00ff_strawberry_graphql-0.168.2-py3-none-any.whl/strawberry/extensions/tracing/opentelemetry.py | from __future__ import annotations
import enum
from copy import deepcopy
from inspect import isawaitable
from typing import TYPE_CHECKING, Any, Callable, Dict, Generator, Optional
from opentelemetry import trace
from opentelemetry.trace import SpanKind
from strawberry.extensions import SchemaExtension
from strawberry.extensions.utils import get_path_from_info
from .utils import should_skip_tracing
if TYPE_CHECKING:
from graphql import GraphQLResolveInfo
from opentelemetry.trace import Span, Tracer
from strawberry.types.execution import ExecutionContext
DATETIME_FORMAT = "%Y-%m-%dT%H:%M:%S.%fZ"
ArgFilter = Callable[[Dict[str, Any], "GraphQLResolveInfo"], Dict[str, Any]]
class RequestStage(enum.Enum):
REQUEST = enum.auto()
PARSING = enum.auto()
VALIDATION = enum.auto()
class OpenTelemetryExtension(SchemaExtension):
_arg_filter: Optional[ArgFilter]
_span_holder: Dict[RequestStage, Span] = dict()
_tracer: Tracer
def __init__(
self,
*,
execution_context: Optional[ExecutionContext] = None,
arg_filter: Optional[ArgFilter] = None,
):
self._arg_filter = arg_filter
self._tracer = trace.get_tracer("strawberry")
if execution_context:
self.execution_context = execution_context
def on_operation(self) -> Generator[None, None, None]:
self._operation_name = self.execution_context.operation_name
span_name = (
f"GraphQL Query: {self._operation_name}"
if self._operation_name
else "GraphQL Query"
)
self._span_holder[RequestStage.REQUEST] = self._tracer.start_span(
span_name, kind=SpanKind.SERVER
)
self._span_holder[RequestStage.REQUEST].set_attribute("component", "graphql")
if self.execution_context.query:
self._span_holder[RequestStage.REQUEST].set_attribute(
"query", self.execution_context.query
)
yield
# If the client doesn't provide an operation name then GraphQL will
# execute the first operation in the query string. This might be a named
# operation but we don't know until the parsing stage has finished. If
# that's the case we want to update the span name so that we have a more
# useful name in our trace.
if not self._operation_name and self.execution_context.operation_name:
span_name = f"GraphQL Query: {self.execution_context.operation_name}"
self._span_holder[RequestStage.REQUEST].update_name(span_name)
self._span_holder[RequestStage.REQUEST].end()
def on_validate(self) -> Generator[None, None, None]:
ctx = trace.set_span_in_context(self._span_holder[RequestStage.REQUEST])
self._span_holder[RequestStage.VALIDATION] = self._tracer.start_span(
"GraphQL Validation",
context=ctx,
)
yield
self._span_holder[RequestStage.VALIDATION].end()
def on_parse(self) -> Generator[None, None, None]:
ctx = trace.set_span_in_context(self._span_holder[RequestStage.REQUEST])
self._span_holder[RequestStage.PARSING] = self._tracer.start_span(
"GraphQL Parsing", context=ctx
)
yield
self._span_holder[RequestStage.PARSING].end()
def filter_resolver_args(
self, args: Dict[str, Any], info: GraphQLResolveInfo
) -> Dict[str, Any]:
if not self._arg_filter:
return args
return self._arg_filter(deepcopy(args), info)
def add_tags(
self, span: Span, info: GraphQLResolveInfo, kwargs: Dict[str, Any]
) -> None:
graphql_path = ".".join(map(str, get_path_from_info(info)))
span.set_attribute("component", "graphql")
span.set_attribute("graphql.parentType", info.parent_type.name)
span.set_attribute("graphql.path", graphql_path)
if kwargs:
filtered_kwargs = self.filter_resolver_args(kwargs, info)
for kwarg, value in filtered_kwargs.items():
span.set_attribute(f"graphql.param.{kwarg}", value)
async def resolve(self, _next, root, info, *args, **kwargs) -> Any:
if should_skip_tracing(_next, info):
result = _next(root, info, *args, **kwargs)
if isawaitable(result): # pragma: no cover
result = await result
return result
with self._tracer.start_as_current_span(
f"GraphQL Resolving: {info.field_name}",
context=trace.set_span_in_context(self._span_holder[RequestStage.REQUEST]),
) as span:
self.add_tags(span, info, kwargs)
result = _next(root, info, *args, **kwargs)
if isawaitable(result):
result = await result
return result
class OpenTelemetryExtensionSync(OpenTelemetryExtension):
def resolve(self, _next, root, info, *args, **kwargs) -> Any:
if should_skip_tracing(_next, info):
result = _next(root, info, *args, **kwargs)
return result
with self._tracer.start_as_current_span(
f"GraphQL Resolving: {info.field_name}",
context=trace.set_span_in_context(self._span_holder[RequestStage.REQUEST]),
) as span:
self.add_tags(span, info, kwargs)
result = _next(root, info, *args, **kwargs)
return result | PypiClean |
/AltAnalyze-2.1.3.15.tar.gz/AltAnalyze-2.1.3.15/altanalyze/stats_scripts/preAligned.py | import sys,string,os,shutil
sys.path.insert(1, os.path.join(sys.path[0], '..')) ### import parent dir dependencies
from scipy import sparse, io
import numpy
import LineageProfilerIterate
import cluster_corr
import export
from import_scripts import ChromiumProcessing
import traceback
""" cellHarmony without alignment """
def cellHarmony(species,platform,query_exp_file,exp_output,
customMarkers=False,useMulti=False,fl=None,customLabels=None):
""" Prepare pre-aligned result files in a pre-defined format for cellHarmony post-aligment
differential and visualization analyses """
customLabels = fl.Labels()
reference_exp_file = customMarkers ### pre-formatted from Seurat or other outputs
export_directory = os.path.abspath(os.path.join(query_exp_file, os.pardir))
if 'ExpressionInput' in query_exp_file:
### Change to the root directory above ExpressionINput
export_directory = os.path.abspath(os.path.join(export_directory, os.pardir))
dataset_name = string.replace(string.split(query_exp_file,'/')[-1][:-4],'exp.','')
try: os.mkdir(export_directory+'/cellHarmony/')
except: pass
try: os.mkdir(export_directory+'/cellHarmony/CellClassification/')
except: pass
try: os.mkdir(export_directory+'/cellHarmony/OtherFiles/')
except: pass
### Get the query and reference cells, dataset names
refererence_cells, query_cells, reference_dataset, query_dataset = importCelltoClusterAnnotations(customLabels) ### Get the reference and query cells in their respective order
### copy and re-name the input expression file to the output cellHarmony directory
if len(reference_dataset)>0 and len(query_dataset)>0:
target_exp_dir = export_directory+'/cellHarmony/exp.'+reference_dataset+'__'+query_dataset+'-AllCells.txt'
else:
target_exp_dir = export_directory+'/cellHarmony/exp.cellHarmony-reference__Query-AllCells.txt'
reference_dataset = 'cellHarmony-reference'
shutil.copy(query_exp_file,target_exp_dir)
### filter and export the heatmap with just reference cells
cell_cluster_order = simpleHeaderImport(reference_exp_file)
filtered_reference_cells=[]
filtered_query_cells_db={}
filtered_query_cells=[]
representative_refcluster_cell = {}
for cell_id in cell_cluster_order:
if cell_id in refererence_cells:
filtered_reference_cells.append(cell_id)
cluster_label = refererence_cells[cell_id].Label()
### Identifies where to place each query cell
try: representative_refcluster_cell[cluster_label].append(cell_id)
except: representative_refcluster_cell[cluster_label] = [cell_id]
elif cell_id in query_cells:
filtered_query_cells_db[cell_id]=query_cells[cell_id]
filtered_query_cells.append(cell_id)
#reference_output_file = export.findParentDir(reference_exp_file)+'/'+reference_dataset+'.txt'
reference_output_file = export_directory+'/cellHarmony/OtherFiles/'+reference_dataset+'.txt'
reference_output_file2 = export_directory+'/cellHarmony/exp.'+reference_dataset+'__'+query_dataset+'-Reference.txt'
query_output_file =export_directory+'/'+query_dataset+'.txt'
### Write out separate refernece and query files
from import_scripts import sampleIndexSelection
sampleIndexSelection.filterFile(reference_exp_file,reference_output_file,['row_clusters-flat']+filtered_reference_cells,force=True)
sampleIndexSelection.filterFile(target_exp_dir,query_output_file,filtered_query_cells,force=True)
shutil.copy(reference_output_file,reference_output_file2)
### export the CellClassification file
output_classification_file = export_directory+'/cellHarmony/CellClassification/CellClassification.txt'
exportCellClassifications(output_classification_file,filtered_query_cells_db,filtered_query_cells,representative_refcluster_cell)
labels_file = export_directory+'/labels.txt'
exportLabels(labels_file,filtered_reference_cells,refererence_cells)
fl.setLabels(labels_file)
print 'Files formatted for cellHarmony... running differential expression analyses'
try:
print reference_output_file
print query_output_file
print output_classification_file
LineageProfilerIterate.harmonizeClassifiedSamples(species, reference_output_file, query_output_file, output_classification_file,fl=fl)
except:
print '\nFAILED TO COMPLETE THE FULL CELLHARMONY ANALYSIS (SEE LOG FILE)...'
print traceback.format_exc()
return True
def exportCellClassifications(output_file,query_cells,filtered_query_cells,representative_refcluster_cell):
""" Match the Louvain cellHarmony export format for the classification file """
header = 'Query Barcode\tRef Barcode\tCorrelation\tQuery Partition\tRef Partition\tLabel\n'
o = open(output_file,'w')
o.write(header)
for query_barcode in filtered_query_cells:
CI = query_cells[query_barcode]
cluster_number = CI.ClusterNumber()
label = CI.Label()
ref_barcode = representative_refcluster_cell[label][-1]
values = [query_barcode,ref_barcode,'1.0',cluster_number,cluster_number,label]
o.write(string.join(values,'\t')+'\n')
o.close()
def exportLabels(labels_file,filtered_reference_cells,refererence_cells):
l = open(labels_file,'w')
for cell_id in filtered_reference_cells:
CI = refererence_cells[cell_id]
cluster_number = CI.ClusterNumber()
label = CI.Label()
values = [cell_id,cluster_number,label]
l.write(string.join(values,'\t')+'\n')
l.close()
def simpleHeaderImport(filename):
for line in open(filename,'rU').xreadlines():
data = cleanUpLine(line)
if '\t' in data:
t = string.split(data,'\t')
else:
t = string.split(data,',')
header = t[2:]
header2 = []
for h in header:
if ":" in h:
h = string.split(h,':')[-1]
header2.append(h)
break
return header2
class CellInfo:
def __init__(self,cell_id, cluster_number, dataset_name, dataset_type, label):
self.cell_id = cell_id; self.cluster_number = cluster_number; self.dataset_name = dataset_name
self.dataset_type = dataset_type; self.label = label
def CellID(self): return self.cell_id
def ClusterNumber(self): return self.cluster_number
def DatasetName(self): return self.dataset_name
def DataSetType(self): return self.dataset_type
def Label(self): return self.label
def __repr__(self):
return self.CellID()+'|'+self.Label()+'|'+self.DataSetType()
def importCelltoClusterAnnotations(filename):
firstRow = True
refererence_cells={}
query_cells={}
for line in open(filename,'rU').xreadlines():
data = cleanUpLine(line)
if '\t' in data:
t = string.split(data,'\t')
else:
t = string.split(data,',')
if firstRow:
ci = t.index('cell_id')
cn = t.index('cluster_number')
try: cm = t.index('cluster_name')
except: cm = False
dn = t.index('dataset_name')
dt = t.index('dataset_type')
firstRow = False
else:
cell_id = t[ci]
cluster_number = t[cn]
dataset_name = t[dn]
dataset_type = t[dt]
if cm != False:
cluster_name = t[cm]
label = cluster_name + '_c'+cluster_number
else:
label = 'c'+cluster_number
if string.lower(dataset_type)[0] == 'r':
dataset_type = 'Reference'
reference_dataset = dataset_name
CI = CellInfo(cell_id, cluster_number, dataset_name, dataset_type, label)
refererence_cells[cell_id]=CI
else:
dataset_type = 'Query'
query_dataset = dataset_name
CI = CellInfo(cell_id, cluster_number, dataset_name, dataset_type, label)
query_cells[cell_id]=CI
return refererence_cells, query_cells, reference_dataset, query_dataset
def cleanUpLine(line):
line = string.replace(line,'\n','')
line = string.replace(line,'\c','')
data = string.replace(line,'\r','')
data = string.replace(data,'"','')
return data
if __name__ == '__main__':
platform = 'RNASeq'
cellHarmony(genome,platform,args.query_h5,None,
customMarkers=args.reference_h5,useMulti=False,fl=None,customLabels=labels) | PypiClean |
/Nasse-1.1-py3-none-any.whl/nasse/utils/logging.py | import datetime
import inspect
import linecache
import flask
from nasse import config
RECORDING = False
LOG_STACK = []
CALL_STACK = []
class Colors:
normal = '\033[0m'
grey = '\033[90m'
red = '\033[91m'
green = '\033[92m'
blue = '\033[94m'
cyan = '\033[96m'
white = '\033[97m'
yellow = '\033[93m'
magenta = '\033[95m'
_colors = {normal, grey, red, green, blue, cyan, white, yellow, magenta}
class LogLevel():
def __init__(self, level: str, template: str, debug: bool = False) -> None:
self.level = str(level)
self.template = str(template)
self.debug = bool(debug)
self._draw_time = "{time}" in self.template
self._draw_name = "{name}" in self.template
self._draw_step = "{step}" in self.template
self._draw_message = "{message}" in self.template
def __repr__(self) -> str:
return "<LogLevel: {level}>".format(level=self.level)
class LogLevels:
INFO = LogLevel(level="Info", template=Colors.grey +
"{time}｜" + Colors.normal + "[INFO] ({name}) [{step}] {message}")
DEBUG = LogLevel(debug=True, level="Debug", template=Colors.grey +
"{time}｜" + Colors.normal + "[DEBUG] ({name}) [{step}] {message}")
WARNING = LogLevel(level="Warning", template=Colors.grey +
"{time}｜" + Colors.normal + "[WARNING] ({name}) [{step}] " + Colors.yellow + "{message}" + Colors.normal)
ERROR = LogLevel(level="Error", template=Colors.grey +
"{time}｜" + Colors.normal + "[ERROR] ({name}) [{step}] " + Colors.red + "!! {message} !!" + Colors.normal)
def __repr__(self) -> str:
return "<LogLevels Container>"
class StackFrame():
def __init__(self, frame) -> None:
# print(dir(frame))
# print(dir(frame.f_code))
self.name = frame.f_code.co_name
self.filename = frame.f_code.co_filename
self.lineno = frame.f_lineno
self.back_frame = frame.f_back
self._line = None
self._calling_line = None
def __repr__(self) -> str:
return "<NasseStackFrame '{name}' {filename} on {line_number}>".format(name=self.name, filename=self.filename, line_number=self.lineno)
@property
def line(self):
if self._line is None:
self._line = linecache.getline(self.filename, self.lineno)
return self._line.strip()
@property
def calling_line(self):
if self._calling_line is None:
self._calling_line = linecache.getline(
self.back_frame.f_code.co_filename, self.back_frame.f_lineno)
return self._calling_line.strip()
def as_dict(self) -> dict:
return {
"name": self.name,
"filename": self.filename,
"lineNumber": self.lineno,
"calledBy": "<{name}>, in {filename} at line {line_number}".format(name=self.back_frame.f_code.co_name, filename=self.back_frame.f_code.co_filename, line_number=self.back_frame.f_code.co_firstlineno)
}
def add_to_call_stack(frame, event, arg):
"""
Internal function to add a call to the call stack
"""
if RECORDING and event == "call":
if config.Mode.FULL_DEBUG:
CALL_STACK.append(StackFrame(frame))
elif frame.f_code.co_filename.startswith(str(config.General.BASE_DIR)):
CALL_STACK.append(StackFrame(frame))
return None
def clear_log():
try:
name = flask.g.request.app.name
except Exception:
name = config.General.NAME
try:
app_id = flask.g.request.app.id
except Exception:
app_id = "".join(l for l in str(name) if l.isalpha()
or l.isdecimal()).lower()
with open(config.General.BASE_DIR / "{id}.nasse.log".format(id=app_id), "w", encoding="utf8") as out:
out.write("-- {name} DEBUG LOG --\n\n".format(name=str(name).upper()))
def write_log(new_line: str):
"""Writing out the log, wether it's to the log stack or the log file"""
#new_line = str(new_line).replace("\n", " ")
new_line = str(new_line)
for color in Colors._colors:
new_line = new_line.replace(color, "")
if RECORDING:
LOG_STACK.append(new_line)
if config.Mode.DEBUG:
try:
name = flask.g.request.app.name
except Exception:
name = config.General.NAME
try:
app_id = flask.g.request.app.id
except Exception:
app_id = "".join(l for l in str(
name) if l.isalpha() or l.isdecimal()).lower()
with open(config.General.BASE_DIR / "{id}.nasse.log".format(id=app_id), "a", encoding="utf8") as out:
out.write(str(new_line) + "\n")
def caller_name(skip: int = 2):
"""
https://stackoverflow.com/a/9812105/11557354
Get a name of a caller in the format module.class.method
`skip` specifies how many levels of stack to skip while getting caller
name. skip=1 means "who calls me", skip=2 "who calls my caller" etc.
An empty string is returned if skipped levels exceed stack height
"""
stack = inspect.stack()
start = 0 + skip
if len(stack) < start + 1:
return ''
parentframe = stack[start][0]
name = []
module = inspect.getmodule(parentframe)
if module:
name.append(module.__name__)
if 'self' in parentframe.f_locals:
name.append(parentframe.f_locals['self'].__class__.__name__)
codename = parentframe.f_code.co_name
if codename != '<module>': # top level usually
name.append(codename) # function or a method
del parentframe, stack
return ".".join(name)
def log(message: str = "Log", level: LogLevel = LogLevels.DEBUG, step: str = None):
if config.Mode.PRODUCTION:
return
now = datetime.datetime.now()
write_log("{time}｜[{level}] [{step}] {message}".format(time=now.timestamp(), level=level.level.upper(), step=(
step if step is not None else (caller_name() if config.Mode.DEBUG else 'app')), message=message))
if not level.debug or config.Mode.DEBUG:
formatting = {}
if level._draw_time:
formatting["time"] = config.General.LOGGING_TIME_FORMAT(now) if callable(
config.General.LOGGING_TIME_FORMAT) else now.strftime(str(config.General.LOGGING_TIME_FORMAT))
if level._draw_step:
formatting["step"] = step if step is not None else (
caller_name() if config.Mode.DEBUG else 'Nasse App')
if level._draw_name:
try:
name = flask.g.request.app.name
except Exception:
name = config.General.NAME
formatting["name"] = name
if level._draw_message:
formatting["message"] = message
print(level.template.format(**formatting))
class Record():
_call_stack = []
_log_stack = []
@property
def CALL_STACK(self):
if RECORDING:
return CALL_STACK.copy()
return self._call_stack.copy()
@property
def LOG_STACK(self):
if RECORDING:
return LOG_STACK.copy()
return self._log_stack.copy()
def start(self):
global RECORDING
CALL_STACK.clear()
LOG_STACK.clear()
RECORDING = True
def stop(self):
global RECORDING
self._call_stack = CALL_STACK.copy()
self._log_stack = LOG_STACK.copy()
RECORDING = False
CALL_STACK.clear()
LOG_STACK.clear()
return self._call_stack, self._log_stack
def __enter__(self):
self.start()
return self
def __exit__(self, type, value, traceback):
self.stop() | PypiClean |
/Mopidy-Transistor-0.2.0.tar.gz/Mopidy-Transistor-0.2.0/mopidy_transistor/library.py | import mopidy
import logging
from urllib.request import urlopen
import ssl
import certifi
from pathlib import Path
import podcastparser
import threading
from mopidy.internal import storage as internal_storage
logger = logging.getLogger(__name__)
class Library(object):
def __init__(self, json_file, podcast_timeout=5.0):
self._json_file = Path(json_file)
self._podcast_timeout = podcast_timeout
self.load()
def save(self):
internal_storage.dump(self._json_file, self.data)
def load(self):
if not self._json_file.is_file():
self.data = {
"version": mopidy.__version__,
"radio_banks": {
"AM": [
{
"name": "FIP",
"stream_url": "http://direct.fipradio.fr/live/fip-midfi.mp3",
"position": 64,
},
{
"name": "Meeeuh",
"stream_url": "http://radiomeuh.ice.infomaniak.ch/radiomeuh-128.mp3",
"position": 32,
},
],
"FM": [
{
"name": "Inter",
"stream_url": "http://direct.franceinter.fr/live/franceinter-midfi.mp3",
"position": 32,
},
{
"name": "Culture",
"stream_url": "http://direct.franceculture.fr/live/franceculture-midfi.mp3",
"position": 64,
},
],
},
"podcasts": [
{
"name": "TEDx",
"feed_url": "http://www.npr.org/rss/podcast.php?id=510298",
"episodes": [],
"position": 64,
},
{
"name": "Revolt",
"feed_url": "http://wordsmith.podomatic.com/rss2.xml",
"episodes": [],
"position": 32,
},
{
"name": "Neo Geo",
"feed_url": "http://feeds.feedburner.com/NeoGeoNova",
"position": 10,
},
{
"name": "Juke Box",
"feed_url": "http://radiofrance-podcast.net/podcast09/rss_16999.xml",
"position": 20,
},
],
}
self.save()
self.data = internal_storage.load(self._json_file)
def update_podcasts(self):
def run():
try:
for podcast in self.data["podcasts"]:
raw = urlopen(
podcast["feed_url"],
timeout=self._podcast_timeout,
context=ssl.create_default_context(
cafile=certifi.where()
),
)
parsed = podcastparser.parse(podcast["feed_url"], raw)
episodes = parsed["episodes"]
podcast["episodes"] = []
for episode in episodes:
title = episode["title"]
media_url = episode["enclosures"][0]["url"]
# podcast['episodes'].append({"title":unicodedata.normalize('NFKD', title).encode('ascii','ignore'), "url":media_url})
podcast["episodes"].append(
{"title": title, "url": media_url}
)
self.save()
logger.info(
"Transistor Library: done downloading podcasts infos"
)
except Exception as e:
logger.error(
"Transistor: Can't retrieve podcast data: {}".format(
str(e)
)
)
thr = threading.Thread(target=run)
thr.start() | PypiClean |
/Gammalearn-0.11.0.tar.gz/Gammalearn-0.11.0/gammalearn/data/example_settings/experiment_settings_square_pixels.py | import collections
import os
import importlib
from pathlib import Path
import math
import numpy as np
import torch
from torch.optim import lr_scheduler
from torchvision.models.mobilenet import mobilenet_v2
from torchmetrics.classification import Accuracy, AUROC
from pytorch_lightning.profiler import SimpleProfiler, AdvancedProfiler, PyTorchProfiler
import gammalearn.criterions as criterions
import gammalearn.optimizers as optimizers
import gammalearn.steps as steps
from gammalearn.callbacks import (LogGradientNorm, LogModelWeightNorm, LogModelParameters,
LogUncertaintyLogVars, LogUncertaintyPrecisions, LogGradNormWeights,
LogReLUActivations, LogLinearGradient, LogFeatures, WriteDL2Files)
import gammalearn.utils as utils
import gammalearn.datasets as dsets
from gammalearn.data_handlers import GLearnDataModule
from gammalearn.constants import GAMMA_ID, PROTON_ID, ELECTRON_ID
import gammalearn.data.nets as nets
# Experiment settings
main_directory = str(Path.home()) + '/gammalearn_experiments' # TODO change directory if needed
"""str: mandatory, where the experiments are stored"""
experiment_name = 'test_install'
"""str: mandatory, the name of the experiment. Should be different
for each experiment, except if one wants to resume an old experiment
"""
info = ''
"""str: optional"""
gpus = 1
"""int or list: mandatory, the number of gpus to use. If -1, run on all GPUS,
if None/0 run on CPU. If list, run on GPUS of list.
"""
log_every_n_steps = 3
"""int: optional, the interval in term of iterations for on screen
data printing during experiment. A small value may lead to a very large log file size.
"""
window_size = 100
"""int: optional, the interval in term of stored values for metric moving computation"""
checkpointing_options = dict(every_n_epochs=1, save_top_k=-1, save_last=True)
"""dict: optional, specific options for model checkpointing.
See https://pytorch-lightning.readthedocs.io/en/stable/api/pytorch_lightning.callbacks.ModelCheckpoint.html
for details.
"""
random_seed = 1
"""int: optional, the manual seed to make experiments more reproducible"""
monitor_device = True
"""bool: optional, whether or not monitoring the gpu utilization"""
particle_dict = {GAMMA_ID: 0,
PROTON_ID: 1,
# ELECTRON_ID: 2,
}
"""particle_dict is mandatory and maps cta particle types with class id. e.g. gamma (0) is class 0"""
targets = collections.OrderedDict({
'energy': {
'output_shape': 1,
'loss': torch.nn.L1Loss(reduction='none'),
'loss_weight': 1,
'metrics': {
# 'functions': ,
},
'mt_balancing': True
},
'impact': {
'output_shape': 2,
'loss': torch.nn.L1Loss(reduction='none'),
'loss_weight': 1,
'metrics': {},
'mt_balancing': True
},
'direction': {
'output_shape': 2,
'loss': torch.nn.L1Loss(reduction='none'),
'loss_weight': 1,
'metrics': {},
'mt_balancing': True
},
'class': {
'label_shape': 1,
'output_shape': len(particle_dict),
'loss': torch.nn.CrossEntropyLoss(),
'loss_weight': 1,
'metrics': {
'Accuracy_particle': Accuracy(threshold=0.5),
'AUC_particle': AUROC(pos_label=particle_dict[GAMMA_ID],
num_classes=len(particle_dict),
compute_on_step=True
)
},
'mt_balancing': True
}
})
"""dict: mandatory, defines for every objectives of the experiment
the loss function and its weight
"""
dataset_class = dsets.MemoryLSTDataset
# dataset_class = dsets.FileLSTDataset
"""Dataset: mandatory, the Dataset class to load the data. Currently 2 classes are available, MemoryLSTDataset that
loads images in memory, and FileLSTDataset that loads images from files during training.
"""
dataset_parameters = {
'camera_type': 'LST_LSTCam',
'group_by': 'image',
'use_time': True,
'particle_dict': particle_dict,
'targets': list(targets.keys()),
# 'subarray': [1],
}
"""dict: mandatory, the parameters of the dataset.
camera_type is mandatory and can be:
'LST_LSTCam', 'MST_NectarCam', 'MST_FlashCam', 'SST_ASTRICam', 'SST1M_DigiCam', 'SST_CHEC', 'MST-SCT_SCTCam'.
group_by is mandatory and can be 'image', 'event_all_tels', 'event_triggered_tels'.
particle_dict is mandatory and maps cta particle types with class id. e.g. gamma (0) is class 0,
proton (101) is class 1 and electron (1) is class 2.
use_time (optional): whether or not to use time information
subarray (optional): the list of telescope ids to select as a subarray
"""
preprocessing_workers = 4
"""int: optional, the max number of workers to create dataset."""
dataloader_workers = 4
"""int: optional, the max number of workers for the data loaders. If 0, data are loaded from the main thread."""
mp_start_method = 'fork'
"""str: optional, the method to start new process in [fork, spawn]"""
# Net settings
# Uncomment following lines to import your network from an external file
# net_definition_file = utils.nets_definition_path()
# """str: mandatory, the file where to find the net definition to use"""
# # Load the network definitions module #
# spec = importlib.util.spec_from_file_location("nets", net_definition_file)
# nets = importlib.util.module_from_spec(spec)
# spec.loader.exec_module(nets)
net_parameters_dic = {
'model': nets.GammaPhysNet,
'parameters': {
'backbone': {
'model': nets.TorchConvNet,
'parameters': {
'model': mobilenet_v2,
'parameters': {
'num_channels': 2,
'output_size': (14, 14),
'pretrained': False,
}
}
},
'fc_width': 256,
'non_linearity': torch.nn.ReLU,
'last_bias_init': None,
'targets': {k: v.get('output_shape', 0) for k, v in targets.items()}
}
}
"""dict: mandatory, the parameters of the network. Depends on the
network chosen. Must include at least a model and a parameters field.
"""
# checkpoint_path = main_directory + '/test_install/checkpoint_epoch=1.ckpt'
"""str: optional, the path where to find the backup of the model to resume"""
profiler = None
# profiler = {'profiler': SimpleProfiler,
# 'options': dict(extended=True)
# }
"""str: optional, the profiler to use"""
######################################################################################################################
train = True
"""bool: mandatory, whether or not to train the model"""
# Data settings
data_module_train = {
'module': GLearnDataModule,
'paths': [
Path(__file__).parent.absolute().joinpath('../../../share/data/MC_data').resolve().as_posix(),
], # TODO fill your folder path
'image_filter': {
# utils.intensity_filter: {'intensity': [50, np.inf]},
# utils.cleaning_filter: {'picture_thresh': 6, 'boundary_thresh': 3,
# 'keep_isolated_pixels': False, 'min_number_picture_neighbors': 2},
# utils.leakage_filter: {'leakage2_cut': 0.2, 'picture_thresh': 6, 'boundary_thresh': 3,
# 'keep_isolated_pixels': False, 'min_number_picture_neighbors': 2},
},
'event_filter': {
# utils.energyband_filter: {'energy': [0.02, 2], 'filter_only_gammas': True}, # in TeV
# utils.emission_cone_filter: {'max_angle': 0.0698},
# utils.impact_distance_filter: {'max_distance': 200},
# utils.telescope_multiplicity_filter: {'multiplicity': 2},
},
'transform': dsets.ResampleImage('bilinear_interpolation', (55, 55, 1)),
'target_transform': None
}
"""paths->list: mandatory, the folders where to find the hdf5 data files"""
"""image_filter->dict: optional, the filter(s) to apply to the dataset at image level"""
"""event_filter->dict: optional, the filter(s) to apply to the dataset"""
validating_ratio = 0.2
"""float: mandatory, the ratio of data to create the validating set"""
max_epochs = 2
"""int: mandatory, the maximum number of epochs for the experiment"""
batch_size = 4
"""int: mandatory, the size of the mini-batch"""
# train_files_max_number = 1
"""int: optional, the max number of files to use for the dataset"""
pin_memory = True
"""bool: optional, whether or not to pin memory in dataloader"""
# Training settings
loss_options = {
'conditional': True,
'gamma_class': dataset_parameters['particle_dict'][0],
}
loss_balancing_options = {
'logvar_coeff': [2, 2, 2, 0.5], # for uncertainty
'penalty': 0, # for uncertainty
}
"""dict: mandatory, defines for every objectives of the experiment
the loss function and its weight
"""
loss_balancing = criterions.MultilossBalancing(targets, **loss_balancing_options)
"""function: mandatory, the function to compute the loss"""
optimizer_dic = {
'network': optimizers.load_sgd,
'loss_balancing': optimizers.load_adam
}
"""dict: mandatory, the optimizers to use for the experiment.
One may want to use several optimizers in case of GAN for example
"""
optimizer_parameters = {
'network': {'lr': 1e-4,
'weight_decay': 1e-7,
'momentum': 0.9,
'nesterov': True
},
'loss_balancing': {'lr': 0.025,
'weight_decay': 1e-4,
},
}
"""dict: mandatory, defines the parameters for every optimizers to use"""
# regularization = {'function': 'gradient_penalty',
# 'weight': 10}
"""dict: optional, regularization to use during the training process. See in optimizers.py for
available regularization functions. If `function` is set to 'gradient_penalty', the training step must be
`training_step_mt_gradient_penalty`."""
experiment_hparams = {
'add_pointing': False
}
training_step = steps.get_training_step_mt(**experiment_hparams)
# training_step = steps.training_step_gradnorm
# training_step = steps.training_step_mt_gradient_penalty
"""function: mandatory, the function to compute the training step"""
eval_step = steps.get_eval_step_mt(**experiment_hparams)
"""function: mandatory, the function to compute the validating step"""
check_val_every_n_epoch = 1
"""int: optional, the interval in term of epoch for validating the model"""
lr_schedulers = {
'network': {
lr_scheduler.StepLR: {
'gamma': 0.1,
'step_size': 10,
}
},
# 'network': {
# lr_scheduler.ReduceLROnPlateau: {
# 'factor': 0.1,
# 'patience': 30,
# }
# },
# 'network': {
# lr_scheduler.MultiStepLR: {
# 'gamma': 0.1,
# 'milestones': [10, 15, 18],
# }
# },
# 'network': {
# lr_scheduler.ExponentialLR: {
# 'gamma': 0.9,
# }
# },
}
"""dict: optional, defines the learning rate schedulers"""
# callbacks
training_callbacks = [
LogGradientNorm(),
LogModelWeightNorm(),
LogModelParameters(),
LogUncertaintyLogVars(),
LogUncertaintyPrecisions(),
# LogGradNormWeights(),
LogReLUActivations(),
LogLinearGradient(),
# LogFeatures(), # Do not use during training !! Very costly !!
]
"""dict: list of callbacks
"""
######################################################################################################################
# Testing settings
test = True
"""bool: mandatory, whether or not to test the model at the end of training"""
merge_test_datasets = False
"""bool: optional, whether or not to merge test datasets"""
data_module_test = {
'module': GLearnDataModule,
'paths': [
Path(__file__).parent.absolute().joinpath('../../../share/data/MC_data').resolve().as_posix(),
],
'image_filter': {
utils.intensity_filter: {'intensity': [10, np.inf]},
# # utils.cleaning_filter: {'picture_thresh': 6, 'boundary_thresh': 3,
# # 'keep_isolated_pixels': False, 'min_number_picture_neighbors': 2},
# utils.leakage_filter: {'leakage2_cut': 0.2, 'picture_thresh': 6, 'boundary_thresh': 3,
# 'keep_isolated_pixels': False, 'min_number_picture_neighbors': 2},
},
'event_filter': {
# utils.energyband_filter: {'energy': [0.02, 2], 'filter_only_gammas': True}, # in TeV
# utils.emission_cone_filter: {'max_angle': 0.0698},
# utils.impact_distance_filter: {'max_distance': 200},
# utils.telescope_multiplicity_filter: {'multiplicity': 2},
},
'transform': dsets.ResampleImage('bilinear_interpolation', (55, 55, 1)),
'target_transform': None
}
"""
dict: optional, must at least contain a non-empty 'source':{'paths:[]'}
path->list of str: optional, the folders containing the hdf5 data files for the test
image_filter->dict: optional, filter(s) to apply to the test set at image level
event_filter->dict: optional, filter(s) to apply to the test set
"""
test_step = steps.get_test_step_mt(**experiment_hparams)
"""function: mandatory, the function to compute the validating step"""
dl2_path = ''
"""str: optional, path to store dl2 files"""
test_dataset_parameters = {
# 'subarray': [1],
}
"""dict: optional, the parameters of the dataset specific to the test operation."""
test_batch_size = 10
"""int: optional, the size of the mini-batch for the test"""
test_callbacks = [
WriteDL2Files()
]
"""dict: list of callbacks
""" | PypiClean |
/Ceygen-0.3.tar.gz/Ceygen-0.3/doc/llt.rst | ========================================
Cholesky Decomposition-powered Functions
========================================
This module contains algebraic functions powered by the Cholesky matrix decomposition (as
provided by the <`Eigen/Cholesky`_> include).
.. module:: ceygen.llt
.. function:: cholesky(x[, out=None])
Compute Cholesky decomposition of matrix *x* (which must be square, Hermitian and
positive-definite) so that *x* = *out* \* *out*.H (*out*.H being conjugate transpose of
*out*)
:param x: matrix to decompose
:type x: |nonint_matrix|
:param out: |out|
:type out: |nonint_matrix|
:raises: |valueerror|
:raises: |typeerror|
:rtype: |nonint_matrix|
.. _`Eigen/Cholesky`: http://eigen.tuxfamily.org/dox/QuickRefPage.html#QuickRef_Headers
.. include:: definitions.rst
| PypiClean |
/django-chuck-0.2.3.tar.gz/django-chuck/modules/feincms/project/static/scripts/libs/tiny_mce/plugins/contextmenu/editor_plugin.js | (function(){var a=tinymce.dom.Event,c=tinymce.each,b=tinymce.DOM;tinymce.create("tinymce.plugins.ContextMenu",{init:function(e){var h=this,f,d,i;h.editor=e;d=e.settings.contextmenu_never_use_native;h.onContextMenu=new tinymce.util.Dispatcher(this);f=e.onContextMenu.add(function(j,k){if((i!==0?i:k.ctrlKey)&&!d){return}a.cancel(k);if(k.target.nodeName=="IMG"){j.selection.select(k.target)}h._getMenu(j).showMenu(k.clientX||k.pageX,k.clientY||k.pageY);a.add(j.getDoc(),"click",function(l){g(j,l)});j.nodeChanged()});e.onRemove.add(function(){if(h._menu){h._menu.removeAll()}});function g(j,k){i=0;if(k&&k.button==2){i=k.ctrlKey;return}if(h._menu){h._menu.removeAll();h._menu.destroy();a.remove(j.getDoc(),"click",g);h._menu=null}}e.onMouseDown.add(g);e.onKeyDown.add(g);e.onKeyDown.add(function(j,k){if(k.shiftKey&&!k.ctrlKey&&!k.altKey&&k.keyCode===121){a.cancel(k);f(j,k)}})},getInfo:function(){return{longname:"Contextmenu",author:"Moxiecode Systems AB",authorurl:"http://tinymce.moxiecode.com",infourl:"http://wiki.moxiecode.com/index.php/TinyMCE:Plugins/contextmenu",version:tinymce.majorVersion+"."+tinymce.minorVersion}},_getMenu:function(e){var g=this,d=g._menu,j=e.selection,f=j.isCollapsed(),h=j.getNode()||e.getBody(),i,k;if(d){d.removeAll();d.destroy()}k=b.getPos(e.getContentAreaContainer());d=e.controlManager.createDropMenu("contextmenu",{offset_x:k.x+e.getParam("contextmenu_offset_x",0),offset_y:k.y+e.getParam("contextmenu_offset_y",0),constrain:1,keyboard_focus:true});g._menu=d;d.add({title:"advanced.cut_desc",icon:"cut",cmd:"Cut"}).setDisabled(f);d.add({title:"advanced.copy_desc",icon:"copy",cmd:"Copy"}).setDisabled(f);d.add({title:"advanced.paste_desc",icon:"paste",cmd:"Paste"});if((h.nodeName=="A"&&!e.dom.getAttrib(h,"name"))||!f){d.addSeparator();d.add({title:"advanced.link_desc",icon:"link",cmd:e.plugins.advlink?"mceAdvLink":"mceLink",ui:true});d.add({title:"advanced.unlink_desc",icon:"unlink",cmd:"UnLink"})}d.addSeparator();d.add({title:"advanced.image_desc",icon:"image",cmd:e.plugins.advimage?"mceAdvImage":"mceImage",ui:true});d.addSeparator();i=d.addMenu({title:"contextmenu.align"});i.add({title:"contextmenu.left",icon:"justifyleft",cmd:"JustifyLeft"});i.add({title:"contextmenu.center",icon:"justifycenter",cmd:"JustifyCenter"});i.add({title:"contextmenu.right",icon:"justifyright",cmd:"JustifyRight"});i.add({title:"contextmenu.full",icon:"justifyfull",cmd:"JustifyFull"});g.onContextMenu.dispatch(g,d,h,f);return d}});tinymce.PluginManager.add("contextmenu",tinymce.plugins.ContextMenu)})(); | PypiClean |
/Lantz-0.3.zip/Lantz-0.3/lantz/drivers/legacy/andor/neo.py | import ctypes as ct
import numpy as np
from lantz import Feat, Action, Q_
from lantz.foreign import RetStr, RetTuple
from .andor import Andor
class Neo(Andor):
"""Neo Andor CMOS Camera
"""
def initialize(self):
super().initialize()
self.flush()
self.fan_speed = 1
self.width ,self.height = self.sensor_size
self.length = self.width * self.height
self.clock_rate = 100
self.pixel_encoding = 32
self.imagesizebytes = self.getint("ImageSizeBytes")
self.userbuffer = ct.create_string_buffer(' ' * self.imagesizebytes)
@Feat(None, values={32: 'Mono32', 64: 'Mono64'})
def pixel_encoding(self, value):
"""Pixel encoding.
"""
self.setenumstring("PixelEncoding", value)
@Feat()
def sensor_size(self):
width = self.getint("SensorWidth")
height = self.getint("SensorHeight")
return width, height
@Feat(None, values={100: '100 MHz', 200: '200 MHz', 280: '280 MHz'})
def clock_rate(self, value):
"""Pixel clock rate
"""
self.setenumstring("PixelReadoutRate", value)
@Feat(None)
def fan_peed(self, value = 1):
"""Fan speed.
"""
self.setenumerated("FanSpeed", value)
@Feat()
def sensor_temp(self):
"""Sensor temperature.
"""
return self.getfloat("SensorTemperature")
@Feat()
def exposure_time(self):
"""Get exposure time.
"""
return self.getfloat("ExposureTime")
@exposure_time.setter
def exposure_time(self, exposure):
self.setfloat("ExposureTime", exposure)
@Feat(None)
def roi(self, width_height_top_left):
"""Set region of interest
"""
width, height, top, left = width_height_top_left
self.setint("AOIWidth", width)
self.setint("AOILeft", left)
self.setint("AOIHeight", height)
self.setint("AOITop", top)
@Action()
def take_image(self):
"""Image acquisition.
"""
self.queuebuffer(self.userbuffer, self.imagesizebytes)
self.command("AcquisitionStart")
self.waitbuffer(*RetStr(1))
self.command("AcquisitionStop")
self.flush()
image = np.fromstring(self.userbuffer, dtype=np.uint32, count=self.length)
image.shape = (self.height, self.width)
return image
@Action()
def take_image(self, numbuff, numframes):
"""Image acquisition with circular buffer.
"""
imagesizebytes = self.getint("ImageSizeBytes")
userbuffer = []
for i in range(numbuff):
userbuffer.append(ct.create_string_buffer(' ' * imagesizebytes))
self.queuebuffer(userbuffer, imagesizebytes)
self.command("AcquisitionStart")
for i in range(numbuff):
self.waitbuffer(*RetStr(1))
self.queuebuffer(userbuffer[i], imagesizebytes)
self.command("AcquisitionStop")
self.flush()
image = np.fromstring(userbuffer[0], dtype=np.uint32, count=self.length)
image.shape = (self.height, self.width)
return image | PypiClean |
/MegEngine-1.13.1-cp37-cp37m-macosx_10_14_x86_64.whl/megengine/functional/utils.py | from ..core._imperative_rt.core2 import apply
from ..core._imperative_rt.core2 import sync as _sync
from ..core.ops.builtin import AssertEqual
from ..tensor import Tensor
from ..utils.deprecation import deprecated_func
from .elemwise import abs, maximum, minimum
from .tensor import ones, zeros
__all__ = ["topk_accuracy"]
def _assert_equal(
expect: Tensor, actual: Tensor, *, maxerr: float = 0.0001, verbose: bool = False
):
r"""Asserts two tensors equal and returns expected value (first input).
It is a variant of python assert which is symbolically traceable (similar to ``numpy.testing.assert_equal``).
If we want to verify the correctness of model, just ``assert`` its states and outputs.
While sometimes we need to verify the correctness at different backends for *dumped* model
(or in :class:`~jit.trace` context), and no python code could be executed in that case.
Thus we have to use :func:`~functional.utils._assert_equal` instead.
Args:
expect: expected tensor value
actual: tensor to check value
maxerr: max allowed error; error is defined as the minimal of absolute and relative error
verbose: whether to print maxerr to stdout during opr exec
Examples:
>>> x = Tensor([1, 2, 3], dtype="float32")
>>> y = Tensor([1, 2, 3], dtype="float32")
>>> F.utils._assert_equal(x, y, maxerr=0)
Tensor([1. 2. 3.], device=xpux:0)
"""
err = (
abs(expect - actual)
/ maximum(
minimum(abs(expect), abs(actual)),
Tensor(1.0, dtype="float32", device=expect.device),
)
).max()
result = apply(AssertEqual(maxerr=maxerr, verbose=verbose), expect, actual, err)[0]
_sync() # sync interpreter to get exception
return result
def _simulate_error():
x1 = zeros(100)
x2 = ones(100)
(ret,) = apply(AssertEqual(maxerr=0, verbose=False), x1, x2, x2)
return ret
topk_accuracy = deprecated_func(
"1.3", "megengine.functional.metric", "topk_accuracy", True
)
copy = deprecated_func("1.3", "megengine.functional.tensor", "copy", True) | PypiClean |
/node_managment_application-0.0.1.tar.gz/node_managment_application-0.0.1/nms_app/static/admin/js/SelectBox.js | 'use strict';
{
const SelectBox = {
cache: {},
init: function(id) {
const box = document.getElementById(id);
SelectBox.cache[id] = [];
const cache = SelectBox.cache[id];
for (const node of box.options) {
cache.push({value: node.value, text: node.text, displayed: 1});
}
},
redisplay: function(id) {
// Repopulate HTML select box from cache
const box = document.getElementById(id);
const scroll_value_from_top = box.scrollTop;
box.innerHTML = '';
for (const node of SelectBox.cache[id]) {
if (node.displayed) {
const new_option = new Option(node.text, node.value, false, false);
// Shows a tooltip when hovering over the option
new_option.title = node.text;
box.appendChild(new_option);
}
}
box.scrollTop = scroll_value_from_top;
},
filter: function(id, text) {
// Redisplay the HTML select box, displaying only the choices containing ALL
// the words in text. (It's an AND search.)
const tokens = text.toLowerCase().split(/\s+/);
for (const node of SelectBox.cache[id]) {
node.displayed = 1;
const node_text = node.text.toLowerCase();
for (const token of tokens) {
if (!node_text.includes(token)) {
node.displayed = 0;
break; // Once the first token isn't found we're done
}
}
}
SelectBox.redisplay(id);
},
get_hidden_node_count(id) {
const cache = SelectBox.cache[id] || [];
return cache.filter(node => node.displayed === 0).length;
},
delete_from_cache: function(id, value) {
let delete_index = null;
const cache = SelectBox.cache[id];
for (const [i, node] of cache.entries()) {
if (node.value === value) {
delete_index = i;
break;
}
}
cache.splice(delete_index, 1);
},
add_to_cache: function(id, option) {
SelectBox.cache[id].push({value: option.value, text: option.text, displayed: 1});
},
cache_contains: function(id, value) {
// Check if an item is contained in the cache
for (const node of SelectBox.cache[id]) {
if (node.value === value) {
return true;
}
}
return false;
},
move: function(from, to) {
const from_box = document.getElementById(from);
for (const option of from_box.options) {
const option_value = option.value;
if (option.selected && SelectBox.cache_contains(from, option_value)) {
SelectBox.add_to_cache(to, {value: option_value, text: option.text, displayed: 1});
SelectBox.delete_from_cache(from, option_value);
}
}
SelectBox.redisplay(from);
SelectBox.redisplay(to);
},
move_all: function(from, to) {
const from_box = document.getElementById(from);
for (const option of from_box.options) {
const option_value = option.value;
if (SelectBox.cache_contains(from, option_value)) {
SelectBox.add_to_cache(to, {value: option_value, text: option.text, displayed: 1});
SelectBox.delete_from_cache(from, option_value);
}
}
SelectBox.redisplay(from);
SelectBox.redisplay(to);
},
sort: function(id) {
SelectBox.cache[id].sort(function(a, b) {
a = a.text.toLowerCase();
b = b.text.toLowerCase();
if (a > b) {
return 1;
}
if (a < b) {
return -1;
}
return 0;
} );
},
select_all: function(id) {
const box = document.getElementById(id);
for (const option of box.options) {
option.selected = true;
}
}
};
window.SelectBox = SelectBox;
} | PypiClean |
/Giraffe_View-0.0.9.5.tar.gz/Giraffe_View-0.0.9.5/Giraffe_View/function.py | import subprocess
import re
import os
from termcolor import colored
from subprocess import Popen, PIPE
def print_with_color(input_string):
print(colored(input_string, "green"))
def error_with_color(input_string):
print(colored(input_string, "red"))
def cmd_shell(cammands, string):
process = Popen(cammands.split(' '), stdout=subprocess.DEVNULL, universal_newlines=True)
process.wait()
err = process.communicate()
if process.returncode == 0:
# print('{} SUCCESS'.format(string))
pass
else:
# print('{} FAILED'.format(string))
error_with_color(err)
def Data_process(read, ref, threads=10):
# Define the commands as a list of strings to avoid issues with spaces
# in file names or command arguments
# path = os.getcwd()
cmd0 = ["mkdir", "-p", "results/observed_quality"]
cmd1 = ["seqkit", "seq", read, "-m", "200", "-Q", "7", "-g", "-j", str(threads), "-o", "results/observed_quality/clean.fastq"]
cmd2 = ["minimap2", "-ax", "map-ont", "-o", "results/observed_quality/tmp.sam", "--MD", "--secondary=no", "-L", "-t", str(threads), ref, "results/observed_quality/clean.fastq"]
cmd3 = ["samtools", "view", "-bS", "-F4", "-@", str(threads), "-o", "results/observed_quality/tmp.bam", "results/observed_quality/tmp.sam"]
cmd4 = ["samtools", "sort", "-@", str(threads), "-o", "results/observed_quality/tmp.sort.bam", "results/observed_quality/tmp.bam"]
cmd5 = ["samtools", "index", "-@", str(threads), "results/observed_quality/tmp.sort.bam"]
cmd6 = ["rm", "-rf", "results/observed_quality/tmp.sam", "results/observed_quality/tmp.bam"]
# Run each command and check the return code
for i, cmd in enumerate([cmd0, cmd1, cmd2, cmd3, cmd4, cmd5, cmd6]):
try:
subprocess.run(cmd, check=True)
# print("Command {} succeeded".format(i + 1))
except subprocess.CalledProcessError as e:
print("Command {} failed with error code {}".format(i + 1, e.returncode))
print(e.output)
# Raise an exception to indicate that processing failed
raise Exception("Data processing failed")
def mkdir_d(input_name):
mes = "results/" + str(input_name)
cmd = ["mkdir", "-p", str(mes)]
subprocess.run(cmd, check=True)
def count_indel_and_snv(str):
dict = {}
for i in str:
dict[i] = dict.get(i, 0) + 1
return dict
#remove the insertion (I) in the tail of string
def remove_I(string):
while string[-1] == "I":
string = string[:-1]
return(string)
# remove soft (S) and hard (H) clip in CIGAR and return the matched pairs
def remove_clip_list(input_cigar, input_pairs, input_ID):
remove_cigarstring = re.findall(r"\d+[S, H]+", input_cigar)
#HH & 0H & H0 & 00
if ((len(remove_cigarstring) == 2) and (remove_cigarstring[0][-1] == remove_cigarstring[1][-1] == "H")) or ((len(remove_cigarstring) == 1) and (remove_cigarstring[-1] == "H")) or (len(remove_cigarstring) == 0):
valid_pairs = input_pairs
#SS
elif (len(remove_cigarstring) == 2) and (remove_cigarstring[0][-1] == remove_cigarstring[1][-1] == "S"):
remove_start_site = int(remove_cigarstring[0][:-1])
tmp_pairs = input_pairs[remove_start_site:]
remove_end_site = int(remove_cigarstring[1][:-1])
valid_pairs = tmp_pairs[:len(tmp_pairs)-remove_end_site]
# 0S & HS
elif ((len(remove_cigarstring) == 1) and (input_cigar[-1] == "S")) or (len(remove_cigarstring) == 2) and (remove_cigarstring[0][-1] == "H") and ((remove_cigarstring[1][-1] == "S")):
remove_end_site = int(remove_cigarstring[-1][:-1])
valid_pairs = input_pairs[:len(input_pairs)-remove_end_site]
# S0 & SH
elif (len(remove_cigarstring) == 1) and (input_cigar[-1] != "S") or ((len(remove_cigarstring) == 2) and (remove_cigarstring[0][-1] == "S") and (remove_cigarstring[1][-1] == "H")):
remove_start_site = int(remove_cigarstring[0][:-1])
valid_pairs = input_pairs[remove_start_site:]
else:
print(str(input_ID) + ", please recheck this CIGAR and MD!")
return(valid_pairs)
"""
only for base A T G C
(read_position, ref_position, "ref_base")
none √ √ Deletion(D)
√ none none Insertion(I)
√ √ N(A,T,G,C) Match(M)
√ √ n(a,t,g,c) Substitution(S)
"""
def get_base_alignment(input_list):
map_list = ["A", "T", "G", "C"]
result = ""
if input_list[0] == None:
result = "D" # D = deletion
else:
if input_list[1] == None:
result = "I" # I = insertion
else:
if input_list[2] in map_list:
result = "M" # M = match
else:
result = "S" # S = substitution
return result | PypiClean |
/Kotti-2.0.9.tar.gz/Kotti-2.0.9/kotti/migrate.py | import os
from typing import Callable
from typing import List
import pkg_resources
from alembic.config import Config
from alembic.environment import EnvironmentContext
from alembic.script import ScriptDirectory
from alembic.util import load_python_file
from zope.sqlalchemy import mark_changed
from kotti import DBSession
from kotti import conf_defaults
from kotti import get_settings
from kotti.util import command
KOTTI_SCRIPT_DIR = pkg_resources.resource_filename("kotti", "alembic")
DEFAULT_LOCATION = "kotti:alembic"
class ScriptDirectoryWithDefaultEnvPy(ScriptDirectory):
@property
def env_py_location(self) -> str:
loc = super().env_py_location
if not os.path.exists(loc):
loc = os.path.join(KOTTI_SCRIPT_DIR, "env.py")
return loc
def run_env(self) -> None:
dir_, filename = self.env_py_location.rsplit(os.path.sep, 1)
load_python_file(dir_, filename)
class PackageEnvironment:
def __init__(self, location: str) -> None:
self.location = location
self.config = self._make_config(location)
self.script_dir = self._make_script_dir(self.config)
@property
def pkg_name(self) -> str:
return self.location.split(":")[0]
@property
def version_table(self) -> str:
return f"{self.pkg_name}_alembic_version"
def run_env(self, fn: Callable, **kw) -> None:
with EnvironmentContext(
self.config, self.script_dir, fn=fn, version_table=self.version_table, **kw
):
self.script_dir.run_env()
@staticmethod
def _make_config(location: str) -> Config:
cfg = Config()
cfg.set_main_option("script_location", location)
cfg.set_main_option("sqlalchemy.url", get_settings()["sqlalchemy.url"])
return cfg
@staticmethod
def _make_script_dir(alembic_cfg: Config) -> ScriptDirectoryWithDefaultEnvPy:
script_dir = ScriptDirectory.from_config(alembic_cfg)
script_dir.__class__ = ScriptDirectoryWithDefaultEnvPy # O_o
return script_dir
def get_locations() -> List[str]:
conf_str = get_settings()["kotti.alembic_dirs"]
return [line.strip() for line in conf_str.split() if line.strip()]
def stamp_head(location: str = DEFAULT_LOCATION, revision: None = None) -> None:
env = PackageEnvironment(location)
def do_stamp(rev, context, revision=revision):
if revision is None:
revision = context.script.get_current_head()
elif revision == "None":
revision = None
context.stamp(env.script_dir, revision)
mark_changed(DBSession())
return []
env.run_env(do_stamp)
def stamp_heads() -> None:
for location in get_locations():
stamp_head(location)
def upgrade(location=DEFAULT_LOCATION, revision=None):
# We don't want to fire any kind of events during a migration,
# because "migrations are a low-level thing".
from kotti import events
events.clear()
pkg_env = PackageEnvironment(location)
if revision is None:
revision = pkg_env.script_dir.get_current_head()
print(f"Upgrading {pkg_env.location}:")
def upgrade(heads, context):
# alembic supports multiple heads, we don't.
# initial revision is () in alembic >= 0.7
rev = heads[0] if heads else None
if rev == revision:
print(" - already up to date.")
return []
print(f" - upgrading from {rev} to {revision}...")
return context.script._upgrade_revs(revision, rev)
pkg_env.run_env(upgrade, starting_rev=None, destination_rev=revision)
print()
def upgrade_all():
for location in get_locations():
upgrade(location)
def list_all():
pkg_envs = [PackageEnvironment(location) for location in get_locations()]
for pkg_env in pkg_envs:
print(f"{pkg_env.pkg_name}:")
for script in pkg_env.script_dir.walk_revisions():
print(
" - {} -> {}: {}".format(
script.down_revision, script.revision, script.doc
)
)
def current_revision(rev, context):
rev = rev[0] if rev else None
print(f" - current revision: {rev}")
return []
pkg_env.run_env(current_revision)
print()
def kotti_migrate_command():
__doc__ = """Migrate Kotti and Kotti add-ons.
Usage:
kotti-migrate <config_uri> list_all
kotti-migrate <config_uri> upgrade [--scripts=<location>] [--rev=<rev>]
kotti-migrate <config_uri> upgrade_all
kotti-migrate <config_uri> stamp_head [--scripts=<location>] [--rev=<rev>]
o 'list_all' prints a list of all available migrations of Kotti
and registered add-ons.
o 'upgrade' will run Kotti's upgrades to upgrade the database to
the latest version.
Use '--scripts=kotti_myaddon:alembic' to run the upgrades of the
'kotti_myaddon' package instead.
o 'upgrade_all' will run all upgrades of all packages registered
with Kotti.
o 'stamp_head' allows you to manually set the stamped version to
the latest version inside the 'kotti_alembic_version' table,
that is, without actually running any migrations.
You may use this command for a different package by using the
'--scripts' option.
Options:
-h --help Show this screen.
"""
# We need to turn off populators and root_factory when we run
# migrations, because they would access the database, which may
# not be possible prior to the migration.
#
# Unfortunately, we're not able to just set the 'kotti.populators'
# setting to an empty list. Since add-ons might add to this list
# again later, when we call 'bootstrap' (and thus their
# 'includeme' function).
save_conf_defaults = conf_defaults.copy()
os.environ["KOTTI_DISABLE_POPULATORS"] = "1"
conf_defaults["kotti.root_factory"] = [lambda req: None]
def callback(arguments):
args = ()
args_with_location = (arguments["--scripts"] or DEFAULT_LOCATION,)
if arguments["list_all"]:
func = list_all
elif arguments["upgrade"]:
func = upgrade
args = args_with_location + (arguments["--rev"],)
elif arguments["upgrade_all"]:
func = upgrade_all
elif arguments["stamp_head"]:
func = stamp_head
args = args_with_location + (arguments["--rev"],)
else:
raise ValueError("Unknown command")
func(*args)
try:
return command(callback, __doc__)
finally:
conf_defaults.clear()
conf_defaults.update(save_conf_defaults)
del os.environ["KOTTI_DISABLE_POPULATORS"] | PypiClean |
/AcDummyLib-0.2.0.tar.gz/AcDummyLib-0.2.0/README.md | # Assetto Corsa dammy Python library
Dummy library for Assetto Corsa native functions presented in Python.
Actually, it has a single interface for `ac` module.
The main goal of this package: provide convenient autocomplete in IDE (tested in PyCharm).
## Installation to develop AC mod
You will need to install the package:
```shell
pip install AcDummyLib
```
Add following in your script instead of `import ac`:
```python
if __name__ == '__main__':
### pip install AcDummyLib
from AcDummyLib import ac
else:
import ac
```
Now you can check your IDE, autocomplete shall work.
## Contribution
You are very welcome to add changes into this code. =)
Please feel free to push merge/pull requests.
Or, you may raise an issue to highlight found discrepancies.
## Roadmap
- Migrate function descriptions into the interface file.
## References
#### Source documents:
- https://docs.google.com/document/d/13trBp6K1TjWbToUQs_nfFsB291-zVJzRZCNaTYt4Dzc/pub
- https://assettocorsamods.net/attachments/inofficial_acpythondoc_v2-pdf.7415/
#### Initial forum threads:
- https://assettocorsamods.net/threads/doc-python-doc.59
- https://assettocorsamods.net/threads/is-there-a-way-to-load-ac-library-to-have-autocomplete-in-an-ide-e-g-pycharm.3088/ | PypiClean |
/Gestus-0.3.4.tar.gz/Gestus-0.3.4/gestus/migrations/0003_fill_environment_url.py | from south.utils import datetime_utils as datetime
from south.db import db
from south.v2 import DataMigration
from django.db import models
class Migration(DataMigration):
def forwards(self, orm):
for environment in orm.WebsiteEnvironment.objects.all():
environment.url = environment.website.url
environment.save()
def backwards(self, orm):
"Write your backwards methods here."
models = {
u'gestus.egg': {
'Meta': {'object_name': 'Egg'},
'created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '50'}),
'package': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '50'}),
'url': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'})
},
u'gestus.eggversion': {
'Meta': {'object_name': 'EggVersion'},
'created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
'egg': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'versions'", 'to': u"orm['gestus.Egg']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '20'})
},
u'gestus.website': {
'Meta': {'object_name': 'Website'},
'created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
'description': ('django.db.models.fields.TextField', [], {'blank': 'True'}),
'enabled': ('django.db.models.fields.BooleanField', [], {'default': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}),
'url': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'})
},
u'gestus.websiteenvironment': {
'Meta': {'object_name': 'WebsiteEnvironment'},
'created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
'eggs': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['gestus.EggVersion']", 'symmetrical': 'False', 'blank': 'True'}),
'enabled': ('django.db.models.fields.BooleanField', [], {'default': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'modified': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'blank': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}),
'server': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'url': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}),
'website': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'environments'", 'to': u"orm['gestus.Website']"})
}
}
complete_apps = ['gestus']
symmetrical = True | PypiClean |
/Activate_App-0.0.10-py3-none-any.whl/activate/app/checklist.py | from __future__ import annotations
from typing import overload
from PyQt5 import QtWidgets
from PyQt5.QtCore import Qt
Unchecked, PartiallyChecked, Checked = Qt.Unchecked, Qt.PartiallyChecked, Qt.Checked
class CheckList(QtWidgets.QListWidget):
"""A QListWidget with checkboxes on items."""
def __init__(self, *args, **kwargs):
self.do_not_recurse = False
self.all_row = False
super().__init__(*args, **kwargs)
self.itemChanged.connect(self.item_changed)
self.itemDoubleClicked.connect(self.item_double_clicked)
@overload
def __getitem__(self, index: int) -> QtWidgets.QListWidgetItem:
...
@overload
def __getitem__(self, index: slice) -> list[QtWidgets.QListWidgetItem]:
...
def __getitem__(self, index):
if isinstance(index, slice):
return [self.item(i) for i in range(len(self))[index]]
result = self.item(index)
if result is None:
raise IndexError(f"{self.__class__.__qualname__} index out of range")
return result
@property
def row_names(self):
return [row.text() for row in self]
@row_names.setter
def row_names(self, new_items):
self.clear()
self.addItems(new_items)
for row in self:
row.setCheckState(Unchecked)
@property
def states(self):
return {row.text(): row.checkState() for row in self}
@states.setter
def states(self, new_states):
for index, item in enumerate(self.row_names):
if item in new_states:
self.set_check_state(index, new_states[item])
@property
def num_states(self):
return {
row.text(): {Unchecked: 0, PartiallyChecked: 0.5, Checked: 1}[
row.checkState()
]
for row in self
}
@num_states.setter
def num_states(self, new_states):
for index, item in enumerate(self.row_names):
if item in new_states:
if new_states[item] == 0:
self.set_check_state(index, Unchecked)
elif new_states[item] == 0.5:
self.set_check_state(index, PartiallyChecked)
elif new_states[item] == 1:
self.set_check_state(index, Checked)
def get_row(self, row):
"""Get a row from a string, index or row."""
if isinstance(row, str):
for real_row in self:
if real_row.text() == row:
return real_row
raise ValueError(f"{row} is not a row.")
if isinstance(row, int):
return self[row]
return row
def set_check_state(self, row, state):
self.get_row(row).setCheckState(state)
def check_state(self, row):
return self.get_row(row).checkState()
@property
def checked_rows(self):
return [r.text() for r in self if r.checkState() == Checked]
def item_changed(self, item):
if self.do_not_recurse or not self.all_row:
return
self.stop_updates()
if self.is_all(item):
for item_ in self[1:]:
item_.setCheckState(item.checkState())
else:
states = {i.checkState() for i in self[1:]}
self.set_all_state(
next(iter(states)) if len(states) == 1 else PartiallyChecked
)
self.start_updates()
def item_double_clicked(self, item):
if self.is_all(item):
self.set_all_state(Checked)
return
self.stop_updates()
if self.all_row and len(self) > 2:
self.set_all_state(PartiallyChecked)
for item_ in self:
if not self.is_all(item_):
item_.setCheckState(Checked if item_ is item else Unchecked)
self.start_updates()
def check_all(self):
for row in self:
row.setCheckState(Checked)
def add_all_row(self):
self.insertItem(0, "All")
self.all_row = True
def is_all(self, item):
"""Check if a row is the 'All' row."""
return self.all_row and self.row(item) == 0
def set_all_state(self, state):
if self.all_row:
self.set_check_state(0, state)
def stop_updates(self):
self.do_not_recurse = True
self.blockSignals(True)
def start_updates(self):
self.do_not_recurse = False
self.blockSignals(False) | PypiClean |
/DBQuery-0.4.1.tar.gz/DBQuery-0.4.1/src/dbquery/postgres.py | from psycopg2 import OperationalError as PGOperationalError
from psycopg2 import connect
from .db import DB
from .query import SelectOne
class _NextVal(SelectOne):
def __init__(self, db, sequence):
super(_NextVal, self).__init__(
db, 'SELECT nextval(\'{}\')'.format(sequence), None)
class PostgresDB(DB):
""" PostgreSQL DB class using a single psycopg2 connection.
Use either a 'dsn' connection string or keyword parameter to define the
connection (from the psycopg2 documentation):
database – the database name (only as keyword argument)
user – user name used to authenticate
password – password used to authenticate
host – database host address (defaults to UNIX socket if not provided)
port – connection port number (defaults to 5432 if not provided)
"""
OperationalError = PGOperationalError
def __init__(self, dsn=None, retry=0, **kwds):
super(PostgresDB, self).__init__(retry=retry)
self._kwds = kwds or {}
if dsn:
self._kwds["dsn"] = dsn
self._connection = None
def _connect(self):
if self._connection is not None:
raise RuntimeError("Connection still exists.")
self._connection = connect(**self._kwds)
self._connection.set_session(autocommit=True)
def close(self):
if self._connection is not None:
try:
self._connection.close()
except Exception:
pass # ignore
self._connection = None
@DB.connected
def execute(self, sql, params, return_function=None):
with self._connection.cursor() as cursor:
cursor.execute(sql, params)
if return_function:
return return_function(cursor)
@DB.connected
def nonclosing_execute(self, sql, params, return_function=None):
cursor = self._connection.cursor()
cursor.execute(sql, params)
return cursor
@DB.connected
def show(self, sql, params):
with self._connection.cursor() as cursor:
return cursor.mogrify(sql, params).decode(
self._connection.encoding)
def NextVal(self, sequence):
return _NextVal(self, sequence)
@DB.connected
def _begin(self):
self._connection.autocommit = False
def _commit(self):
if self._connection is None:
raise RuntimeError("Connection lost, can not commit!")
self._connection.commit()
self._connection.autocommit = True
def _rollback(self):
if self._connection is None:
raise RuntimeError("Connection lost, can not roll back!")
self._connection.rollback()
self._connection.autocommit = True | PypiClean |
/MyAutoman-1.7.3.tar.gz/MyAutoman-1.7.3/Automan/plugins/odps.py | import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
import matplotlib.font_manager
# from pyod.models.abod import ABOD # 基于概率
# from pyod.models. knn import KNN # 基于近邻
# from pyod.models.mcd import MCD #基于线性模型
# from pyod.models.ocsvm import OCSVM
import pandas as pd
from Automan.plugins.DDViz import out_null,auto_bin,manual_bin,out_iv,plt_multi_mosaic,plt_mosaic
from tqdm import tqdm
import joblib
import datetime
from sklearn.preprocessing import StandardScaler,MinMaxScaler
from multiprocessing.pool import ThreadPool
class ODPS():
def __init__(self,
col_x,
data_parts='data_parts',
data_parts_use=None,
algo_dict = {},
num_of_round =50 ,
num_of_compile=5,
play_report=True,
verbose=True,
ks_limit=0.02,
is_filter=True ,
fill_dict={-99:-1},
scale_type=1,
n_jobs = 2,
contamination=.2):
'''
Parameters
----------
col_x: list
特征列表.
data_parts: str
数据集切分字段.
data_parts_use: list or None
样本分析列表，eg:[1,2],只会分析data_parts为1和2的样本，如果为None分析整个数据集
algo_dict : dict
算法列表
num_of_round : int
变量生成轮次 : default 50
num_of_compile : int
组合变量个数 : default 5
play_report : bool
是否生成报告 : default True
verbose : bool
ks_limit : float
复合变量的ks下限 : default 0.02
is_filter : bool
是否做变量筛选 : default True
fill_dict : dict
变量值映射列表 : default {-99 : -1}
scale_type : int
归一化方法 : default 1
n_jobs : int
进程数 : default 1
contamination : float
污染比例 : 0.2
'''
self.col_x = col_x
self.data_parts = data_parts
self.data_parts_use = data_parts_use
self.dict_map=dict()
self.algo_dict = algo_dict
self.var_list = col_x
self.num_of_round = num_of_round
self.num_of_compile = num_of_compile
self.play_report = play_report
self.verbose = verbose
self.ks_limit = ks_limit
self.is_filter = is_filter
self.fill_dict = fill_dict
self.scale_type = scale_type
self.n_jobs = n_jobs
self.contamination = contamination
def _preprocess(self, data, training=True):
'''变量预处理方法
Args:
data : pandas.DataFrame : 待处理数据集
training : bool : 是否为测试机
Return:
data : pandas.DataFrame
'''
mem_cols = data.columns
data = data.fillna(-99)
data = data.replace(self.fill_dict)
# 归一化过程训练
if training:
if self.scale_type == 1:
self.st = StandardScaler()
elif self.scale_type ==2:
self.st = MinMaxScaler()
if self.scale_type !=1 and self.scale_type!=2 and self.scale_type!=0:
raise ValueError('scale_type must be 1--StandardScaler, 2--MinMaxScaler')
if self.scale_type==1 or self.scale_type==2 :
self.st.fit_transform(data)
# 归一化过程演绎
data = self.st.transform(data)
data = pd.DataFrame(data)
data.columns = list(mem_cols)
return data
def fit(self,data,y=None):
'''fit函数
Parameters
----------
data: pd.DataFrame
数据集-数据集中需要包含col_x所有字段，如果y不为None，数据集中需要包含y字段
Returns
-------
self:对象本身对象本身
'''
if y is None:
raise TypeError('missing argument: ''y''')
if self.data_parts_use is None and self.data_parts is not None:
self.data_parts_use = list(data.data_parts.unique())
if self.data_parts_use:
self.train_X = data.loc[data[self.data_parts].isin(self.data_parts_use),:].reset_index(drop=True).copy(deep=True)
self.val_X = data.loc[~data[self.data_parts].isin(self.data_parts_use),:].reset_index(drop=True).copy(deep=True)
self.train_Y = pd.DataFrame(y).loc[data[self.data_parts].isin(self.data_parts_use),:].reset_index(drop=True).copy(deep=True).iloc[:,0]
self.val_Y = pd.DataFrame(y).loc[~data[self.data_parts].isin(self.data_parts_use),:].reset_index(drop=True).copy(deep=True).iloc[:,0]
else:
self.train_X = data.copy(deep=True)
self.val_X = data.copy(deep=True)
self.train_Y = y.copy()
self.val_Y = y.copy()
if len(self.val_X) == 0:
self.val_X = data.copy(deep=True)
self.val_Y = y.copy(deep=True)
#self.train_Y = self.train_X.pop(y)
#self.val_Y = self.val_X.pop(y)
self.choose_var_dict = {}
self.final_var_dict = {}
self.algo_names = list(self.algo_dict.keys())
# 训练集变量衍生数据集
self.output_train_set = self.train_X[self.var_list].copy()
# 验证集变量衍生数据集
self.output_val_set = self.val_X[self.var_list].copy()
# var to id 映射
self.var2id = {var : idx for idx, var in enumerate(self.var_list)}
# id to var 映射
self.id2var = {idx : var for idx, var in enumerate(self.var_list)}
# 变量衍生列表
self.choose_var_list = []
# 最终变量列表
self.final_var_list = []
self.algo_lists = []
self.outdict = {}
# 中间特征重要性存贮字典
self.imp_var_dict = {}
# 中间算法重要性存贮字典
self.imp_algo_dict = {}
self.ks_iv_outs = None
# 归一化实例
self.st = None
# 数据集缺失值填空及归一化预处理
if self.scale_type in [0, 1, 2]:
self.train_X_normed = self._preprocess(self.train_X[self.var_list], True)
self.val_X_normed = self._preprocess(self.val_X[self.var_list], False)
else:
self.train_X_normed = self.train_X
self.val_X_normed = self.val_X
# 训练集变量衍生数据集
self.output_train_set = self.train_X.copy()
# 验证集变量衍生数据集
self.output_val_set = self.val_X.copy()
def _fun_var_choice(i):
##for i in tqdm(range(self.num_of_round)):
# 计算特征重要性
var_imp_dict_rnd = self._cal_feature_importance()
# 计算算法重要性
algo_imp_dict_rnd = self._cal_algo_importance()
# 特征重要性归一化
p_algo = [algo_imp_dict_rnd[t] for t in self.algo_names]
p_algo = p_algo / np.sum(p_algo)
# 算法重要性归一化
p_var = [var_imp_dict_rnd[t] for t in self.var_list]
p_var = p_var / np.sum(p_var)
# 按照算法重要性分布选取变量
t_algo = np.random.choice(self.algo_names, 1, p=p_algo,replace=False)[0]
t_clf = self.algo_dict[t_algo](contamination=self.contamination)
# 按照特征重要性分布选取变量
t_vars = np.random.choice(self.var_list, self.num_of_compile, p=p_var,replace=False)
# 按变量入模顺序排序
t_ids = sorted([self.var2id[i] for i in t_vars])
# 合并变量id作为变量名
t_var_name = 'odps_' + t_algo +''.join([str(i) + '_' for i in t_ids])[:-1]
# 打印变量名
if self.verbose:
print(t_var_name)
# 防止生成重复变量
if t_var_name not in self.choose_var_list:
# 初始化变量字典
self.choose_var_dict[t_var_name] = []
# 添加到变量选择列表
self.choose_var_list.append(t_var_name)
# 参数训练
t_clf.fit(self.train_X_normed[t_vars])
# 将异常算法实例添加到算法列表
self.algo_lists.append(t_clf)
# 变量字典t_var_name : [t_clf]
self.choose_var_dict[t_var_name].append(t_clf)
# 变量字典t_var_name : [t_clf, [va1, va2...]]
self.choose_var_dict[t_var_name].append(t_vars)
# Train
# 训练集预测
y_pred = t_clf.predict_proba(self.train_X_normed[t_vars])[:,0]
# 保持已经存在的变量名
orig = self.output_train_set.columns
self.output_train_set[t_var_name] = y_pred
# 生成输入iv计算器的临时数据集
tmp_df = self.output_train_set.copy()
tmp_df = pd.concat([tmp_df, self.train_Y], axis=1)
tmp_df.columns = list(orig) + [t_var_name] + ['fpd4']
tmp_df['dt'] = 1
# Validation
# 验证集预测
y_pred = t_clf.predict_proba(self.val_X_normed[t_vars])[:,0]
# 保持已经存在的变量名
self.output_val_set[t_var_name] = y_pred
# 计算本轮生成变量的KS
tmp_ks = self._cal_ks(tmp_df, t_var_name)
# 遍历所选用的变量
for t_var in t_vars:
# 更新变量特征重要性字典
if t_var not in self.imp_var_dict:
self.imp_var_dict[t_var] = []
self.imp_var_dict[t_var].append(tmp_ks)
# 更新算法重要性字典
if t_algo not in self.imp_algo_dict:
self.imp_algo_dict[t_algo] = []
self.imp_algo_dict[t_algo].append(tmp_ks)
with ThreadPool(processes=self.n_jobs) as pool:
pool.map(_fun_var_choice, range(self.num_of_round))
if self.verbose:
print('总共有%d个衍生变量'%len(self.algo_lists))
# 报告生成
if self.play_report is True:
self._play_report()
# 过滤KS较低变量
if self.is_filter:
self._filter_var()
else:
self.final_var_dict = self.choose_var_dict
self.final_var_list = self.choose_var_list
ids = []
for k, v in self.final_var_dict.items():
ids.extend(v[1])
ids = list(set(ids))
self.final_var_list_inputs = ids
self.col_new = list(data.columns) + list(self.final_var_dict.keys())
# 删除无用的属性，释放空间
del self.train_X
del self.val_X
del self.train_Y
del self.val_Y
del self.train_X_normed
del self.val_X_normed
del self.output_train_set
del self.output_val_set
def _cal_algo_importance(self):
'''_cal_algo_importance函数
Parameters
----------
Returns
-------
algo_imp_dict_rnd : dict
算法重要性字典
'''
# 算法重要性字典容器
algo_imp_dict_rnd = {}
# 遍历算法列表
for algo_name in self.algo_names:
if algo_name not in self.imp_algo_dict:
algo_imp_dict_rnd[algo_name] = 0.05
elif self.imp_algo_dict[algo_name] == []:
algo_imp_dict_rnd[algo_name] = 0.05
else:
algo_imp_dict_rnd[algo_name] = np.mean(self.imp_algo_dict[algo_name])
return algo_imp_dict_rnd
def _cal_feature_importance(self):
'''_cal_feature_importance函数
Parameters
----------
Returns
-------
var_imp_dict_rnd : dict
变量重要性字典
'''
var_imp_dict_rnd = {}
for var_name in self.var_list:
if var_name not in self.imp_var_dict:
var_imp_dict_rnd[var_name] = 0.05
elif self.imp_var_dict[var_name] == []:
var_imp_dict_rnd[var_name] = 0.05
else:
var_imp_dict_rnd[var_name] = np.mean(self.imp_var_dict[var_name])
return var_imp_dict_rnd
def _cal_ks(self, df, var_name):
'''_cal_ks函数
Parameters
----------
df : pandas.DataFrame
数据集
var_name : string
变量名
Returns
-------
: float
变量KS效果
'''
df["dt_cut"] = 'all'
iv_ks = out_iv(df, [var_name], y='fpd4', dt='dt',dt_cut = 'dt_cut',isformat = False)
print ("iv_ks = ", iv_ks['df_iv'])
del df["dt_cut"]
# return iv_ks['df_iv'][var_name]
return iv_ks['df_iv'].loc[var_name]
def _play_report(self):
'''_play_report
Parameters
----------
Returns
-------
: dict
报告
'''
# 结果容器
outs = {}
# 训练集
df_train = pd.concat([self.output_train_set[self.choose_var_list], self.train_Y], axis=1)
df_train.columns = self.choose_var_list + ['fpd4']
df_train['dt']= '1'
train_iv_ks = out_iv(df_train, self.choose_var_list, y='fpd4', dt='dt',isformat=False,dt_cut = 'dt')
outs['train_iv'] = train_iv_ks['df_iv'].loc[self.choose_var_list]
outs['train_ks'] = train_iv_ks['df_ks'].loc[self.choose_var_list]
# 验证集
df_val = pd.concat([self.output_val_set[self.choose_var_list], self.val_Y], axis=1)
df_val.columns = self.choose_var_list + ['fpd4']
df_val['dt']= '1'
val_iv_ks = out_iv(df_val, self.choose_var_list, y='fpd4', dt='dt',isformat=False,dt_cut = 'dt')
outs['val_iv'] = val_iv_ks['df_iv'].loc[self.choose_var_list]
outs['val_ks'] = val_iv_ks['df_ks'].loc[self.choose_var_list]
self.ks_iv_outs = outs
return outs
def _filter_var(self):
'''_filter_var
Parameters
----------
Returns
-------
'''
if self.ks_iv_outs is None:
self._play_report()
outs = self.ks_iv_outs
# print ("!!!outs['train_ks']=!!!",outs['train_ks'])
out_train_ks = outs['train_ks'].to_dict()[1]
# print ("out_train_ks",out_train_ks)
for var_name, ks in out_train_ks.items():
if out_train_ks[var_name] >= self.ks_limit:
self.final_var_dict[var_name] = self.choose_var_dict[var_name]
self.final_var_list.append(var_name)
def transform(self,data,y=None):
'''transform函数
Parameters
----------
data: pd.DataFrame
需要转换的数据集
Returns
-------
data:pd.DataFrame
转换后的数据集
'''
test_X = data[self.var_list]
# 数据预处理
if self.scale_type==1 or self.scale_type==2 :
test_X = self._preprocess(test_X, False)
output_df = data.copy()
# 遍历最终变量字典
for var_name in self.final_var_dict:
# 单变量列表
t_dict = self.final_var_dict[var_name]
# 算法实例
t_algo = t_dict[0]
# 组合变量的单变量列表
t_vars = t_dict[1]
# 预测衍生
output_df[var_name] = t_algo.predict_proba(test_X[t_vars])[:,0]
return output_df | PypiClean |
/NehorayRapid1-0.0.1-py3-none-any.whl/mmedit/models/components/discriminators/multi_layer_disc.py | import torch.nn as nn
from mmcv.cnn import ConvModule
from mmcv.runner import load_checkpoint
from mmedit.models.common import LinearModule
from mmedit.models.registry import COMPONENTS
from mmedit.utils import get_root_logger
@COMPONENTS.register_module()
class MultiLayerDiscriminator(nn.Module):
"""Multilayer Discriminator.
This is a commonly used structure with stacked multiply convolution layers.
Args:
in_channels (int): Input channel of the first input convolution.
max_channels (int): The maximum channel number in this structure.
num_conv (int): Number of stacked intermediate convs (including input
conv but excluding output conv).
fc_in_channels (int | None): Input dimension of the fully connected
layer. If `fc_in_channels` is None, the fully connected layer will
be removed.
fc_out_channels (int): Output dimension of the fully connected layer.
kernel_size (int): Kernel size of the conv modules. Default to 5.
conv_cfg (dict): Config dict to build conv layer.
norm_cfg (dict): Config dict to build norm layer.
act_cfg (dict): Config dict for activation layer, "relu" by default.
out_act_cfg (dict): Config dict for output activation, "relu" by
default.
with_input_norm (bool): Whether add normalization after the input conv.
Default to True.
with_out_convs (bool): Whether add output convs to the discriminator.
The output convs contain two convs. The first out conv has the same
setting as the intermediate convs but a stride of 1 instead of 2.
The second out conv is a conv similar to the first out conv but
reduces the number of channels to 1 and has no activation layer.
Default to False.
with_spectral_norm (bool): Whether use spectral norm after the conv
layers. Default to False.
kwargs (keyword arguments).
"""
def __init__(self,
in_channels,
max_channels,
num_convs=5,
fc_in_channels=None,
fc_out_channels=1024,
kernel_size=5,
conv_cfg=None,
norm_cfg=None,
act_cfg=dict(type='ReLU'),
out_act_cfg=dict(type='ReLU'),
with_input_norm=True,
with_out_convs=False,
with_spectral_norm=False,
**kwargs):
super().__init__()
if fc_in_channels is not None:
assert fc_in_channels > 0
self.max_channels = max_channels
self.with_fc = fc_in_channels is not None
self.num_convs = num_convs
self.with_out_act = out_act_cfg is not None
self.with_out_convs = with_out_convs
cur_channels = in_channels
for i in range(num_convs):
out_ch = min(64 * 2**i, max_channels)
norm_cfg_ = norm_cfg
act_cfg_ = act_cfg
if i == 0 and not with_input_norm:
norm_cfg_ = None
elif (i == num_convs - 1 and not self.with_fc
and not self.with_out_convs):
norm_cfg_ = None
act_cfg_ = out_act_cfg
self.add_module(
f'conv{i + 1}',
ConvModule(
cur_channels,
out_ch,
kernel_size=kernel_size,
stride=2,
padding=kernel_size // 2,
norm_cfg=norm_cfg_,
act_cfg=act_cfg_,
with_spectral_norm=with_spectral_norm,
**kwargs))
cur_channels = out_ch
if self.with_out_convs:
cur_channels = min(64 * 2**(num_convs - 1), max_channels)
out_ch = min(64 * 2**num_convs, max_channels)
self.add_module(
f'conv{num_convs + 1}',
ConvModule(
cur_channels,
out_ch,
kernel_size,
stride=1,
padding=kernel_size // 2,
norm_cfg=norm_cfg,
act_cfg=act_cfg,
with_spectral_norm=with_spectral_norm,
**kwargs))
self.add_module(
f'conv{num_convs + 2}',
ConvModule(
out_ch,
1,
kernel_size,
stride=1,
padding=kernel_size // 2,
act_cfg=None,
with_spectral_norm=with_spectral_norm,
**kwargs))
if self.with_fc:
self.fc = LinearModule(
fc_in_channels,
fc_out_channels,
bias=True,
act_cfg=out_act_cfg,
with_spectral_norm=with_spectral_norm)
def forward(self, x):
"""Forward Function.
Args:
x (torch.Tensor): Input tensor with shape of (n, c, h, w).
Returns:
torch.Tensor: Output tensor with shape of (n, c, h', w') or (n, c).
"""
input_size = x.size()
# out_convs has two additional ConvModules
num_convs = self.num_convs + 2 * self.with_out_convs
for i in range(num_convs):
x = getattr(self, f'conv{i + 1}')(x)
if self.with_fc:
x = x.view(input_size[0], -1)
x = self.fc(x)
return x
def init_weights(self, pretrained=None):
"""Init weights for models.
Args:
pretrained (str, optional): Path for pretrained weights. If given
None, pretrained weights will not be loaded. Defaults to None.
"""
if isinstance(pretrained, str):
logger = get_root_logger()
load_checkpoint(self, pretrained, strict=False, logger=logger)
elif pretrained is None:
for m in self.modules():
# Here, we only initialize the module with fc layer since the
# conv and norm layers has been intialized in `ConvModule`.
if isinstance(m, nn.Linear):
nn.init.normal_(m.weight.data, 0.0, 0.02)
nn.init.constant_(m.bias.data, 0.0)
else:
raise TypeError('pretrained must be a str or None') | PypiClean |
/DACBench-0.2.0.tar.gz/DACBench-0.2.0/dacbench/instance_sets/cma/Sample CMA Instances.ipynb | ```
import numpy as np
def save_cma_instances(filename, n_instances=100, dim=10, fcn_ids=[12, 11, 2, 23, 15, 8, 17, 20, 1, 16], fcn_names = ["BentCigar", "Discus", "Ellipsoid", "Katsuura", "Rastrigin", "Rosenbrock", "Schaffers", "Schwefel", "Sphere", "Weierstrass"]):
init_locs = list(np.random.randn(n_instances, dim))
init_sigmas = list(np.random.rand(n_instances))
with open(filename, 'a') as f:
id_string="ID,dim,fcn_name,fcn_index,init_sigma,init_loc0,init_loc1,init_loc2,init_loc3,init_loc4,init_loc5,init_loc6,init_loc7,init_loc8,init_loc9\n"
f.write(id_string)
for i in range(n_instances):
inst_string = f"{i},10,{fcn_names[i%10]},{fcn_ids[i%10]},{init_sigmas[i]}"
for j in range(dim):
inst_string += f",{init_locs[i][j]}"
inst_string += "\n"
f.write(inst_string)
save_cma_instances("new_cma_set.csv")
```
| PypiClean |
/Diofant-0.14.0a2.tar.gz/Diofant-0.14.0a2/docs/release/notes-0.7.2.rst | ===========
SymPy 0.7.2
===========
16 Oct 2012
Major Changes
=============
* Python 3 support
- SymPy now supports Python 3. The officially supported versions are 3.2 and
3.3, but 3.1 should also work in a pinch. The Python 3-compatible tarballs
will be provided separately, but it is also possible to download Python 2 code
and convert it manually, via the bin/use2to3 utility. See the README for more.
* PyPy support
- All SymPy tests pass in recent nightlies of PyPy, and so it should have full
support as of the next version after 1.9.
* Combinatorics
- A new module called Combinatorics was added which is the result of a
successful GSoC project. It attempts to replicate the functionality of
Combinatorica and currently has full featured support for Permutations,
Subsets, Gray codes and Prufer codes.
- In another GSoC project, facilities from computational group theory were added
to the combinatorics module, mainly following the book "Handbook of
computational group theory". Currently only permutation groups are
supported. The main functionalities are: basic properties (orbits,
stabilizers, random elements...), the Schreier-Sims algorithm (three
implementations, in increasing speed: with Jerrum's filter, incremental, and
randomized (Monte Carlo)), backtrack searching for subgroups with certain
properties.
* Definite Integration
- A new module called meijerint was added, which is also the result of a
successful GSoC project. It implements a heuristic algorithm for (mainly)
definite integration, similar to the one used in Mathematica. The code is
automatically called by the standard integrate() function. This new algorithm
allows computation of important integral transforms in many interesting cases,
so helper functions for Laplace, Fourier and Mellin transforms were added as
well.
* Random Variables
- A new module called stats was added. This introduces a RandomSymbol type which
can be used to model uncertainty in expressions.
* Matrix Expressions
- A new matrix submodule named expressions was added. This introduces a
MatrixSymbol type which can be used to describe a matrix without explicitly
stating its entries. A new family of expression types were also added:
Transpose, Inverse, Trace, and BlockMatrix. ImmutableMatrix was added so that
explicitly defined matrices could interact with other SymPy expressions.
* Sets
- A number of new sets were added including atomic sets like FiniteSet, Reals,
Naturals, Integers, UniversalSet as well as compound sets like ProductSet and
TransformationSet. Using these building blocks it is possible to build up a
great variety of interesting sets.
* Classical Mechanics
- A physics submodule named machanics was added which assists in formation of
equations of motion for constrained multi-body systems. It is the result of 3
GSoC projects. Some nontrivial systems can be solved, and examples are
provided.
* Quantum Mechanics
- Density operator module has been added. The operator can be initialized with
generic Kets or Qubits. The Density operator can also work with TensorProducts
as arguments. Global methods are also added that compute entropy and fidelity
of states. Trace and partial-trace operations can also be performed on these
density operators.
- To enable partial trace operations a Tr module has been added to the core
library. While the functionality should remain same, this module is likely to
be relocated to an alternate folder in the future. One can currently also use
sympy.core.Tr to work on general trace operations, but this module is what is
needed to work on trace and partial-trace operations on any
sympy.physics.quantum objects.
- The Density operators, Tr and Partial trace functionality was implemented as
part of student participation in GSoC 2012.
- Expanded angular momentum to include coupled-basis states and product-basis
states. Operators can also be treated as acting on the coupled basis (default
behavior) or on one component of the tensor product states. The methods for
coupling and uncoupling these states can work on an arbitrary number of
states. Representing, rewriting and applying states and operators between
bases has been improved.
* Commutative Algebra
- A new module ``agca`` was started which seeks to support computations in
commutative algebra (and eventually algebraic geometry) in the style of
Macaulay2 and Singular. Currently there is support for computing Gröbner
bases of modules over a (generalized) polynomial ring over a field. Based on
this, there are algorithms for various standard problems in commutative
algebra, e.g., computing intersections of submodules, equality tests in
quotient rings, etc...
* Plotting Module
- A new plotting module has been added which uses Matplotlib as its
back-end. The plotting module has functions to plot the following:
* 2D line plots
* 2D parametric plots.
* 2D implicit and region plots.
* 3D surface plots.
* 3D parametric surface plots.
* 3D parametric line plots.
* Differential Geometry
- Thanks to a GSoC project the beginning of a new module covering the theory of
differential geometry was started. It can be imported with
``sympy.diffgeom``. It is based on "Functional Differential Geometry" by Sussman
and Wisdom. Currently implemented are scalar, vector and form fields over
manifolds as well as covariant and other derivatives.
Compatibility breaks
====================
- The KroneckerDelta class was moved from ``sympy/physics/quantum/kronecker.py`` to
``sympy/functions/special/tensor_functions.py``.
- Merged the KroneckerDelta class in ``sympy/physics/secondquant.py`` with the
class above.
- The Dij class in ``sympy/functions/special/tensor_functions.py`` was replaced
with KroneckerDelta.
- The errors raised for invalid ``float`` calls on SymPy objects were changed in
order to emulate more closely the errors raised by the standard library. The
``__float__`` and ``__complex__`` methods of ``Expr`` are concerned with that
change.
- The ``solve()`` function returns empty lists instead of ``None`` objects if no
solutions were found. Idiomatic code of the form ``sol = solve(...); if
sol:...`` will not be affected by this change.
- Piecewise no longer accepts a Set or Interval as a condition. One should
explicitly specify a variable using ``Set().contains(x)`` to obtain a valid
conditional.
- The statistics module has been deprecated in favor of the new stats module.
- ``sympy/galgebra/GA.py``:
* ``set_main()`` is no longer needed
* ``make_symbols()`` is deprecated (use ``sympy.symbols()`` instead)
* the symbols used in this package are no longer broadcast to the main program
- The classes for Infinity, NegativeInfinity, and NaN no longer subclass from
Rational. Creating a Rational with 0 in the denominator will still return
one of these classes, however.
Minor changes
=============
- A new module ``gaussopt`` was added supporting the most basic constructions
from Gaussian optics (ray tracing matrices, geometric rays and Gaussian
beams).
- New classes were added to represent the following special functions:
classical and generalized exponential integrals (Ei, expint), trigonometric
(Si, Ci) and hyperbolic integrals (Shi, Chi), the polylogarithm (polylog)
and the Lerch transcendent (lerchphi). In addition to providing all the
standard sympy functionality (differentiation, numerical evaluation,
rewriting ...), they are supported by both the new meijerint module and the
existing hypergeometric function simplification module.
- An ImmutableMatrix class was created. It has the same interface and
functionality of the old Matrix but is immutable and inherits from Basic.
- A new function in ``geometry.util`` named ``centroid`` was added which will
calculate the centroid of a collection of geometric entities. And the
polygon module now allows triangles to be instantiated from combinations of
side lengths and angles (using keywords sss, asa, sas) and defines utility
functions to convert between degrees and radians.
- In ``ntheory.modular`` there is a function (``solve_congruence``) to solve
congruences such as "What number is 2 mod 3, 3 mod 5 and 2 mod 7?"
- A utility function named ``find_unit`` has been added to physcis.units that
allows one to find units that match a given pattern or contain a given unit.
- There have been some additions and modifications to Expr's methods:
- Although the problem of proving that two expressions are equal is in general
a difficult one (since whatever algorithm is used, there will always be an
expression that will slip through the algorithm) the new method of Expr
named ``equals`` will do its best to answer whether A equals B: A.equals(B)
might given True, False or None.
- coeff now supports a third argument ``n`` (which comes 2nd now, instead of
``right``). This ``n`` is used to indicate the exponent on x which one seeks:
``(x**2 + 3*x + 4).coeff(x, 1)`` -> ``3``. This makes it possible to extract the
constant term from a polynomial: ``(x**2 + 3*x + 4).coeff(x, 0)`` -> ``4``.
- The method ``round`` has been added to round a SymPy expression to a given a
number of decimal places (to the left or right of the decimal point).
- divmod is now supported for all SymPy numbers.
- In the simplify module, the algorithms for denesting of radicals
(sqrtdenest) and simplifying gamma functions (in combsimp) has been
significantly improved.
- The mathematica-similar ``TableForm`` function has been added to the
printing.tableform module so one can easily generate tables with headings.
- The expand API has been updated. ``expand()`` now officially supports
arbitrary ``_eval_expand_hint()`` methods on custom
objects. ``_eval_expand_hint()`` methods are now only responsible for
expanding the top-level expression. All ``deep=True`` related logic happens
in ``expand()`` itself. See the docstring of ``expand()``
for more information and an example.
- Two options were added to ``isympy`` to aid in interactive usage. ``isympy -a``
automatically creates symbols, so that typing something like ``a`` will give
``Symbol('a')``, even if you never typed ``a = Symbol('a')`` or ``var('a')``.
``isympy -i`` automatically wraps integer literals with Integer, so that ``1/2``
will give ``Rational(1, 2)`` instead of ``0.5``. ``isympy -I`` is the same as
``isympy -a -i``. ``isympy -I`` makes isympy act much more like a traditional
interactive computer algebra system. These both require IPython.
- The official documentation at https://docs.sympy.org/ now includes an
extension that automatically hooks the documentation examples in to
`SymPy Live <https://live.sympy.org>`_.
In addition to the more noticeable changes listed above, there have been
numerous smaller additions, improvements and bug fixes in the commits in
this release. See the git log for a full list of all changes. The command
``git log sympy-0.7.1..sympy-0.7.2`` will show all commits made between this
release and the last. You can also see the issues closed since the last
release `here <https://github.com/sympy/sympy/issues?utf8=%E2%9C%93&q=is%3Aissue%20closed%3A%222011-07-29%20..%202012-10-16%22>`_.
| PypiClean |
/DNASpiderWeb-1.1-py3-none-any.whl/dsw/biofilter.py | class DefaultBioFilter(object):
def __init__(self, screen_name):
"""
Initialize the default screen.
:param screen_name: name of screen.
:type screen_name: str
"""
self.screen_name = screen_name
def valid(self, dna_string):
"""
Judge whether the DNA string meets the requirements.
:param dna_string: DNA string to be judged.
:type dna_string: str
:raise: this interface needs to be implemented.
:return: judgement.
:rtype: bool
"""
raise NotImplementedError("This interface \"def valid(dna_string)\" needs to be implemented.")
class LocalBioFilter(DefaultBioFilter):
def __init__(self, observed_length, max_homopolymer_runs=None, gc_range=None, undesired_motifs=None):
"""
Initialize the screen of local biochemical constraints.
:param observed_length: length of the DNA sequence observed in the window.
:type observed_length: int
:param max_homopolymer_runs: maximum homopolymer runs.
:type max_homopolymer_runs: int
:param gc_range: range of GC content.
:type gc_range: list
:param undesired_motifs: undesired DNA motifs.
:type undesired_motifs: list
Example
>>> from dsw import LocalBioFilter
>>> bio_filter = LocalBioFilter(observed_length=8, \
max_homopolymer_runs=2, gc_range=[0.4, 0.6], undesired_motifs=["GC"])
>>> bio_filter.valid(dna_sequence="ACGTACGT")
True
>>> bio_filter.valid(dna_sequence="GCATGCAT")
False
>>> bio_filter.valid(dna_sequence="AAACCGGA")
False
.. notes::
Reference [1] Nick Goldman et al. (2013) Nature
Reference [2] Yaniv Erlich and Dina Zielinski (2017) Science
Reference [3] William H. Press et al. (2020) Proceedings of the National Academy of Sciences
Reference [4] Hannah F Lochel et al. (2021) Nucleic Acids Research
If the maximum homopolymer runs (max_homopolymer_runs) is 1,
"AA", "CC", "GG", "TT" cannot be included in tue valid DNA sequences.
If the range of GC content (gc_range) is [0.4, 0.6],
the GC content of valid DNA sequences must between 40% and 60%.
If "GC" in the undesired DNA motifs (undesired_motifs), "GC" cannot be included in tue valid DNA sequences.
This parameter could contain the restriction enzyme sites or some low compatibility DNA patterns.
"""
super().__init__(screen_name="Local")
if max_homopolymer_runs is not None:
if observed_length < max_homopolymer_runs:
raise ValueError("The parameter \"observed_length\" must "
+ "longer than the parameter \"max_homopolymer_runs\"!")
if undesired_motifs is not None:
for index, undesired_motif in enumerate(undesired_motifs):
if len(undesired_motif) > observed_length:
raise ValueError("The parameter \"observed_length\" must "
+ "longer than the length of any motif in the parameter \"undesired_motifs\"!")
self.observed_length = observed_length
self.max_homopolymer_runs = max_homopolymer_runs
self.gc_range = gc_range
self.undesired_motifs = undesired_motifs
def valid(self, dna_sequence, only_last=True):
"""
Judge whether the DNA sequence meets the local biochemical constraints.
:param dna_sequence: DNA sequence to be judged.
:type dna_sequence: str
:param only_last: only check the DNA sequence of the last observed window.
:type only_last: bool
:return: judgement.
:rtype: bool
.. note::
"only_last" parameter is used to save time.
For most tree-based coding algorithms,
it is not necessary to detect the sub DNA sequences observed in each window from scratch every time.
"""
if only_last:
observed_dna_sequence = dna_sequence[-self.observed_length:]
else:
observed_dna_sequence = dna_sequence
for nucleotide in observed_dna_sequence:
if nucleotide not in "ACGT":
return False
if self.max_homopolymer_runs is not None:
for nucleotide in "ACGT":
if nucleotide * (1 + self.max_homopolymer_runs) in observed_dna_sequence:
return False
if self.undesired_motifs is not None:
for special in self.undesired_motifs:
if special in observed_dna_sequence:
return False
reverse_complement = special.replace("A", "t").replace("C", "g").replace("G", "c").replace("T", "a")
reverse_complement = reverse_complement[::-1].upper()
if reverse_complement in observed_dna_sequence:
return False
if self.gc_range is not None:
if len(observed_dna_sequence) >= self.observed_length:
for index in range(len(observed_dna_sequence) - self.observed_length + 1):
sub_dna_sequence = observed_dna_sequence[index: index + self.observed_length]
gc_count = sub_dna_sequence.count("C") + sub_dna_sequence.count("G")
if gc_count > self.gc_range[1] * self.observed_length:
return False
if gc_count < self.gc_range[0] * self.observed_length:
return False
else:
gc_count = observed_dna_sequence.count("C") + observed_dna_sequence.count("G")
if gc_count > self.gc_range[1] * self.observed_length:
return False
at_count = observed_dna_sequence.count("A") + observed_dna_sequence.count("T")
if at_count > (1 - self.gc_range[0]) * self.observed_length:
return False
return True
def __str__(self):
info = self.screen_name + "\n"
info += "maximum homopolymer runs : " + str(self.max_homopolymer_runs) + "\n"
info += "local GC content range : " + str(self.gc_range[0]) + " <= GC <= " + str(self.gc_range[1]) + "\n"
info += "undesired DNA motifs : " + str(self.undesired_motifs).replace("\"", "") + "\n"
return info | PypiClean |
/JumpScale-core-6.0.0.tar.gz/JumpScale-core-6.0.0/lib/JumpScale/baselib/http_client/httplib2/iri2uri.py | __author__ = "Joe Gregorio (joe@bitworking.org)"
__copyright__ = "Copyright 2006, Joe Gregorio"
__contributors__ = []
__version__ = "1.0.0"
__license__ = "MIT"
__history__ = """
"""
import urlparse
# Convert an IRI to a URI following the rules in RFC 3987
#
# The characters we need to enocde and escape are defined in the spec:
#
# iprivate = %xE000-F8FF / %xF0000-FFFFD / %x100000-10FFFD
# ucschar = %xA0-D7FF / %xF900-FDCF / %xFDF0-FFEF
# / %x10000-1FFFD / %x20000-2FFFD / %x30000-3FFFD
# / %x40000-4FFFD / %x50000-5FFFD / %x60000-6FFFD
# / %x70000-7FFFD / %x80000-8FFFD / %x90000-9FFFD
# / %xA0000-AFFFD / %xB0000-BFFFD / %xC0000-CFFFD
# / %xD0000-DFFFD / %xE1000-EFFFD
escape_range = [
(0xA0, 0xD7FF ),
(0xE000, 0xF8FF ),
(0xF900, 0xFDCF ),
(0xFDF0, 0xFFEF),
(0x10000, 0x1FFFD ),
(0x20000, 0x2FFFD ),
(0x30000, 0x3FFFD),
(0x40000, 0x4FFFD ),
(0x50000, 0x5FFFD ),
(0x60000, 0x6FFFD),
(0x70000, 0x7FFFD ),
(0x80000, 0x8FFFD ),
(0x90000, 0x9FFFD),
(0xA0000, 0xAFFFD ),
(0xB0000, 0xBFFFD ),
(0xC0000, 0xCFFFD),
(0xD0000, 0xDFFFD ),
(0xE1000, 0xEFFFD),
(0xF0000, 0xFFFFD ),
(0x100000, 0x10FFFD)
]
def encode(c):
retval = c
i = ord(c)
for low, high in escape_range:
if i < low:
break
if i >= low and i <= high:
retval = "".join(["%%%2X" % ord(o) for o in c.encode('utf-8')])
break
return retval
def iri2uri(uri):
"""Convert an IRI to a URI. Note that IRIs must be
passed in a unicode strings. That is, do not utf-8 encode
the IRI before passing it into the function."""
if isinstance(uri ,unicode):
(scheme, authority, path, query, fragment) = urlparse.urlsplit(uri)
authority = authority.encode('idna')
# For each character in 'ucschar' or 'iprivate'
# 1. encode as utf-8
# 2. then %-encode each octet of that utf-8
uri = urlparse.urlunsplit((scheme, authority, path, query, fragment))
uri = "".join([encode(c) for c in uri])
return uri
if __name__ == "__main__":
import unittest
class Test(unittest.TestCase):
def test_uris(self):
"""Test that URIs are invariant under the transformation."""
invariant = [
u"ftp://ftp.is.co.za/rfc/rfc1808.txt",
u"http://www.ietf.org/rfc/rfc2396.txt",
u"ldap://[2001:db8::7]/c=GB?objectClass?one",
u"mailto:John.Doe@example.com",
u"news:comp.infosystems.www.servers.unix",
u"tel:+1-816-555-1212",
u"telnet://192.0.2.16:80/",
u"urn:oasis:names:specification:docbook:dtd:xml:4.1.2" ]
for uri in invariant:
self.assertEqual(uri, iri2uri(uri))
def test_iri(self):
""" Test that the right type of escaping is done for each part of the URI."""
self.assertEqual("http://xn--o3h.com/%E2%98%84", iri2uri(u"http://\N{COMET}.com/\N{COMET}"))
self.assertEqual("http://bitworking.org/?fred=%E2%98%84", iri2uri(u"http://bitworking.org/?fred=\N{COMET}"))
self.assertEqual("http://bitworking.org/#%E2%98%84", iri2uri(u"http://bitworking.org/#\N{COMET}"))
self.assertEqual("#%E2%98%84", iri2uri(u"#\N{COMET}"))
self.assertEqual("/fred?bar=%E2%98%9A#%E2%98%84", iri2uri(u"/fred?bar=\N{BLACK LEFT POINTING INDEX}#\N{COMET}"))
self.assertEqual("/fred?bar=%E2%98%9A#%E2%98%84", iri2uri(iri2uri(u"/fred?bar=\N{BLACK LEFT POINTING INDEX}#\N{COMET}")))
self.assertNotEqual("/fred?bar=%E2%98%9A#%E2%98%84", iri2uri(u"/fred?bar=\N{BLACK LEFT POINTING INDEX}#\N{COMET}".encode('utf-8')))
unittest.main() | PypiClean |
/123_object_detection-0.1.tar.gz/123_object_detection-0.1/slim/nets/nasnet/nasnet_utils.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow.compat.v1 as tf
import tf_slim as slim
arg_scope = slim.arg_scope
DATA_FORMAT_NCHW = 'NCHW'
DATA_FORMAT_NHWC = 'NHWC'
INVALID = 'null'
# The cap for tf.clip_by_value, it's hinted from the activation distribution
# that the majority of activation values are in the range [-6, 6].
CLIP_BY_VALUE_CAP = 6
def calc_reduction_layers(num_cells, num_reduction_layers):
"""Figure out what layers should have reductions."""
reduction_layers = []
for pool_num in range(1, num_reduction_layers + 1):
layer_num = (float(pool_num) / (num_reduction_layers + 1)) * num_cells
layer_num = int(layer_num)
reduction_layers.append(layer_num)
return reduction_layers
@slim.add_arg_scope
def get_channel_index(data_format=INVALID):
assert data_format != INVALID
axis = 3 if data_format == 'NHWC' else 1
return axis
@slim.add_arg_scope
def get_channel_dim(shape, data_format=INVALID):
assert data_format != INVALID
assert len(shape) == 4
if data_format == 'NHWC':
return int(shape[3])
elif data_format == 'NCHW':
return int(shape[1])
else:
raise ValueError('Not a valid data_format', data_format)
@slim.add_arg_scope
def global_avg_pool(x, data_format=INVALID):
"""Average pool away the height and width spatial dimensions of x."""
assert data_format != INVALID
assert data_format in ['NHWC', 'NCHW']
assert x.shape.ndims == 4
if data_format == 'NHWC':
return tf.reduce_mean(input_tensor=x, axis=[1, 2])
else:
return tf.reduce_mean(input_tensor=x, axis=[2, 3])
@slim.add_arg_scope
def factorized_reduction(net, output_filters, stride, data_format=INVALID):
"""Reduces the shape of net without information loss due to striding."""
assert data_format != INVALID
if stride == 1:
net = slim.conv2d(net, output_filters, 1, scope='path_conv')
net = slim.batch_norm(net, scope='path_bn')
return net
if data_format == 'NHWC':
stride_spec = [1, stride, stride, 1]
else:
stride_spec = [1, 1, stride, stride]
# Skip path 1
path1 = tf.nn.avg_pool2d(
net,
ksize=[1, 1, 1, 1],
strides=stride_spec,
padding='VALID',
data_format=data_format)
path1 = slim.conv2d(path1, int(output_filters / 2), 1, scope='path1_conv')
# Skip path 2
# First pad with 0's on the right and bottom, then shift the filter to
# include those 0's that were added.
if data_format == 'NHWC':
pad_arr = [[0, 0], [0, 1], [0, 1], [0, 0]]
path2 = tf.pad(tensor=net, paddings=pad_arr)[:, 1:, 1:, :]
concat_axis = 3
else:
pad_arr = [[0, 0], [0, 0], [0, 1], [0, 1]]
path2 = tf.pad(tensor=net, paddings=pad_arr)[:, :, 1:, 1:]
concat_axis = 1
path2 = tf.nn.avg_pool2d(
path2,
ksize=[1, 1, 1, 1],
strides=stride_spec,
padding='VALID',
data_format=data_format)
# If odd number of filters, add an additional one to the second path.
final_filter_size = int(output_filters / 2) + int(output_filters % 2)
path2 = slim.conv2d(path2, final_filter_size, 1, scope='path2_conv')
# Concat and apply BN
final_path = tf.concat(values=[path1, path2], axis=concat_axis)
final_path = slim.batch_norm(final_path, scope='final_path_bn')
return final_path
@slim.add_arg_scope
def drop_path(net, keep_prob, is_training=True):
"""Drops out a whole example hiddenstate with the specified probability."""
if is_training:
batch_size = tf.shape(input=net)[0]
noise_shape = [batch_size, 1, 1, 1]
random_tensor = keep_prob
random_tensor += tf.random.uniform(noise_shape, dtype=tf.float32)
binary_tensor = tf.cast(tf.floor(random_tensor), net.dtype)
keep_prob_inv = tf.cast(1.0 / keep_prob, net.dtype)
net = net * keep_prob_inv * binary_tensor
return net
def _operation_to_filter_shape(operation):
splitted_operation = operation.split('x')
filter_shape = int(splitted_operation[0][-1])
assert filter_shape == int(
splitted_operation[1][0]), 'Rectangular filters not supported.'
return filter_shape
def _operation_to_num_layers(operation):
splitted_operation = operation.split('_')
if 'x' in splitted_operation[-1]:
return 1
return int(splitted_operation[-1])
def _operation_to_info(operation):
"""Takes in operation name and returns meta information.
An example would be 'separable_3x3_4' -> (3, 4).
Args:
operation: String that corresponds to convolution operation.
Returns:
Tuple of (filter shape, num layers).
"""
num_layers = _operation_to_num_layers(operation)
filter_shape = _operation_to_filter_shape(operation)
return num_layers, filter_shape
def _stacked_separable_conv(net, stride, operation, filter_size,
use_bounded_activation):
"""Takes in an operations and parses it to the correct sep operation."""
num_layers, kernel_size = _operation_to_info(operation)
activation_fn = tf.nn.relu6 if use_bounded_activation else tf.nn.relu
for layer_num in range(num_layers - 1):
net = activation_fn(net)
net = slim.separable_conv2d(
net,
filter_size,
kernel_size,
depth_multiplier=1,
scope='separable_{0}x{0}_{1}'.format(kernel_size, layer_num + 1),
stride=stride)
net = slim.batch_norm(
net, scope='bn_sep_{0}x{0}_{1}'.format(kernel_size, layer_num + 1))
stride = 1
net = activation_fn(net)
net = slim.separable_conv2d(
net,
filter_size,
kernel_size,
depth_multiplier=1,
scope='separable_{0}x{0}_{1}'.format(kernel_size, num_layers),
stride=stride)
net = slim.batch_norm(
net, scope='bn_sep_{0}x{0}_{1}'.format(kernel_size, num_layers))
return net
def _operation_to_pooling_type(operation):
"""Takes in the operation string and returns the pooling type."""
splitted_operation = operation.split('_')
return splitted_operation[0]
def _operation_to_pooling_shape(operation):
"""Takes in the operation string and returns the pooling kernel shape."""
splitted_operation = operation.split('_')
shape = splitted_operation[-1]
assert 'x' in shape
filter_height, filter_width = shape.split('x')
assert filter_height == filter_width
return int(filter_height)
def _operation_to_pooling_info(operation):
"""Parses the pooling operation string to return its type and shape."""
pooling_type = _operation_to_pooling_type(operation)
pooling_shape = _operation_to_pooling_shape(operation)
return pooling_type, pooling_shape
def _pooling(net, stride, operation, use_bounded_activation):
"""Parses operation and performs the correct pooling operation on net."""
padding = 'SAME'
pooling_type, pooling_shape = _operation_to_pooling_info(operation)
if use_bounded_activation:
net = tf.nn.relu6(net)
if pooling_type == 'avg':
net = slim.avg_pool2d(net, pooling_shape, stride=stride, padding=padding)
elif pooling_type == 'max':
net = slim.max_pool2d(net, pooling_shape, stride=stride, padding=padding)
else:
raise NotImplementedError('Unimplemented pooling type: ', pooling_type)
return net
class NasNetABaseCell(object):
"""NASNet Cell class that is used as a 'layer' in image architectures.
Args:
num_conv_filters: The number of filters for each convolution operation.
operations: List of operations that are performed in the NASNet Cell in
order.
used_hiddenstates: Binary array that signals if the hiddenstate was used
within the cell. This is used to determine what outputs of the cell
should be concatenated together.
hiddenstate_indices: Determines what hiddenstates should be combined
together with the specified operations to create the NASNet cell.
use_bounded_activation: Whether or not to use bounded activations. Bounded
activations better lend themselves to quantized inference.
"""
def __init__(self, num_conv_filters, operations, used_hiddenstates,
hiddenstate_indices, drop_path_keep_prob, total_num_cells,
total_training_steps, use_bounded_activation=False):
self._num_conv_filters = num_conv_filters
self._operations = operations
self._used_hiddenstates = used_hiddenstates
self._hiddenstate_indices = hiddenstate_indices
self._drop_path_keep_prob = drop_path_keep_prob
self._total_num_cells = total_num_cells
self._total_training_steps = total_training_steps
self._use_bounded_activation = use_bounded_activation
def _reduce_prev_layer(self, prev_layer, curr_layer):
"""Matches dimension of prev_layer to the curr_layer."""
# Set the prev layer to the current layer if it is none
if prev_layer is None:
return curr_layer
curr_num_filters = self._filter_size
prev_num_filters = get_channel_dim(prev_layer.shape)
curr_filter_shape = int(curr_layer.shape[2])
prev_filter_shape = int(prev_layer.shape[2])
activation_fn = tf.nn.relu6 if self._use_bounded_activation else tf.nn.relu
if curr_filter_shape != prev_filter_shape:
prev_layer = activation_fn(prev_layer)
prev_layer = factorized_reduction(
prev_layer, curr_num_filters, stride=2)
elif curr_num_filters != prev_num_filters:
prev_layer = activation_fn(prev_layer)
prev_layer = slim.conv2d(
prev_layer, curr_num_filters, 1, scope='prev_1x1')
prev_layer = slim.batch_norm(prev_layer, scope='prev_bn')
return prev_layer
def _cell_base(self, net, prev_layer):
"""Runs the beginning of the conv cell before the predicted ops are run."""
num_filters = self._filter_size
# Check to be sure prev layer stuff is setup correctly
prev_layer = self._reduce_prev_layer(prev_layer, net)
net = tf.nn.relu6(net) if self._use_bounded_activation else tf.nn.relu(net)
net = slim.conv2d(net, num_filters, 1, scope='1x1')
net = slim.batch_norm(net, scope='beginning_bn')
# num_or_size_splits=1
net = [net]
net.append(prev_layer)
return net
def __call__(self, net, scope=None, filter_scaling=1, stride=1,
prev_layer=None, cell_num=-1, current_step=None):
"""Runs the conv cell."""
self._cell_num = cell_num
self._filter_scaling = filter_scaling
self._filter_size = int(self._num_conv_filters * filter_scaling)
i = 0
with tf.variable_scope(scope):
net = self._cell_base(net, prev_layer)
for iteration in range(5):
with tf.variable_scope('comb_iter_{}'.format(iteration)):
left_hiddenstate_idx, right_hiddenstate_idx = (
self._hiddenstate_indices[i],
self._hiddenstate_indices[i + 1])
original_input_left = left_hiddenstate_idx < 2
original_input_right = right_hiddenstate_idx < 2
h1 = net[left_hiddenstate_idx]
h2 = net[right_hiddenstate_idx]
operation_left = self._operations[i]
operation_right = self._operations[i+1]
i += 2
# Apply conv operations
with tf.variable_scope('left'):
h1 = self._apply_conv_operation(h1, operation_left,
stride, original_input_left,
current_step)
with tf.variable_scope('right'):
h2 = self._apply_conv_operation(h2, operation_right,
stride, original_input_right,
current_step)
# Combine hidden states using 'add'.
with tf.variable_scope('combine'):
h = h1 + h2
if self._use_bounded_activation:
h = tf.nn.relu6(h)
# Add hiddenstate to the list of hiddenstates we can choose from
net.append(h)
with tf.variable_scope('cell_output'):
net = self._combine_unused_states(net)
return net
def _apply_conv_operation(self, net, operation,
stride, is_from_original_input, current_step):
"""Applies the predicted conv operation to net."""
# Dont stride if this is not one of the original hiddenstates
if stride > 1 and not is_from_original_input:
stride = 1
input_filters = get_channel_dim(net.shape)
filter_size = self._filter_size
if 'separable' in operation:
net = _stacked_separable_conv(net, stride, operation, filter_size,
self._use_bounded_activation)
if self._use_bounded_activation:
net = tf.clip_by_value(net, -CLIP_BY_VALUE_CAP, CLIP_BY_VALUE_CAP)
elif operation in ['none']:
if self._use_bounded_activation:
net = tf.nn.relu6(net)
# Check if a stride is needed, then use a strided 1x1 here
if stride > 1 or (input_filters != filter_size):
if not self._use_bounded_activation:
net = tf.nn.relu(net)
net = slim.conv2d(net, filter_size, 1, stride=stride, scope='1x1')
net = slim.batch_norm(net, scope='bn_1')
if self._use_bounded_activation:
net = tf.clip_by_value(net, -CLIP_BY_VALUE_CAP, CLIP_BY_VALUE_CAP)
elif 'pool' in operation:
net = _pooling(net, stride, operation, self._use_bounded_activation)
if input_filters != filter_size:
net = slim.conv2d(net, filter_size, 1, stride=1, scope='1x1')
net = slim.batch_norm(net, scope='bn_1')
if self._use_bounded_activation:
net = tf.clip_by_value(net, -CLIP_BY_VALUE_CAP, CLIP_BY_VALUE_CAP)
else:
raise ValueError('Unimplemented operation', operation)
if operation != 'none':
net = self._apply_drop_path(net, current_step=current_step)
return net
def _combine_unused_states(self, net):
"""Concatenate the unused hidden states of the cell."""
used_hiddenstates = self._used_hiddenstates
final_height = int(net[-1].shape[2])
final_num_filters = get_channel_dim(net[-1].shape)
assert len(used_hiddenstates) == len(net)
for idx, used_h in enumerate(used_hiddenstates):
curr_height = int(net[idx].shape[2])
curr_num_filters = get_channel_dim(net[idx].shape)
# Determine if a reduction should be applied to make the number of
# filters match.
should_reduce = final_num_filters != curr_num_filters
should_reduce = (final_height != curr_height) or should_reduce
should_reduce = should_reduce and not used_h
if should_reduce:
stride = 2 if final_height != curr_height else 1
with tf.variable_scope('reduction_{}'.format(idx)):
net[idx] = factorized_reduction(
net[idx], final_num_filters, stride)
states_to_combine = (
[h for h, is_used in zip(net, used_hiddenstates) if not is_used])
# Return the concat of all the states
concat_axis = get_channel_index()
net = tf.concat(values=states_to_combine, axis=concat_axis)
return net
@slim.add_arg_scope # No public API. For internal use only.
def _apply_drop_path(self, net, current_step=None,
use_summaries=False, drop_connect_version='v3'):
"""Apply drop_path regularization.
Args:
net: the Tensor that gets drop_path regularization applied.
current_step: a float32 Tensor with the current global_step value,
to be divided by hparams.total_training_steps. Usually None, which
defaults to tf.train.get_or_create_global_step() properly casted.
use_summaries: a Python boolean. If set to False, no summaries are output.
drop_connect_version: one of 'v1', 'v2', 'v3', controlling whether
the dropout rate is scaled by current_step (v1), layer (v2), or
both (v3, the default).
Returns:
The dropped-out value of `net`.
"""
drop_path_keep_prob = self._drop_path_keep_prob
if drop_path_keep_prob < 1.0:
assert drop_connect_version in ['v1', 'v2', 'v3']
if drop_connect_version in ['v2', 'v3']:
# Scale keep prob by layer number
assert self._cell_num != -1
# The added 2 is for the reduction cells
num_cells = self._total_num_cells
layer_ratio = (self._cell_num + 1)/float(num_cells)
if use_summaries:
with tf.device('/cpu:0'):
tf.summary.scalar('layer_ratio', layer_ratio)
drop_path_keep_prob = 1 - layer_ratio * (1 - drop_path_keep_prob)
if drop_connect_version in ['v1', 'v3']:
# Decrease the keep probability over time
if current_step is None:
current_step = tf.train.get_or_create_global_step()
current_step = tf.cast(current_step, tf.float32)
drop_path_burn_in_steps = self._total_training_steps
current_ratio = current_step / drop_path_burn_in_steps
current_ratio = tf.minimum(1.0, current_ratio)
if use_summaries:
with tf.device('/cpu:0'):
tf.summary.scalar('current_ratio', current_ratio)
drop_path_keep_prob = (1 - current_ratio * (1 - drop_path_keep_prob))
if use_summaries:
with tf.device('/cpu:0'):
tf.summary.scalar('drop_path_keep_prob', drop_path_keep_prob)
net = drop_path(net, drop_path_keep_prob)
return net
class NasNetANormalCell(NasNetABaseCell):
"""NASNetA Normal Cell."""
def __init__(self, num_conv_filters, drop_path_keep_prob, total_num_cells,
total_training_steps, use_bounded_activation=False):
operations = ['separable_5x5_2',
'separable_3x3_2',
'separable_5x5_2',
'separable_3x3_2',
'avg_pool_3x3',
'none',
'avg_pool_3x3',
'avg_pool_3x3',
'separable_3x3_2',
'none']
used_hiddenstates = [1, 0, 0, 0, 0, 0, 0]
hiddenstate_indices = [0, 1, 1, 1, 0, 1, 1, 1, 0, 0]
super(NasNetANormalCell, self).__init__(num_conv_filters, operations,
used_hiddenstates,
hiddenstate_indices,
drop_path_keep_prob,
total_num_cells,
total_training_steps,
use_bounded_activation)
class NasNetAReductionCell(NasNetABaseCell):
"""NASNetA Reduction Cell."""
def __init__(self, num_conv_filters, drop_path_keep_prob, total_num_cells,
total_training_steps, use_bounded_activation=False):
operations = ['separable_5x5_2',
'separable_7x7_2',
'max_pool_3x3',
'separable_7x7_2',
'avg_pool_3x3',
'separable_5x5_2',
'none',
'avg_pool_3x3',
'separable_3x3_2',
'max_pool_3x3']
used_hiddenstates = [1, 1, 1, 0, 0, 0, 0]
hiddenstate_indices = [0, 1, 0, 1, 0, 1, 3, 2, 2, 0]
super(NasNetAReductionCell, self).__init__(num_conv_filters, operations,
used_hiddenstates,
hiddenstate_indices,
drop_path_keep_prob,
total_num_cells,
total_training_steps,
use_bounded_activation) | PypiClean |
/EggBasket-0.6.1b.tar.bz2/EggBasket-0.6.1b/README.txt | EggBasket
=========
:Author: Christopher Arndt
:Version: 0.6.1b
:Date: 2008-07-04
:Description: A simple, lightweight Python Package Index (aka Cheeseshop) clone.
.. contents::
:depth: 1
Overview
--------
EggBasket_ is a web application which provides a service similar and compatible
to the `Python Package Index`_ (aka Cheeseshop). It allows you to maintain your
own local repository of Python packages required by your installations.
It is implemented using the TurboGears_ web framework, Genshi_ and SQLAlchemy_.
.. warning::
This is beta-stage software. All the basic operations necessary
to support a setuptools-based infrastructure are there, but some
convenience features are missing and the software has not been tested
extensively. **Use at your own risk!**
Features
--------
* Can be used by setuptools/easy_install as the package index and repository.
* Supports the distutils ``upload`` protocol.
* Has a simple, role-based permission system to grant/deny access to the
functions of the server (for example package uploads) to groups of users.
* Requires only SQLite as the database system (included with Python 2.5).
* Is able to read and display meta data from the following distribution package
formats (source and binary):
``.egg``, ``.tar``, ``.tar.bz2``, ``.tar.gz``, ``.tgz``, ``.zip``
* Any other file format can be configured to be listed under the distribution
files for a package (by default this includes ``.exe`` and ``.rpm`` and
``.tar.Z`` files in addition to the filetypes listed above).
* Can be run without any configuration by just initializing the database and
starting the server from within a directory containing package directories
(see "Usage").
Todo
----
During beta phase:
* Add support for MD5 check sums.
* Add more error and sanity checks to the upload handling.
* Add pagination to the main package list.
Post 1.0 release:
* Cache package listings and meta data.
* Improve DBmechanic-based admin interface for adding users and groups and
setting configuration values (currently disabled by default).
* Add support for GPG signatures.
Acknowledgments
---------------
This application is a re-implementation (almost no shared code) of the
haufe.eggserver_ Grok application with some improvements.
Installation
------------
To install EggBasket_ from the Cheeseshop_ use `easy_install`_::
[sudo] easy_install EggBasket
This requires the setuptools_ package to be installed. If you have not done so
already, download the `ez_setup.py`_ script and run it to install setuptools.
Usage
-----
EggBasket server
~~~~~~~~~~~~~~~~
* Your packages should all reside under a common root directory, with a
sub-directory for each package with the same base name as the distribution.
The sub-directories should each contain the egg files and source archives for
all available versions of the package. The package directories will be created
by the application when using the upload command (see below).
* Open a terminal, change to the directory which contains the packages and, if
you are haven't already done so, initialize the database with::
eggbasket-server --init [<config file>]
* Start the application server with::
eggbasket-server [<config file>]
You can also set the location of the package root directory in the
configuration with the ``eggbasket.package_root`` setting and start the
server anywhere you want.
If no configuration file is specified on the command line, the default
configuration file included in the egg will be used. The default
configuration file can also be found in the source distribution and be
adapted for your environment.
The server either needs write permissions in the directory where it is
started, or you need to change the path of the database and the access log in
the configuration so they can be written by the server. Of course, package
uploads will also only work if the server has the permissions to create any
missing package directories or write in existing ones.
* To stop the server just hit ``Control-C`` in the terminal or kill the process.
* You can look at the package index with your web browser by opening the URL
``http://localhost:3442/``. The default port ``3442`` can be changed by
setting the ``server.socket_port`` option in the configuration file.
Using EggBasket with ``distutils`` & ``easy_install``
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
* You can instruct easy_install_ to search & download packages from your
package repository by specifying the URL to your server with the ``-i``
option. Example::
easy_install -i http://localhost:3442/ PACKAGE_NAME
* Additionally, it might be necessary to restrict the hosts from which
easy_install will download to your EggBasket server with the ``-H`` option.
Example::
easy_install -H localhost:3442 -i http::/localhost:3442/ PACKAGE_NAME
* You can also set the ``eggbasket.rewrite_download_url`` resp.
``eggbasket.rewrite_homepage_url`` settings in the configuration to ``True``
and EggBasket will replace the download resp. homepage URL of each package
in the package meta data view with the URL of the package distribution files
listing on the EggBasket server.
* You can upload a package to your repository with the distutils ``upload``
command, for example::
python setup.py bdist_egg upload -r http://localhost:3442/upload
This command will ask for your username and password on the server. You can
store these and the repository URL in your ``.pypirc`` file. See the
`distutils documentation`_ for more information.
* Of course you can always just copy package distribution files manually in the
filesystem to your repository or upload them to the appropriate place with
``scp`` etc. The application will find and list new files without the need to
"register" them as is necessary with the original PyPI.
Permissions
~~~~~~~~~~~
EggBasket uses a simple, role-based permission system to grant/restrict access
to the functions of the server. Here is a list of the defined permissions and
their meaning:
* ``viewpkgs`` - User can view the list of all packages
* ``viewfiles`` - User can view the list of distribution files for a package.
* ``viewinfo`` - User can view the meta data for a package distribution file.
* ``download`` - User can download a package distribution file.
* ``upload`` - User can upload a package distribution file.
* ``overwrite`` - User can overwrite and existing package distribution file.
* ``delete`` - User can delete a package distribution file through the web
interface.
You can let EggBasket create an initial admin user, groups and permissions in
the database by giving the ``--init`` option to the ``eggbasket-server``
command::
eggbasket-server --init [<config file>]
This will create the following objects and relations in the database:
* The above listed permissions.
* The following groups (with permissions in brackets):
* anonymous (viewpkgs, viewfiles, viewinfo, download)
* authenticated (viewpkgs, viewfiles, viewinfo, download)
* maintainer (upload, overwrite, delete)
* admin
* A user with user name/password "admin", belonging to the groups "maintainer"
and "admin".
The groups "anonymous" and "authenticated" are special groups to which all
anonymous (i.e. not logged in) resp. all authenticated (logged in) users belong
automatically.
With the default permission setup, uploading through the server is restricted
to users that are members of a group that has the "upload" permission. The
configuration page can only be accessed by members of the "admin" group.
Everything else can be accessed all users, whether authenticated or not.
Please note that if you want to give a certain permission to all users, whether
logged in or not, you need to give this permission to both the "anonymous" AND
the "authenticated" group. This is what the standard permission setup already
does for all permissions except "upload".
See the TurboGears documentation on Identity_ for background information.
.. _turbogears: http://www.turbogears.org/
.. _genshi: http://genshi.edgewall.org/
.. _sqlalchemy: http://www.sqlalchemy.org/
.. _haufe.eggserver: http://cheeseshop.python.org/pypi/haufe.eggserver
.. _eggbasket: http://chrisarndt.de/projects/eggbasket/
.. _cheeseshop:
.. _python package index: http://cheeseshop.python.org/pypi/
.. _setuptools: http://peak.telecommunity.com/DevCenter/setuptools
.. _easy_install: http://peak.telecommunity.com/DevCenter/EasyInstall
.. _ez_setup.py: http://peak.telecommunity.com/dist/ez_setup.py
.. _distutils documentation: http://docs.python.org/dist/package-upload.html
.. _identity: http://docs.turbogears.org/1.0/GettingStartedWithIdentity
.. include:: CHANGELOG.txt
| PypiClean |
/BuildStream-external-0.30.0.tar.gz/BuildStream-external-0.30.0/bst_external/elements/oci.py | import itertools
import stat
import os
import tempfile
import tarfile
import hashlib
import gzip
import json
import codecs
import shutil
import filecmp
from contextlib import contextmanager, ExitStack
from collections.abc import Mapping
from buildstream import Element, ElementError, Scope
class blob:
def __init__(self, root, media_type=None, text=False, mode='oci', legacy_config=None):
self.root = root
self.descriptor = None
self.media_type = media_type
self.text = text
self.mode = mode
self.filename = None
self.legacy_config = {}
if legacy_config:
self.legacy_config.update(legacy_config)
self.legacy_id = None
@contextmanager
def create(self):
with tempfile.NamedTemporaryFile(mode='w+b', dir=self.root, delete=False) as f:
filename = f.name
try:
if self.text:
yield codecs.getwriter('utf-8')(f)
else:
yield f
self.descriptor = {}
if self.media_type:
self.descriptor['mediaType'] = self.media_type
f.seek(0, 2)
self.descriptor['size'] = f.tell()
f.seek(0)
h = hashlib.sha256()
while True:
data = f.read(16*1204)
if len(data) == 0:
break
h.update(data)
if self.mode == 'oci':
self.descriptor['digest'] = 'sha256:{}'.format(h.hexdigest())
os.makedirs(os.path.join(self.root, 'blobs', 'sha256'), exist_ok=True)
self.filename = os.path.join(self.root, 'blobs', 'sha256', h.hexdigest())
else:
assert self.mode == 'docker'
if self.media_type.endswith('+json'):
self.filename = os.path.join(self.root, '{}.json'.format(h.hexdigest()))
self.descriptor = '{}.json'.format(h.hexdigest())
elif self.media_type.startswith('application/vnd.oci.image.layer.v1.tar'):
blobdir = os.path.join(self.root, h.hexdigest())
os.makedirs(blobdir)
self.filename = os.path.join(blobdir, 'layer.tar')
with open(os.path.join(blobdir, 'VERSION'), 'w') as f:
f.write('1.0')
self.legacy_config['id'] = h.hexdigest()
self.legacy_id = h.hexdigest()
with open(os.path.join(blobdir, 'json'), 'w', encoding='utf-8') as f:
json.dump(self.legacy_config, f)
self.descriptor = os.path.join(h.hexdigest(), 'layer.tar')
else:
assert False
os.rename(filename, self.filename)
except:
try:
os.unlink(filename)
except:
pass
raise
def safe_path(path):
norm = os.path.normpath(path)
if os.path.isabs(norm):
return os.path.relpath(norm, '/')
else:
return norm
class OciElement(Element):
BST_ARTIFACT_VERSION = 1
def configure(self, node):
self.node_validate(node, [
'mode', 'gzip',
'images', 'annotations'
])
self.mode = self.node_get_member(node, str, 'mode', 'oci')
if self.mode not in ['docker', 'oci']:
raise ElementError('{}: Mode must be "oci" or "docker"'.format(self.node_provenance(node, 'mode')))
self.gzip = self.node_get_member(node, bool, 'gzip', self.mode == 'oci')
if 'annotations' not in node:
self.annotations = None
else:
self.annotations = {}
annotations = self.node_get_member(node, Mapping, 'images')
for k, _ in self.node_items(annotations):
v = self.node_subst_member(annotations, k)
self.annotations[k] = v
self.images = []
for image in self.node_get_member(node, list, 'images'):
self.node_validate(image, [
'parent', 'layer',
'architecture', 'variant',
'os', 'os.version', 'os.features',
'author', 'comment', 'config',
'annotations'
] + (['tags'] if self.mode == 'docker' else []))
parent = self.node_get_member(image, Mapping, 'parent', None)
image_value = {}
if parent:
self.node_validate(parent, [
'element', 'image'
])
parent = {
'element': self.node_get_member(parent, str, 'element'),
'image': self.node_get_member(parent, int, 'image', 0),
}
image_value['parent'] = parent
if 'layer' in image:
image_value['layer'] = self.node_subst_list(image, 'layer')
image_value['architecture'] = \
self.node_subst_member(image, 'architecture')
if 'tags' in image:
image_value['tags'] = \
self.node_subst_list(image, 'tags')
image_value['os'] = self.node_subst_member(image, 'os')
if 'os.version' in image:
image_value['os.version'] = \
self.node_subst_member(image, 'os.version')
if 'os.features' in image:
image_value['os.features'] = \
self.node_subst_list(image, 'os.features')
if 'os.features' in image:
image_value['variant'] = \
self.node_subst_member(image, 'variant')
if 'author' in image:
image_value['author'] = \
self.node_subst_member(image, 'author')
if 'comment' in image:
image_value['comment'] = \
self.node_subst_member(image, 'comment')
if 'config' in image:
config = self.node_get_member(image, Mapping, 'config')
common_config = [
'User', 'ExposedPorts',
'Env', 'Entrypoint',
'Cmd', 'Volumes',
'WorkingDir'
]
docker_config = [
'Memory', 'MemorySwap',
'CpuShares', 'Healthcheck',
]
oci_config = [
'Labels', 'StopSignal'
]
self.node_validate(config, common_config + (docker_config if self.mode == 'docker' else oci_config))
config_value = {}
for member in ['User', 'WorkingDir', 'StopSignal']:
if member in config:
config_value[member] = \
self.node_subst_member(config, member)
for member in ['Memory', 'MemorySwap', 'CpuShares']:
if member in config:
config_value[member] = \
int(self.node_subst_member(config, member))
for member in ['ExposedPorts', 'Volumes',
'Env', 'Entrypoint', 'Cmd']:
if member in config:
config_value[member] = \
self.node_subst_list(config, member)
if 'Labels' in config:
labels = self.node_get_member(config, Mapping, 'Labels')
config_value['Labels'] = {}
for k, v in self.node_items(labels):
config_value['Labels'][k] = v
if 'Healthcheck' in config:
healthcheck = self.node_get_member(config, Mapping, 'Healthcheck')
self.node_validate(healthcheck, [
'Test', 'Interval',
'Timeout', 'Retries'
])
config_value['Healthcheck'] = {}
if 'Test' in healthcheck:
config_value['Healthcheck']['Test'] = self.node_subst_list(healthcheck, 'Test')
for member in ['Interval', 'Timeout', 'Retries']:
if member in healthcheck:
config_value['Healthcheck'][member] = int(self.node_subst_member(healthcheck, member))
image_value['config'] = config_value
if 'annotations' in image:
image_value['annotations'] = {}
annotations = \
self.node_get_member(image, Mapping, 'annotations')
for k, _ in self.node_items(annotations):
v = self.node_subst_member(annotations, k)
image_value['annotations'][k] = v
self.images.append(image_value)
def preflight(self):
pass
def get_unique_key(self):
return {'annotations': self.annotations,
'images': self.images,
'gzip': self.gzip}
def configure_sandbox(self, sandbox):
pass
def stage(self, sandbox):
pass
def _build_image(self, sandbox, image, root, output):
parent = os.path.join(root, 'parent')
parent_checkout = os.path.join(root, 'parent_checkout')
if 'layer' in image:
if os.path.exists(parent_checkout):
shutil.rmtree(parent_checkout)
os.makedirs(os.path.join(parent_checkout))
layer_descs = []
layer_files = []
diff_ids = []
history = None
legacy_parent = None
config = {}
config['created'] = '2011-11-11T11:11:11Z'
if 'author' in image:
config['author'] = image['author']
config['architecture'] = image['architecture']
config['os'] = image['os']
if 'config' in image:
config['config'] = {}
for k, v in image['config'].items():
if k in ['ExposedPorts', 'Volumes']:
config['config'][k] = {}
for value in v:
config['config'][k][value] = {}
else:
config['config'][k] = v
if 'parent' in image:
if os.path.exists(parent):
shutil.rmtree(parent)
parent_dep = self.search(Scope.BUILD, image['parent']['element'])
if not parent_dep:
raise ElementError('{}: Element not in dependencies: {}'.format(self, image['parent']['element']))
parent_dep.stage_dependency_artifacts(sandbox, Scope.RUN,
path='parent')
if not os.path.exists(os.path.join(parent, 'index.json')):
with open(os.path.join(parent, 'manifest.json'), 'r', encoding='utf-8') as f:
parent_index = json.load(f)
parent_image = parent_index[image['parent']['image']]
layers = parent_image['Layers']
with open(os.path.join(parent, safe_path(parent_image['Config'])), 'r', encoding='utf-8') as f:
image_config = json.load(f)
diff_ids = image_config['rootfs']['diff_ids']
if 'history' in image_config:
history = image_config['history']
for i, layer in enumerate(layers):
_, diff_id = diff_ids[i].split(':', 1)
with open(os.path.join(parent, safe_path(layer)), 'rb') as origblob:
if self.gzip:
targz_blob = blob(output, media_type='application/vnd.oci.image.layer.v1.tar+gzip', mode=self.mode)
with targz_blob.create() as gzipfile:
with gzip.GzipFile(filename=diff_id, fileobj=gzipfile,
mode='wb', mtime=1320937200) as gz:
shutil.copyfileobj(origblob, gz)
layer_descs.append(targz_blob.descriptor)
layer_files.append(targz_blob.filename)
legacy_parent = tar_blob.legacy_id
else:
legacy_config = {
'os': image['os']
}
if legacy_parent:
legacy_config['parent'] = legacy_parent
tar_blob = blob(output, media_type='application/vnd.oci.image.layer.v1.tar', mode=self.mode)
with tar_blob.create() as newfile:
shutil.copyfileobj(origblob, newfile)
layer_descs.append(tar_blob.descriptor)
layer_files.append(tar_blob.filename)
legacy_parent = tar_blob.legacy_id
else:
with open(os.path.join(parent, 'index.json'), 'r', encoding='utf-8') as f:
parent_index = json.load(f)
parent_image_desc = \
parent_index['manifests'][image['parent']['image']]
algo, h = parent_image_desc['digest'].split(':', 1)
with open(os.path.join(parent, 'blobs', safe_path(algo), safe_path(h)), 'r', encoding='utf-8') as f:
image_manifest = json.load(f)
algo, h = image_manifest['config']['digest'].split(':', 1)
with open(os.path.join(parent, 'blobs', safe_path(algo), safe_path(h)), 'r', encoding='utf-8') as f:
image_config = json.load(f)
diff_ids = image_config['rootfs']['diff_ids']
if 'history' in image_config:
history = image_config['history']
for i, layer in enumerate(image_manifest['layers']):
_, diff_id = diff_ids[i].split(':', 1)
algo, h = layer['digest'].split(':', 1)
origfile = os.path.join(parent, 'blobs', safe_path(algo), safe_path(h))
with ExitStack() as e:
if 'layer' not in image and i+1 == len(image_manifest['layers']):
# The case were we do not add a layer, the last imported layer has to be fully reconfigured
legacy_config = {}
legacy_config.update(config)
if legacy_parent:
legacy_config['parent'] = legacy_parent
else:
legacy_config = {
'os': image['os']
}
if legacy_parent:
legacy_config['parent'] = legacy_parent
if self.gzip:
output_blob = blob(output, media_type='application/vnd.oci.image.layer.v1.tar+gzip', mode=self.mode)
else:
output_blob = blob(output, media_type='application/vnd.oci.image.layer.v1.tar', mode=self.mode, legacy_config=legacy_config)
outp = e.enter_context(output_blob.create())
inp = e.enter_context(open(origfile, 'rb'))
if layer['mediaType'].endswith('+gzip'):
if self.gzip:
shutil.copyfileobj(inp, outp)
else:
gz = e.enter_context(gzip.open(filename=inp, mode='rb'))
shutil.copyfileobj(gz, outp)
else:
if self.gzip:
gz = e.enter_context(gzip.GzipFile(filename=diff_id, fileobj=outp,
mode='wb', mtime=1320937200))
shutil.copyfileobj(inp, gz)
else:
shutil.copyfileobj(inp, outp)
layer_descs.append(output_blob.descriptor)
layer_files.append(output_blob.filename)
legacy_parent = output_blob.legacy_id
if 'parent' in image and 'layer' in image:
unpacked = False
if isinstance(parent_dep, OciElement):
# Here we read the parent configuration to checkout
# the artifact which is much faster than unpacking the tar
# files.
layers = []
parent_image = image['parent']['image']
for layer in parent_dep.images[parent_image]['layer']:
layer_dep = parent_dep.search(Scope.BUILD, layer)
if not layer_dep:
raise ElementError('{}: Element not in dependencies: {}'.format(parent_dep, layer))
# We need to verify dependencies. If not in current
# element's dependencies, then we cannnot safely assume
# it is cached. Parent could be cached while its
# dependencies either removed or not pulled.
if layer_dep != self.search(Scope.BUILD, layer):
self.warn('In order to optimize building of {}, you should add {} as build dependency'.format(self.name, layer))
layers = None
break
else:
layers.append(layer_dep)
if layers is not None:
with self.timed_activity('Checking out layer from {}'.format(parent_dep.name)):
for layer_dep in layers:
layer_dep.stage_dependency_artifacts(sandbox, Scope.RUN,
path='parent_checkout')
unpacked = True
if not unpacked:
for layer in layer_files:
if self.gzip:
mode='r:gz'
else:
mode='r:'
with self.timed_activity('Decompressing layer {}'.format(layer)):
with tarfile.open(layer, mode=mode) as t:
members = []
for info in t.getmembers():
if '/../' in info.name:
continue
if info.name.startswith('../'):
continue
dirname, basename = os.path.split(info.name)
if basename == '.wh..wh..opq':
for entry in os.listdir(os.path.join(parent_checkout, dirname)):
full_entry = os.path.join(parent_checkout, dirname, entry)
if os.path.islink(full_entry) or not os.path.isdir(full_entry):
os.unlink(full_entry)
else:
shutil.rmtree(full_entry)
elif basename.startswith('.wh.'):
full_entry = os.path.join(parent_checkout, dirname, basename[4:])
if os.path.islink(full_entry) or not os.path.isdir(full_entry):
os.unlink(full_entry)
else:
shutil.rmtree(full_entry)
else:
members.append(info)
t.extractall(path=parent_checkout, members=members)
legacy_config = {}
legacy_config.update(config)
if legacy_parent:
legacy_config['parent'] = legacy_parent
if 'layer' in image:
deps = []
for name in image['layer']:
dep = self.search(Scope.BUILD, name)
dep.stage_dependency_artifacts(sandbox, Scope.RUN, path='layer')
layer = os.path.join(root, 'layer')
with self.timed_activity('Transforming into layer'):
for root, dirs, files in os.walk(parent_checkout):
for f in itertools.chain(files, dirs):
rel = os.path.relpath(os.path.join(root, f), parent_checkout)
if not os.path.lexists(os.path.join(layer, rel)) \
and os.path.lexists(os.path.dirname(os.path.join(layer, rel))):
whfile = os.path.join(layer, os.path.relpath(root, parent_checkout), '.wh.' + f)
with open(whfile, 'w') as f:
pass
if 'parent' in image:
for root, dirs, files in os.walk(layer):
for f in files:
new = os.path.join(root, f)
rel = os.path.relpath(os.path.join(root, f), layer)
old = os.path.join(parent_checkout, rel)
if os.path.lexists(old):
old_st = os.lstat(old)
new_st = os.lstat(new)
if old_st.st_mode != new_st.st_mode:
continue
if int(old_st.st_mtime) != int(new_st.st_mtime):
continue
if stat.S_ISLNK(old_st.st_mode):
if os.readlink(old) == os.readlink(new):
os.unlink(new)
else:
if filecmp.cmp(new, old):
os.unlink(new)
with tempfile.TemporaryFile(mode='w+b') as tfile:
with tarfile.open(fileobj=tfile, mode='w:') as t:
with self.timed_activity('Building layer tar'):
for root, dirs, files in os.walk(layer):
dirs.sort()
for f in itertools.chain(sorted(files), dirs):
path = os.path.join(root, f)
arcname = os.path.relpath(path, layer)
st = os.lstat(path)
tinfo = tarfile.TarInfo(name=arcname)
tinfo.uid = 0
tinfo.gid = 0
tinfo.mode = stat.S_IMODE(st.st_mode)
tinfo.mtime = st.st_mtime
if stat.S_ISDIR(st.st_mode):
tinfo.type = tarfile.DIRTYPE
t.addfile(tinfo, None)
elif stat.S_ISREG(st.st_mode):
tinfo.type = tarfile.REGTYPE
tinfo.size = st.st_size
with open(path, 'rb') as fd:
t.addfile(tinfo, fd)
elif stat.S_ISLNK(st.st_mode):
tinfo.type = tarfile.SYMTYPE
tinfo.linkname = os.readlink(path)
t.addfile(tinfo, None)
else:
raise ElementError('{}: Unexpected file type for: {}'.format(self, arcname))
tfile.seek(0)
tar_hash = hashlib.sha256()
with self.timed_activity('Hashing layer'):
while True:
data = tfile.read(16*1024)
if len(data) == 0:
break
tar_hash.update(data)
tfile.seek(0)
if self.gzip:
targz_blob = blob(output, media_type='application/vnd.oci.image.layer.v1.tar+gzip', mode=self.mode)
with self.timed_activity('Compressing layer'):
with targz_blob.create() as gzipfile:
with gzip.GzipFile(filename=tar_hash.hexdigest(), fileobj=gzipfile,
mode='wb', mtime=1320937200) as gz:
shutil.copyfileobj(tfile, gz)
layer_descs.append(targz_blob.descriptor)
else:
copied_blob = blob(output, media_type='application/vnd.oci.image.layer.v1.tar', mode=self.mode, legacy_config=legacy_config)
with copied_blob.create() as copiedfile:
shutil.copyfileobj(tfile, copiedfile)
layer_descs.append(copied_blob.descriptor)
legacy_parent = copied_blob.legacy_id
diff_ids.append('sha256:{}'.format(tar_hash.hexdigest()))
if not history:
history = []
hist_entry = {}
if 'layer' not in image:
hist_entry['empty_layer'] = True
if 'author' in image:
hist_entry['author'] = image['author']
if 'comment' in image:
hist_entry['comment'] = image['comment']
history.append(hist_entry)
config['rootfs'] = {'type': 'layers',
'diff_ids': diff_ids}
config['history'] = history
config_blob = blob(output, media_type='application/vnd.oci.image.config.v1+json', text=True, mode=self.mode)
with config_blob.create() as configfile:
json.dump(config, configfile)
if self.mode == 'docker':
manifest = {
'Config': config_blob.descriptor,
'Layers': layer_descs
}
legacy_repositories = {}
if 'tags' in image:
manifest['RepoTags'] = image['tags']
for tag in image['tags']:
name, version = tag.split(':', 1)
if name not in legacy_repositories:
legacy_repositories[name] = {}
legacy_repositories[name][version] = legacy_parent
return manifest, legacy_repositories
else:
manifest = {
'schemaVersion': 2
}
manifest['layers'] = layer_descs
manifest['config'] = config_blob.descriptor
if 'annotations' in image:
manifest['annotations'] = image['annotations']
manifest_blob = blob(output, media_type='application/vnd.oci.image.manifest.v1+json', text=True)
with manifest_blob.create() as manifestfile:
json.dump(manifest, manifestfile)
platform = {
'os': image['os'],
'architecture': image['architecture']
}
if 'os.version' in image:
platform['os.version'] = image['os.version']
if 'os.features' in image:
platform['os.features'] = image['os.features']
if 'variant' in image:
platform['variant'] = image['variant']
manifest_blob.descriptor['platform'] = platform
return manifest_blob.descriptor, {}
def assemble(self, sandbox):
root = sandbox.get_directory()
output = os.path.join(root, 'output')
os.makedirs(output)
manifests = []
legacy_repositories = {}
image_counter = 1
for image in self.images:
with self.timed_activity('Creating image {}'.format(image_counter)):
manifest, legacy_repositories_part = self._build_image(sandbox, image, root, output)
manifests.append(manifest)
legacy_repositories.update(legacy_repositories_part)
image_counter += 1
if self.mode == 'docker':
with open(os.path.join(output, 'manifest.json'), 'w', encoding='utf-8') as f:
json.dump(manifests, f)
with open(os.path.join(output, 'repositories'), 'w', encoding='utf-8') as f:
json.dump(legacy_repositories, f)
else:
index = {
'schemaVersion': 2
}
index['manifests'] = manifests
if self.annotations:
index['annotations'] = self.annotations
with open(os.path.join(output, 'index.json'), 'w', encoding='utf-8') as f:
json.dump(index, f)
oci_layout = {
'imageLayoutVersion': '1.0.0'
}
with open(os.path.join(output, 'oci-layout'), 'w', encoding='utf-8') as f:
json.dump(oci_layout, f)
return 'output'
def setup():
return OciElement | PypiClean |
/MagnetiCalc-1.15.2.tar.gz/MagnetiCalc-1.15.2/magneticalc/API.py |
# ISC License
#
# Copyright (c) 2020–2022, Paul Wilhelm, M. Sc. <anfrage@paulwilhelm.de>
#
# Permission to use, copy, modify, and/or distribute this software for any
# purpose with or without fee is hereby granted, provided that the above
# copyright notice and this permission notice appear in all copies.
#
# THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES
# WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF
# MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR
# ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES
# WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN
# ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF
# OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
import h5py
import numpy as np
from typing import Dict, List, Union
from magneticalc.MagnetiCalc_Data import MagnetiCalc_Data
class API:
""" API class. """
@staticmethod
def import_wire(filename: str) -> np.ndarray:
"""
Imports wire points from a TXT file.
@param filename: Filename
@return: NumPy array of 3D points
"""
data = np.loadtxt(filename)
assert data.shape[1] == 3, "Expecting array of 3D points"
return data
@staticmethod
def export_wire(filename: str, data: Union[List, np.ndarray]) -> None:
"""
Exports wire points to a TXT file.
@param filename: Filename
@param data: NumPy array of 3D points
"""
_data_ = np.array(data)
assert _data_.shape[1] == 3, "Expecting array of 3D points"
np.savetxt(
filename,
_data_ # type: ignore
)
# - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
@staticmethod
def import_hdf5(filename: str) -> MagnetiCalc_Data:
"""
Imports data from an HDF5 container.
Opens an HDF5 file and converts every group and subgroup into a dictionary
where the keys are the group keys and the items are the datasets.
@param filename: Filename
@return: MagnetiCalc_Data object (can be accessed like a dictionary)
"""
hdf5_group = h5py.File(filename, "r")
data = {}
API._hdf5_group_to_dict(hdf5_group, data)
hdf5_group.close()
return MagnetiCalc_Data(data)
@staticmethod
def export_hdf5(filename: str, data: Union[Dict, MagnetiCalc_Data]) -> None:
"""
Exports data to an HDF5 container.
Takes a dictionary and writes an HDF5 file using keys as keys,
and items as groups if they are dictionaries or as datasets otherwise.
@param filename: Filename
@param data: Dictionary or MagnetiCalc_Data object
"""
hdf5_group = h5py.File(filename, "w")
_data_ = data.dictionary if isinstance(data, MagnetiCalc_Data) else data
API._dict_to_hdf5_group(hdf5_group, _data_)
hdf5_group.close()
# ------------------------------------------------------------------------------------------------------------------
@staticmethod
def _dict_to_hdf5_group(hdf5_group: h5py.Group, dictionary: Dict) -> None:
"""
Recursively transforms a dictionary into an HDF5 group (in-place).
@param hdf5_group: HDF5 group
@param dictionary: Dictionary
"""
for key in dictionary.keys():
if isinstance(dictionary[key], dict):
group = hdf5_group.create_group(key)
API._dict_to_hdf5_group(group, dictionary[key])
else:
hdf5_group[key] = dictionary[key]
@staticmethod
def _hdf5_group_to_dict(hdf5_group: h5py.Group, dictionary: Dict) -> None:
"""
Recursively transforms an HDF5 group into a dictionary (in-place).
@param hdf5_group: HDF5 group
@param dictionary: Dictionary
"""
for key in [key for key in hdf5_group]:
if isinstance(hdf5_group[key], h5py.Dataset):
dictionary[key] = hdf5_group[key][()]
else:
dictionary[key] = {}
API._hdf5_group_to_dict(hdf5_group[key], dictionary[key]) | PypiClean |
/Cohen-0.7.4.tar.gz/Cohen-0.7.4/coherence/upnp/services/servers/media_receiver_registrar_server.py |
# Copyright 2006, Frank Scholz <coherence@beebits.net>
# Content Directory service
from twisted.web import resource
from coherence.upnp.core.soap_service import UPnPPublisher
from coherence.upnp.core import service
class FakeMediaReceiverRegistrarBackend:
def upnp_IsAuthorized(self, *args, **kwargs):
r = {'Result': 1}
return r
def upnp_IsValidated(self, *args, **kwargs):
r = {'Result': 1}
return r
def upnp_RegisterDevice(self, *args, **kwargs):
""" in parameter RegistrationReqMsg """
RegistrationReqMsg = kwargs['RegistrationReqMsg']
""" FIXME: check with WMC and WMP """
r = {'RegistrationRespMsg': 'WTF should be in here?'}
return r
class MediaReceiverRegistrarControl(service.ServiceControl, UPnPPublisher):
def __init__(self, server):
service.ServiceControl.__init__(self)
UPnPPublisher.__init__(self)
self.service = server
self.variables = server.get_variables()
self.actions = server.get_actions()
class MediaReceiverRegistrarServer(service.ServiceServer, resource.Resource):
implementation = 'optional'
def __init__(self, device, backend=None):
self.device = device
if backend == None:
backend = self.device.backend
resource.Resource.__init__(self)
self.version = 1
self.namespace = 'microsoft.com'
self.id_namespace = 'microsoft.com'
service.ServiceServer.__init__(self, 'X_MS_MediaReceiverRegistrar', self.version, backend)
self.device_description_tmpl = 'xbox-description-1.xml'
self.control = MediaReceiverRegistrarControl(self)
self.putChild('scpd.xml', service.scpdXML(self, self.control))
self.putChild('control', self.control)
def listchilds(self, uri):
cl = ''
for c in self.children:
cl += '<li><a href=%s/%s>%s</a></li>' % (uri, c, c)
return cl
def render(self, request):
return '<html><p>root of the MediaReceiverRegistrar</p><p><ul>%s</ul></p></html>' % self.listchilds(request.uri) | PypiClean |
/B9gemyaeix-4.14.1.tar.gz/B9gemyaeix-4.14.1/weblate/accounts/migrations/0001_squashed_0019_auto_20200403_2004.py |
import django.db.models.deletion
from django.conf import settings
from django.db import migrations, models
import weblate.utils.fields
import weblate.utils.render
class Migration(migrations.Migration):
replaces = [
("accounts", "0001_squashed_0037_auto_20180416_1406"),
("accounts", "0002_profile_uploaded"),
("accounts", "0003_profile_translate_mode"),
("accounts", "0004_create_profile"),
("accounts", "0005_auto_20190331_2126"),
("accounts", "0006_subscriptions"),
("accounts", "0007_auto_20190411_0807"),
("accounts", "0008_auto_20190426_0941"),
("accounts", "0009_profile_zen_mode"),
("accounts", "0010_auto_20190516_1153"),
("accounts", "0011_auto_20190721_1810"),
("accounts", "0012_auto_20190805_1248"),
("accounts", "0013_auto_20190916_1203"),
("accounts", "0014_auto_20190922_1947"),
("accounts", "0015_auto_20190922_1948"),
("accounts", "0016_auto_20191115_2020"),
("accounts", "0017_auto_20200318_1014"),
("accounts", "0018_announcement_rename"),
("accounts", "0019_auto_20200403_2004"),
]
initial = True
dependencies = [
("trans", "0024_resolve_auto_format"),
("lang", "0001_squashed_0011_auto_20180215_1158"),
("trans", "0001_squashed_0143_auto_20180609_1655"),
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
("social_django", "0001_initial"),
]
operations = [
migrations.CreateModel(
name="Profile",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
(
"language",
models.CharField(
blank=True,
choices=settings.LANGUAGES,
max_length=10,
verbose_name="Interface Language",
),
),
("suggested", models.IntegerField(db_index=True, default=0)),
("translated", models.IntegerField(db_index=True, default=0)),
(
"languages",
models.ManyToManyField(
blank=True,
help_text="Choose the languages you can translate to. These will be offered to you on the dashboard for easier access to your chosen translations.",
to="lang.Language",
verbose_name="Translated languages",
),
),
(
"secondary_languages",
models.ManyToManyField(
blank=True,
help_text="Choose languages you can understand, strings in those languages will be shown in addition to the source string.",
related_name="secondary_profile_set",
to="lang.Language",
verbose_name="Secondary languages",
),
),
(
"watched",
models.ManyToManyField(
blank=True,
help_text="You can receive notifications for watched projects and they are shown on the dashboard by default.",
to="trans.Project",
verbose_name="Watched projects",
),
),
(
"user",
models.OneToOneField(
editable=False,
on_delete=django.db.models.deletion.CASCADE,
to=settings.AUTH_USER_MODEL,
),
),
(
"hide_completed",
models.BooleanField(
default=False,
verbose_name="Hide completed translations on the dashboard",
),
),
(
"secondary_in_zen",
models.BooleanField(
default=True,
verbose_name="Show secondary translations in the Zen mode",
),
),
(
"hide_source_secondary",
models.BooleanField(
default=False,
verbose_name="Hide source if a secondary translation exists",
),
),
(
"dashboard_component_list",
models.ForeignKey(
blank=True,
null=True,
on_delete=django.db.models.deletion.CASCADE,
to="trans.ComponentList",
verbose_name="Default component list",
),
),
(
"dashboard_view",
models.IntegerField(
choices=[
(1, "Watched translations"),
(6, "Component lists"),
(4, "Component list"),
(5, "Suggested translations"),
],
default=1,
verbose_name="Default dashboard view",
),
),
(
"editor_link",
models.CharField(
blank=True,
default="",
help_text="Enter a custom URL to be used as link to the source code. You can use {{branch}} for branch, {{filename}} and {{line}} as filename and line placeholders.",
max_length=200,
validators=[weblate.utils.render.validate_editor],
verbose_name="Editor link",
),
),
(
"special_chars",
models.CharField(
blank=True,
default="",
help_text="You can specify additional special visual keyboard characters to be shown while translating. It can be useful for characters you use frequently, but are hard to type on your keyboard.",
max_length=30,
verbose_name="Special characters",
),
),
("uploaded", models.IntegerField(db_index=True, default=0)),
(
"translate_mode",
models.IntegerField(
choices=[(0, "Full editor"), (1, "Zen mode")],
default=0,
verbose_name="Translation editor mode",
),
),
(
"zen_mode",
models.IntegerField(
choices=[(0, "Top to bottom"), (1, "Side by side")],
default=0,
verbose_name="Zen editor mode",
),
),
],
),
migrations.CreateModel(
name="VerifiedEmail",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
("email", models.EmailField(max_length=254)),
(
"social",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
to="social_django.UserSocialAuth",
),
),
],
),
migrations.CreateModel(
name="Subscription",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
(
"notification",
models.CharField(
choices=[
("MergeFailureNotification", "Repository failure"),
("RepositoryNotification", "Repository operation"),
("ParseErrorNotification", "Parse error"),
("NewStringNotificaton", "New string"),
("NewContributorNotificaton", "New contributor"),
("NewSuggestionNotificaton", "New suggestion"),
(
"LastAuthorCommentNotificaton",
"Comment on own translation",
),
("MentionCommentNotificaton", "Mentioned in comment"),
("NewCommentNotificaton", "New comment"),
("ChangedStringNotificaton", "Changed string"),
("NewTranslationNotificaton", "New language"),
("NewComponentNotificaton", "New translation component"),
("NewAnnouncementNotificaton", "New announcement"),
("NewAlertNotificaton", "New alert"),
("PendingSuggestionsNotification", "Pending suggestions"),
("ToDoStringsNotification", "Unfinished strings"),
],
max_length=100,
),
),
(
"scope",
models.IntegerField(
choices=[
(10, "Defaults"),
(20, "Admin"),
(30, "Project"),
(40, "Component"),
]
),
),
(
"frequency",
models.IntegerField(
choices=[
(0, "Do not notify"),
(1, "Instant notification"),
(2, "Daily digest"),
(3, "Weekly digest"),
(4, "Monthly digest"),
]
),
),
(
"component",
models.ForeignKey(
null=True,
on_delete=django.db.models.deletion.CASCADE,
to="trans.Component",
),
),
(
"project",
models.ForeignKey(
null=True,
on_delete=django.db.models.deletion.CASCADE,
to="trans.Project",
),
),
(
"user",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
to=settings.AUTH_USER_MODEL,
),
),
],
options={
"unique_together": {
("notification", "scope", "project", "component", "user")
},
},
),
migrations.CreateModel(
name="AuditLog",
fields=[
(
"id",
models.AutoField(
auto_created=True,
primary_key=True,
serialize=False,
verbose_name="ID",
),
),
(
"activity",
models.CharField(
choices=[
("auth-connect", "auth-connect"),
("auth-disconnect", "auth-disconnect"),
("connect", "connect"),
("email", "email"),
("failed-auth", "failed-auth"),
("full_name", "full_name"),
("invited", "invited"),
("locked", "locked"),
("login", "login"),
("login-new", "login-new"),
("password", "password"),
("register", "register"),
("removed", "removed"),
("reset", "reset"),
("reset-request", "reset-request"),
("tos", "tos"),
("username", "username"),
],
db_index=True,
max_length=20,
),
),
("params", weblate.utils.fields.JSONField(default={})),
("address", models.GenericIPAddressField(null=True)),
("timestamp", models.DateTimeField(auto_now_add=True, db_index=True)),
(
"user",
models.ForeignKey(
on_delete=django.db.models.deletion.CASCADE,
to=settings.AUTH_USER_MODEL,
),
),
("user_agent", models.CharField(default="", max_length=200)),
],
options={},
),
] | PypiClean |
/GautamsX-6.0.13.tar.gz/GautamsX-6.0.13/bot/modules/watch.py | from telegram.ext import CommandHandler
from telegram import Bot, Update
from bot import Interval, DOWNLOAD_DIR, DOWNLOAD_STATUS_UPDATE_INTERVAL, dispatcher, LOGGER
from bot.helper.ext_utils.bot_utils import setInterval
from bot.helper.telegram_helper.message_utils import update_all_messages, sendMessage, sendStatusMessage
from .mirror import MirrorListener
from bot.helper.mirror_utils.download_utils.youtube_dl_download_helper import YoutubeDLHelper
from bot.helper.telegram_helper.bot_commands import BotCommands
from bot.helper.telegram_helper.filters import CustomFilters
import threading
def _watch(bot: Bot, update, isTar=False):
mssg = update.message.text
message_args = mssg.split(' ')
name_args = mssg.split('|')
try:
link = message_args[1]
except IndexError:
msg = f"/{BotCommands.WatchCommand} [yt_dl supported link] [quality] |[CustomName] to mirror with youtube_dl.\n\n"
msg += "<b>Note :- Quality and custom name are optional</b>\n\nExample of quality :- audio, 144, 240, 360, 480, 720, 1080, 2160."
msg += "\n\nIf you want to use custom filename, plz enter it after |"
msg += f"\n\nExample :-\n<code>/{BotCommands.WatchCommand} https://youtu.be/ocX2FN1nguA 720 |My video bro</code>\n\n"
msg += "This file will be downloaded in 720p quality and it's name will be <b>My video bro</b>"
sendMessage(msg, bot, update)
return
try:
if "|" in mssg:
mssg = mssg.split("|")
qual = mssg[0].split(" ")[2]
if qual == "":
raise IndexError
else:
qual = message_args[2]
if qual != "audio":
qual = f'bestvideo[height<={qual}]+bestaudio/best[height<={qual}]'
except IndexError:
qual = "bestvideo+bestaudio/best"
try:
name = name_args[1]
except IndexError:
name = ""
reply_to = update.message.reply_to_message
if reply_to is not None:
tag = reply_to.from_user.username
else:
tag = None
pswd = ""
listener = MirrorListener(bot, update, pswd, isTar, tag)
ydl = YoutubeDLHelper(listener)
threading.Thread(target=ydl.add_download,args=(link, f'{DOWNLOAD_DIR}{listener.uid}', qual, name)).start()
sendStatusMessage(update, bot)
if len(Interval) == 0:
Interval.append(setInterval(DOWNLOAD_STATUS_UPDATE_INTERVAL, update_all_messages))
def watchTar(update, context):
_watch(context.bot, update, True)
def watch(update, context):
_watch(context.bot, update)
mirror_handler = CommandHandler(BotCommands.WatchCommand, watch,
filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)
tar_mirror_handler = CommandHandler(BotCommands.TarWatchCommand, watchTar,
filters=CustomFilters.authorized_chat | CustomFilters.authorized_user, run_async=True)
dispatcher.add_handler(mirror_handler)
dispatcher.add_handler(tar_mirror_handler) | PypiClean |
/Glances-3.4.0.3.tar.gz/Glances-3.4.0.3/glances/ports_list.py | from glances.compat import range
from glances.logger import logger
from glances.globals import BSD
# XXX *BSDs: Segmentation fault (core dumped)
# -- https://bitbucket.org/al45tair/netifaces/issues/15
# Also used in the glances_ip plugin
if not BSD:
try:
import netifaces
netifaces_tag = True
except ImportError:
netifaces_tag = False
else:
netifaces_tag = False
class GlancesPortsList(object):
"""Manage the ports list for the ports plugin."""
_section = "ports"
_default_refresh = 60
_default_timeout = 3
def __init__(self, config=None, args=None):
# ports_list is a list of dict (JSON compliant)
# [ {'host': 'www.google.fr', 'port': 443, 'refresh': 30, 'description': Internet, 'status': True} ... ]
# Load the configuration file
self._ports_list = self.load(config)
def load(self, config):
"""Load the ports list from the configuration file."""
ports_list = []
if config is None:
logger.debug("No configuration file available. Cannot load ports list.")
elif not config.has_section(self._section):
logger.debug("No [%s] section in the configuration file. Cannot load ports list." % self._section)
else:
logger.debug("Start reading the [%s] section in the configuration file" % self._section)
refresh = int(config.get_value(self._section, 'refresh', default=self._default_refresh))
timeout = int(config.get_value(self._section, 'timeout', default=self._default_timeout))
# Add default gateway on top of the ports_list lists
default_gateway = config.get_value(self._section, 'port_default_gateway', default='False')
if default_gateway.lower().startswith('true') and netifaces_tag:
new_port = {}
try:
new_port['host'] = netifaces.gateways()['default'][netifaces.AF_INET][0]
except KeyError:
new_port['host'] = None
# ICMP
new_port['port'] = 0
new_port['description'] = 'DefaultGateway'
new_port['refresh'] = refresh
new_port['timeout'] = timeout
new_port['status'] = None
new_port['rtt_warning'] = None
new_port['indice'] = str('port_0')
logger.debug("Add default gateway %s to the static list" % (new_port['host']))
ports_list.append(new_port)
# Read the scan list
for i in range(1, 256):
new_port = {}
postfix = 'port_%s_' % str(i)
# Read mandatory configuration key: host
new_port['host'] = config.get_value(self._section, '%s%s' % (postfix, 'host'))
if new_port['host'] is None:
continue
# Read optionals configuration keys
# Port is set to 0 by default. 0 mean ICMP check instead of TCP check
new_port['port'] = config.get_value(self._section, '%s%s' % (postfix, 'port'), 0)
new_port['description'] = config.get_value(
self._section, '%sdescription' % postfix, default="%s:%s" % (new_port['host'], new_port['port'])
)
# Default status
new_port['status'] = None
# Refresh rate in second
new_port['refresh'] = refresh
# Timeout in second
new_port['timeout'] = int(config.get_value(self._section, '%stimeout' % postfix, default=timeout))
# RTT warning
new_port['rtt_warning'] = config.get_value(self._section, '%srtt_warning' % postfix, default=None)
if new_port['rtt_warning'] is not None:
# Convert to second
new_port['rtt_warning'] = int(new_port['rtt_warning']) / 1000.0
# Indice
new_port['indice'] = 'port_' + str(i)
# Add the server to the list
logger.debug("Add port %s:%s to the static list" % (new_port['host'], new_port['port']))
ports_list.append(new_port)
# Ports list loaded
logger.debug("Ports list loaded: %s" % ports_list)
return ports_list
def get_ports_list(self):
"""Return the current server list (dict of dict)."""
return self._ports_list
def set_server(self, pos, key, value):
"""Set the key to the value for the pos (position in the list)."""
self._ports_list[pos][key] = value | PypiClean |
/NIA_image_2latex-1.0-py3-none-any.whl/dataset/preprocessing/third_party/katex/katex.js | * This is the main entry point for KaTeX. Here, we expose functions for
* rendering expressions either to DOM nodes or to markup strings.
*
* We also expose the ParseError class to check if errors thrown from KaTeX are
* errors in the expression, or errors in javascript handling.
*/
var ParseError = require("./src/ParseError");
var Settings = require("./src/Settings");
var buildTree = require("./src/buildTree");
var parseTree = require("./src/parseTree");
var utils = require("./src/utils");
/**
* Parse and build an expression, and place that expression in the DOM node
* given.
*/
var render = function(expression, baseNode, options) {
utils.clearNode(baseNode);
var settings = new Settings(options);
var tree = parseTree(expression, settings);
var node = buildTree(tree, expression, settings).toNode();
baseNode.appendChild(node);
};
// KaTeX's styles don't work properly in quirks mode. Print out an error, and
// disable rendering.
if (typeof document !== "undefined") {
if (document.compatMode !== "CSS1Compat") {
typeof console !== "undefined" && console.warn(
"Warning: KaTeX doesn't work in quirks mode. Make sure your " +
"website has a suitable doctype.");
render = function() {
throw new ParseError("KaTeX doesn't work in quirks mode.");
};
}
}
/**
* Parse and build an expression, and return the markup for that.
*/
var renderToString = function(expression, options) {
var settings = new Settings(options);
var tree = parseTree(expression, settings);
return buildTree(tree, expression, settings).toMarkup();
};
/**
* Parse an expression and return the parse tree.
*/
var generateParseTree = function(expression, options) {
var settings = new Settings(options);
return parseTree(expression, settings);
};
module.exports = {
render: render,
renderToString: renderToString,
/**
* NOTE: This method is not currently recommended for public use.
* The internal tree representation is unstable and is very likely
* to change. Use at your own risk.
*/
__parse: generateParseTree,
ParseError: ParseError,
}; | PypiClean |
/Flask_AdminLTE3-1.0.9-py3-none-any.whl/flask_adminlte3/static/plugins/jquery-mapael/maps/world_countries.min.js | !function(a){"object"==typeof exports?module.exports=a(require("jquery"),require("jquery-mapael")):"function"==typeof define&&define.amd?define(["jquery","mapael"],a):a(jQuery,jQuery.mapael)}(function(a,b){"use strict";return a.extend(!0,b,{maps:{world_countries:{width:999.29852,height:392.03476,getCoords:function(a,b){return{x:2.775076875916*b+471.505926315,y:-2.8112860731578*a+235.89691962022}},elems:{PE:"m 246.37,248.26 c 0.32,-1.79 4.23,-4.35 2.73,-1.46 -1.45,2.09 2.59,0.39 3.11,2.75 2.72,-1.13 1.47,-5.5 4.96,-5.95 3.11,-0.83 7.69,-4.81 5.11,-7.43 2.35,-1.19 4.43,3.08 6.14,4.56 0.7,2.08 3.04,2.21 4.97,1.17 2.11,-0.15 5.75,1.18 2.69,3.69 -0.51,0.71 3.29,2.56 0.76,1.93 -3.16,0.08 -7.44,1.58 -7.92,5.32 -0.06,2.05 -3.42,3.58 -1.21,5.52 0.76,1.37 2.13,3 1.77,3.78 2.26,0.16 3.53,3.49 5.91,0.61 2.26,-1.86 -1.32,6.12 2.9,3.61 2.5,1.32 3.37,4.79 2.23,7.29 0.95,2.52 -2.79,6.04 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/BitGlitter-2.0.0.tar.gz/BitGlitter-2.0.0/bitglitter/config/palettemodels.py | from sqlalchemy import Boolean, Column, Float, Integer, String, UniqueConstraint
import base64
import math
import time
from bitglitter.config.config import engine, SQLBaseClass
from bitglitter.utilities.palette import BitsToColor, ColorsToBits, convert_hex_to_rgb, get_color_distance, \
get_palette_id_from_hash
class Palette(SQLBaseClass):
__tablename__ = 'palettes'
__abstract__ = False
is_24_bit = Column(Boolean, default=False)
is_custom = Column(Boolean, default=True)
is_included_with_repo = Column(Boolean, default=False) # for differentiating other people's colors & our fancy ones
palette_id = Column(String, unique=True, nullable=False)
name = Column(String, unique=True, nullable=False)
description = Column(String)
nickname = Column(String, nullable=True, unique=True)
color_set = Column(String)
color_distance = Column(Float, default=0, nullable=False)
number_of_colors = Column(Integer, default=0, nullable=False)
bit_length = Column(Integer, default=0, nullable=False)
time_created = Column(Integer, default=time.time)
base64_string = Column(String)
is_valid = Column(Boolean)
@classmethod
def create(cls, color_set, **kwargs):
object_ = super().create(**kwargs)
object_._initialize_colors(color_set)
if object_.is_custom:
assembled_string = '\\\\'.join(
[object_.palette_id, object_.name, object_.description, str(object_.time_created),
str(object_.convert_colors_to_tuple())]) + '\\\\'
object_.base64_string = base64.b64encode(assembled_string.encode()).decode()
object_.save()
return object_
__table_args__ = (
UniqueConstraint('palette_id'),
)
def __str__(self):
palette_type = 'Custom' if self.is_custom else 'Default'
return f'{palette_type} Palette - {self.name} - {self.number_of_colors} Colors'
def _calculate_palette_math(self, color_set, save=True):
"""Runs during model creation and when color set is updated."""
self.color_distance = get_color_distance(color_set)
self.number_of_colors = len(color_set)
is_valid = math.log2(self.number_of_colors).is_integer()
if is_valid:
self.bit_length = int(math.log(self.number_of_colors, 2))
else:
self.bit_length = 0
self.is_valid = is_valid
if save: # Added to prevent repetitive saves if used in other methods
self.save()
def convert_colors_to_tuple(self):
"""Since all of their colors are stored as a single string for speed, this function retrieves it and returns
them in a more usable list format.
"""
if not self.is_24_bit:
string_split = self.color_set.split('|')
returned_list = []
for piece in string_split:
channels = piece.split(',')
channels = [int(channel) for channel in channels]
returned_list.append((channels[0], channels[1], channels[2]))
return returned_list
else:
return None
def _initialize_colors(self, color_set):
"""An internal method that blindly accepts tuples. Use palettefunctions functions for prior necessary
validation of values.
"""
color_set_cleaned = convert_hex_to_rgb(color_set) if color_set else None
if not self.is_24_bit:
self._calculate_palette_math(color_set_cleaned, save=False)
string_list = []
for color in color_set_cleaned:
to_string = [str(channel) for channel in color]
string_list.append(','.join(to_string))
self.color_set = '|'.join(string_list)
else:
self.bit_length = 24
self.color_distance = 0
self.number_of_colors = 16777216
if self.is_custom:
self.palette_id = get_palette_id_from_hash(self.name, self.description, self.time_created,
color_set_cleaned)
def return_encoder(self):
color_set_tupled = self.convert_colors_to_tuple()
return BitsToColor(color_set_tupled, self.bit_length, self.name)
def return_decoder(self):
color_set_tupled = self.convert_colors_to_tuple()
return ColorsToBits(color_set_tupled, self.bit_length, self.name)
SQLBaseClass.metadata.create_all(engine) | PypiClean |
/FamcyDev-0.3.71-py3-none-any.whl/Famcy/_util_/_fthread.py | import threading
import enum
from flask import session, g, request
class FPriority(enum.IntEnum):
"""
This is the enum for defining
Famcy module priorities.
"""
Standard = 1
Error = 2
Critical = 3
class FamcyPageQueue:
def __init__(self):
super(FamcyPageQueue, self).__init__()
self.BackgroundQueueDict = {}
# def init_queue(self, _id):
# session["BackgroundQueueDict"] = FamcyPriorityQueue()
def add(self, value, priority):
if isinstance(value.target, list):
_page = value.target[0].find_page_parent(value.target[0])
else:
_page = value.target.find_page_parent(value.target)
route_name = _page.route.replace("/", "_")[1:]
# print('route_name: ', route_name)
session[route_name+"BackgroundQueueDict"].add(value, priority)
# print("add", session[route_name+"BackgroundQueueDict"])
class FamcyPriorityQueue:
"""
This PQ is adopted from:
https://github.com/fafl/priority-queue.git
"""
def __init__(self):
# List of items, flattened binary heap. The first element is not used.
# Each node is a tuple of (value, priority, insert_counter)
self.nodes = [None] # first element is not used
# Current state of the insert counter
self.insert_counter = 0 # tie breaker, keeps the insertion order
# Comparison function between two nodes
# Higher priority wins
# On equal priority: Lower insert counter wins
def _is_higher_than(self, a, b):
return b[1] < a[1] or (a[1] == b[1] and a[2] < b[2])
# Move a node up until the parent is bigger
def _heapify(self, new_node_index):
while 1 < new_node_index:
new_node = self.nodes[new_node_index]
parent_index = new_node_index // 2
parent_node = self.nodes[parent_index]
# Parent too big?
if self._is_higher_than(parent_node, new_node):
break
# Swap with parent
tmp_node = parent_node
self.nodes[parent_index] = new_node
self.nodes[new_node_index] = tmp_node
# Continue further up
new_node_index = parent_index
# Add a new node with a given priority
def add(self, value, priority):
new_node_index = len(self.nodes)
self.insert_counter += 1
self.nodes.append((value, priority, self.insert_counter))
# Move the new node up in the hierarchy
self._heapify(new_node_index)
# Return the top element
def peek(self):
if len(self.nodes) == 1:
return None
else:
return self.nodes[1][0]
# Return the bottom element
def bottom(self):
if len(self.nodes) == 1:
return None
else:
return self.nodes[-1][0]
# Remove the top element and return it
def pop(self):
if len(self.nodes) == 1:
raise LookupError("Heap is empty")
result = self.nodes[1][0]
# Move empty space down
empty_space_index = 1
while empty_space_index * 2 < len(self.nodes):
left_child_index = empty_space_index * 2
right_child_index = empty_space_index * 2 + 1
# Left child wins
if (
len(self.nodes) <= right_child_index
or self._is_higher_than(self.nodes[left_child_index], self.nodes[right_child_index])
):
self.nodes[empty_space_index] = self.nodes[left_child_index]
empty_space_index = left_child_index
# Right child wins
else:
self.nodes[empty_space_index] = self.nodes[right_child_index]
empty_space_index = right_child_index
# Swap empty space with the last element and heapify
last_node_index = len(self.nodes) - 1
self.nodes[empty_space_index] = self.nodes[last_node_index]
self._heapify(empty_space_index)
# Throw out the last element
self.nodes.pop()
return result
class FamcyThread(threading.Thread):
"""
Represent the famcy thread implementation.
Currently it's just inherit from the
basic threading Thread class.
"""
def __init__(self, *args, **kwargs):
super(FamcyThread, self).__init__(*args, **kwargs) | PypiClean |
/Cibyl-1.0.0.0rc1.tar.gz/Cibyl-1.0.0.0rc1/cibyl/models/ci/base/build.py | from typing import Dict, List
from cibyl.cli.argument import Argument
from cibyl.models.attribute import AttributeDictValue, AttributeListValue
from cibyl.models.ci.base.stage import Stage
from cibyl.models.ci.base.test import Test
from cibyl.models.model import Model
class Build(Model):
"""General model for a job build
@DynamicAttrs: Contains attributes added on runtime.
"""
API = {
'build_id': {
'attr_type': str,
'arguments': []
},
'status': {
'attr_type': str,
'arguments': [Argument(name='--build-status', arg_type=str,
func='get_builds', nargs='*',
description="Build status")]
},
'duration': {
'attr_type': int,
'arguments': [],
},
'tests': {
'attr_type': Test,
'attribute_value_class': AttributeDictValue,
'arguments': [Argument(name='--tests', arg_type=str,
nargs='*', func='get_tests',
description="Job test")]
},
'stages': {
'attr_type': Stage,
'attribute_value_class': AttributeListValue,
'arguments': [Argument(name='--stages', arg_type=str,
nargs=0, description="Build stages run")]
}
}
def __init__(self, build_id: str, status: str = None,
duration: int = None, tests: Dict[str, Test] = None,
stages: List[Stage] = None, **kwargs):
if status is not None:
status = status.upper()
super().__init__({'build_id': build_id, 'status': status,
'duration': duration, 'tests': tests,
'stages': stages, **kwargs})
def __eq__(self, other):
if not isinstance(other, self.__class__):
return False
return self.build_id.value == other.build_id.value
def add_test(self, test: Test):
"""Add a test to the build.
:param test: Test to add to the build
:type test: Test
"""
test_name = test.name.value
if test_name in self.tests:
self.tests[test_name].merge(test)
else:
self.tests[test_name] = test
def add_stage(self, stage: Stage):
"""Add a stage to the build.
:param stage: Stage to add to the build
:type stage: Stage
"""
self.stages.append(stage)
def merge(self, other):
"""Merge the information of two build objects representing the same
build.
:param other: The Build object to merge
:type other: :class:`.Build`
"""
if not self.status.value:
self.status.value = other.status.value
for test in other.tests.values():
self.add_test(test)
if not self.stages.value and other.stages.value:
self.stages = other.stages | PypiClean |
/GailBot_Testing_Suite-0.1a8-py3-none-any.whl/gailbot/core/engines/whisperEngine/whisperTimestamped/transcribe_efficient.py |
import sys
import os
import whisper
import torch
import torch.nn.functional as F
from .alignment import perform_word_alignment
from .utils import (
get_logit_filters,
should_use_space,
print_timestamped,
round_confidence
)
from .vars import (
HOP_LENGTH,
SAMPLE_RATE
)
import string
import logging
logger = logging.getLogger()
_punctuation = "".join(c for c in string.punctuation if c not in ["-", "'"])
def _transcribe_timestamped_efficient(
model,
audio,
remove_punctuation_from_words,
compute_word_confidence,
include_punctuation_in_confidence,
refine_whisper_precision_nframes,
plot_word_alignment,
# Whisper specific options
**whisper_options,
):
"""
Timestamps a transcription created by the whisper engine.
Args:
model:
audio:
remove_punctuation_from_words:
compute_word_confidence:
include_punctuation_in_confidence:
refine_whisper_precision_nframes:
plot_word_alignment:
Returns:
"""
# Get options
sample_len = whisper_options["sample_len"]
temperature = whisper_options["temperature"]
no_speech_threshold = whisper_options["no_speech_threshold"]
logprob_threshold = whisper_options["logprob_threshold"]
verbose = whisper_options["verbose"]
# Note: "on-the-fly" verbose is not implementable in the current state (we don't know the absolute position of the current chunk). See issue #18
verbose_bugged = False
whisper_options["verbose"] = None if whisper_options["verbose"] is True else whisper_options["verbose"] # We will print intermediate results ourselves
logit_filters = get_logit_filters(model, whisper_options)
language = whisper_options["language"]
tokenizer = whisper.tokenizer.get_tokenizer(model.is_multilingual, task=whisper_options["task"], language=language)
max_sample_len = sample_len or model.dims.n_text_ctx // 2
# Note: we cannot trust the token in the middle of tokenizer.sot_sequence which refers to the language
# (arbitrarily set to <|en|> if it's actually None/unknown)
token_sot = tokenizer.sot
token_eot = tokenizer.eot
debug = logger.getEffectiveLevel() >= logging.DEBUG
# The main outcome
timestamped_word_segments = [] # list of timestamped word segments that have been collected so far
# Main variables to be accumulated
segment_tokens = [[]] # list of lists of token indices that have been collected so far (one list per segment)
segment_attweights = [[] for _ in range(len(model.decoder.blocks))]
# attention weights on the last segments
segment_avglogprobs = [] # average log probability for each segment (actually of the corresponding chunk, as computed by whisper)
segment_logprobs = [] # token log probabilities for each segment
# Variables related to options that can skip some segments
sot_index = None # index of the SOT token in the current set of processed tokens
no_speech_prob = None # no speech probability for the current 30 sec chunk
chunk_logprobs = [] # log probabilities for the current 30 sec chunk
chunk_tokens = [] # tokens for the current 30 sec chunk (list of Torch tensors)
chunk_tokens_nosot = [] # tokens for the current 30 sec chunk, without the SOT tokens (list of indices)
last_token_fallback = None # last token to use as a fallback if the model gets stuck
has_started = False # whether we have started decoding
mfcc = None # MFCC features for the current 30 sec chunk
new_mfcc = None #
num_inference_steps = 0 # number of inference steps performed so far (for debugging only)
def reset(add_segment, keep_last_token):
""" Reset the list of tokens for the current speech segment, and corresponding cross-attention weights """
nonlocal segment_tokens, segment_attweights
if add_segment:
if keep_last_token:
segment_tokens.append([segment_tokens[-1][-1]])
segment_attweights = [w[-1:] for w in segment_attweights]
else:
segment_tokens.append([])
segment_attweights = [[] for w in segment_attweights]
segment_tokens[-2].pop(0)
if debug:
logger.debug(f"Added new segment: {tokenizer.decode_with_timestamps(segment_tokens[-2])}")
elif len(segment_tokens[-1]) > 0:
segment_tokens[-1] = []
segment_attweights = [[] for w in segment_attweights]
if debug:
logger.debug(f"Reset last segment to: {tokenizer.decode_with_timestamps(segment_tokens[-1])}")
saw_consecutive_timestamps = False
def must_flush_segment(curr_tokens):
""" Return whether or not the previously collected tokens must be used to add a new speech segment """
nonlocal segment_tokens, saw_consecutive_timestamps, chunk_tokens_nosot
if curr_tokens is not None and len(curr_tokens) == 1:
is_timestamp = curr_tokens[0] >= tokenizer.timestamp_begin
is_previous_timestamp = segment_tokens[-1][-1] >= tokenizer.timestamp_begin if len(segment_tokens[-1]) > 0 else False
consecutive_timestamps = is_timestamp and is_previous_timestamp
if consecutive_timestamps:
saw_consecutive_timestamps = True
if len(chunk_tokens_nosot) == max_sample_len - 2 and is_timestamp:
consecutive_timestamps = True
return consecutive_timestamps
else: # Several tokens as a prompt or must flush last segments
must_flush = not saw_consecutive_timestamps and len(segment_tokens[-1]) > 1
logger.debug(f"New prompt: flushing = {must_flush}")
if not must_flush:
# Discard the end of the last transcription
reset(False, True)
saw_consecutive_timestamps = False
return must_flush
index_begin_30sec_chunck = 0
def get_index_begin_30sec_chunck(curr_tokens):
nonlocal index_begin_30sec_chunck
if curr_tokens is None or len(curr_tokens) > 1:
res = index_begin_30sec_chunck
index_begin_30sec_chunck = len(segment_tokens)-1
return res
def may_flush_segment(curr_tokens = None):
""" Add a speech segment with the new tokens if necessary.
May also remove the last collected segments if filtered out by Whisper (no_speech_prob <= no_speech_threshold)
"""
nonlocal segment_tokens, segment_attweights, timestamped_word_segments, has_started, no_speech_prob, chunk_tokens, chunk_tokens_nosot, chunk_logprobs, mfcc, new_mfcc, logit_filters, index_begin_30sec_chunck, last_token_fallback, num_inference_steps
# Check if a new segment should be added
unfinished_decoding = False
if must_flush_segment(curr_tokens):
if mfcc is None:
mfcc = new_mfcc
if debug:
logger.debug(f"Adding segment {len(timestamped_word_segments)+1} at step {num_inference_steps}:\n\t{tokenizer.decode_with_timestamps(segment_tokens[-1])}")
tokens = segment_tokens[-1][1:]
# When the decoding hit the max limit (number of tokens) -- usually when the language model gets stuck --
# then we have to recover the last token from what is send to the decoder
unfinished_decoding = len(tokens) and tokens[-1] < tokenizer.timestamp_begin
last_token_reliable = True
if unfinished_decoding:
logger.debug(f"WARNING: decoding hit the max limit for segment {segment_tokens} (It usually happens when the language model gets stuck)")
# The last token chosen is in the prompt for the new chunk
if curr_tokens is not None and curr_tokens[0] == tokenizer.sot_prev:
logger.debug(" Guess last token from the prompt for the new chunk")
last_token_fallback = curr_tokens[-4].item()
# Fallback for the last segment, or without prompt: Assume greedy decoding
else:
logger.debug(f" Guess last token using probas (assuming greedy decoding)")
last_token_fallback = torch.argmax(chunk_logprobs[-1]).item()
last_token_reliable = (temperature == 0)
if debug:
logger.debug(f"WARNING: also add last token: {tokenizer.decode_with_timestamps([last_token_fallback])}")
tokens.append(last_token_fallback)
segment_tokens[-1].append(last_token_fallback)
attention_weights = [torch.cat(w, dim=-2) for w in segment_attweights]
last_logprobs = chunk_logprobs[-1]
else:
attention_weights = [torch.cat(w[:-1], dim=-2) for w in segment_attweights]
last_logprobs = chunk_logprobs[-2]
# Check prediction of last token
end_token = tokens[-1]
if end_token >= tokenizer.timestamp_begin:
start_token = tokens[0]
assert start_token >= tokenizer.timestamp_begin
# If Whisper prediction of the end is obviously wrong, we predict it again (constrained)
if end_token <= start_token:
end_token = last_logprobs[start_token+1:].argmax() + start_token + 1
tokens[-1] = end_token
ws = perform_word_alignment(
tokens,
attention_weights,
tokenizer,
use_space=should_use_space(language),
remove_punctuation_from_words=remove_punctuation_from_words,
refine_whisper_precision_nframes=refine_whisper_precision_nframes,
unfinished_decoding=unfinished_decoding,
mfcc=mfcc,
plot=plot_word_alignment,
)
add_segment = len(ws) > 0
if add_segment:
timestamped_word_segments.append(ws)
else:
logger.debug(f"Not added!")
reset(add_segment, curr_tokens is not None and len(curr_tokens) == 1)
i_start = get_index_begin_30sec_chunck(curr_tokens)
# All segments from previous 30sec chunck have been collected
if (i_start is not None and has_started):
mfcc = new_mfcc
# Get word confidence and/or check if previous segments shoud have been skipped
should_skip = False
if compute_word_confidence or no_speech_threshold is not None:
# no voice activity check
should_skip = (no_speech_prob > no_speech_threshold) if (no_speech_threshold is not None) else False
if compute_word_confidence or (should_skip and logprob_threshold is not None):
n = len(chunk_logprobs)
if n == len(chunk_tokens_nosot):
chunk_tokens_nosot = chunk_tokens_nosot[1:]
if unfinished_decoding:
assert last_token_fallback is not None
last_tokens = [last_token_fallback]
timestamped_word_segments[-1][-1]["avg_logprob_reliable"] = last_token_reliable
n += 1
elif len(chunk_tokens_nosot) >= max_sample_len - 3:
# there were segments in the 30sec chunck, and then the LM got stuck
last_tokens = [torch.argmax(chunk_logprobs[-1]).item()]
timestamped_word_segments[-1][-1]["avg_logprob_reliable"] = (temperature == 0)
else:
last_tokens = [tokenizer.eot]
chunck_indices = chunk_tokens_nosot + last_tokens
assert len(chunk_logprobs) == len(chunck_indices), f"{len(chunk_logprobs)} != {len(chunck_indices)}"
logprobs = torch.cat([logprob[i].unsqueeze(0) for (logprob, i) in zip(chunk_logprobs, chunck_indices)])
assert min([p.isfinite().item() for p in logprobs]), \
f"Got infinite logprob among ({len(logprobs)}) {[(i, tokenizer.decode_with_timestamps([i]), v.item()) for (i,v) in zip(chunck_indices, logprobs)]}"
sum_logprob = sum(logprobs)
avg_logprob = sum_logprob/n
# don't skip if the logprob is high enough, despite the no_speech_prob
if avg_logprob > logprob_threshold:
should_skip = False
if should_skip:
logger.debug(f"Skipping last {len(segment_tokens)-1-i_start} segments (no_speech_prob {no_speech_prob} > {no_speech_threshold} and avg_logprob {avg_logprob} < {logprob_threshold})")
index_begin_30sec_chunck -= len(segment_tokens)-1-i_start
segment_tokens = segment_tokens[:i_start] + [segment_tokens[-1]]
timestamped_word_segments = timestamped_word_segments[:i_start]
elif compute_word_confidence:
avg_logprob = avg_logprob.item()
i_token_end = -1
for i in range(i_start, len(segment_tokens)-1):
tokens = segment_tokens[i]
i_token_start = i_token_end + 1
i_token_end = i_token_start + len(tokens)
assert chunck_indices[i_token_start:i_token_end] == tokens, f"Inconsistent token list {tokenizer.decode_with_timestamps(chunck_indices[i_token_start:i_token_end])} != {tokenizer.decode_with_timestamps(tokens)}"
i_token_start += 1 # skip sos (start time)
if not unfinished_decoding:
i_token_end -= 1 # skip eos (end time)
segment_logprobs.append(logprobs[i_token_start:i_token_end])
segment_avglogprobs.append(avg_logprob)
else:
for i in range(i_start, len(segment_tokens)-1):
segment_logprobs.append(None)
segment_avglogprobs.append(None)
else:
for i in range(i_start, len(segment_tokens)-1):
segment_logprobs.append(None)
segment_avglogprobs.append(None)
if verbose_bugged and not should_skip:
for segment in timestamped_word_segments[i_start:]:
for word in segment:
print_timestamped(word)
# Reset counters
chunk_tokens = []
chunk_tokens_nosot = []
chunk_logprobs = []
no_speech_prob = None
def hook_attention_weights(layer, ins, outs, index):
nonlocal segment_attweights
# In old version of whisper, output is a single tensor
assert isinstance(outs, tuple) and len(outs) == 2, "whisper seems to be outdated, please update it (pip install --upgrade --no-deps --force-reinstall git+https://github.com/openai/whisper.git)"
w = outs[-1]
# Only the last attention weights is useful
if w.shape[-2] > 1:
w = w[:, :, -1:, :]
segment_attweights[index].append(w)
def hook_mfcc(layer, ins, outs):
nonlocal new_mfcc
new_mfcc = ins[0]
def hook_input_tokens(layer, ins, outs):
nonlocal segment_tokens, sot_index, chunk_tokens, chunk_tokens_nosot, logit_filters, has_started, language, num_inference_steps
num_inference_steps += 1
curr_tokens = ins[0]
assert curr_tokens.shape[0] == 1, "Batch decoding is not supported"
curr_tokens = curr_tokens.squeeze(0)
if len(curr_tokens) > 1 or curr_tokens[0] == tokenizer.sot:
chunk_prompt = curr_tokens.tolist()
if not has_started and language is None:
if len(curr_tokens) == 1: # English model
language = "en"
else:
language = tokenizer.decode(curr_tokens[1:2])[2:-2]
whisper_options["language"] = language
if verbose and not whisper_options["verbose"] and len(curr_tokens) > 1:
# Reproduce whisper verbose (2/2)
print(f"Detected language: {whisper.tokenizer.LANGUAGES[language].title()}")
sys.stdout.flush()
logit_filters = get_logit_filters(model, whisper_options, prompt = chunk_prompt[1:-len(tokenizer.sot_sequence)])
may_flush_segment(curr_tokens)
# Keep the last token only
segment_tokens[-1].append(curr_tokens[-1].item())
# Get the index of the <|startoftranscript|> tokens (to get proba of silence later)
if len(curr_tokens) > 1 or curr_tokens[0] == tokenizer.sot:
has_started = True
if no_speech_threshold is not None:
sot_index = curr_tokens.tolist().index(tokenizer.sot)
else:
sot_index = None
# Accumulate tokens
if has_started:
chunk_tokens.append(curr_tokens)
if len(curr_tokens) == 1:
chunk_tokens_nosot.append(curr_tokens[-1].item())
else:
if verbose and not whisper_options["verbose"]:
# Reproduce whisper verbose (1/2)
print("Detecting language using up to the first 30 seconds. Use `--language` to specify the language")
embedding_weights = None
def hook_output_logits(layer, ins, outs):
nonlocal no_speech_prob, chunk_logprobs, segment_tokens, chunk_tokens, embedding_weights, has_started
if embedding_weights is None:
embedding_weights = torch.transpose(model.decoder.token_embedding.weight, 0, 1).to(outs[0].dtype)
# Get the probability of silence
if sot_index is not None:
logits = (outs[0][sot_index,:] @ embedding_weights).float()
logits = logits.softmax(dim=-1)
no_speech_prob = logits[tokenizer.no_speech].item()
# Get the log-probabilities of tokens (we don't know yet which one will be chosen)
if has_started:
logits = (outs[0][-1:,:] @ embedding_weights).float()
tokens = torch.cat(chunk_tokens).unsqueeze(0)
for logit_filter in logit_filters:
logit_filter.apply(logits, tokens)
logits = F.log_softmax(logits.squeeze(0), dim=-1)
chunk_logprobs.append(logits)
try:
# Add hooks to the model, to get tokens and attention weights on the fly
all_hooks = []
all_hooks.append(model.encoder.conv1.register_forward_hook(hook_mfcc))
all_hooks.append(model.decoder.token_embedding.register_forward_hook(hook_input_tokens))
for i, block in enumerate(model.decoder.blocks):
all_hooks.append(
block.cross_attn.register_forward_hook(
lambda layer, ins, outs, index=i: hook_attention_weights(layer, ins, outs, index))
)
if compute_word_confidence or no_speech_threshold is not None:
all_hooks.append(model.decoder.ln.register_forward_hook(hook_output_logits))
transcription = model.transcribe(audio, **whisper_options)
finally:
# Remove hooks
for hook in all_hooks:
hook.remove()
# Finalize (collect last segment)
may_flush_segment()
segment_tokens.pop(-1)
token_special_idx = min(token_sot, token_eot)
def filter_tokens(tokens):
while len(tokens) and tokens[0] >= token_special_idx:
tokens = tokens[1:]
while len(tokens) and tokens[-1] >= token_special_idx:
tokens = tokens[:-1]
return tokens
assert len(segment_tokens) == len(timestamped_word_segments), f"Inconsistent number of segments: tokens ({len(segment_tokens)}) != timestamped_word_segments ({len(timestamped_word_segments)})"
assert len(segment_avglogprobs) == len(segment_tokens), f"Inconsistent number of segments: avg logprobs ({len(segment_avglogprobs)}) != tokens ({len(segment_tokens)})"
assert len(segment_logprobs) == len(segment_tokens), f"Inconsistent number of segments: logprobs ({len(segment_logprobs)}) != tokens ({len(segment_tokens)})"
whisper_segments = transcription["segments"]
l1 = len(whisper_segments)
l2 = len(timestamped_word_segments)
if l1 != l2 and l1 != 0:
logger.warning(f"Inconsistent number of segments: whisper_segments ({l1}) != timestamped_word_segments ({l2})")
assert l1 == l2 or l1 == 0, f"Inconsistent number of segments: whisper_segments ({l1}) != timestamped_word_segments ({l2})"
logger.debug("Compile results")
words = []
for i, (segment, timestamped_words, token, avglogprob, logprobs) in enumerate(zip(whisper_segments, timestamped_word_segments, segment_tokens, segment_avglogprobs, segment_logprobs)):
timestamped_tokens = filter_tokens(token)
whisper_tokens = filter_tokens(segment["tokens"])
if timestamped_tokens != whisper_tokens:
if len(timestamped_tokens) == len(whisper_tokens) + 1:
logger.warn(f"An additional token was added on segment {i}")
else:
assert len(timestamped_tokens) < len(whisper_tokens) and timestamped_tokens == whisper_tokens[:len(timestamped_tokens)], \
f"Fatal Error: Got inconsistent text for segment {i}:\n({tokenizer.decode(timestamped_tokens)}) {timestamped_tokens}\n!=({len(whisper_tokens)}) \n{tokenizer.decode(whisper_tokens)}"
logger.warn(f"Text had to be shortned on segment {i}:\n{tokenizer.decode(timestamped_tokens)}\n!=\n{tokenizer.decode(whisper_tokens)}")
timestamped_words[-1]["avg_logprob_reliable"] = False
offset = segment["seek"] * HOP_LENGTH / SAMPLE_RATE
for timestamped_word in timestamped_words:
timestamped_word["start"] += offset
timestamped_word["end"] += offset
timestamped_word["idx_segment"] = i
if compute_word_confidence:
if "avg_logprob_reliable" not in timestamped_words[-1] or timestamped_words[-1]["avg_logprob_reliable"]:
if abs(segment["avg_logprob"] - avglogprob) >= 1e-2:
logger.warn(f"Recomputed different logprob for segment {i}: {avglogprob} != {segment['avg_logprob']}")
if include_punctuation_in_confidence:
segment["confidence"] = round_confidence(logprobs.mean().exp().item())
else:
logprobs_nopunc = []
i_end = 0
for timestamped_word in timestamped_words:
i_start = i_end
tokens = timestamped_word["tokens"]
i_end += len(tokens)
assert i_end <= len(logprobs), f"Fatal Error: Got out-of-bound index for segment {i}: {i_end} > {len(logprobs)}"
if include_punctuation_in_confidence:
word_logprobs = logprobs[i_start:i_end]
else:
tokens_str = [tokenizer.decode([t]) for t in tokens]
while len(tokens_str) > 1 and tokens_str[-1][-1] in _punctuation: # Note: look at the last character of token, to take into account "...", "!!", etc.
tokens_str = tokens_str[:-1]
tokens = tokens[:-1]
word_logprobs = logprobs[i_start:i_start + len(tokens)]
logprobs_nopunc.append(word_logprobs)
timestamped_word["confidence"] = round_confidence(word_logprobs.mean().exp().item())
if i_end != len(logprobs):
logger.warn(f"Got inconsistent length for segment {i} ({len(logprobs)} != {i_end}). Some words have been ignored.")
if not include_punctuation_in_confidence:
logprobs_nopunc = torch.cat(logprobs_nopunc)
segment["confidence"] = round_confidence(logprobs_nopunc.mean().exp().item())
words.extend(timestamped_words)
return transcription, words | PypiClean |
/Falmark-1.1.0-py3-none-any.whl/falmark4.py | import tkinter as tk
from tkinter import messagebox
from tkinter import simpledialog
import psycopg2
import webbrowser
USER_DATA_TABLE = "user_data"
entry_email = None
entry_budget = None
entry_product = None
entry_description = None
entry_developer_type = None
def get_user_input():
email = entry_email.get()
budget = float(entry_budget.get())
product = entry_product.get()
description = entry_description.get("1.0", tk.END).strip()
developer_type = entry_developer_type.get()
return email, budget, product, description, developer_type
def save_user_data(data):
conn = psycopg2.connect(
host="127.0.0.1",
port="5432",
database="postgres",
user="postgres",
password="fender123"
)
cur = conn.cursor()
cur.execute(f"CREATE TABLE IF NOT EXISTS {USER_DATA_TABLE} (email TEXT, budget FLOAT, product TEXT, description TEXT, developer_type TEXT);")
for user in data:
cur.execute(f"INSERT INTO {USER_DATA_TABLE} VALUES (%s, %s, %s, %s, %s);", (user["email"], user["budget"], user["product"], user["description"], user["developer_type"]))
conn.commit()
cur.close()
conn.close()
def load_user_data():
conn = psycopg2.connect(
host="127.0.0.1",
port="5432",
database="postgres",
user="postgres",
password="fender123"
)
cur = conn.cursor()
cur.execute(f"SELECT * FROM {USER_DATA_TABLE};")
data = cur.fetchall()
cur.close()
conn.close()
users = []
for user in data:
users.append({
"email": user[0],
"budget": user[1],
"product": user[2],
"description": user[3],
"developer_type": user[4]
})
return users
def match_developers (user_data):
conn = psycopg2.connect(
host="127.0.0.1",
port="5432",
database="postgres",
user="owner",
password="fender123"
)
cur = conn.cursor()
cur.execute(f"SELECT * FROM {USER_DATA_TABLE} WHERE budget >= %s AND LOWER(product) = LOWER(%s) AND LOWER(developer_type) = LOWER(%s);",
(user_data["budget"], user_data["product"], user_data["developer_type"]))
data = cur.fetchall()
cur.close()
conn.close()
matching_developers = []
for developer in data:
matching_developers.append({
"email": developer[0],
"budget": developer[1],
"product": developer[2],
"description": developer[3],
"developer_type": developer[4]
})
return matching_developers
def register_developer():
email, budget, product, description, developer_type = get_user_input()
user_data = {
"email": email,
"budget": budget,
"product": product,
"description": description,
"developer_type": developer_type
}
save_user_data([user_data])
messagebox.showinfo("Registration Successful", "You have been registered as a freelance developer.")
def register_client():
email, budget, product, description, developer_type = get_user_input()
user_data = {
"email": email,
"budget": budget,
"product": product,
"description": description,
"developer_type": developer_type
}
save_user_data([user_data])
messagebox.showinfo("Registration Successful", "You have been registered as a client searching for a developer.")
def find_developer():
user_email, user_budget, user_product, user_description, user_developer_type = get_user_input()
user_data = {
"email": user_email,
"budget": user_budget,
"product": user_product,
"description": user_description,
"marketing_type": user_developer_type
}
matching_developers = match_developers(user_data)
if matching_developers:
result = "Matching developers:\n"
for developer in matching_developers:
result += f"Email: {developer['email']}\n"
result += f"Description: {developer['description']}\n"
result += f"Marketing Type: {developer['developer_type']}\n\n"
messagebox.showinfo("Match Found", result)
selected_developer = simpledialog.askstring("Select developer", "Enter the email of the developer you want to message:")
if selected_developer:
message = simpledialog.askstring("Send Message", "Enter your message:")
if message:
messagebox.showinfo("Message Sent", "Your message has been sent.")
else:
messagebox.showinfo("Message Not Sent", "Please enter a message.")
else:
messagebox.showinfo("No Match", "No matching developer/client found.")
def view_profile():
email = entry_email.get()
users = load_user_data()
for user in users:
if user["email"] == email:
profile = f"Email: {user['email']}\n"
profile += f"Budget: {user['budget']}\n"
profile += f"Product: {user['product']}\n"
profile += f"Description: {user['description']}\n"
profile += f"developer type: {user['developer_type']}"
messagebox.showinfo("Profile", profile)
break
else:
messagebox.showinfo("Profile", "No profile found for the provided email.")
def open_help_website():
webbrowser.open("https://pencil13130.wixsite.com/falcon")
def main():
global entry_email, entry_budget, entry_product, entry_description, entry_developer_type
window = tk.Tk()
window.title("falmark. instant clinets.")
# Styling
window.configure(bg="#F5F5F5")
window.geometry("400x400")
window.resizable(False, False)
label_email = tk.Label(window, text="Email:", bg="#F5F5F5")
label_email.grid(row=0, column=0, pady=5)
entry_email = tk.Entry(window)
entry_email.grid(row=0, column=1, pady=5)
label_budget = tk.Label(window, text="Budget:", bg="#F5F5F5")
label_budget.grid(row=1, column=0, pady=5)
entry_budget = tk.Entry(window)
entry_budget.grid(row=1, column=1, pady=5)
label_product = tk.Label(window, text="your Project idea/service you provide:", bg="#F5F5F5")
label_product.grid(row=2, column=0, pady=5)
entry_product = tk.Entry(window)
entry_product.grid(row=2, column=1, pady=5)
label_description = tk.Label(window, text="Description:", bg="#F5F5F5")
label_description.grid(row=3, column=0, pady=5)
entry_description = tk.Text(window, height=4, width=20)
entry_description.grid(row=3, column=1, pady=5)
label_developer_type = tk.Label(window, text="Developer type:", bg="#F5F5F5")
label_developer_type.grid(row=4, column=0, pady=5)
entry_developer_type = tk.Entry(window)
entry_developer_type.grid(row=4, column=1, pady=5)
button_register_developer = tk.Button(window, text="Register as a developer", command=register_developer, width=20)
button_register_developer.grid(row=5, column=0, pady=10)
button_register_client = tk.Button(window, text="Register as a Client", command=register_client, width=20)
button_register_client.grid(row=5, column=1, pady=10)
button_find_developer = tk.Button(window, text="Find a developer or client", command=find_developer, width=20)
button_find_developer.grid(row=6, column=0, columnspan=2, pady=10)
button_view_profile = tk.Button(window, text="View Profile", command=view_profile, width=20)
button_view_profile.grid(row=7, column=0, columnspan=2, pady=10)
window.mainloop()
if __name__ == "__main__":
main() | PypiClean |
/GENDIS-1.0.14.tar.gz/GENDIS-1.0.14/gendis/other/example.ipynb | ```
import numpy as np
import pandas as pd
%matplotlib inline
import matplotlib.pyplot as plt
import sys
sys.path.append('..')
from data.load_all_datasets import load_data_train_test
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score
import warnings
warnings.filterwarnings('ignore')
np.random.seed(1337) # Random seed for reproducibility
# Load in all datasets and sort them by complexity
metadata = sorted(
load_data_train_test(),
key=lambda x: x['train']['n_samples']**2*x['train']['n_features']**3 # O(n**2 * m**3)
)
dataset = metadata[0] # Take the dataset which is expected to take the least long
# Read in the datafiles, split them into features and labels
train_df = pd.read_csv(dataset['train']['data_path'])
test_df = pd.read_csv(dataset['test']['data_path'])
X_train = train_df.drop('target', axis=1)
y_train = train_df['target']
X_test = test_df.drop('target', axis=1)
y_test = test_df['target']
# Map the labels to the range [0, ..., C-1] with C the number of classes
map_dict = {}
for j, c in enumerate(np.unique(y_train)):
map_dict[c] = j
y_train = y_train.map(map_dict)
y_test = y_test.map(map_dict)
# Convert everything to numpy arrays
X_train = X_train.values
X_test = X_test.values
y_train = y_train.values
y_test = y_test.values
```
# 1. Brute-force algorithm
```
from brute_force import BruteForceExtractor
bfe = BruteForceExtractor()
# Let's extract shapelets of a specific length, else it would take quite a while...
shapelets = bfe.extract(X_train, y_train, nr_shapelets=3, min_len=10, max_len=11)
plt.figure(figsize=(10, 5))
for shap in shapelets:
plt.plot(range(len(shap)), shap)
plt.show()
```
# 2. Fast Shapelets (a faster brute-force algorithm)
```
from fast import FastExtractor
fe = FastExtractor()
shapelets = fe.extract(X_train, y_train, nr_shapelets=3, min_len=10, max_len=11)
plt.figure(figsize=(10, 5))
for shap in shapelets:
plt.plot(range(len(shap)), shap)
plt.show()
```
# 3. SAX Shapelets (approximative algorithm with SAX representations)
```
from sax import SAXExtractor
se = SAXExtractor()
shapelets = se.extract(X_train, y_train, nr_shapelets=3, min_len=10, max_len=11)
plt.figure(figsize=(10, 5))
for shap in shapelets:
plt.plot(range(len(shap)), shap)
plt.show()
```
# 4. Particle Swarm Optimization (a bio-inspired algorithm)
```
from pso import ParticleSwarmExtractor
pse = ParticleSwarmExtractor()
shapelets = pse.extract(X_train, y_train)
plt.figure(figsize=(10, 5))
for shap in shapelets:
plt.plot(range(len(shap)), shap)
plt.show()
```
| PypiClean |
/JTdata-1.5.21-py3-none-any.whl/DataLoader/status.py | import os
import abc
import pandas as pd
from datetime import datetime
from .config import data_path,stk_uiverse
from .tools import print_func_time,to_intdate
aindex_member = os.path.join(data_path,r'AIndexMembers')
aindex_membercitics = os.path.join(data_path,r'AIndexMembersCITICS')
aindex_altermember = os.path.join(data_path,r'AIndexAlternativeMembers')
ashare_description = os.path.join(data_path,r'AShareDescription')
ashare_st = os.path.join(data_path,r'AShareST')
ashare_suspension = os.path.join(data_path,r'AShareTradingSuspension')
ashare_isparticipant = os.path.join(data_path,r'AShareISParticipant')
suntime_typedict = os.path.join(data_path,r'RPT_RATING_COMPARE')
cfutures_contract_mapping = os.path.join(data_path,r'CFuturesContractMapping')
ashare_idu_citics = os.path.join(data_path,r"AShareIndustriesClass_CITICS")
ashare_idu_cs = os.path.join(data_path,r"AShareIndustriesClass_CS")
ashare_idu_gics =os.path.join(data_path,r"AShareIndustriesClass_GICS")
ashare_idu_sw = os.path.join(data_path,r'AShareIndustriesClass_SW')
ashare_idu_wind = os.path.join(data_path,r'AShareIndustriesClass_WIND')
ashare_idu_code = os.path.join(data_path,r'AShareIndustriesCode')
class BaseStatusInfoProvider(abc.ABC):
@abc.abstractmethod
def get_status_data(self,instruments,fields,start_date,end_date):
raise NotImplementedError
class LocalIndexStatusProvider(BaseStatusInfoProvider):
""" index, stockcode, indate, outdate"""
def get_status_data(self,datapath,indexcode,start_date =None,end_date = None):
df = pd.read_hdf(os.path.join(datapath,'all.h5'),"data")
try:
df = df.loc[indexcode]
dfcp = df['outdate'].fillna(int(datetime.now().strftime("%Y%m%d")))
if (start_date is not None) & (end_date is not None):
start_date,end_date = to_intdate(start_date),to_intdate(end_date)
df = df.loc[(df.indate <= end_date)&(dfcp >= start_date)]
return df
except KeyError:
print('Index %s info not found'%indexcode)
return pd.DataFrame()
@print_func_time
def index_member(self,indexcode,start_date =None,end_date = None):
""" AIndexMembers """
return self.get_status_data(aindex_member,indexcode,start_date,end_date)
@print_func_time
def index_member_citics(self,indexcode,start_date =None,end_date = None):
""" AIndexMembersCITICS """
return self.get_status_data(aindex_membercitics,indexcode,start_date ,end_date)
@print_func_time
def index_member_alternative(self,indexcode,start_date =None,end_date = None):
"""AIndexAlternativeMembers"""
return self.get_status_data(aindex_altermember,indexcode,start_date ,end_date)
class LocalInstStatusProvider(BaseStatusInfoProvider):
""" index, stockcode, indate, outdate"""
def get_status_data(self,datapath,stkcodes,fields = None):
path = os.path.join(datapath,'all.h5')
df = pd.read_hdf(path,'data')
if stkcodes:
if isinstance(stkcodes,str):
stkcodes = [stkcodes,]
df = df.loc[df.index.isin(stkcodes)]
if fields:
df = df[fields]
df = df.dropna(how='all',axis=0)
return df
@print_func_time
def list_instrument(self,univ,start_date,end_date):
start_date,end_date = to_intdate(start_date),to_intdate(end_date)
if univ == 'all':
path = os.path.join(ashare_description,'all.h5')
df = pd.read_hdf(path,'data')
dfcp = df['delistdate'].fillna(int(datetime.now().strftime("%Y%m%d")))
if (start_date is not None) & (end_date is not None):
start_date,end_date = to_intdate(start_date),to_intdate(end_date)
df = df.loc[(df.listdate <= end_date)&(dfcp >= start_date)]
return df
else:
univ = stk_uiverse.get(univ)
IdxSP = LocalIndexStatusProvider()
return IdxSP.index_member(univ,start_date,end_date).set_index("stockcode")
@print_func_time
def ashare_ipodate(self,stkcode,fields = None):
""" AIndexMembers """
return self.get_status_data(ashare_description,stkcode,fields)
@print_func_time
def ashare_st(self,stkcode,fields = None):
""" AIndexMembers """
return self.get_status_data(ashare_st,stkcode,fields)
@print_func_time
def ashare_suspension(self,stkcode,fields = None):
""" AIndexMembers """
return self.get_status_data(ashare_suspension,stkcode,fields)
@print_func_time
def ashare_isparticipant(self,stkcode,fields = None):
""" AIndexMembers """
return self.get_status_data(ashare_isparticipant,stkcode,fields)
@print_func_time
def suntime_typedict(self,organcode,fields = None):
"""RPT_RATING_COMPARE"""
return self.get_status_data(suntime_typedict,organcode,fields)
@print_func_time
def cfutures_contract_mapping(self,organcode,fields = None):
"""CFUTURESCONTRACTMAPPING"""
return self.get_status_data(cfutures_contract_mapping,organcode,fields)
class LocalIndustryMemberProvider:
def get_indexmember(self,datapath,stockcode = None,level = None):
""" indexmenber reader """
path = os.path.join(datapath,'all.h5')
df = pd.read_hdf(path,'data')
if level:
df = df[[level, "entry_date", "remove_date"]]
if stockcode:
df = df.loc[stockcode]
return df
@print_func_time
def Industrycompo_citics(self,stockcode = None,level = None):
return self.get_indexmember(ashare_idu_citics,stockcode,level)
@print_func_time
def Industrycompo_sw(self,stockcode = None,level = None):
return self.get_indexmember(ashare_idu_sw,stockcode,level)
@print_func_time
def Industrycompo_cs(self,stockcode = None,level = None):
return self.get_indexmember(ashare_idu_cs,stockcode,level)
@print_func_time
def Industrycompo_gics(self,stockcode = None,level = None):
return self.get_indexmember(ashare_idu_gics,stockcode,level)
@print_func_time
def Industrycompo_wind(self,stockcode = None,level = None):
return self.get_indexmember(ashare_idu_wind,stockcode,level)
@print_func_time
def Industrycodes(self):
return pd.read_hdf(os.path.join(ashare_idu_code,"all.h5"),"data") | PypiClean |
/Heterogeneous_Highway_Env-0.0.3-py3-none-any.whl/Heteogeneous_Highway_Env/envs/common/graphics.py | import os
from typing import TYPE_CHECKING, Callable, List, Optional
import numpy as np
import pygame
from highway_env.envs.common.action import ActionType, DiscreteMetaAction, ContinuousAction
from highway_env.road.graphics import WorldSurface, RoadGraphics
from highway_env.vehicle.graphics import VehicleGraphics
if TYPE_CHECKING:
from highway_env.envs import AbstractEnv
from highway_env.envs.common.abstract import Action
class EnvViewer(object):
"""A viewer to render a highway driving environment."""
SAVE_IMAGES = False
def __init__(self, env: 'AbstractEnv', config: Optional[dict] = None) -> None:
self.env = env
self.config = config or env.config
self.offscreen = self.config["offscreen_rendering"]
pygame.init()
pygame.display.set_caption("Highway-env")
panel_size = (self.config["screen_width"], self.config["screen_height"])
# A display is not mandatory to draw things. Ignoring the display.set_mode()
# instruction allows the drawing to be done on surfaces without
# handling a screen display, useful for e.g. cloud computing
if not self.offscreen:
self.screen = pygame.display.set_mode([self.config["screen_width"], self.config["screen_height"]])
self.sim_surface = WorldSurface(panel_size, 0, pygame.Surface(panel_size))
self.sim_surface.scaling = self.config.get("scaling", self.sim_surface.INITIAL_SCALING)
self.sim_surface.centering_position = self.config.get("centering_position", self.sim_surface.INITIAL_CENTERING)
self.clock = pygame.time.Clock()
self.enabled = True
if os.environ.get("SDL_VIDEODRIVER", None) == "dummy":
self.enabled = False
self.observer_vehicle = None
self.agent_display = None
self.agent_surface = None
self.vehicle_trajectory = None
self.frame = 0
self.directory = None
def set_agent_display(self, agent_display: Callable) -> None:
"""
Set a display callback provided by an agent
So that they can render their behaviour on a dedicated agent surface, or even on the simulation surface.
:param agent_display: a callback provided by the agent to display on surfaces
"""
if self.agent_display is None:
if not self.offscreen:
if self.config["screen_width"] > self.config["screen_height"]:
self.screen = pygame.display.set_mode((self.config["screen_width"],
2 * self.config["screen_height"]))
else:
self.screen = pygame.display.set_mode((2 * self.config["screen_width"],
self.config["screen_height"]))
self.agent_surface = pygame.Surface((self.config["screen_width"], self.config["screen_height"]))
self.agent_display = agent_display
def set_agent_action_sequence(self, actions: List['Action']) -> None:
"""
Set the sequence of actions chosen by the agent, so that it can be displayed
:param actions: list of action, following the env's action space specification
"""
if isinstance(self.env.action_type, DiscreteMetaAction):
actions = [self.env.action_type.actions[a] for a in actions]
if len(actions) > 1:
self.vehicle_trajectory = self.env.vehicle.predict_trajectory(actions,
1 / self.env.config["policy_frequency"],
1 / 3 / self.env.config["policy_frequency"],
1 / self.env.config["simulation_frequency"])
def handle_events(self) -> None:
"""Handle pygame events by forwarding them to the display and environment vehicle."""
for event in pygame.event.get():
if event.type == pygame.QUIT:
self.env.close()
self.sim_surface.handle_event(event)
if self.env.action_type:
EventHandler.handle_event(self.env.action_type, event)
def display(self) -> None:
"""Display the road and vehicles on a pygame window."""
if not self.enabled:
return
self.sim_surface.move_display_window_to(self.window_position())
RoadGraphics.display(self.env.road, self.sim_surface)
if self.vehicle_trajectory:
VehicleGraphics.display_trajectory(
self.vehicle_trajectory,
self.sim_surface,
offscreen=self.offscreen)
RoadGraphics.display_road_objects(
self.env.road,
self.sim_surface,
offscreen=self.offscreen
)
if self.agent_display:
self.agent_display(self.agent_surface, self.sim_surface)
if not self.offscreen:
if self.config["screen_width"] > self.config["screen_height"]:
self.screen.blit(self.agent_surface, (0, self.config["screen_height"]))
else:
self.screen.blit(self.agent_surface, (self.config["screen_width"], 0))
RoadGraphics.display_traffic(
self.env.road,
self.sim_surface,
simulation_frequency=self.env.config["simulation_frequency"],
offscreen=self.offscreen)
ObservationGraphics.display(self.env.observation_type, self.sim_surface)
if not self.offscreen:
self.screen.blit(self.sim_surface, (0, 0))
if self.env.config["real_time_rendering"]:
self.clock.tick(self.env.config["simulation_frequency"])
pygame.display.flip()
if self.SAVE_IMAGES and self.directory:
pygame.image.save(self.sim_surface, str(self.directory / "highway-env_{}.png".format(self.frame)))
self.frame += 1
def get_image(self) -> np.ndarray:
"""
The rendered image as a rgb array.
OpenAI gym's channel convention is H x W x C
"""
surface = self.screen if self.config["render_agent"] and not self.offscreen else self.sim_surface
data = pygame.surfarray.array3d(surface) # in W x H x C channel convention
return np.moveaxis(data, 0, 1)
def window_position(self) -> np.ndarray:
"""the world position of the center of the displayed window."""
if self.observer_vehicle:
return self.observer_vehicle.position
elif self.env.vehicle:
return self.env.vehicle.position
else:
return np.array([0, 0])
def close(self) -> None:
"""Close the pygame window."""
pygame.quit()
class EventHandler(object):
@classmethod
def handle_event(cls, action_type: ActionType, event: pygame.event.EventType) -> None:
"""
Map the pygame keyboard events to control decisions
:param action_type: the ActionType that defines how the vehicle is controlled
:param event: the pygame event
"""
if isinstance(action_type, DiscreteMetaAction):
cls.handle_discrete_action_event(action_type, event)
elif action_type.__class__ == ContinuousAction:
cls.handle_continuous_action_event(action_type, event)
@classmethod
def handle_discrete_action_event(cls, action_type: DiscreteMetaAction, event: pygame.event.EventType) -> None:
if event.type == pygame.KEYDOWN:
if event.key == pygame.K_RIGHT and action_type.longitudinal:
action_type.act(action_type.actions_indexes["FASTER"])
if event.key == pygame.K_LEFT and action_type.longitudinal:
action_type.act(action_type.actions_indexes["SLOWER"])
if event.key == pygame.K_DOWN and action_type.lateral:
action_type.act(action_type.actions_indexes["LANE_RIGHT"])
if event.key == pygame.K_UP:
action_type.act(action_type.actions_indexes["LANE_LEFT"])
@classmethod
def handle_continuous_action_event(cls, action_type: ContinuousAction, event: pygame.event.EventType) -> None:
action = action_type.last_action.copy()
steering_index = action_type.space().shape[0] - 1
if event.type == pygame.KEYDOWN:
if event.key == pygame.K_RIGHT and action_type.lateral:
action[steering_index] = 0.7
if event.key == pygame.K_LEFT and action_type.lateral:
action[steering_index] = -0.7
if event.key == pygame.K_DOWN and action_type.longitudinal:
action[0] = -0.7
if event.key == pygame.K_UP and action_type.longitudinal:
action[0] = 0.7
elif event.type == pygame.KEYUP:
if event.key == pygame.K_RIGHT and action_type.lateral:
action[steering_index] = 0
if event.key == pygame.K_LEFT and action_type.lateral:
action[steering_index] = 0
if event.key == pygame.K_DOWN and action_type.longitudinal:
action[0] = 0
if event.key == pygame.K_UP and action_type.longitudinal:
action[0] = 0
action_type.act(action)
class ObservationGraphics(object):
COLOR = (0, 0, 0)
@classmethod
def display(cls, obs, sim_surface):
from highway_env.envs.common.observation import LidarObservation
if isinstance(obs, LidarObservation):
cls.display_grid(obs, sim_surface)
@classmethod
def display_grid(cls, lidar_observation, surface):
psi = np.repeat(np.arange(-lidar_observation.angle/2,
2 * np.pi - lidar_observation.angle/2,
2 * np.pi / lidar_observation.grid.shape[0]), 2)
psi = np.hstack((psi[1:], [psi[0]]))
r = np.repeat(np.minimum(lidar_observation.grid[:, 0], lidar_observation.maximum_range), 2)
points = [(surface.pos2pix(lidar_observation.origin[0] + r[i] * np.cos(psi[i]),
lidar_observation.origin[1] + r[i] * np.sin(psi[i])))
for i in range(np.size(psi))]
pygame.draw.lines(surface, ObservationGraphics.COLOR, True, points, 1) | PypiClean |
/Docassemble-Flask-User-0.6.28.tar.gz/Docassemble-Flask-User-0.6.28/README.rst | Flask-User v0.6
===============
Modified for Docassemble.
.. attention::
The documentation has moved to http://flask-user.readthedocs.io/en/v0.6
User Authentication and Management
----------------------------------
| So, you're writing a Flask web application and would like to authenticate your users.
| You start with a simple **Login** page, but soon enough you'll need to handle:
* **Registrations** and **Email Confirmations**
* **Change Usernames**, **Change Passwords**, and **Forgotten Passwords**
And wouldn't it be nice to also offer:
* **Added security**
* **Increased reliability**
* **Role-based Authorization**
* **Internationalization**
* **Support for multiple emails per user**
| Flask-User offers these features and more.
Customizable, yet Ready to use
------------------------------
* **Largely Configurable** -- By overriding configuration settings.
* **Almost fully Customizable** -- By overriding functions and properties.
* **Ready to use** -- Through sensible defaults.
* Supports **SQL Databases** and **MongoDB Databases**.
* **Event hooking** -- Through efficient signals.
Secure and Reliable
-------------------
* **Secure** -- Built on top of widely deployed Passlib, PyCrypto, ItsDangerous.
* **Reliable** -- Code coverage of over 90%
* **Available** -- Tested on Python 2.6, 2.7 and 3.3-3.6
Well documented
---------------
- `Flask-User v0.6 documentation <http://flask-user.readthedocs.io/en/v0.6/>`_
- `Flask-User v0.5 documentation <http://flask-user.readthedocs.io/en/v0.5/>`_
Comes with translations
-----------------------
Chinese, Dutch, English, Farsi, Finnish, French, German, Italian, Russian, Spanish, Swedish, and Turkish
Alternatives
------------
* `Flask-Login <https://flask-login.readthedocs.org/en/latest/>`_
* `Flask-Security <https://pythonhosted.org/Flask-Security/>`_
Authors
-------
| **Lead developer and Maintainer**
| Ling Thio -- ling.thio AT gmail DOT com
|
| **Contributors**
| `Many contributors <https://github.com/lingthio/Flask-User/graphs/contributors>`_
| PypiClean |
/Djaloha-0.4.2.tar.gz/Djaloha-0.4.2/djaloha/static/aloha.0.20/lib/aloha/sidebar.js | * Aloha Editor is free software: you can redistribute it and/or modify
* it under the terms of the GNU Affero General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.*
*
* Aloha Editor is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Affero General Public License for more details.
*
* You should have received a copy of the GNU Affero General Public License
* along with this program. If not, see <http://www.gnu.org/licenses/>.
*/
/**
* @todo: - Make the sidebars resizable using drag handles
* - Make overlayPage setting settable from external config
*/
define( [
'aloha/core',
'aloha/jquery',
'aloha/selection'
// 'aloha/plugin' // For when we plugify sidebar
], function ( Aloha, jQuery, Selection, Plugin ) {
var $ = jQuery;
var undefined = void 0;
// Pseudo-namespace prefix for Sidebar elements
// Rational:
// We use a prefix instead of an enclosing class or id because we need to
// be paranoid of unintended style inheritance in an environment like the
// one in which Aloha-Editor operates in, with its numerous custom plugins.
// eg: .inner or .btn can be used in several plugins, with eaching adding
// to the class styles properties that we don't want.
var ns = 'aloha-sidebar';
var uid = +( new Date );
// namespaced classnames
var nsClasses = {
'bar' : nsClass( 'bar' ),
'handle' : nsClass( 'handle' ),
'inner' : nsClass( 'inner' ),
'panels' : nsClass( 'panels' ),
'config-btn' : nsClass( 'config-btn' ),
'handle-icon' : nsClass( 'handle-icon' ),
'panel-content' : nsClass( 'panel-content' ),
'panel-content-inner' : nsClass( 'panel-content-inner' ),
'panel-content-inner-text' : nsClass( 'panel-content-inner-text' ),
'panel-title' : nsClass( 'panel-title' ),
'panel-title-arrow' : nsClass( 'panel-title-arrow' ),
'panel-title-text' : nsClass( 'panel-title-text' )
};
// Extend jQuery easing animations
if ( !jQuery.easing.easeOutExpo ) {
jQuery.extend(jQuery.easing, {
easeOutExpo: function (x, t, b, c, d) {
return (t==d)?b+c:c*(-Math.pow(2,-10*t/d)+1)+b;
},
easeOutElastic: function (x, t, b, c, d) {
var m=Math,s=1.70158,p=0,a=c;
if(!t)return b;
if((t/=d)==1)return b+c;
if(!p)p=d*.3;
if(a<m.abs(c)){a=c;var s=p/4;}else var s=p/(2*m.PI)*m.asin(c/a);
return a*m.pow(2,-10*t)*m.sin((t*d-s)*(2*m.PI)/p)+c+b;
}
});
}
// ------------------------------------------------------------------------
// Local (helper) functions
// ------------------------------------------------------------------------
/**
* Simple templating
*
* @param {String} str - The string containing placeholder keys in curly
* brackets
* @param {Object} obj - Associative array of replacing placeholder keys
* with corresponding values
*/
function supplant ( str, obj ) {
return str.replace( /\{([a-z0-9\-\_]+)\}/ig, function ( str, p1, offset, s ) {
var replacement = obj[ p1 ] || str;
return ( typeof replacement == 'function' ) ? replacement() : replacement;
} );
};
/**
* Wrapper to call the supplant method on a given string, taking the
* nsClasses object as the associative array containing the replacement
* pairs
*
* @param {String} str
* @return {String}
*/
function renderTemplate ( str ) {
return ( typeof str == 'string' ) ? supplant( str, nsClasses ) : str;
};
/**
* Generates a selector string with this plugins's namespace prefixed the
* each classname
*
* Usage:
* nsSel('header,', 'main,', 'foooter ul')
* will return
* ".aloha-myplugin-header, .aloha-myplugin-main, .aloha-mypluzgin-footer ul"
*
* @return {String}
*/
function nsSel () {
var strBldr = [], prx = ns;
jQuery.each( arguments, function () {
strBldr.push( '.' + ( this == '' ? prx : prx + '-' + this ) );
} );
return jQuery.trim( strBldr.join( ' ' ) );
};
/**
* Generates a string with this plugins's namespace prefixed the each
* classname
*
* Usage:
* nsClass('header', 'innerheaderdiv')
* will return
* "aloha-myplugin-header aloha-myplugin-innerheaderdiv"
*
* @return {String}
*/
function nsClass () {
var strBldr = [], prx = ns;
jQuery.each( arguments, function () {
strBldr.push( this == '' ? prx : prx + '-' + this );
} );
return jQuery.trim( strBldr.join(' ') );
};
// ------------------------------------------------------------------------
// Sidebar constructor
// Only instance properties are to be defined here
// ------------------------------------------------------------------------
var Sidebar = function Sidebar ( opts ) {
var sidebar = this;
this.id = nsClass( ++uid );
this.panels = {};
this.container = jQuery( renderTemplate(
'<div class="{bar}">' +
'<div class="{handle}">' +
'<span class="{handle-icon}"></span>' +
'</div>' +
'<div class="{inner}">' +
'<ul class="{panels}"></ul>' +
'</div>' +
'</div>'
) );
// defaults
this.width = 300;
this.opened = false;
this.isOpen = false;
this.settings = {
// We automatically set this to true when we are in IE, where rotating
// elements using filters causes undesirable rendering ugliness.
// Our solution is to fallback to swapping icon images.
// We set this as a sidebar property so that it can overridden by
// whoever thinks they are smarter than we are.
rotateIcons : !jQuery.browser.msie,
overlayPage : true
};
// Initialize after dom is ready
jQuery( function () {
if ( !( ( typeof Aloha.settings.sidebar != 'undefined' ) &&
Aloha.settings.sidebar.disabled ) ) {
sidebar.init( opts );
}
} );
};
// ------------------------------------------------------------------------
// Sidebar prototype
// All properties to be shared across Sidebar instances can be placed in
// the prototype object
// ------------------------------------------------------------------------
jQuery.extend(Sidebar.prototype, {
// Build as much of the sidebar as we can before appending it to DOM to
// minimize reflow.
init: function (opts) {
var that = this;
var panels;
// Pluck panels list from opts
if (typeof opts == 'object') {
panels = opts.panels;
delete opts.panels;
}
// Copy any implements, and overrides in opts to this Sidebar instance
jQuery.extend(this, opts);
if (typeof panels == 'object') {
jQuery.each(panels, function () {
that.addPanel(this, true);
});
}
var bar = this.container;
if (this.position == 'right') {
bar.addClass(nsClass('right'));
}
// Place the bar into the DOM
bar.hide()
.appendTo(jQuery('body'))
.click(function () {that.barClicked.apply(that, arguments);})
.find(nsSel('panels')).width(this.width);
// IE7 needs us to explicitly set the container width, since it is
// unable to determine it on its own
bar.width(this.width);
this.width = bar.width();
jQuery(window).resize(function () {
that.updateHeight();
});
this.updateHeight();
this.roundCorners();
this.initToggler();
this.container.css(this.position == 'right' ? 'marginRight' : 'marginLeft', -this.width);
if (this.opened) {
this.open(0);
}
this.toggleHandleIcon(this.isOpen);
this.subscribeToEvents();
jQuery(window).resize(function () {
that.correctHeight();
});
this.correctHeight();
},
show: function () {
this.container.css( 'display', 'block' );
//.animate({opacity: 1}, 1000);
return this;
},
hide: function () {
this.container.css( 'display','none' );
// .animate({opacity: 0}, 1000, function () {
// jQuery(this).css('display', 'block')
// });
return this;
},
/**
* Determines the effective elements at the current selection.
* Iterates through all panels and checks whether the panel should be
* activated for any of the effective elements in the selection.
*
* @param {Object} range - The Aloha.RangeObject
*/
checkActivePanels: function( range ) {
var effective = [];
if ( typeof range != 'undefined' &&
typeof range.markupEffectiveAtStart != 'undefined' ) {
var l = range.markupEffectiveAtStart.length;
for ( var i = 0; i < l; ++i ) {
effective.push( jQuery( range.markupEffectiveAtStart[ i ] ) );
}
}
var that = this;
jQuery.each( this.panels, function () {
that.showActivePanel( this, effective );
} );
this.correctHeight();
},
subscribeToEvents: function () {
var that = this;
var $container = this.container;
Aloha.bind( 'aloha-selection-changed', function( event, range ) {
that.checkActivePanels( range );
} );
$container.mousedown( function( e ) {
e.originalEvent.stopSelectionUpdate = true;
Aloha.eventHandled = true;
//e.stopSelectionUpdate = true;
} );
$container.mouseup( function ( e ) {
e.originalEvent.stopSelectionUpdate = true;
Aloha.eventHandled = false;
} );
Aloha.bind( 'aloha-editable-deactivated', function ( event, params ) {
that.checkActivePanels();
} );
},
/**
* Dynamically set appropriate heights for panels.
* The height for each panel is determined by the amount of space that
* is available in the viewport and the number of panels that need to
* share that space.
*/
correctHeight: function () {
var height = this.container.find(nsSel('inner')).height() - (15 * 2);
var panels = [];
jQuery.each(this.panels, function () {
if (this.isActive) {
panels.push(this);
}
});
if (panels.length == 0) {
return;
}
var remainingHeight = height - ((panels[0].title.outerHeight() + 10) * panels.length);
var panel;
var targetHeight;
var panelInner;
var panelText;
var undone;
var toadd = 0;
var math = Math; // Local reference for quicker lookup
while (panels.length > 0 && remainingHeight > 0) {
remainingHeight += toadd;
toadd = 0;
undone = [];
for (var j = panels.length - 1; j >= 0; --j) {
panel = panels[j];
panelInner = panel.content.find(nsSel('panel-content-inner'));
targetHeight = math.min(
panelInner.height('auto').height(),
math.floor(remainingHeight / (j + 1))
);
panelInner.height(targetHeight);
remainingHeight -= targetHeight;
panelText = panelInner.find(nsSel('panel-content-inner-text'));
if (panelText.height() > targetHeight) {
undone.push(panel);
toadd += targetHeight;
panelInner.css({
'overflow-x': 'hidden',
'overflow-y': 'scroll'
});
} else {
panelInner.css('overflow-y', 'hidden');
}
if (panel.expanded) {
panel.expand();
}
}
panels = undone;
}
},
/**
* Checks whether this panel should be activated (ie: made visible) for
* any of the elements specified in a given list of elements.
*
* We have to add a null object to the list of elements to allow us to
* check whether the panel should be visible when we have no effective
* elements in the current selection
*
* @param {Object} panel - The Panel object we will test
* @param {Array} elements - The effective elements (jQuery), any of
* which may activate the panel
*/
showActivePanel: function (panel, elements) {
elements.push(null);
var j = elements.length;
var count = 0;
var li = panel.content.parent('li');
var activeOn = panel.activeOn;
var effective = jQuery();
for (var i = 0; i < j; ++i) {
if (activeOn(elements[i])) {
++count;
if (elements[i]) {
jQuery.merge(effective, elements[i]);
}
}
}
if (count) {
panel.activate(effective);
} else {
panel.deactivate();
}
this.roundCorners();
},
/**
* Sets up the functionality, event listeners, and animation of the
* sidebar handle
*/
initToggler: function () {
var that = this;
var bar = this.container;
var icon = bar.find(nsSel('handle-icon'));
var toggledClass = nsClass('toggled');
var bounceTimer;
var isRight = (this.position == 'right');
if (this.opened) {
this.rotateHandleArrow(isRight ? 0 : 180, 0);
}
// configure the position of the sidebar handle
jQuery( function () {
if ( typeof Aloha.settings.sidebar != 'undefined' &&
Aloha.settings.sidebar.handle &&
Aloha.settings.sidebar.handle.top ) {
jQuery(bar.find(nsSel('handle'))).get(0).style.top = Aloha.settings.sidebar.handle.top;
}
} );
bar.find(nsSel('handle'))
.click(function () {
if (bounceTimer) {
clearInterval(bounceTimer);
}
icon.stop().css('marginLeft', 4);
if (that.isOpen) {
jQuery(this).removeClass(toggledClass);
that.close();
that.isOpen = false;
} else {
jQuery(this).addClass(toggledClass);
that.open();
that.isOpen = true;
}
}).hover(
function () {
var flag = that.isOpen ? -1 : 1;
if (bounceTimer) {
clearInterval(bounceTimer);
}
icon.stop();
jQuery(this).stop().animate(
isRight ? {marginLeft: '-=' + (flag * 5)} : {marginRight: '-=' + (flag * 5)},
200
);
bounceTimer = setInterval(function () {
flag *= -1;
icon.animate(
isRight ? {left: '-=' + (flag * 4)} : {right: '-=' + (flag * 4)},
300
);
}, 300);
},
function () {
if (bounceTimer) {
clearInterval(bounceTimer);
}
icon.stop().css(isRight ? 'left' : 'right', 5);
jQuery(this).stop().animate(
isRight ? {marginLeft: 0} : {marginRight: 0},
600, 'easeOutElastic'
);
}
);
},
/**
* Rounds the top corners of the first visible panel, and the bottom
* corners of the last visible panel elements in the panels ul list
*/
roundCorners: function () {
var bar = this.container;
var lis = bar.find(nsSel('panels>li:not(', 'deactivated)'));
var topClass = nsClass('panel-top');
var bottomClass = nsClass('panel-bottom');
bar.find(nsSel('panel-top,', 'panel-bottom'))
.removeClass(topClass)
.removeClass(bottomClass);
lis.first().find(nsSel('panel-title')).addClass(topClass);
lis.last().find(nsSel('panel-content')).addClass(bottomClass);
},
/**
* Updates the height of the inner div of the sidebar. This is done
* whenever the viewport is resized
*/
updateHeight: function () {
var h = jQuery(window).height();
this.container.height(h).find(nsSel('inner')).height(h);
},
/**
* Delegate all sidebar onclick events to the container.
* Then use handleBarclick method until we bubble up to the first
* significant element that we can interact with
*/
barClicked: function (ev) {
this.handleBarclick(jQuery(ev.target));
},
/**
* We handle all click events on the sidebar from here--dispatching
* calls to which ever methods that should be invoked for the each
* interaction
*/
handleBarclick: function (el) {
if (el.hasClass(nsClass('panel-title'))) {
this.togglePanel(el);
} else if (el.hasClass(nsClass('panel-content'))) {
// Aloha.Log.log('Content clicked');
} else if (el.hasClass(nsClass('handle'))) {
// Aloha.Log.log('Handle clicked');
} else if (el.hasClass(nsClass('bar'))) {
// Aloha.Log.log('Sidebar clicked');
} else {
this.handleBarclick(el.parent());
}
},
getPanelById: function (id) {
return this.panels[id];
},
getPanelByElement: function (el) {
var li = (el[0].tagName == 'LI') ? el : el.parent('li');
return this.getPanelById(li[0].id);
},
togglePanel: function (el) {
this.getPanelByElement(el).toggle();
},
/**
* Animation to rotate the sidebar arrow
*
* @param {Number} angle - The angle two which the arrow should rotate
* (0 or 180)
* @param {Number|String} duration - (Optional) How long the animation
* should play for
*/
rotateHandleIcon: function (angle, duration) {
var arr = this.container.find(nsSel('handle-icon'));
arr.animate({angle: angle}, {
duration : (typeof duration == 'number' || typeof duration == 'string') ? duration : 500,
easing : 'easeOutExpo',
step : function (val, fx) {
arr.css({
'-o-transform' : 'rotate(' + val + 'deg)',
'-webkit-transform' : 'rotate(' + val + 'deg)',
'-moz-transform' : 'rotate(' + val + 'deg)',
'-ms-transform' : 'rotate(' + val + 'deg)'
// We cannot use Microsoft Internet Explorer filters
// because Microsoft Internet Explore 8 does not support
// Microsoft Internet Explorer filters correctly. It
// breaks the layout
// filter : 'progid:DXImageTransform.Microsoft.BasicImage(rotation=' + (angle / 90) + ')'
});
}
});
},
/**
* Sets the handle icon to the "i am opened, click me to close the
* sidebar" state, or vice versa. The direction of the arrow depends
* on whether the sidebar is on the left or right, and whether it is
* in an opened state or not.
*
* Question:
* Given that the arrow icon is by default pointing right, should
* we make it point left?
*
* Answer:
* isRight & isOpen : no
* isRight & isClosed : yes
* isLeft & isOpen : yes
* isLeft & isClosed : no
*
* Truth table:
* isRight | isOpen | XOR
* ---------+--------+-----
* T | T | F
* T | F | T
* F | T | T
* F | F | F
*
* Therefore:
* isPointingLeft = isRight XOR isOpen
*
* @param {Boolean} isOpened - Whether or not the sidebar is in the
* opened state
*/
toggleHandleIcon: function (isOpen) {
var isPointingLeft = (this.position == 'right') ^ isOpen;
if (this.settings.rotateIcons) {
this.rotateHandleIcon(isPointingLeft ? 180 : 0, 0);
} else {
var icon = this.container.find(nsSel('handle-icon'));
if (isPointingLeft) {
icon.addClass(nsClass('handle-icon-left'));
} else {
icon.removeClass(nsClass('handle-icon-left'));
}
}
},
/**
* Slides the sidebar into view
*/
open: function (duration, callback) {
if (this.isOpen) {
return this;
}
var isRight = (this.position == 'right');
var anim = isRight ? {marginRight: 0} : {marginLeft: 0};
this.toggleHandleIcon(true);
this.container.animate(
anim,
(typeof duration == 'number' || typeof duration == 'string')
? duration : 500,
'easeOutExpo'
);
if (!this.settings.overlayPage) {
jQuery('body').animate(
isRight ? {marginRight: '+=' + this.width} : {marginLeft: '+=' + this.width},
500, 'easeOutExpo'
);
}
this.isOpen = true;
jQuery('body').trigger(nsClass('opened'), this);
return this;
},
/**
* Slides that sidebar out of view
*/
close: function (duration, callback) {
if (!this.isOpen) {
return this;
}
var isRight = (this.position == 'right');
var anim = isRight ? {marginRight: -this.width} : {marginLeft: -this.width};
this.toggleHandleIcon(false);
this.container.animate(
anim,
(typeof duration == 'number' || typeof duration == 'string')
? duration : 500,
'easeOutExpo'
);
if (!this.settings.overlayPage) {
jQuery('body').animate(
isRight ? {marginRight: '-=' + this.width} : {marginLeft: '-=' + this.width},
500, 'easeOutExpo'
);
}
this.isOpen = false;
return this;
},
/**
* Activates the given panel and passes to it the given element as the
* the effective that we want it to think activated it.
*
* @param {Object|String} panel - Panel instance or the id of a panel
* object
* @param {jQuery} element - Element to pass to the panel as effective
* element (the element that activated it)
*/
activatePanel: function (panel, element) {
if (typeof panel == 'string') {
panel = this.getPanelById(panel);
}
if (panel){
panel.activate(element);
}
this.roundCorners();
return this;
},
/**
* Invokes the expand method for the given panel so that it expands its
* height to display its contents
*
* @param {Object|String} panel - Panel instance or the id of a panel
* object
* @param {Funtion} callback
*/
expandPanel: function (panel, callback) {
if (typeof panel == 'string') {
panel = this.getPanelById(panel);
}
if (panel){
panel.expand(callback);
}
return this;
},
/**
* Collapses the panel contents by invoking the given panel's collapse
* method.
*
* @param {Object|String} panel - Panel instance or the id of a panel
* object
* @param {Funtion} callback
*/
collapsePanel: function (panel, callback) {
if (typeof panel == 'string') {
panel = this.getPanelById(panel);
}
if (panel){
panel.collapse(callback);
}
return this;
},
/**
* Adds a panel to this sidebar instance.
* We try and build as much of the panel DOM as we can before inserting
* it into the DOM in order to reduce reflow.
*
* @param {Object} panel - either a panel instance or an associative
* array containing settings for the construction
* of a new panel.
* @param {Boolean} deferRounding - (Optional) If true, the rounding-off
* of the top most and bottom most panels
* will not be automatically done. Set
* this to true when adding a lot of panels
* at once.
* @return {Object} - The newly created panel.
*/
addPanel: function (panel, deferRounding) {
if (!(panel instanceof Panel)) {
if (!panel.width) {
panel.width = this.width;
}
panel.sidebar = this;
panel = new Panel(panel);
}
this.panels[panel.id] = panel;
this.container.find(nsSel('panels')).append(panel.element);
if (deferRounding !== true) {
this.roundCorners();
}
this.checkActivePanels(Selection.getRangeObject());
return panel;
}
});
// ------------------------------------------------------------------------
// Panel constructor
// ------------------------------------------------------------------------
var Panel = function Panel (opts) {
this.id = null;
this.folds = {};
this.button = null;
this.title = jQuery(renderTemplate(' \
<div class="{panel-title}"> \
<span class="{panel-title-arrow}"></span> \
<span class="{panel-title-text}">Untitled</span> \
</div> \
'));
this.content = jQuery(renderTemplate(' \
<div class="{panel-content}"> \
<div class="{panel-content-inner}"> \
<div class="{panel-content-inner-text}">\
</div> \
</div> \
</div> \
'));
this.element = null;
this.expanded = false;
this.effectiveElement = null;
this.isActive = true;
this.init(opts);
};
// ------------------------------------------------------------------------
// Panel prototype
// ------------------------------------------------------------------------
jQuery.extend(Panel.prototype, {
init: function (opts) {
this.setTitle(opts.title)
.setContent(opts.content);
delete opts.title;
delete opts.content;
jQuery.extend(this, opts);
if (!this.id) {
this.id = nsClass(++uid);
}
var li = this.element =
jQuery('<li id="' +this.id + '">')
.append(this.title, this.content);
if (this.expanded){
this.content.height('auto');
}
this.toggleTitleIcon(this.expanded);
this.coerceActiveOn();
// Disable text selection on title element
this.title
.attr('unselectable', 'on')
.css('-moz-user-select', 'none')
.each(function() {this.onselectstart = function() {return false;};});
if (typeof this.onInit == 'function') {
this.onInit.apply(this);
}
},
/**
* @param {Boolean} isExpanded - Whether or not the panel is in an
* expanded state
*/
toggleTitleIcon: function (isExpanded) {
if (this.sidebar.settings.rotateIcons) {
this.rotateTitleIcon(isExpanded ? 90 : 0);
} else {
var icon = this.title.find(nsSel('panel-title-arrow'));
if (isExpanded) {
icon.addClass(nsClass('panel-title-arrow-down'));
} else {
icon.removeClass(nsClass('panel-title-arrow-down'));
}
}
},
/**
* Normalizes the activeOn property into a predicate function
*/
coerceActiveOn: function () {
if (typeof this.activeOn != 'function') {
var activeOn = this.activeOn;
this.activeOn = (function () {
var typeofActiveOn = typeof activeOn,
fn;
if (typeofActiveOn == 'boolean') {
fn = function () {
return activeOn;
};
} else if (typeofActiveOn == 'undefined') {
fn = function () {
return true;
};
} else if (typeofActiveOn == 'string') {
fn = function (el) {
return el ? el.is(activeOn) : false;
};
} else {
fn = function () {
return false;
};
}
return fn;
})();
}
},
/**
* Activates (displays) this panel
*/
activate: function (effective) {
this.isActive = true;
this.content.parent('li').show().removeClass(nsClass('deactivated'));
this.effectiveElement = effective;
if (typeof this.onActivate == 'function') {
this.onActivate.call(this, effective);
}
},
/**
* Hides this panel
*/
deactivate: function () {
this.isActive = false;
this.content.parent('li').hide().addClass(nsClass('deactivated'));
this.effectiveElement = null;
},
toggle: function () {
if (this.expanded) {
this.collapse();
} else {
this.expand();
}
},
/**
* Displays the panel's contents
*/
expand: function (callback) {
var that = this;
var el = this.content;
var old_h = el.height();
var new_h = el.height('auto').height();
el.height(old_h).stop().animate(
{height: new_h}, 500, 'easeOutExpo',
function () {
if (typeof callback == 'function') {
callback.call(that);
}
}
);
this.element.removeClass('collapsed');
this.toggleTitleIcon(true);
this.expanded = true;
return this;
},
/**
* Hides the panel's contents--leaving only it's header
*/
collapse: function (duration, callback) {
var that = this;
this.element.addClass('collapsed');
this.content.stop().animate(
{height: 5}, 250, 'easeOutExpo',
function () {
if (typeof callback == 'function') {
callback.call(that);
}
}
);
this.toggleTitleIcon(false);
this.expanded = false;
return this;
},
/**
* May also be called by the Sidebar to update title of panel
*
* @param html - Markup string, DOM object, or jQuery object
*/
setTitle: function (html) {
this.title.find(nsSel('panel-title-text')).html(html);
return this;
},
/**
* May also be called by the Sidebar to update content of panel
*
* @param html - Markup string, DOM object, or jQuery object
*/
setContent: function (html) {
// We do this so that empty panels don't appear collapsed
if (!html || html == '') {
html = ' ';
}
this.content.find(nsSel('panel-content-inner-text')).html(html);
return this;
},
rotateTitleIcon: function (angle, duration) {
var arr = this.title.find(nsSel('panel-title-arrow'));
arr.animate({angle: angle}, {
duration : (typeof duration == 'number') ? duration : 500,
easing : 'easeOutExpo',
step : function (val, fx) {
arr.css({
'-o-transform' : 'rotate(' + val + 'deg)',
'-webkit-transform' : 'rotate(' + val + 'deg)',
'-moz-transform' : 'rotate(' + val + 'deg)',
'-ms-transform' : 'rotate(' + val + 'deg)'
// filter : 'progid:DXImageTransform.Microsoft.BasicImage(rotation=' + (angle / 90) + ')'
});
}
});
},
/**
* Walks up the ancestors chain for the given effective element, and
* renders subpanels using the specified renderer function.
*
* @param {jQuery} effective - The effective element, whose lineage we
* want to render
* @param {Function} renderer - (Optional) function that will render
* each element in the parental lineage
* of the effective element
*/
renderEffectiveParents: function (effective, renderer) {
var el = effective.first();
var content = [];
var path = [];
var activeOn = this.activeOn;
var l;
var pathRev;
while (el.length > 0 && !el.is('.aloha-editable')) {
if (activeOn(el)) {
path.push('<span>' + el[0].tagName.toLowerCase() + '</span>');
l = path.length;
pathRev = [];
while (l--) {
pathRev.push(path[l]);
}
content.push(supplant(
'<div class="aloha-sidebar-panel-parent">' +
'<div class="aloha-sidebar-panel-parent-path">{path}</div>' +
'<div class="aloha-sidebar-panel-parent-content aloha-sidebar-opened">{content}</div>' +
'</div>',
{
path : pathRev.join(''),
content : (typeof renderer == 'function') ? renderer(el) : '----'
}
));
}
el = el.parent();
}
this.setContent(content.join(''));
jQuery('.aloha-sidebar-panel-parent-path').click(function () {
var c = jQuery(this).parent().find('.aloha-sidebar-panel-parent-content');
if (c.hasClass('aloha-sidebar-opened')) {
c.hide().removeClass('aloha-sidebar-opened');
} else {
c.show().addClass('aloha-sidebar-opened');
}
});
this.content.height('auto').find('.aloha-sidebar-panel-content-inner').height('auto');
}
});
var left = new Sidebar({
position : 'left',
width : 250 // TODO define in config
});
var right = new Sidebar({
position : 'right',
width : 250 // TODO define in config
});
Aloha.Sidebar = {
left : left,
right : right
};
return Aloha.Sidebar;
}); | PypiClean |
/JaqalPaw-1.2.0a1.tar.gz/JaqalPaw-1.2.0a1/src/jaqalpaw/emulator/arbiters.py | import time
import asyncio
from jaqalpaw.bytecode.encoding_parameters import (
CLR_FRAME_LSB,
APPLY_EOF_LSB,
ANCILLA_COMPILER_TAG_BIT,
ANCILLA_STATE_LSB,
FWD_FRM_T0_LSB,
INV_FRM_T0_LSB,
FRMROT0INT,
FRMROT1INT,
)
from .byte_decoding import *
def construct_fifos(
num_spline_fifos=8,
num_channels=8,
spline_fifo_depth=4,
gate_seq_fifo_depth=32,
dma_depth=256,
):
spline_fifos = [
[asyncio.Queue(maxsize=spline_fifo_depth) for _ in range(num_spline_fifos)]
for _ in range(num_channels)
]
gseq_fifos = [
asyncio.Queue(maxsize=gate_seq_fifo_depth) for _ in range(num_channels)
]
dma_queue = asyncio.Queue(maxsize=dma_depth)
return spline_fifos, gseq_fifos, dma_queue
async def DMA_arbiter(name, queue, data_output_queues):
"""Send data to the correct channel (or gate sequencer input FIFO) based on metadata"""
while True:
raw_data = await queue.get()
data = int.from_bytes(raw_data, byteorder="little", signed=False)
channel = (data >> DMA_MUX_LSB) & 0b111
await data_output_queues[channel].put(raw_data)
queue.task_done()
async def gate_seq_arbiter(name, queue, data_output_queues):
"""Performs the same functions as the hardware GateSequencer IP cores.
Input words are 256 bits, and are parsed and treated accordingly depending on the
metadata tags in the raw data in order to program LUTs or run gate sequences etc...
If the LUTs are not being programmed, the resulting output is sent to the spline engine FIFOs"""
while True:
raw_data = await queue.get()
data = int.from_bytes(raw_data, byteorder="little", signed=False)
mod_type = (data >> MODTYPE_LSB) & 0b111
prog_mode = (data >> PROG_MODE_LSB) & 0b111
if prog_mode == 0b111:
await data_output_queues[mod_type].put(raw_data)
elif prog_mode == 0b001:
parse_GLUT_prog_data(data)
elif prog_mode == 0b010:
parse_SLUT_prog_data(data)
elif prog_mode == 0b011:
parse_PLUT_prog_data(raw_data)
elif prog_mode == 0b100 or prog_mode == 0b101 or prog_mode == 0b110:
if prog_mode == 0b101 or prog_mode == 0b110:
# at the very least we'll need the streamed data to be augmented
# by the tag bit. Additional cases can be applied by ORing the
# "OR address", oraddr, (representing external hardware input)
# via some (binary) state by adding the following line after
# oraddr is initially set to 1 << ANCILLA_COMPILER_TAG_BIT
#
# oraddr |= state << ANCILLA_STATE_LSB
#
# to execute a different branch. But this is not yet worked into
# the emulator in a way that supports a sequence of ancilla
# measurement states.
oraddr = 1 << ANCILLA_COMPILER_TAG_BIT
else:
oraddr = 0
for gs_data in parse_gate_seq_data(data, oraddr=oraddr):
new_mod_type = (
int.from_bytes(gs_data, byteorder="little", signed=False)
>> MODTYPE_LSB
) & 0b111
await data_output_queues[new_mod_type].put(gs_data)
queue.task_done()
async def spline_engine(
name,
queue,
time_list,
data_list,
waittrig_list,
enablemask_list,
fwd_frame0_mask_list,
inv_frame0_mask_list,
fwd_frame1_mask_list,
inv_frame1_mask_list,
):
"""Converts the spline coefficients to a format that can be passed into a SplineEngine emulator,
which generates the corresponding output and stores the data in time_list and data_list for
plotting and/or inspecting the data"""
eof_data = 0
while True:
raw_data = await queue.get()
data = int.from_bytes(raw_data, byteorder="little", signed=False)
waittrig = (data >> WAIT_TRIG_LSB) & 0b1
enablemask = (data >> OUTPUT_EN_LSB) & 0b1
fwd_frame0_mask = 0
inv_frame0_mask = 0
fwd_frame1_mask = 0
inv_frame1_mask = 0
mod_type = (data >> MODTYPE_LSB) & 0b111
if mod_type == FRMROT0INT:
fwd_frame0_mask = (data >> FWD_FRM_T0_LSB) & 0b11
inv_frame0_mask = (data >> INV_FRM_T0_LSB) & 0b11
elif mod_type == FRMROT1INT:
fwd_frame1_mask = (data >> FWD_FRM_T0_LSB) & 0b11
inv_frame1_mask = (data >> INV_FRM_T0_LSB) & 0b11
shift = (data >> SPLSHIFT_LSB) & 0b11111
channel = (data >> DMA_MUX_LSB) & 0b111
reset_accum = (data >> CLR_FRAME_LSB) & 0b1
apply_at_eof = (data >> APPLY_EOF_LSB) & 0b1
dur, U0, U1, U2, U3 = parse_bypass_data(raw_data)
# Convert binary values to real-unit equivalents for monitoring
# dur += TIMECORR+0#+4
dur_real = convert_time_from_clock_cycles(dur)
U0_real = mod_type_dict[mod_type]["realConvFunc"](U0)
U1_real = mod_type_dict[mod_type]["realConvFunc"](U1)
U2_real = mod_type_dict[mod_type]["realConvFunc"](U2)
U3_real = mod_type_dict[mod_type]["realConvFunc"](U3)
# This if statement is not absolutely necessary but reduces number of points to plot, forcing
# the function to always jump to the else clause will produce the same output and is more
# consistent with how the hardware is actually operating.
if U1 == 0 and U2 == 0 and U3 == 0:
time_list.append(time_list[-1] + dur)
if mod_type in (
FRMROT0INT,
FRMROT1INT,
): # then we have a z rotation which must accumulate from old values
if reset_accum:
last_val = 0
eof_data = 0
else:
last_val = data_list[-1]
if apply_at_eof:
data_list.append(last_val + eof_data)
eof_data = U0_real
else:
data_list.append(last_val + U0_real + eof_data)
eof_data = 0
if mod_type == FRMROT0INT:
fwd_frame0_mask_list.append(fwd_frame0_mask)
inv_frame0_mask_list.append(inv_frame0_mask)
else:
fwd_frame1_mask_list.append(fwd_frame1_mask)
inv_frame1_mask_list.append(inv_frame1_mask)
else:
data_list.append(U0_real)
waittrig_list[-1] = waittrig
waittrig_list.append(0)
enablemask_list[-1] = enablemask
enablemask_list.append(0)
print(
f"channel: {channel}, type: {mod_type}, Duration: {dur_real} s, U0: {U0_real}, U1: {U1_real}, U2: {U2_real}, U3: {U3_real}"
)
else:
# Bit shifting is done to enhance precision within firmware
U1_shift = U1
U2_shift = U2
U3_shift = U3
# Calculate the same for real values for monitoring purposes only
U1_rshift = U1_real / (1 << shift)
U2_rshift = U2_real / (1 << (shift * 2))
U3_rshift = U3_real / (1 << (shift * 3))
# Pack the coefficients in a format that can be handled by the spline engine emulator
coeffs = np.zeros((4, 1))
coeffs[0, 0] = U3_shift
coeffs[1, 0] = U2_shift
coeffs[2, 0] = U1_shift
coeffs[3, 0] = U0
# The additional 3 clock cycles are related to a subtle hardware issue
xdata = np.array(list(range(dur))) + 1
spline_data = pdq_spline(coeffs, [0], nsteps=dur, shift=shift)
spline_data_real = list(
map(mod_type_dict[mod_type]["realConvFunc"], spline_data)
)
xdata_real = list(map(lambda x: time_list[-1] + x, xdata))
time_list.extend(xdata_real[:])
last_val = data_list[-1]
if mod_type in (
FRMROT0INT,
FRMROT1INT,
): # then we have a z rotation which must accumulate from old values
if reset_accum:
last_val = 0
eof_data = 0
data_list.extend(last_val + eof_data + np.array(spline_data_real))
eof_data = 0
if mod_type == FRMROT0INT:
fwd_frame0_mask_list.extend([fwd_frame0_mask] * len(xdata_real))
inv_frame0_mask_list.extend([inv_frame0_mask] * len(xdata_real))
else:
fwd_frame1_mask_list.extend([fwd_frame1_mask] * len(xdata_real))
inv_frame1_mask_list.extend([inv_frame1_mask] * len(xdata_real))
else:
data_list.extend(spline_data_real)
print(
f"channel: {channel}, type: {mod_type}, Duration: {dur_real} s, "
f"U0: {U0_real}, U1: {U1_rshift}, U2: {U2_rshift}, U3: {U3_rshift}"
)
# For good measure, wait for the duration encoded in the raw data, for more accurate emulation, this duration
# should be scaled so as to reduce the influence imposed by computational delay
# await asyncio.sleep(dur_real)
queue.task_done() | PypiClean |
/Color_Match-0.0.1-py3-none-any.whl/Color_Match/color_match_tmp.py | import numpy as np
class Color_Match:
def __init__(self):
self.hc_kB = 0.0143877735
data = np.loadtxt('lin2012xyz10_fine_7sf.csv', delimiter=',')
self.wavelengths = data[:,0] * 10**-9
self.s1 = data[:,1]
self.s2 = data[:,2]
self.s3 = data[:,3]
def planck(self, l, t):
"""Returns the relative intensity of a Planck's Law distribution at a given wavelength (l -- in meters) and temperature (t -- in Kelvin)."""
return 1. / l**5.0 * 1. / (np.exp(self.hc_kB / (l * t)) - 1.)
def planck_spectrum(self, t):
"""Returns the relative intensities of the full Planck spectrum for a light source at a given temperature (t -- in Kelvin), across the entire range of human-visible frequencies, as defined in Color_Match.wavelengths ."""
return np.array([planck(l, t) for l in self.wavelengths])
def sense_vector(spectrum):
"""Returns the expected sensory-perception vector corresponding to the normalized (and relative) amounts of signal received on the L(ong), M(edium), and S(hort) wavelength color receptors according to the 10-deg XYZ CMFs transformed from the CIE (2006) 2-deg LMS cone fundamentals with a 0.1nm spacing from: http://cvri.ioo.ucl.ac.uk/cmfs.htm
Return value format is as a numpy Matrix, 3x1 (aka - 3-row column vector), to facilitate use of this output with other package functions.
Note that length(spectrum) must equal length(Color_Match.wavelengths) for this to work properly. Automatic tests and error-catching coming soon!"""
s = np.matrix([np.sum(self.s1 * spectrum), np.sum(self.s2 * spectrum), np.sum(self.s3 * spectrum)]).T
return s / np.max(s)
def s_lookup(self, num, l):
"""num = 1, 2, 3 (corresponds to L(ong), M(edium), S(hort) wavelength receptors)
l (wavelength) should be in units of meters, and lie between np.min(Color_Match.wavelengths) and np.max(Color_Match.wavelengths)"""
if num == 1:
s = self.s1
elif num == 2:
s = self.s2
elif num == 3:
s = s3
return s[np.argmin((self.wavelengths - l)**2.0)]
def rgb_composition(l1, l2, l3, sv):
"""Finds relative intensities required for light sources at l1, l2, and l3 in wavelength (meters) space to match the sense vector (sv) provided in the arguments.
sv should be a 3x1 np.Matrix (aka - 3-row column vector). For convenience, this is the same as the output of the Color_Match.sense_vector function.
l1, l2, l3 should have units of meters, and are most commonly the primary emission wavelengths of your RGB channels in an LED light source."""
s_mat = np.matrix([[self.s_lookup(1, l1), self.s_lookup(1, l2), self.s_lookup(1, l3)],
[self.s_lookup(2, l1), self.s_lookup(2, l2), self.s_lookup(2, l3)],
[self.s_lookup(3, l1), self.s_lookup(3, l2), self.s_lookup(3, l3)]])
c_mat = s_mat.I * sv
return c_mat / np.max(c_mat) | PypiClean |
/InvestOpenDataTools-1.0.2.tar.gz/InvestOpenDataTools-1.0.2/opendatatools/stock/stock_interface.py |
import datetime
import pandas as pd
from .stock_agent import SHExAgent, SZExAgent, CSIAgent, XueqiuAgent, SinaAgent, CNInfoAgent, EastMoneyAgent
from opendatatools.common import get_current_day
shex_agent = SHExAgent()
szex_agent = SZExAgent()
csi_agent = CSIAgent()
xq_agent = XueqiuAgent()
sina_agent = SinaAgent()
cninfo_agent = CNInfoAgent()
eastmoney_agent = EastMoneyAgent()
xq_count_map = {
'1m': 240,
'5m': 48,
'15m': 16,
'30m': 8,
'60m': 4,
'day': 1,
}
bar_span_map = {
'1m': 1,
'5m': 5,
'15m': 15,
'30m': 30,
'60m': 60,
'day': 1440,
}
def make_index(period, trade_date):
bar_index = list()
span = bar_span_map[period]
dt = datetime.datetime.strptime(trade_date, '%Y-%m-%d')
bar_index.extend(
pd.DatetimeIndex(start="%s 09:30:00" % trade_date, end="%s 11:30:00" % trade_date, freq='%sT' % span)[1:])
bar_index.extend(
pd.DatetimeIndex(start="%s 13:00:00" % trade_date, end="%s 15:00:00" % trade_date, freq='%sT' % span)[1:])
return bar_index
def set_proxies(proxies):
shex_agent.set_proxies(proxies)
szex_agent.set_proxies(proxies)
csi_agent.set_proxies(proxies)
xq_agent.set_proxies(proxies)
def get_index_list(market='SH'):
if market == 'SH':
return shex_agent.get_index_list()
if market == 'SZ':
return szex_agent.get_index_list()
if market == 'CSI':
return csi_agent.get_index_list()
def get_index_component(symbol):
temp = symbol.split(".")
if len(temp) == 2:
market = temp[1]
index = temp[0]
if market == 'SH':
return shex_agent.get_index_component(index)
elif market == 'SZ':
return szex_agent.get_index_component(index)
elif market == 'CSI':
return csi_agent.get_index_component(index)
else:
return None
else:
return None
def get_rzrq_info(market='SH', date=None):
if date is None:
date = get_current_day(format='%Y-%m-%d')
if market == 'SH':
return shex_agent.get_rzrq_info(date)
if market == 'SZ':
return szex_agent.get_rzrq_info(date)
return None, None
def get_pledge_info(market='SH', date=None):
if date is None:
date = get_current_day(format='%Y-%m-%d')
if market == 'SH':
return shex_agent.get_pledge_info(date)
if market == 'SZ':
return szex_agent.get_pledge_info(date)
return None, None
def get_dividend(symbol):
temp = symbol.split(".")
if len(temp) == 2:
market = temp[1]
code = temp[0]
if market == 'SH':
return shex_agent.get_dividend(code)
if market == 'SZ':
return cninfo_agent.get_dividend(code)
def get_quote(symbols):
return xq_agent.get_quote(symbols)
def fill_df(df, period, trade_date, symbol):
df.index = df['time']
index = make_index(period, trade_date)
df_new = pd.DataFrame(index=index, columns=['last'])
df_new['last'] = df['last']
df_new.fillna(method='ffill', inplace=True)
df_new['high'] = df['high']
df_new['low'] = df['low']
df_new['open'] = df['open']
df_new.fillna(method='ffill', axis=1, inplace=True)
df_new['change'] = df['change']
df_new['percent'] = df['percent']
df_new['symbol'] = symbol
df_new['turnover_rate'] = df['turnover_rate']
df_new['volume'] = df['volume']
df_new['time'] = df_new.index
df_new.fillna(0, inplace=True)
return df_new
# period 1m, 5m, 15m, 30m, 60m, day
def get_kline(symbol, start_date, end_date, period='day'):
start_date = datetime.datetime.strptime(start_date, '%Y-%m-%d')
end_date = datetime.datetime.strptime(end_date, '%Y-%m-%d') + datetime.timedelta(days=1)
timestamp = end_date.timestamp()
cnt = (end_date - start_date).days * -1 * xq_count_map[period]
timestamp = int(timestamp * 1000)
df, msg = xq_agent.get_kline(symbol, timestamp, period, cnt)
if len(df) == 0:
return df, msg
df = df[(df.time < end_date) & (df.time >= start_date)]
return df, ''
def get_kline_multisymbol(symbols, trade_date, period):
symbol_list = symbols.split(',')
timestamp = datetime.datetime.strptime(trade_date, '%Y-%m-%d').timestamp()
timestamp = int(timestamp * 1000)
df, msg = xq_agent.get_kline_multisymbol(symbol_list, timestamp, period, xq_count_map[period])
next_date = datetime.datetime.strptime(trade_date, '%Y-%m-%d') + datetime.timedelta(days=1)
if df is None:
return df, msg
df = df[df.time < next_date]
gp = df.groupby('symbol')
df_list = list()
for symbol, df_item in gp:
if len(df_item) < xq_count_map[period]:
df_list.append(fill_df(df_item, period, trade_date, symbol))
else:
df_list(df_item)
return pd.concat(df_list), ''
def get_timestamp_list(start_date, end_date):
timestamp_list = []
curr_date = start_date
while curr_date <= end_date:
curr_datetime = datetime.datetime.strptime(curr_date, '%Y-%m-%d')
timestamp = curr_datetime.timestamp()
timestamp_list.append(int(timestamp * 1000))
next_time = curr_datetime + datetime.timedelta(days=1)
curr_date = datetime.datetime.strftime(next_time, '%Y-%m-%d')
return timestamp_list
def get_kline_multidate(symbol, start_date, end_date, period):
timestamp_list = get_timestamp_list(start_date, end_date)
return xq_agent.get_kline_multitimestamp(symbol, timestamp_list, period, xq_count_map[period])
def get_daily(symbol, start_date, end_date):
curr_date = start_date
df_result = []
while curr_date <= end_date:
curr_datetime = datetime.datetime.strptime(curr_date, '%Y-%m-%d')
next_time = curr_datetime + datetime.timedelta(days=100)
next_date = datetime.datetime.strftime(next_time, '%Y-%m-%d')
timestamp = curr_datetime.timestamp()
df, msg = xq_agent.get_kline(symbol, int(timestamp * 1000), 'day', 100)
if len(df) != 0:
df_result.append(df[df['time'] < next_time])
curr_date = next_date
if len(df_result) > 0:
df = pd.concat(df_result)
df = df[(df['time'] >= start_date) & (df['time'] <= end_date)]
return df, ''
else:
return None, '没有获取到数据'
def get_adj_factor(symbol):
return sina_agent.get_adj_factor(symbol)
def get_trade_detail(symbol, trade_date):
return sina_agent.get_trade_detail(symbol, trade_date)
def get_report_data(symbol='600000.SH', type='资产负债表'):
dict_type = {
'利润表': 'lrb',
'资产负债表': 'fzb',
'现金流量表': 'llb',
}
if type not in dict_type:
return None, 'type输入错误，可以输入 %s' % dict_type.keys()
data = symbol.split(sep='.')
market = data[1].lower()
code = data[0]
return cninfo_agent.get_report_data(market, code, dict_type[type])
def get_shareholder_structure(symbol='600000.SH'):
data = symbol.split(sep='.')
market = data[1].lower()
code = data[0]
return cninfo_agent.get_shareholder_structure(market, code)
# 单位：百万元
def get_hist_money_flow(symbol):
data = symbol.split(sep='.')
market = data[1]
if market == 'SH':
marketnum = '1'
else:
marketnum = '2'
code = data[0] + marketnum
return eastmoney_agent.get_hist_money_flow(code)
# 单位：万元
def get_realtime_money_flow(symbol):
data = symbol.split(sep='.')
market = data[1]
if market == 'SH':
marketnum = '1'
else:
marketnum = '2'
code = data[0] + marketnum
return eastmoney_agent.get_realtime_money_flow(code)
# 单位：亿元
def get_realtime_money_flow_market():
return eastmoney_agent.get_realtime_money_flow_market()
def get_hist_money_flow_market():
return eastmoney_agent.get_hist_money_flow_market()
def get_allstock_flow():
return eastmoney_agent.get_allstock_flow() | PypiClean |
/Andencento-0.24.tar.gz/Andencento-0.24/userbot/helpers/fasttelethon.py | import asyncio
import hashlib
import inspect
import logging
import math
import os
from collections import defaultdict
from typing import (AsyncGenerator, Awaitable, BinaryIO, DefaultDict, List,
Optional, Tuple, Union)
from telethon import TelegramClient, helpers, utils
from telethon.crypto import AuthKey
from telethon.errors import FloodWaitError
from telethon.network import MTProtoSender
from telethon.tl.alltlobjects import LAYER
from telethon.tl.functions import InvokeWithLayerRequest
from telethon.tl.functions.auth import (ExportAuthorizationRequest,
ImportAuthorizationRequest)
from telethon.tl.functions.upload import (GetFileRequest,
SaveBigFilePartRequest,
SaveFilePartRequest)
from telethon.tl.types import (Document, InputDocumentFileLocation, InputFile,
InputFileBig, InputFileLocation,
InputPeerPhotoFileLocation,
InputPhotoFileLocation, TypeInputFile)
try:
from mautrix.crypto.attachments import async_encrypt_attachment
except ImportError:
async_encrypt_attachment = None
log: logging.Logger = logging.getLogger("fasttelethon")
TypeLocation = Union[
Document,
InputDocumentFileLocation,
InputPeerPhotoFileLocation,
InputFileLocation,
InputPhotoFileLocation,
]
class DownloadSender:
client: TelegramClient
sender: MTProtoSender
request: GetFileRequest
remaining: int
stride: int
def __init__(
self,
client: TelegramClient,
sender: MTProtoSender,
file: TypeLocation,
offset: int,
limit: int,
stride: int,
count: int,
) -> None:
self.sender = sender
self.client = client
self.request = GetFileRequest(file, offset=offset, limit=limit)
self.stride = stride
self.remaining = count
async def next(self) -> Optional[bytes]:
if not self.remaining:
return None
while True:
try:
result = await self.client._call(self.sender, self.request)
except FloodWaitError as e:
await asyncio.sleep(e.seconds)
else:
break
self.remaining -= 1
self.request.offset += self.stride
return result.bytes
def disconnect(self) -> Awaitable[None]:
return self.sender.disconnect()
class UploadSender:
client: TelegramClient
sender: MTProtoSender
request: Union[SaveFilePartRequest, SaveBigFilePartRequest]
part_count: int
stride: int
previous: Optional[asyncio.Task]
loop: asyncio.AbstractEventLoop
def __init__(
self,
client: TelegramClient,
sender: MTProtoSender,
file_id: int,
part_count: int,
big: bool,
index: int,
stride: int,
loop: asyncio.AbstractEventLoop,
) -> None:
self.client = client
self.sender = sender
self.part_count = part_count
if big:
self.request = SaveBigFilePartRequest(file_id, index, part_count, b"")
else:
self.request = SaveFilePartRequest(file_id, index, b"")
self.stride = stride
self.previous = None
self.loop = loop
async def next(self, data: bytes) -> None:
if self.previous:
await self.previous
self.previous = self.loop.create_task(self._next(data))
async def _next(self, data: bytes) -> None:
self.request.bytes = data
log.debug(
f"Sending file part {self.request.file_part}/{self.part_count}"
f" with {len(data)} bytes"
)
await self.client._call(self.sender, self.request)
self.request.file_part += self.stride
async def disconnect(self) -> None:
if self.previous:
await self.previous
return await self.sender.disconnect()
class ParallelTransferrer:
client: TelegramClient
loop: asyncio.AbstractEventLoop
dc_id: int
senders: Optional[List[Union[DownloadSender, UploadSender]]]
auth_key: AuthKey
upload_ticker: int
def __init__(self, client: TelegramClient, dc_id: Optional[int] = None) -> None:
self.client = client
self.loop = self.client.loop
self.dc_id = dc_id or self.client.session.dc_id
self.auth_key = (
None
if dc_id and self.client.session.dc_id != dc_id
else self.client.session.auth_key
)
self.senders = None
self.upload_ticker = 0
async def _cleanup(self) -> None:
await asyncio.gather(*[sender.disconnect() for sender in self.senders])
self.senders = None
@staticmethod
def _get_connection_count(
file_size: int, max_count: int = 20, full_size: int = 100 * 1024 * 1024
) -> int:
if file_size > full_size:
return max_count
return math.ceil((file_size / full_size) * max_count)
async def _init_download(
self, connections: int, file: TypeLocation, part_count: int, part_size: int
) -> None:
minimum, remainder = divmod(part_count, connections)
def get_part_count() -> int:
nonlocal remainder
if remainder > 0:
remainder -= 1
return minimum + 1
return minimum
# The first cross-DC sender will export+import the authorization, so we always create it
# before creating any other senders.
self.senders = [
await self._create_download_sender(
file, 0, part_size, connections * part_size, get_part_count()
),
*await asyncio.gather(
*[
self._create_download_sender(
file, i, part_size, connections * part_size, get_part_count()
)
for i in range(1, connections)
]
),
]
async def _create_download_sender(
self,
file: TypeLocation,
index: int,
part_size: int,
stride: int,
part_count: int,
) -> DownloadSender:
return DownloadSender(
self.client,
await self._create_sender(),
file,
index * part_size,
part_size,
stride,
part_count,
)
async def _init_upload(
self, connections: int, file_id: int, part_count: int, big: bool
) -> None:
self.senders = [
await self._create_upload_sender(file_id, part_count, big, 0, connections),
*await asyncio.gather(
*[
self._create_upload_sender(file_id, part_count, big, i, connections)
for i in range(1, connections)
]
),
]
async def _create_upload_sender(
self, file_id: int, part_count: int, big: bool, index: int, stride: int
) -> UploadSender:
return UploadSender(
self.client,
await self._create_sender(),
file_id,
part_count,
big,
index,
stride,
loop=self.loop,
)
async def _create_sender(self) -> MTProtoSender:
dc = await self.client._get_dc(self.dc_id)
sender = MTProtoSender(self.auth_key, loggers=self.client._log)
await sender.connect(
self.client._connection(
dc.ip_address,
dc.port,
dc.id,
loggers=self.client._log,
proxy=self.client._proxy,
)
)
if not self.auth_key:
log.debug(f"Exporting auth to DC {self.dc_id}")
auth = await self.client(ExportAuthorizationRequest(self.dc_id))
self.client._init_request.query = ImportAuthorizationRequest(
id=auth.id, bytes=auth.bytes
)
req = InvokeWithLayerRequest(LAYER, self.client._init_request)
await sender.send(req)
self.auth_key = sender.auth_key
return sender
async def init_upload(
self,
file_id: int,
file_size: int,
part_size_kb: Optional[float] = None,
connection_count: Optional[int] = None,
) -> Tuple[int, int, bool]:
connection_count = connection_count or self._get_connection_count(file_size)
part_size = (part_size_kb or utils.get_appropriated_part_size(file_size)) * 1024
part_count = (file_size + part_size - 1) // part_size
is_large = file_size > 10 * 1024 * 1024
await self._init_upload(connection_count, file_id, part_count, is_large)
return part_size, part_count, is_large
async def upload(self, part: bytes) -> None:
await self.senders[self.upload_ticker].next(part)
self.upload_ticker = (self.upload_ticker + 1) % len(self.senders)
async def finish_upload(self) -> None:
await self._cleanup()
async def download(
self,
file: TypeLocation,
file_size: int,
part_size_kb: Optional[float] = None,
connection_count: Optional[int] = None,
) -> AsyncGenerator[bytes, None]:
connection_count = connection_count or self._get_connection_count(file_size)
part_size = (part_size_kb or utils.get_appropriated_part_size(file_size)) * 1024
part_count = math.ceil(file_size / part_size)
log.debug(
"Starting parallel download: "
f"{connection_count} {part_size} {part_count} {file!s}"
)
await self._init_download(connection_count, file, part_count, part_size)
part = 0
while part < part_count:
tasks = [self.loop.create_task(sender.next()) for sender in self.senders]
for task in tasks:
data = await task
if not data:
break
yield data
part += 1
log.debug(f"Part {part} downloaded")
log.debug("Parallel download finished, cleaning up connections")
await self._cleanup()
parallel_transfer_locks: DefaultDict[int, asyncio.Lock] = defaultdict(
lambda: asyncio.Lock()
)
def stream_file(file_to_stream: BinaryIO, chunk_size=1024):
while True:
data_read = file_to_stream.read(chunk_size)
if not data_read:
break
yield data_read
async def _internal_transfer_to_telegram(
client: TelegramClient, response: BinaryIO, progress_callback: callable
) -> Tuple[TypeInputFile, int]:
file_id = helpers.generate_random_long()
file_size = os.path.getsize(response.name)
hash_md5 = hashlib.md5()
uploader = ParallelTransferrer(client)
part_size, part_count, is_large = await uploader.init_upload(file_id, file_size)
buffer = bytearray()
for data in stream_file(response):
if progress_callback:
r = progress_callback(response.tell(), file_size)
if inspect.isawaitable(r):
await r
if not is_large:
hash_md5.update(data)
if len(buffer) == 0 and len(data) == part_size:
await uploader.upload(data)
continue
new_len = len(buffer) + len(data)
if new_len >= part_size:
cutoff = part_size - len(buffer)
buffer.extend(data[:cutoff])
await uploader.upload(bytes(buffer))
buffer.clear()
buffer.extend(data[cutoff:])
else:
buffer.extend(data)
if len(buffer) > 0:
await uploader.upload(bytes(buffer))
await uploader.finish_upload()
if is_large:
return InputFileBig(file_id, part_count, "upload"), file_size
else:
return InputFile(file_id, part_count, "upload", hash_md5.hexdigest()), file_size
async def download_file(
client: TelegramClient,
location: TypeLocation,
out: BinaryIO,
progress_callback: callable = None,
) -> BinaryIO:
size = location.size
dc_id, location = utils.get_input_location(location)
# We lock the transfers because telegram has connection count limits
downloader = ParallelTransferrer(client, dc_id)
downloaded = downloader.download(location, size)
async for x in downloaded:
out.write(x)
if progress_callback:
r = progress_callback(out.tell(), size)
if inspect.isawaitable(r):
await r
return out
async def upload_file(
client: TelegramClient,
file: BinaryIO,
progress_callback: callable = None,
) -> TypeInputFile:
return (await _internal_transfer_to_telegram(client, file, progress_callback))[0] | PypiClean |
/Eskapade_Core-1.0.0-py3-none-any.whl/escore/core/definitions.py | import ast
import collections
import os
from enum import IntEnum, unique
from pkg_resources import resource_filename
from escore.logger import LogLevel
@unique
class StatusCode(IntEnum):
"""Return status code enumeration class.
A StatusCode should be returned by the initialize, execute,
and finalize methods of links, chains, and the process manager.
The enumerations are:
* Undefined (-1): Default status.
* Success (0 == EX_OK / EXIT_SUCCESS): All OK, i.e. there were no errors.
* RepeatChain (1): Repeat execution of this chain.
* SkipChain (2): Skip this chain: initialize, execute, and finalize.
* BreakChain (3): Skip the further execution of this this, but do perform finalize.
* Recoverable (4): Not OK, but can continue, i.e. there was an error, but the
application can recover from it.
* Failure (5): An error occurred and the application cannot recover from it.
In this case the application should just quit.
"""
Undefined = -1 # type: int
Success = 0 # type: int
RepeatChain = 1 # type: int
SkipChain = 2 # type: int
BreakChain = 3 # type: int
Recoverable = 4 # type: int
Failure = 5 # type: int
def __str__(self) -> str:
"""Get string representation of :class:`StatusCode`.
:return: String representation of :class:`StatusCode`.
:rtype: str
"""
return self.name
def is_undefined(self) -> bool:
"""Check if status is `StatusCode.Undefined`.
:return: True when `StatusCode.Undefined`, False otherwise.
:rtype: bool
"""
return StatusCode.Undefined == self
def is_success(self) -> bool:
"""Check if status is `StatusCode.Success`.
:return: True when `StatusCode.Success`, False otherwise.
:rtype: bool
"""
return StatusCode.Success == self
def is_repeat_chain(self) -> bool:
"""Check if status is `StatusCode.RepeatChain`.
:return: True when `StatusCode.RepeatChain`, False otherwise.
:rtype: bool
"""
return StatusCode.RepeatChain == self
def is_skip_chain(self) -> bool:
"""Check if status is `StatusCode.SkipChain`.
:return: True when `StatusCode.SkipChain`, False otherwise.
:rtype: bool
"""
return StatusCode.SkipChain == self
def is_break_chain(self) -> bool:
"""Check if status is `StatusCode.BreakChain`.
:return: True when `StatusCode.BreakChain`, False otherwise.
:rtype: bool
"""
return StatusCode.BreakChain == self
def is_recoverable(self) -> bool:
"""Check if status is `StatusCode.Recoverable`.
:return: True when `StatusCode.Recoverable`, False otherwise.
:rtype: bool
"""
return StatusCode.Recoverable == self
def is_failure(self) -> bool:
"""Check if status is `StatusCode.Failure`.
:return: True when `StatusCode.Failure`, False otherwise.
:rtype: bool
"""
return StatusCode.Failure == self
class RandomSeeds:
"""Container for seeds of random generators.
Seeds are stored as key-value pairs and are accessed with getitem and
setitem methods. A default seed can be accessed with the key "default".
The default seed is also returned if no seed is set for the specified
key.
>>> import numpy as np
>>> seeds = RandomSeeds(default=999, foo=42, bar=13)
>>> seeds['NumPy'] = 100
>>> np.random.seed(seeds['NumPy'])
>>> print(seeds['nosuchseed'])
999
"""
def __init__(self, **kwargs):
"""Initialize an instance.
Values of the specified keyword arguments must be integers, which are
set as seed values for the corresponding key.
"""
# initialize attributes
self._seeds = {}
self._default = 1
# set specified seeds
for key, seed in kwargs.items():
self[key] = seed
def __getitem__(self, key):
"""Return seed for specified lowercase-string key."""
return self._seeds.get(str(key).strip().lower(), self._default)
def __setitem__(self, key, seed):
"""Set integer seed for specified lowercase-string key."""
# parse key and seed
key = str(key).strip().lower()
try:
seed = int(seed)
except Exception:
raise TypeError('specified seed for key "{0:s}" is not an integer: "{1!s}"'.format(key, seed))
# check if this is the default key
if key == 'default':
self._default = seed
else:
self._seeds[key] = seed
def __str__(self):
seed_str = ', '.join('{0:s}: {1:d}'.format(*kv) for kv in self._seeds.items())
return '{{default: {0:d} | {1:s}}}'.format(self._default, seed_str)
# configuration variables
CONFIG_VARS = collections.OrderedDict()
CONFIG_VARS['run'] = ['analysisName',
'version',
'macro',
'batchMode',
'interactive',
'logLevel',
'logFormat',
'doCodeProfiling', ]
CONFIG_VARS['chains'] = ['beginWithChain',
'endWithChain',
'storeResultsEachChain',
'storeResultsOneChain',
'doNotStoreResults', ]
CONFIG_VARS['file_io'] = ['esRoot',
'resultsDir',
'dataDir',
'macrosDir',
'templatesDir',
'configDir', ]
CONFIG_VARS['config'] = ['sparkCfgFile', ]
CONFIG_VARS['db_io'] = ['all_mongo_collections', ]
CONFIG_VARS['rand_gen'] = ['seeds', ]
CONFIG_TYPES = dict(version=int,
batchMode=bool,
interactive=bool,
storeResultsEachChain=bool,
doNotStoreResults=bool,
all_mongo_collections=list, )
CONFIG_DEFAULTS = dict(analysisName='MyAnalysis',
version=0,
batchMode=True,
interactive=False,
logLevel=LogLevel.INFO,
logFormat='%(asctime)s %(levelname)s [%(module)s]: %(message)s',
doCodeProfiling=None,
storeResultsEachChain=False,
doNotStoreResults=False,
esRoot=os.getcwd() + '/',
resultsDir=os.getcwd() + '/results/',
dataDir=os.getcwd() + '/data/',
macrosDir=os.getcwd() + '/macros/',
templatesDir=resource_filename('escore', 'templates') + '/',
configDir=os.getcwd() + '/config/',
sparkCfgFile='spark.cfg',
seeds=RandomSeeds(), )
# user options in command-line arguments
USER_OPTS = collections.OrderedDict()
USER_OPTS['run'] = ['analysis_name',
'analysis_version',
'batch_mode',
'interactive',
'log_level',
'log_format',
'unpickle_config',
'profile',
'conf_var', ]
USER_OPTS['chains'] = ['begin_with',
'end_with',
'single_chain',
'store_all',
'store_one',
'store_none', ]
USER_OPTS['file_io'] = ['results_dir',
'data_dir',
'macros_dir',
'templates_dir', ]
USER_OPTS['config'] = ['spark_cfg_file', ]
USER_OPTS['rand_gen'] = ['seed', ]
USER_OPTS_SHORT = dict(analysis_name='n',
analysis_version='v',
interactive='i',
log_level='L',
conf_var='c',
begin_with='b',
end_with='e',
single_chain='s', )
USER_OPTS_KWARGS = dict(analysis_name=dict(help='set name of analysis in run',
metavar='NAME'),
analysis_version=dict(help='set version of analysis version in run',
type=int,
metavar='VERSION'),
batch_mode=dict(help='run in batch mode (no X Windows)',
action='store_true'),
interactive=dict(help='start Python shell after run',
action='store_true'),
log_level=dict(help='set logging level',
choices=['NOTSET', 'DEBUG', 'INFO', 'WARNING', 'ERROR', 'FATAL'],
metavar='{NOTSET,DEBUG,INFO,WARNING,ERROR,FATAL}'),
log_format=dict(help='set log-message format',
metavar='FORMAT'),
unpickle_config=dict(help='interpret first CONFIG_FILE as path to pickled settings',
action='store_true'),
profile=dict(help='run Python profiler, sort output by specified column',
choices=['stdname', 'nfl', 'pcalls', 'file', 'calls', 'time', 'line',
'cumulative', 'module', 'name'],
metavar='{stdname,nfl,pcalls,file,calls,time,line,cumulative,module,name}'),
conf_var=dict(help='set configuration variable',
action='append',
metavar='KEY=VALUE'),
begin_with=dict(help='begin execution with chain CHAIN_NAME',
metavar='CHAIN_NAME'),
end_with=dict(help='end execution with chain CHAIN_NAME',
metavar='CHAIN_NAME'),
single_chain=dict(help='only execute chain CHAIN_NAME',
metavar='CHAIN_NAME'),
store_all=dict(help='store run-process services after every chain',
action='store_true'),
store_one=dict(help='store run-process services after chain CHAIN_NAME',
metavar='CHAIN_NAME'),
store_none=dict(help='do not store run-process services',
action='store_true'),
results_dir=dict(help='set directory path for results output',
metavar='RESULTS_DIR'),
data_dir=dict(help='set directory path for data',
metavar='DATA_DIR'),
macros_dir=dict(help='set directory path for macros',
metavar='MACROS_DIR'),
templates_dir=dict(help='set directory path for template files',
metavar='TEMPLATES_DIR'),
spark_cfg_file=dict(help='set path of Spark configuration file',
metavar='SPARK_CONFIG_FILE'),
seed=dict(help='set seed for random-number generation',
action='append',
metavar='KEY=SEED'), )
USER_OPTS_CONF_KEYS = dict(analysis_name='analysisName',
analysis_version='version',
batch_mode='batchMode',
log_level='logLevel',
log_format='logFormat',
profile='doCodeProfiling',
begin_with='beginWithChain',
end_with='endWithChain',
store_all='storeResultsEachChain',
store_one='storeResultsOneChain',
store_none='doNotStoreResults',
spark_cfg_file='sparkCfgFile',
seed='seeds', )
def set_opt_var(opt_key, settings, args):
"""Set configuration variable from user options."""
value = args.get(opt_key)
if value is None:
return
conf_key = USER_OPTS_CONF_KEYS.get(opt_key, opt_key)
value_type = CONFIG_TYPES.get(conf_key, str)
val = CONFIG_TYPES.get(conf_key, str)(value)
if value_type != bool:
settings[conf_key] = val
return
# default boolean user-opt arg is always False!
if val:
# user set it to true on cmd line, so adopt
settings[conf_key] = val
elif conf_key not in settings:
# missing anyhow, so let's adopt
settings[conf_key] = val
else:
# a default value is already present; ignoring this one
pass
CONFIG_OPTS_SETTERS = collections.defaultdict(lambda: set_opt_var)
def set_log_level_opt(opt_key, settings, args):
"""Set configuration log level from user option."""
level = args.get(opt_key)
if not level:
return
if level not in LogLevel.__members__:
raise ValueError('invalid logging level specified: "{!s}"'.format(level))
settings[USER_OPTS_CONF_KEYS.get(opt_key, opt_key)] = level
CONFIG_OPTS_SETTERS['log_level'] = set_log_level_opt
def set_begin_end_chain_opt(opt_key, settings, args):
"""Set begin/end-chain variable from user option."""
chain = args.get(opt_key)
if not chain:
return
if args.get('single_chain'):
raise RuntimeError('"begin-with" and "end-with" chain options cannot be combined with "single-chain" option')
settings[USER_OPTS_CONF_KEYS.get(opt_key, opt_key)] = str(chain)
CONFIG_OPTS_SETTERS['begin_with'] = set_begin_end_chain_opt
CONFIG_OPTS_SETTERS['end_with'] = set_begin_end_chain_opt
def set_single_chain_opt(opt_key, settings, args):
"""Set single-chain variable from user option."""
chain = args.get(opt_key)
if not chain:
return
settings[USER_OPTS_CONF_KEYS['begin_with']] = str(chain)
settings[USER_OPTS_CONF_KEYS['end_with']] = str(chain)
CONFIG_OPTS_SETTERS['single_chain'] = set_single_chain_opt
def set_seeds(opt_key, settings, args):
"""Set random seeds."""
seed_args = args.get(opt_key)
if not seed_args:
return
seeds = settings[USER_OPTS_CONF_KEYS.get(opt_key, opt_key)]
for kv in seed_args:
kv = kv.strip()
eq_pos = kv.find('=')
if eq_pos == 0 or eq_pos == len(kv) - 1:
raise RuntimeError('expected "key=seed" for --seed command-line argument; got "{}"'.format(kv))
key, value = (kv[:eq_pos].strip().lower(), kv[eq_pos + 1:].strip()) if eq_pos > 0 else ('default', kv.strip())
seeds[key] = value
CONFIG_OPTS_SETTERS['seed'] = set_seeds
def set_custom_user_vars(opt_key, settings, args):
"""Set custom user configuration variables."""
custom_vars = args.get(opt_key)
if not custom_vars:
return
for var in custom_vars:
# parse key-value pair
var = var.strip()
eq_pos = var.find('=')
if eq_pos < 1 or eq_pos > len(var) - 2:
raise RuntimeError('Expected "key=value" for --conf-var command-line argument; got "{}"'.format(var))
key, value = var[:eq_pos].strip(), var[eq_pos + 1:].strip()
# interpret type of value
try:
settings[key] = ast.literal_eval(value)
except Exception:
settings[key] = value
CONFIG_OPTS_SETTERS['conf_var'] = set_custom_user_vars | PypiClean |
/Explainer/dashboard_components/connectors.py | __all__ = [
'CutoffPercentileComponent',
'PosLabelConnector',
'CutoffConnector',
'IndexConnector',
'HighlightConnector'
]
import numpy as np
import dash_core_components as dcc
import dash_bootstrap_components as dbc
import dash_html_components as html
from dash.dependencies import Input, Output, State
from dash.exceptions import PreventUpdate
from ..dashboard_methods import *
class CutoffPercentileComponent(ExplainerComponent):
def __init__(self, explainer, title="Global cutoff", name=None,
hide_title=False, hide_cutoff=False, hide_percentile=False,
hide_selector=False,
pos_label=None, cutoff=0.5, percentile=None,
description=None, **kwargs):
"""
Slider to set a cutoff for Classifier components, based on setting the
cutoff at a certain percentile of predictions, e.g.:
percentile=0.8 means "mark the 20% highest scores as positive".
This cutoff can then be conencted with other components like e.g.
RocAucComponent with a CutoffConnector.
Args:
explainer (Explainer): explainer object constructed with either
ClassifierExplainer() or RegressionExplainer()
title (str, optional): Title of tab or page. Defaults to
"Global Cutoff".
name (str, optional): unique name to add to Component elements.
If None then random uuid is generated to make sure
it's unique. Defaults to None.
hide_title (bool, optional): Hide title.
hide_cutoff (bool, optional): Hide the cutoff slider. Defaults to False.
hide_percentile (bool, optional): Hide percentile slider. Defaults to False.
hide_selector (bool, optional): hide pos label selectors. Defaults to False.
pos_label ({int, str}, optional): initial pos label.
Defaults to explainer.pos_label
cutoff (float, optional): Initial cutoff. Defaults to 0.5.
percentile ([type], optional): Initial percentile. Defaults to None.
description (str, optional): Tooltip to display when hover over
component title. When None default text is shown.
"""
super().__init__(explainer, title, name)
self.cutoff_name = 'cutoffconnector-cutoff-'+self.name
self.selector = PosLabelSelector(explainer, name=self.name, pos_label=pos_label)
if self.description is None: self.description = """
Select a model cutoff such that all predicted probabilities higher than
the cutoff will be labeled positive, and all predicted probabilities
lower than the cutoff will be labeled negative. You can also set
the cutoff as a percenntile of all observations. Setting the cutoff
here will automatically set the cutoff in multiple other connected
component.
"""
self.register_dependencies(['preds', 'pred_percentiles'])
def layout(self):
return dbc.Card([
make_hideable(
dbc.CardHeader([
html.H3(self.title, className="card-title", id='cutoffconnector-title-'+self.name),
dbc.Tooltip(self.description, target='cutoffconnector-title-'+self.name),
]), hide=self.hide_title),
dbc.CardBody([
dbc.Row([
dbc.Col([
dbc.Row([
make_hideable(
dbc.Col([
html.Div([
html.Label('Cutoff prediction probability:'),
dcc.Slider(id='cutoffconnector-cutoff-'+self.name,
min = 0.01, max = 0.99, step=0.01, value=self.cutoff,
marks={0.01: '0.01', 0.25: '0.25', 0.50: '0.50',
0.75: '0.75', 0.99: '0.99'},
included=False,
tooltip = {'always_visible' : False}),
], style={'margin-bottom': 15}, id='cutoffconnector-cutoff-div-'+self.name),
dbc.Tooltip(f"Scores above this cutoff will be labeled positive",
target='cutoffconnector-cutoff-div-'+self.name,
placement='bottom'),
]), hide=self.hide_cutoff),
]),
dbc.Row([
make_hideable(
dbc.Col([
html.Div([
html.Label('Cutoff percentile of samples:'),
dcc.Slider(id='cutoffconnector-percentile-'+self.name,
min = 0.01, max = 0.99, step=0.01, value=self.percentile,
marks={0.01: '0.01', 0.25: '0.25', 0.50: '0.50',
0.75: '0.75', 0.99: '0.99'},
included=False,
tooltip = {'always_visible' : False}),
], style={'margin-bottom': 15}, id='cutoffconnector-percentile-div-'+self.name),
dbc.Tooltip(f"example: if set to percentile=0.9: label the top 10% highest scores as positive, the rest negative.",
target='cutoffconnector-percentile-div-'+self.name,
placement='bottom'),
]), hide=self.hide_percentile),
])
]),
make_hideable(
dbc.Col([
self.selector.layout()
], width=2), hide=self.hide_selector),
])
])
])
def component_callbacks(self, app):
@app.callback(
Output('cutoffconnector-cutoff-'+self.name, 'value'),
[Input('cutoffconnector-percentile-'+self.name, 'value'),
Input('pos-label-'+self.name, 'value')]
)
def update_cutoff(percentile, pos_label):
if percentile is not None:
return np.round(self.explainer.cutoff_from_percentile(percentile, pos_label=pos_label), 2)
raise PreventUpdate
class PosLabelConnector(ExplainerComponent):
def __init__(self, input_pos_label, output_pos_labels):
self.input_pos_label_name = self._get_pos_label(input_pos_label)
self.output_pos_label_names = self._get_pos_labels(output_pos_labels)
# if self.input_pos_label_name in self.output_pos_label_names:
# # avoid circulat callbacks
# self.output_pos_label_names.remove(self.input_pos_label_name)
def _get_pos_label(self, input_pos_label):
if isinstance(input_pos_label, PosLabelSelector):
return 'pos-label-' + input_pos_label.name
elif hasattr(input_pos_label, 'selector') and isinstance(input_pos_label.selector, PosLabelSelector):
return 'pos-label-' + input_pos_label.selector.name
elif isinstance(input_pos_label, str):
return input_pos_label
else:
raise ValueError("input_pos_label should either be a str, "
"PosLabelSelector or an instance with a .selector property"
" that is a PosLabelSelector!")
def _get_pos_labels(self, output_pos_labels):
def get_pos_labels(o):
if isinstance(o, PosLabelSelector):
return ['pos-label-'+o.name]
elif isinstance(o, str):
return [str]
elif hasattr(o, 'pos_labels'):
return o.pos_labels
return []
if hasattr(output_pos_labels, '__iter__'):
pos_labels = []
for comp in output_pos_labels:
pos_labels.extend(get_pos_labels(comp))
return list(set(pos_labels))
else:
return get_pos_labels(output_pos_labels)
def component_callbacks(self, app):
if self.output_pos_label_names:
@app.callback(
[Output(pos_label_name, 'value') for pos_label_name in self.output_pos_label_names],
[Input(self.input_pos_label_name, 'value')]
)
def update_pos_labels(pos_label):
return tuple(pos_label for i in range(len(self.output_pos_label_names)))
class CutoffConnector(ExplainerComponent):
def __init__(self, input_cutoff, output_cutoffs):
"""Connect the cutoff selector of input_cutoff with those of output_cutoffs.
You can use this to connect a CutoffPercentileComponent with a
RocAucComponent for example,
When you change the cutoff in input_cutoff, all the cutoffs in output_cutoffs
will automatically be updated.
Args:
input_cutoff ([{str, ExplainerComponent}]): Either a str or an
ExplainerComponent. If str should be equal to the
name of the cutoff property. If ExplainerComponent then
should have a .cutoff_name property.
output_cutoffs (list(str, ExplainerComponent)): list of str of
ExplainerComponents.
"""
self.input_cutoff_name = self.cutoff_name(input_cutoff)
self.output_cutoff_names = self.cutoff_name(output_cutoffs)
if not isinstance(self.output_cutoff_names, list):
self.output_cutoff_names = [self.output_cutoff_names]
@staticmethod
def cutoff_name(cutoffs):
def get_cutoff_name(o):
if isinstance(o, str): return o
elif isinstance(o, ExplainerComponent):
if not hasattr(o, "cutoff_name"):
raise ValueError(f"{o} does not have an .cutoff_name property!")
return o.cutoff_name
raise ValueError(f"{o} is neither str nor an ExplainerComponent with an .cutoff_name property")
if hasattr(cutoffs, '__iter__'):
cutoff_name_list = []
for cutoff in cutoffs:
cutoff_name_list.append(get_cutoff_name(cutoff))
return cutoff_name_list
else:
return get_cutoff_name(cutoffs)
def component_callbacks(self, app):
@app.callback(
[Output(cutoff_name, 'value') for cutoff_name in self.output_cutoff_names],
[Input(self.input_cutoff_name, 'value')]
)
def update_cutoffs(cutoff):
return tuple(cutoff for i in range(len(self.output_cutoff_names)))
class IndexConnector(ExplainerComponent):
def __init__(self, input_index, output_indexes):
"""Connect the index selector of input_index with those of output_indexes.
You can use this to connect a RandomIndexComponent with a
PredictionSummaryComponent for example.
When you change the index in input_index, all the indexes in output_indexes
will automatically be updated.
Args:
input_index ([{str, ExplainerComponent}]): Either a str or an
ExplainerComponent. If str should be equal to the
name of the index property. If ExplainerComponent then
should have a .index_name property.
output_indexes (list(str, ExplainerComponent)): list of str of
ExplainerComponents.
"""
self.input_index_name = self.index_name(input_index)
self.output_index_names = self.index_name(output_indexes)
if not isinstance(self.output_index_names, list):
self.output_index_names = [self.output_index_names]
@staticmethod
def index_name(indexes):#, multi=False):
def get_index_name(o):
if isinstance(o, str): return o
elif isinstance(o, ExplainerComponent):
if not hasattr(o, "index_name"):
raise ValueError(f"{o} does not have an .index_name property!")
return o.index_name
raise ValueError(f"{o} is neither str nor an ExplainerComponent with an .index_name property")
if hasattr(indexes, '__iter__'):
index_name_list = []
for index in indexes:
index_name_list.append(get_index_name(index))
return index_name_list
else:
return get_index_name(indexes)
def component_callbacks(self, app):
@app.callback(
[Output(index_name, 'value') for index_name in self.output_index_names],
[Input(self.input_index_name, 'value')]
)
def update_indexes(index):
return tuple(index for i in range(len(self.output_index_names)))
class HighlightConnector(ExplainerComponent):
def __init__(self, input_highlight, output_highlights):
"""Connect the highlight selector of input_highlight with those of output_highlights.
You can use this to connect a DecisionTreesComponent component to a
DecisionPathGraphComponent for example.
When you change the highlight in input_highlight, all the highlights in output_highlights
will automatically be updated.
Args:
input_highlight ([{str, ExplainerComponent}]): Either a str or an
ExplainerComponent. If str should be equal to the
name of the highlight property. If ExplainerComponent then
should have a .highlight_name property.
output_highlights (list(str, ExplainerComponent)): list of str of
ExplainerComponents.
"""
self.input_highlight_name = self.highlight_name(input_highlight)
self.output_highlight_names = self.highlight_name(output_highlights)
if not isinstance(self.output_highlight_names, list):
self.output_highlight_names = [self.output_highlight_names]
@staticmethod
def highlight_name(highlights):
def get_highlight_name(o):
if isinstance(o, str): return o
elif isinstance(o, ExplainerComponent):
if not hasattr(o, "highlight_name"):
raise ValueError(f"{o} does not have an .highlight_name property!")
return o.highlight_name
raise ValueError(f"{o} is neither str nor an ExplainerComponent with an .highlight_name property")
if hasattr(highlights, '__iter__'):
highlight_name_list = []
for highlight in highlights:
highlight_name_list.append(get_highlight_name(highlight))
return highlight_name_list
else:
return get_highlight_name(highlights)
def component_callbacks(self, app):
@app.callback(
[Output(highlight_name, 'value') for highlight_name in self.output_highlight_names],
[Input(self.input_highlight_name, 'value')])
def update_highlights(highlight):
return tuple(highlight for i in range(len(self.output_highlight_names))) | PypiClean |
/FlaskCms-0.0.4.tar.gz/FlaskCms-0.0.4/flask_cms/static/js/ckeditor/plugins/codemirror/js/mode/dtd/dtd.js | (function(mod) {
if (typeof exports == "object" && typeof module == "object") // CommonJS
mod(require("../../lib/codemirror"));
else if (typeof define == "function" && define.amd) // AMD
define(["../../lib/codemirror"], mod);
else // Plain browser env
mod(CodeMirror);
})(function(CodeMirror) {
"use strict";
CodeMirror.defineMode("dtd", function(config) {
var indentUnit = config.indentUnit, type;
function ret(style, tp) {type = tp; return style;}
function tokenBase(stream, state) {
var ch = stream.next();
if (ch == "<" && stream.eat("!") ) {
if (stream.eatWhile(/[\-]/)) {
state.tokenize = tokenSGMLComment;
return tokenSGMLComment(stream, state);
} else if (stream.eatWhile(/[\w]/)) return ret("keyword", "doindent");
} else if (ch == "<" && stream.eat("?")) { //xml declaration
state.tokenize = inBlock("meta", "?>");
return ret("meta", ch);
} else if (ch == "#" && stream.eatWhile(/[\w]/)) return ret("atom", "tag");
else if (ch == "|") return ret("keyword", "seperator");
else if (ch.match(/[\(\)\[\]\-\.,\+\?>]/)) return ret(null, ch);//if(ch === ">") return ret(null, "endtag"); else
else if (ch.match(/[\[\]]/)) return ret("rule", ch);
else if (ch == "\"" || ch == "'") {
state.tokenize = tokenString(ch);
return state.tokenize(stream, state);
} else if (stream.eatWhile(/[a-zA-Z\?\+\d]/)) {
var sc = stream.current();
if( sc.substr(sc.length-1,sc.length).match(/\?|\+/) !== null )stream.backUp(1);
return ret("tag", "tag");
} else if (ch == "%" || ch == "*" ) return ret("number", "number");
else {
stream.eatWhile(/[\w\\\-_%.{,]/);
return ret(null, null);
}
}
function tokenSGMLComment(stream, state) {
var dashes = 0, ch;
while ((ch = stream.next()) != null) {
if (dashes >= 2 && ch == ">") {
state.tokenize = tokenBase;
break;
}
dashes = (ch == "-") ? dashes + 1 : 0;
}
return ret("comment", "comment");
}
function tokenString(quote) {
return function(stream, state) {
var escaped = false, ch;
while ((ch = stream.next()) != null) {
if (ch == quote && !escaped) {
state.tokenize = tokenBase;
break;
}
escaped = !escaped && ch == "\\";
}
return ret("string", "tag");
};
}
function inBlock(style, terminator) {
return function(stream, state) {
while (!stream.eol()) {
if (stream.match(terminator)) {
state.tokenize = tokenBase;
break;
}
stream.next();
}
return style;
};
}
return {
startState: function(base) {
return {tokenize: tokenBase,
baseIndent: base || 0,
stack: []};
},
token: function(stream, state) {
if (stream.eatSpace()) return null;
var style = state.tokenize(stream, state);
var context = state.stack[state.stack.length-1];
if (stream.current() == "[" || type === "doindent" || type == "[") state.stack.push("rule");
else if (type === "endtag") state.stack[state.stack.length-1] = "endtag";
else if (stream.current() == "]" || type == "]" || (type == ">" && context == "rule")) state.stack.pop();
else if (type == "[") state.stack.push("[");
return style;
},
indent: function(state, textAfter) {
var n = state.stack.length;
if( textAfter.match(/\]\s+|\]/) )n=n-1;
else if(textAfter.substr(textAfter.length-1, textAfter.length) === ">"){
if(textAfter.substr(0,1) === "<")n;
else if( type == "doindent" && textAfter.length > 1 )n;
else if( type == "doindent")n--;
else if( type == ">" && textAfter.length > 1)n;
else if( type == "tag" && textAfter !== ">")n;
else if( type == "tag" && state.stack[state.stack.length-1] == "rule")n--;
else if( type == "tag")n++;
else if( textAfter === ">" && state.stack[state.stack.length-1] == "rule" && type === ">")n--;
else if( textAfter === ">" && state.stack[state.stack.length-1] == "rule")n;
else if( textAfter.substr(0,1) !== "<" && textAfter.substr(0,1) === ">" )n=n-1;
else if( textAfter === ">")n;
else n=n-1;
//over rule them all
if(type == null || type == "]")n--;
}
return state.baseIndent + n * indentUnit;
},
electricChars: "]>"
};
});
CodeMirror.defineMIME("application/xml-dtd", "dtd");
}); | PypiClean |
/FreeClimb-4.5.0-py3-none-any.whl/freeclimb/model/remove_from_conference.py | import re # noqa: F401
import sys # noqa: F401
from freeclimb.model_utils import ( # noqa: F401
ApiTypeError,
ModelComposed,
ModelNormal,
ModelSimple,
cached_property,
change_keys_js_to_python,
convert_js_args_to_python_args,
date,
datetime,
file_type,
none_type,
validate_get_composed_info,
OpenApiModel
)
from freeclimb.exceptions import ApiAttributeError
def lazy_import():
from freeclimb.model.add_to_conference import AddToConference
from freeclimb.model.create_conference import CreateConference
from freeclimb.model.dequeue import Dequeue
from freeclimb.model.enqueue import Enqueue
from freeclimb.model.get_digits import GetDigits
from freeclimb.model.get_speech import GetSpeech
from freeclimb.model.hangup import Hangup
from freeclimb.model.out_dial import OutDial
from freeclimb.model.park import Park
from freeclimb.model.pause import Pause
from freeclimb.model.percl_command import PerclCommand
from freeclimb.model.play import Play
from freeclimb.model.play_early_media import PlayEarlyMedia
from freeclimb.model.record_utterance import RecordUtterance
from freeclimb.model.redirect import Redirect
from freeclimb.model.reject import Reject
from freeclimb.model.remove_from_conference import RemoveFromConference
from freeclimb.model.remove_from_conference_all_of import RemoveFromConferenceAllOf
from freeclimb.model.say import Say
from freeclimb.model.send_digits import SendDigits
from freeclimb.model.set_listen import SetListen
from freeclimb.model.set_talk import SetTalk
from freeclimb.model.sms import Sms
from freeclimb.model.start_record_call import StartRecordCall
from freeclimb.model.terminate_conference import TerminateConference
from freeclimb.model.unpark import Unpark
globals()['AddToConference'] = AddToConference
globals()['CreateConference'] = CreateConference
globals()['Dequeue'] = Dequeue
globals()['Enqueue'] = Enqueue
globals()['GetDigits'] = GetDigits
globals()['GetSpeech'] = GetSpeech
globals()['Hangup'] = Hangup
globals()['OutDial'] = OutDial
globals()['Park'] = Park
globals()['Pause'] = Pause
globals()['PerclCommand'] = PerclCommand
globals()['Play'] = Play
globals()['PlayEarlyMedia'] = PlayEarlyMedia
globals()['RecordUtterance'] = RecordUtterance
globals()['Redirect'] = Redirect
globals()['Reject'] = Reject
globals()['RemoveFromConference'] = RemoveFromConference
globals()['RemoveFromConferenceAllOf'] = RemoveFromConferenceAllOf
globals()['Say'] = Say
globals()['SendDigits'] = SendDigits
globals()['SetListen'] = SetListen
globals()['SetTalk'] = SetTalk
globals()['Sms'] = Sms
globals()['StartRecordCall'] = StartRecordCall
globals()['TerminateConference'] = TerminateConference
globals()['Unpark'] = Unpark
class RemoveFromConference(ModelComposed):
"""NOTE: This class is auto generated by OpenAPI Generator.
Ref: https://openapi-generator.tech
Do not edit the class manually.
Attributes:
allowed_values (dict): The key is the tuple path to the attribute
and the for var_name this is (var_name,). The value is a dict
with a capitalized key describing the allowed value and an allowed
value. These dicts store the allowed enum values.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
discriminator_value_class_map (dict): A dict to go from the discriminator
variable value to the discriminator class name.
validations (dict): The key is the tuple path to the attribute
and the for var_name this is (var_name,). The value is a dict
that stores validations for max_length, min_length, max_items,
min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum,
inclusive_minimum, and regex.
additional_properties_type (tuple): A tuple of classes accepted
as additional properties values.
"""
allowed_values = {
}
validations = {
}
@cached_property
def additional_properties_type():
"""
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
"""
lazy_import()
return (bool, date, datetime, dict, float, int, list, str, none_type,) # noqa: E501
_nullable = False
@cached_property
def openapi_types():
"""
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type.
"""
lazy_import()
return {
'call_id': (str,), # noqa: E501
'command': (str,), # noqa: E501
}
@cached_property
def discriminator():
return None
attribute_map = {
'call_id': 'callId', # noqa: E501
'command': 'command', # noqa: E501
}
read_only_vars = {
}
@classmethod
@convert_js_args_to_python_args
def _from_openapi_data(cls, *args, **kwargs): # noqa: E501
"""RemoveFromConference - a model defined in OpenAPI
Keyword Args:
call_id (str): ID of the Call leg to be removed from the Conference. The Call must be in a Conference or an error will be triggered.
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
command (str): Name of PerCL Command (this is automatically derived from mapping configuration and should not be manually supplied in any arguments). [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
self = super(OpenApiModel, cls).__new__(cls)
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
constant_args = {
'_check_type': _check_type,
'_path_to_item': _path_to_item,
'_spec_property_naming': _spec_property_naming,
'_configuration': _configuration,
'_visited_composed_classes': self._visited_composed_classes,
}
composed_info = validate_get_composed_info(
constant_args, kwargs, self)
self._composed_instances = composed_info[0]
self._var_name_to_model_instances = composed_info[1]
self._additional_properties_model_instances = composed_info[2]
discarded_args = composed_info[3]
for var_name, var_value in kwargs.items():
if var_name in discarded_args and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self._additional_properties_model_instances:
# discard variable.
continue
setattr(self, var_name, var_value)
return self
required_properties = set([
'_data_store',
'_check_type',
'_spec_property_naming',
'_path_to_item',
'_configuration',
'_visited_composed_classes',
'_composed_instances',
'_var_name_to_model_instances',
'_additional_properties_model_instances',
])
@convert_js_args_to_python_args
def __init__(self, *args, **kwargs): # noqa: E501
"""RemoveFromConference - a model defined in OpenAPI
Keyword Args:
call_id (str): ID of the Call leg to be removed from the Conference. The Call must be in a Conference or an error will be triggered.
_check_type (bool): if True, values for parameters in openapi_types
will be type checked and a TypeError will be
raised if the wrong type is input.
Defaults to True
_path_to_item (tuple/list): This is a list of keys or values to
drill down to the model in received_data
when deserializing a response
_spec_property_naming (bool): True if the variable names in the input data
are serialized names, as specified in the OpenAPI document.
False if the variable names in the input data
are pythonic names, e.g. snake case (default)
_configuration (Configuration): the instance to use when
deserializing a file_type parameter.
If passed, type conversion is attempted
If omitted no type conversion is done.
_visited_composed_classes (tuple): This stores a tuple of
classes that we have traveled through so that
if we see that class again we will not use its
discriminator again.
When traveling through a discriminator, the
composed schema that is
is traveled through is added to this set.
For example if Animal has a discriminator
petType and we pass in "Dog", and the class Dog
allOf includes Animal, we move through Animal
once using the discriminator, and pick Dog.
Then in Dog, we will make an instance of the
Animal class but this time we won't travel
through its discriminator because we passed in
_visited_composed_classes = (Animal,)
command (str): Name of PerCL Command (this is automatically derived from mapping configuration and should not be manually supplied in any arguments). [optional] # noqa: E501
"""
_check_type = kwargs.pop('_check_type', True)
_spec_property_naming = kwargs.pop('_spec_property_naming', False)
_path_to_item = kwargs.pop('_path_to_item', ())
_configuration = kwargs.pop('_configuration', None)
_visited_composed_classes = kwargs.pop('_visited_composed_classes', ())
if args:
raise ApiTypeError(
"Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % (
args,
self.__class__.__name__,
),
path_to_item=_path_to_item,
valid_classes=(self.__class__,),
)
self._data_store = {}
self._check_type = _check_type
self._spec_property_naming = _spec_property_naming
self._path_to_item = _path_to_item
self._configuration = _configuration
self._visited_composed_classes = _visited_composed_classes + (self.__class__,)
constant_args = {
'_check_type': _check_type,
'_path_to_item': _path_to_item,
'_spec_property_naming': _spec_property_naming,
'_configuration': _configuration,
'_visited_composed_classes': self._visited_composed_classes,
}
composed_info = validate_get_composed_info(
constant_args, kwargs, self)
self._composed_instances = composed_info[0]
self._var_name_to_model_instances = composed_info[1]
self._additional_properties_model_instances = composed_info[2]
discarded_args = composed_info[3]
for var_name, var_value in kwargs.items():
if var_name in discarded_args and \
self._configuration is not None and \
self._configuration.discard_unknown_keys and \
self._additional_properties_model_instances:
# discard variable.
continue
setattr(self, var_name, var_value)
if var_name in self.read_only_vars:
raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate "
f"class with read only attributes.")
@cached_property
def command():
mappings = PerclCommand.discriminator['command']
mapping = next((mapping for mapping,schema in mappings.items() if schema == RemoveFromConference), None)
if mapping == None:
raise ApiAttributeError("{0} has no mapping '{1}'".format(RemoveFromConference.__class__.name, 'command'))
return mapping
@cached_property
def _composed_schemas():
# we need this here to make our import statements work
# we must store _composed_schemas in here so the code is only run
# when we invoke this method. If we kept this at the class
# level we would get an error because the class level
# code would be run when this module is imported, and these composed
# classes don't exist yet because their module has not finished
# loading
lazy_import()
return {
'anyOf': [
],
'allOf': [
PerclCommand,
RemoveFromConferenceAllOf,
],
'oneOf': [
],
} | PypiClean |
/Muntjac-1.1.2.tar.gz/Muntjac-1.1.2/muntjac/demo/sampler/features/table/TableStylingExample.py | from muntjac.demo.sampler.ExampleUtil import ExampleUtil
from muntjac.api import VerticalLayout, Table, Link, Button, Alignment
from muntjac.ui import button
from muntjac.event.action import Action
from muntjac.event import action
from muntjac.ui.table import IColumnGenerator, ICellStyleGenerator
from muntjac.terminal.external_resource import ExternalResource
from muntjac.event.item_click_event import IItemClickListener, ItemClickEvent
ACTION_RED = Action('red')
ACTION_BLUE = Action('blue')
ACTION_GREEN = Action('green')
ACTION_NONE = Action('none')
ACTIONS = [ACTION_RED, ACTION_GREEN, ACTION_BLUE, ACTION_NONE]
class TableStylingExample(VerticalLayout):
def __init__(self):
super(TableStylingExample, self).__init__()
self.setSpacing(True)
self._table = Table()
self._markedRows = dict()
self._markedCells = dict()
self.addComponent(self._table)
# set a style name, so we can style rows and cells
self._table.setStyleName('contacts')
# size
self._table.setWidth('100%')
self._table.setPageLength(7)
# connect data source
self._table.setContainerDataSource(ExampleUtil.getPersonContainer())
# Generate the email-link from firstname & lastname
self._table.addGeneratedColumn('Email', TableColumnGenerator(self))
# turn on column reordering and collapsing
self._table.setColumnReorderingAllowed(True)
self._table.setColumnCollapsingAllowed(True)
# Actions (a.k.a context menu)
self._table.addActionHandler( TableActionHandler(self) )
# style generator
self._table.setCellStyleGenerator( TableStyleGenerator(self) )
# toggle cell 'marked' styling when double-clicked
self._table.addListener(TableClickListener(self), IItemClickListener)
# Editing
# we don't want to update container before pressing 'save':
self._table.setWriteThrough(False)
# edit button
editButton = Button('Edit')
self.addComponent(editButton)
editButton.addListener(EditListener(self, editButton),
button.IClickListener)
self.setComponentAlignment(editButton, Alignment.TOP_RIGHT)
class TableColumnGenerator(IColumnGenerator):
def __init__(self, c):
self._c = c
def generateCell(self, source, itemId, columnId):
item = self._c._table.getItem(itemId)
fn = item.getItemProperty(
ExampleUtil.PERSON_PROPERTY_FIRSTNAME).getValue()
ln = item.getItemProperty(
ExampleUtil.PERSON_PROPERTY_LASTNAME).getValue()
email = fn.lower() + '.' + ln.lower() + '@example.com'
# the Link -component:
emailLink = Link(email, ExternalResource('mailto:' + email))
return emailLink
class TableActionHandler(action.IHandler):
def __init__(self, c):
self._c = c
def getActions(self, target, sender):
return ACTIONS
def handleAction(self, a, sender, target):
if target in self._c._markedRows:
del self._c._markedRows[target]
if a != ACTION_NONE:
# we're using the cations caption as stylename as well:
self._c._markedRows[target] = a.getCaption()
# this causes the CellStyleGenerator to return new styles,
# but table can't automatically know, we must tell it:
self._c._table.requestRepaint()
class TableStyleGenerator(ICellStyleGenerator):
def __init__(self, c):
self._c = c
def getStyle(self, itemId, propertyId):
if propertyId is None:
# no propertyId, styling row
return self._c._markedRows.get(itemId)
elif propertyId == 'Email':
# style the generated email column
return 'email'
else:
cells = self._c._markedCells.get(itemId)
if cells is not None and propertyId in cells:
return 'marked' # marked cell
else:
return None # no style
class TableClickListener(IItemClickListener):
def __init__(self, c):
self._c = c
def itemClick(self, event):
if event.getButton() == ItemClickEvent.BUTTON_RIGHT:
# you can handle left/right/middle -mouseclick
pass
if event.isDoubleClick():
itemId = event.getItemId()
propertyId = event.getPropertyId()
cells = self._c._markedCells.get(itemId)
if cells is None:
cells = set()
self._c._markedCells[itemId] = cells
if propertyId in cells:
# toggle marking off
cells.remove(propertyId)
else:
# toggle marking on
cells.add(propertyId)
# this causes the CellStyleGenerator to return new styles,
# but table can't automatically know, we must tell it:
self._c._table.requestRepaint()
class EditListener(button.IClickListener):
def __init__(self, c, editButton):
self._c = c
self._editButton = editButton
def buttonClick(self, event):
self._c._table.setEditable(not self._c._table.isEditable())
if self._c._table.isEditable():
self._editButton.setCaption('Save')
else:
self._editButton.setCaption('Edit') | PypiClean |
/HTSQL-2.3.3.tar.gz/HTSQL-2.3.3/src/htsql/tweak/etl/cmd/merge.py |
from ....core.util import listof
from ....core.adapter import Utility, adapt
from ....core.context import context
from ....core.error import Error, PermissionError
from ....core.entity import TableEntity, ColumnEntity
from ....core.model import TableArc
from ....core.classify import localize, relabel
from ....core.connect import transaction, scramble, unscramble
from ....core.domain import IdentityDomain, RecordDomain, ListDomain, Product
from ....core.cmd.fetch import build_fetch
from ....core.cmd.act import Act, ProduceAction, act
from ....core.tr.bind import BindingState, Select
from ....core.syn.syntax import VoidSyntax
from ....core.tr.binding import (VoidBinding, RootBinding, FormulaBinding,
LocateBinding, SelectionBinding, SieveBinding, AliasBinding,
SegmentBinding, QueryBinding, FreeTableRecipe, ColumnRecipe)
from ....core.tr.signature import IsEqualSig, AndSig, PlaceholderSig
from ....core.tr.decorate import decorate
from ....core.tr.coerce import coerce
from ....core.tr.lookup import identify
from .command import MergeCmd
from .insert import (BuildExtractNode, BuildExtractTable, BuildExecuteInsert,
BuildResolveIdentity, BuildResolveChain)
from ..tr.dump import serialize_update
import itertools
class ExtractIdentityPipe(object):
def __init__(self, node, arcs, id_indices, other_indices):
self.node = node
self.arcs = arcs
self.id_indices = id_indices
self.other_indices = other_indices
def __call__(self, row):
return (tuple(row[idx] for idx in self.id_indices),
tuple(row[idx] for idx in self.other_indices))
class BuildExtractIdentity(Utility):
def __init__(self, node, arcs):
self.node = node
self.arcs = arcs
def __call__(self):
identity_arcs = localize(self.node)
if identity_arcs is None:
raise Error("Expected a table with identity")
index_by_arc = dict((arc, index) for index, arc in enumerate(self.arcs))
id_indices = []
for arc in identity_arcs:
if arc not in index_by_arc:
labels = relabel(arc)
if not labels:
raise Error("Missing identity field")
else:
label = labels[0]
raise Error("Missing identity field %s"
% label.name.encode('utf-8'))
index = index_by_arc[arc]
id_indices.append(index)
other_indices = []
arcs = []
for idx, arc in enumerate(self.arcs):
if arc in identity_arcs:
continue
other_indices.append(idx)
arcs.append(arc)
return ExtractIdentityPipe(self.node, arcs, id_indices, other_indices)
class ResolveKeyPipe(object):
def __init__(self, name, columns, domain, pipe, with_error):
self.name = name
self.columns = columns
self.pipe = pipe
self.domain = domain
self.leaves = domain.leaves
self.with_error = with_error
def __call__(self, value):
assert value is not None
raw_values = []
for leaf in self.leaves:
raw_value = value
for idx in leaf:
raw_value = raw_value[idx]
raw_values.append(raw_value)
product = self.pipe(raw_values)
data = product.data
assert len(data) <= 1
if data:
return data[0]
if self.with_error:
quote = None
if self.name:
quote = u"%s[%s]" % (self.name, self.domain.dump(value))
else:
quote = u"[%s]" % self.domain.dump(value)
raise Error("Unable to find an entity", quote)
return None
class BuildResolveKey(Utility):
def __init__(self, node, with_error=True):
self.node = node
self.table = node.table
self.with_error = with_error
def __call__(self):
labels = relabel(TableArc(self.table))
name = labels[0].name if labels else None
state = BindingState()
syntax = VoidSyntax()
scope = RootBinding(syntax)
state.set_root(scope)
seed = state.use(FreeTableRecipe(self.table), syntax)
recipe = identify(seed)
if recipe is None:
raise Error("Cannot determine identity of a link")
identity = state.use(recipe, syntax, scope=seed)
count = itertools.count()
def make_images(identity):
images = []
for field in identity.elements:
if isinstance(field.domain, IdentityDomain):
images.extend(make_images(field))
else:
item = FormulaBinding(scope,
PlaceholderSig(next(count)),
field.domain,
syntax)
images.append((item, field))
return images
images = make_images(identity)
scope = LocateBinding(scope, seed, images, None, syntax)
state.push_scope(scope)
columns = []
if self.table.primary_key is not None:
columns = self.table.primary_key.origin_columns
else:
for key in self.table.unique_keys:
if key.is_partial:
continue
if all(not column.is_nullable
for column in key.origin_columns):
rcolumns = key.origin_columns
break
if not columns:
raise Error("Table does not have a primary key")
elements = []
for column in columns:
binding = state.use(ColumnRecipe(column), syntax)
elements.append(binding)
fields = [decorate(element) for element in elements]
domain = RecordDomain(fields)
scope = SelectionBinding(scope, elements, domain, syntax)
binding = Select.__invoke__(scope, state)
domain = ListDomain(binding.domain)
binding = SegmentBinding(state.root, binding, domain, syntax)
profile = decorate(binding)
binding = QueryBinding(state.root, binding, profile, syntax)
pipe = build_fetch(binding)
domain = identity.domain
return ResolveKeyPipe(name, columns, domain, pipe, self.with_error)
class ExecuteUpdatePipe(object):
def __init__(self, table, input_columns, key_columns,
output_columns, sql):
assert isinstance(table, TableEntity)
assert isinstance(input_columns, listof(ColumnEntity))
assert isinstance(key_columns, listof(ColumnEntity))
assert isinstance(output_columns, listof(ColumnEntity))
assert isinstance(sql, unicode)
self.table = table
self.input_columns = input_columns
self.key_columns = key_columns
self.output_columns = output_columns
self.sql = sql
self.input_converts = [scramble(column.domain)
for column in input_columns]
self.key_converts = [scramble(column.domain)
for column in key_columns]
self.output_converts = [unscramble(column.domain)
for column in output_columns]
def __call__(self, key_row, row):
key_row = tuple(convert(item)
for item, convert in zip(key_row, self.key_converts))
row = tuple(convert(item)
for item, convert in zip(row, self.input_converts))
if not row:
return key_row
if not context.env.can_write:
raise PermissionError("No write permissions")
with transaction() as connection:
cursor = connection.cursor()
cursor.execute(self.sql.encode('utf-8'), row+key_row)
rows = cursor.fetchall()
if len(rows) != 1:
raise Error("Unable to locate the updated row")
[row] = rows
return row
class BuildExecuteUpdate(Utility):
def __init__(self, table, columns):
assert isinstance(table, TableEntity)
assert isinstance(columns, listof(ColumnEntity))
self.table = table
self.columns = columns
def __call__(self):
table = self.table
returning_columns = []
if table.primary_key is not None:
returning_columns = table.primary_key.origin_columns
else:
for key in table.unique_keys:
if key.is_partial:
continue
if all(not column.is_nullable
for column in key.origin_columns):
returning_columns = key.origin_columns
break
if not returning_columns:
raise Error("Table does not have a primary key")
sql = serialize_update(table, self.columns, returning_columns,
returning_columns)
return ExecuteUpdatePipe(table, self.columns, returning_columns,
returning_columns, sql)
class ProduceMerge(Act):
adapt(MergeCmd, ProduceAction)
def __call__(self):
with transaction() as connection:
product = act(self.command.feed, self.action)
extract_node = BuildExtractNode.__invoke__(product.meta)
extract_table = BuildExtractTable.__invoke__(
extract_node.node, extract_node.arcs)
extract_identity = BuildExtractIdentity.__invoke__(
extract_node.node, extract_node.arcs)
resolve_key = BuildResolveKey.__invoke__(
extract_node.node, False)
extract_table_for_update = BuildExtractTable.__invoke__(
extract_identity.node, extract_identity.arcs)
execute_insert = BuildExecuteInsert.__invoke__(
extract_table.table, extract_table.columns)
execute_update = BuildExecuteUpdate.__invoke__(
extract_table_for_update.table,
extract_table_for_update.columns)
resolve_identity = BuildResolveIdentity.__invoke__(
execute_insert.table, execute_insert.output_columns,
extract_node.is_list)
meta = resolve_identity.profile
data = []
if extract_node.is_list:
records = product.data
record_domain = product.meta.domain.item_domain
else:
records = [product.data]
record_domain = product.meta.domain
for idx, record in enumerate(records):
if record is None:
continue
try:
row = extract_node(record)
update_id, update_row = extract_identity(row)
key = resolve_key(update_id)
if key is not None:
row = extract_table_for_update(update_row)
key = execute_update(key, row)
else:
row = extract_table(row)
key = execute_insert(row)
row = resolve_identity(key)
except Error, exc:
if extract_node.is_list:
message = "While merging record #%s" % (idx+1)
else:
message = "While merging a record"
quote = record_domain.dump(record)
exc.wrap(message, quote)
raise
data.append(row)
if not extract_node.is_list:
assert len(data) <= 1
if data:
data = data[0]
else:
data = None
return Product(meta, data) | PypiClean |
/Aries-Python-0.1.330.tar.gz/Aries-Python-0.1.330/Aries/storage/gs.py | import os
import logging
import warnings
import tempfile
import base64
import binascii
from functools import wraps
from google.cloud import storage
from google.cloud.exceptions import ServerError, Forbidden
from ..strings import Base64String
from ..tasks import FunctionTask
from .base import StorageFolderBase
from .cloud import BucketStorageObject, CloudStoragePrefix, CloudStorageIO
logger = logging.getLogger(__name__)
def setup_credentials(env_name, to_json_file=None):
"""Configures the GOOGLE_APPLICATION_CREDENTIALS
by saving the value of an environment variable to a JSON file.
"""
# Use the b64 encoded content as credentials if "GOOGLE_CREDENTIALS" is set.
credentials = os.environ.get(env_name)
if credentials and credentials.startswith("ew"):
if not to_json_file:
temp_file = tempfile.NamedTemporaryFile(suffix=".json", delete=False)
temp_file.close()
to_json_file = temp_file.name
Base64String(credentials).decode_to_file(to_json_file)
# Set "GOOGLE_APPLICATION_CREDENTIALS" if json file exists.
if os.path.exists(to_json_file):
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = to_json_file
def api_call(func=None, *args, **kwargs):
"""Makes API call and retry if there is an exception.
This is designed to resolve the 500 Backend Error from Google.
Args:
func (callable): A function or method.
Examples:
api_call(self.bucket.get_blob, self.prefix)
See Also: https://developers.google.com/drive/api/v3/handle-errors#resolve_a_500_error_backend_error
"""
if not func:
return None
# logger.debug("Making API call: %s..." % func.__name__)
with warnings.catch_warnings():
warnings.simplefilter("ignore", ResourceWarning)
warnings.simplefilter("ignore", UserWarning)
return FunctionTask(func, *args, **kwargs).run_and_retry(
max_retry=3,
exceptions=ServerError,
base_interval=60,
retry_pattern='linear',
capture_output=False
)
def api_decorator(method):
"""Decorator for making API call and retry if there is an exception.
This is designed to resolve the 500 Backend Error from Google.
When the decorated function is called, the function call will be retry if there is an exception.
Examples:
@api_decorator
def exists(self):
return self.blob.exists
"""
# logger.debug("Decorating %s for API call..." % method.__name__)
@wraps(method)
def wrapper(*method_args, **method_kwargs):
return api_call(method, *method_args, **method_kwargs)
return wrapper
class GSObject(BucketStorageObject):
"""The base class for Google Storage Object.
"""
MAX_BATCH_SIZE = 900
@property
def blob(self):
"""Gets or initialize a Google Cloud Storage Blob.
Returns: A Google Cloud Storage Blob object.
This does not check whether the object exists.
Use blob.exists() to determine whether or not the blob exists.
"""
if self._blob is None:
# logger.debug("Getting blob: %s" % self.uri)
# The following line will avoid sending a GET request
# but bucket object will not have the real metadata
bucket = self.client.bucket(self.bucket_name)
file_blob = api_call(bucket.get_blob, self.prefix)
if file_blob is None:
# The following will not make an HTTP request.
# It simply instantiates a blob object owned by this bucket.
# See https://googleapis.github.io/google-cloud-python/latest/storage/buckets.html
# #google.cloud.storage.bucket.Bucket.blob
file_blob = self.bucket.blob(self.prefix)
self._blob = file_blob
return self._blob
@api_decorator
def init_client(self):
return storage.Client()
@api_decorator
def init_bucket(self):
try:
# The get_bucket() method requires permission to access the bucket.
# The permission is not needed for getting the size or downloading the file.
bucket = self.client.get_bucket(self.bucket_name)
except Forbidden:
# Fallback to initializing a bucket object without sending GET request
logger.debug("Account does not have permission to access bucket: %s" % self.bucket_name)
bucket = self.client.bucket(self.bucket_name)
return bucket
@property
def gs_path(self):
return self.uri
@api_decorator
def exists(self):
"""Determines if there is an actual blob corresponds to this object.
"""
return self.blob.exists()
@api_decorator
def create(self):
"""Creates an empty blob, if the blob does not exist.
Returns:
Blob: The Google Cloud Storage blob.
"""
blob = storage.Blob(self.prefix, self.bucket)
if not blob.exists():
blob.upload_from_string("")
return blob
def delete(self):
self.delete_blob(self.blob)
def copy(self, to):
self.copy_blob(self.blob, to)
def copy_blob(self, blob, to):
"""Copies a blob object in the bucket to a new location.
Args:
blob: A Google Cloud Storage Blob object in the bucket.
to: URI of the new blob (gs://...).
Returns: True if the blob is copied. Otherwise False.
"""
destination = GSObject(to)
new_name = str(blob.name).replace(self.prefix, destination.prefix, 1)
if new_name != str(blob.name) or self.bucket_name != destination.bucket_name:
self.bucket.copy_blob(blob, destination.bucket, new_name)
return True
return False
@staticmethod
def delete_blob(blob):
blob.delete()
class GSPrefix(CloudStoragePrefix, GSObject):
# @api_decorator
def batch_request(self, blobs, method, *args, **kwargs):
"""Sends a batch request to run method of a batch of blobs.
The "method" will be applied to each blob in blobs like method(blob, *args, **kwargs)
Args:
blobs: A list of blobs, to be processed in a SINGLE batch.
method: The method for processing each blob.
*args: Additional arguments for method.
**kwargs: Keyword arguments for method.
Returns:
"""
if not blobs:
return 0
counter = 0
try:
with self.client.batch():
for blob in blobs:
method(blob, *args, **kwargs)
counter += 1
except ValueError as ex:
# Suppress the no deferred request errors
# This error occurs when there is no file/blob in the batch.
if str(ex).strip() == "No deferred requests":
return 0
raise ex
return counter
# @api_decorator
def batch_operation(self, method, *args, **kwargs):
blobs = self.blobs()
batch = []
counter = 0
for blob in blobs:
batch.append(blob)
if len(batch) > self.MAX_BATCH_SIZE:
counter += self.batch_request(batch, method, *args, **kwargs)
batch = []
if batch:
counter += self.batch_request(batch, method, *args, **kwargs)
return counter
@api_decorator
def blobs(self, delimiter=None):
"""Gets the blobs in the bucket having the prefix.
The returning list will contain object in the folder and all sub-folders
Args:
delimiter: Use this to emulate hierarchy.
If delimiter is None, the returning list will contain objects in the folder and in all sub-directories.
Set delimiter to "/" to eliminate files in sub-directories.
Returns: A list of GCS blobs.
See Also: https://googleapis.github.io/google-cloud-python/latest/storage/blobs.html
"""
return list(self.bucket.list_blobs(prefix=self.prefix, delimiter=delimiter))
@property
def uri_list(self):
"""Gets all file URIs with the prefix
"""
return [
"gs://%s/%s" % (self.bucket_name, b.name)
for b in self.blobs()
if not b.name.endswith("/")
]
@property
def files(self):
from .io import StorageFile
storage_files = []
for b in self.blobs("/"):
if b.name.endswith("/"):
continue
storage_file = StorageFile("gs://%s/%s" % (self.bucket_name, b.name))
storage_file.raw_io._blob = b
storage_files.append(storage_file)
return storage_files
@property
def folders(self):
return self.list_folders()
@api_decorator
def list_folders(self):
from .io import StorageFolder
iterator = self.bucket.list_blobs(prefix=self.prefix, delimiter='/')
list(iterator)
return [
StorageFolder("gs://%s/%s" % (self.bucket_name, p))
for p in iterator.prefixes
]
def exists(self):
return True if self.blob.exists() or self.objects else False
@api_decorator
def delete(self):
"""Deletes all objects with the same prefix."""
counter = self.batch_operation(self.delete_blob)
logger.debug("%d files deleted." % counter)
return counter
@api_decorator
def copy(self, to, contents_only=False):
"""Copies folder/file in a Google Cloud storage directory to another one.
Args:
to (str): Destination Google Cloud Storage path.
contents_only: Copies only the content of the folder. This applies only if the GSObject is a folder.
Defaults to False, i.e. a folder (with the same name as this folder)
will be created at the destination to contain the files.
Returns: The number of files copied.
Warnings:
When the URI of GSObject ends with "/", i.e. it is a folder,
use "contents_only" to indicate if a new folder should be created to contain all files copied.
When the GSObject is a file or a set of filtered files with the same prefix:
If to ends with slash ("/"), all files will be copied under the "to" folder.
folders partially in the prefix will be kept.
If to does NOT end with slash, the prefix of all files will simply be replaced with the prefix in "to".
See the following examples for more details.
Example:
Either
GSFolder("gs://bucket_a/alpha/beta/").copy("gs://bucket_b/x/y")
or
GSFolder("gs://bucket_a/alpha/beta/").copy("gs://bucket_b/x/y/")
will copy the following files:
gs://bucket_a/alpha/beta/gamma/example.txt
gs://bucket_a/alpha/beta/example.txt
to
gs://bucket_b/x/y/beta/gamma/example.txt
gs://bucket_b/x/y/beta/example.txt
Either
GSFolder("gs://bucket_a/alpha/beta/").copy("gs://bucket_b/x/y", contents_only=True)
or
GSFolder("gs://bucket_a/alpha/beta/").copy("gs://bucket_b/x/y/", contents_only=True)
will copy the following files:
gs://bucket_a/alpha/beta/gamma/example.txt
gs://bucket_a/alpha/beta/example.txt
to
gs://bucket_b/x/y/gamma/example.txt
gs://bucket_b/x/y/example.txt
Also
GSFolder("gs://bucket_a/alpha/be").copy("gs://bucket_b/x/y/")
will copy the following files:
gs://bucket_a/alpha/beta/gamma/example.txt
gs://bucket_a/alpha/beta/example.txt
to
gs://bucket_b/x/y/beta/gamma/example.txt
gs://bucket_b/x/y/beta/example.txt
However
GSFolder("gs://bucket_a/alpha/be").copy("gs://bucket_b/x/y")
will copy the following files:
gs://bucket_a/alpha/beta/gamma/example.txt
gs://bucket_a/alpha/beta/example.txt
to
gs://bucket_b/x/yta/gamma/example.txt
gs://bucket_b/x/yta/example.txt
"""
# Check if the destination is a bucket root.
# Prefix will be empty if destination is bucket root.
# Always append "/" to bucket root.
if not GSObject(to).prefix and not to.endswith("/"):
to += "/"
if self.prefix.endswith("/"):
# The source is a folder if its prefix ends with "/"
if contents_only:
to += "/"
else:
# Copy the contents into a folder with the same name.
to = os.path.join(to, self.name) + "/"
else:
# Otherwise, it can be a file or an object or a set of filtered objects or a folder.
if to.endswith("/"):
# If the destination ends with "/",
# copy all objects under the destination
to += self.name
else:
# If the destination does not end with "/",
# simply replace the prefix.
pass
# logger.debug("Copying files to %s" % to)
source_files = self.blobs()
if not source_files:
logger.debug("No files in %s" % self.uri)
return 0
counter = self.batch_operation(self.copy_blob, to)
logger.debug("%d files copied." % counter)
return counter
class GSFolder(GSPrefix, StorageFolderBase):
"""Represents a Google Cloud Storage Folder
Method Resolution Order: GSFolder, GSObject, StorageFolder, StorageObject
"""
def __init__(self, uri):
"""Initializes a Google Cloud Storage Directory.
Args:
uri: The path of the object, e.g. "gs://bucket_name/path/to/dir/".
"""
# super() will call the __init__() of StorageObject, StorageFolder and GSObject
GSObject.__init__(self, uri)
StorageFolderBase.__init__(self, uri)
# Make sure prefix ends with "/", otherwise it is not a "folder"
if self.prefix and not self.prefix.endswith("/"):
self.prefix += "/"
def exists(self):
return True if self.blob.exists() or self.file_paths or self.folder_paths else False
@property
def folder_paths(self):
"""Folders(Directories) in the directory.
"""
return self.__folders_paths()
@api_decorator
def __folders_paths(self):
iterator = self.bucket.list_blobs(prefix=self.prefix, delimiter='/')
list(iterator)
return [
"gs://%s/%s" % (self.bucket_name, p)
for p in iterator.prefixes
]
@property
def file_paths(self):
"""Files in the directory
"""
paths = self.__file_paths()
return paths
def __file_paths(self):
return [
"gs://%s/%s" % (self.bucket_name, b.name)
for b in self.blobs("/")
if not b.name.endswith("/")
]
@api_decorator
def filter_files(self, prefix):
return [
GSFile("gs://%s/%s" % (self.bucket_name, b.name))
for b in self.bucket.list_blobs(prefix=os.path.join(self.prefix, prefix), delimiter='/')
if not b.name.endswith("/")
]
class GSFile(GSObject, CloudStorageIO):
def __init__(self, uri):
"""Represents a file on Google Cloud Storage as a file-like object implementing the IOBase interface.
Args:
uri:
GSFile allows seek and read without opening the file.
However, position/offset will be reset when open() is called.
The context manager calls open() when enter.
"""
GSObject.__init__(self, uri)
CloudStorageIO.__init__(self, uri)
@property
def updated_time(self):
return self.blob.updated
@property
def md5_hex(self):
return binascii.hexlify(base64.urlsafe_b64decode(self.blob.md5_hash)).decode()
def get_size(self):
return self.blob.size
def read_bytes(self, start, end):
return api_call(self.blob.download_as_bytes, start=start, end=end)
def download(self, to_file_obj):
api_call(self.blob.download_to_filename, to_file_obj.name)
return to_file_obj
def upload(self, from_file_obj):
api_call(self.blob.upload_from_file, from_file_obj) | PypiClean |
/AN-DiscordBot-3.9.4.tar.gz/AN-DiscordBot-3.9.4/anbot/__main__.py |
# Discord Version check
import sys
import discord
from anbot.core.bot import AN, ExitCodes
from anbot.core.data_manager import create_temp_config, load_basic_configuration, config_file
from anbot.core.json_io import JsonIO
from anbot.core.global_checks import init_global_checks
from anbot.core.events import init_events
from anbot.core.cli import interactive_config, confirm, parse_cli_flags, ask_sentry
from anbot.core.core_commands import Core
from anbot.core import __version__
import asyncio
import logging.handlers
import logging
import os
# Let's not force this dependency, uvloop is much faster on cpython
if sys.implementation.name == "cpython":
try:
import uvloop
except ImportError:
pass
else:
asyncio.set_event_loop_policy(uvloop.EventLoopPolicy())
if sys.platform == "win32":
asyncio.set_event_loop(asyncio.ProactorEventLoop())
#
# AN - Discord Bot v3
#
# Made by Aditya Nugraha, improved by many
#
def init_loggers(cli_flags):
# d.py stuff
dpy_logger = logging.getLogger("discord")
dpy_logger.setLevel(logging.WARNING)
console = logging.StreamHandler()
console.setLevel(logging.WARNING)
dpy_logger.addHandler(console)
# AN stuff
logger = logging.getLogger("an")
an_format = logging.Formatter(
"%(asctime)s %(levelname)s %(module)s %(funcName)s %(lineno)d: %(message)s",
datefmt="[%d/%m/%Y %H:%M]",
)
stdout_handler = logging.StreamHandler(sys.stdout)
stdout_handler.setFormatter(an_format)
if cli_flags.debug:
os.environ["PYTHONASYNCIODEBUG"] = "1"
logger.setLevel(logging.DEBUG)
else:
logger.setLevel(logging.INFO)
from anbot.core.data_manager import core_data_path
logfile_path = core_data_path() / "an.log"
fhandler = logging.handlers.RotatingFileHandler(
filename=str(logfile_path), encoding="utf-8", mode="a", maxBytes=10 ** 7, backupCount=5
)
fhandler.setFormatter(an_format)
logger.addHandler(fhandler)
logger.addHandler(stdout_handler)
# Sentry stuff
sentry_logger = logging.getLogger("an.sentry")
sentry_logger.setLevel(logging.WARNING)
return logger, sentry_logger
async def _get_prefix_and_token(an, indict):
"""
Again, please blame <@269933075037814786> for this.
:param indict:
:return:
"""
indict["token"] = await an.db.token()
indict["prefix"] = await an.db.prefix()
indict["enable_sentry"] = await an.db.enable_sentry()
def list_instances():
if not config_file.exists():
print(
"No instances have been configuan! Configure one "
"using `anbot-setup` before trying to run the bot!"
)
sys.exit(1)
else:
data = JsonIO(config_file)._load_json()
text = "Configuan Instances:\n\n"
for instance_name in sorted(data.keys()):
text += "{}\n".format(instance_name)
print(text)
sys.exit(0)
def main():
description = "AN V3"
cli_flags = parse_cli_flags(sys.argv[1:])
if cli_flags.list_instances:
list_instances()
elif cli_flags.version:
print(description)
sys.exit(0)
elif not cli_flags.instance_name and not cli_flags.no_instance:
print("Error: No instance name was provided!")
sys.exit(1)
if cli_flags.no_instance:
print(
"\033[1m"
"Warning: The data will be placed in a temporary folder and removed on next system reboot."
"\033[0m"
)
cli_flags.instance_name = "temporary_an"
create_temp_config()
load_basic_configuration(cli_flags.instance_name)
log, sentry_log = init_loggers(cli_flags)
an = AN(cli_flags=cli_flags, description=description, pm_help=None)
init_global_checks(an)
init_events(an, cli_flags)
an.add_cog(Core(an))
loop = asyncio.get_event_loop()
tmp_data = {}
loop.run_until_complete(_get_prefix_and_token(an, tmp_data))
token = os.environ.get("RED_TOKEN", tmp_data["token"])
if cli_flags.token:
token = cli_flags.token
prefix = cli_flags.prefix or tmp_data["prefix"]
if not (token and prefix):
if cli_flags.no_prompt is False:
new_token = interactive_config(an, token_set=bool(token), prefix_set=bool(prefix))
if new_token:
token = new_token
else:
log.critical("Token and prefix must be set in order to login.")
sys.exit(1)
loop.run_until_complete(_get_prefix_and_token(an, tmp_data))
if cli_flags.dry_run:
loop.run_until_complete(an.http.close())
sys.exit(0)
if tmp_data["enable_sentry"]:
an.enable_sentry()
try:
loop.run_until_complete(an.start(token, bot=True))
except discord.LoginFailure:
log.critical("This token doesn't seem to be valid.")
db_token = loop.run_until_complete(an.db.token())
if db_token and not cli_flags.no_prompt:
print("\nDo you want to reset the token? (y/n)")
if confirm("> "):
loop.run_until_complete(an.db.token.set(""))
print("Token has been reset.")
except KeyboardInterrupt:
log.info("Keyboard interrupt detected. Quitting...")
loop.run_until_complete(an.logout())
an._shutdown_mode = ExitCodes.SHUTDOWN
except Exception as e:
log.critical("Fatal exception", exc_info=e)
sentry_log.critical("Fatal Exception", exc_info=e)
loop.run_until_complete(an.logout())
finally:
pending = asyncio.Task.all_tasks(loop=an.loop)
gathean = asyncio.gather(*pending, loop=an.loop, return_exceptions=True)
gathean.cancel()
try:
loop.run_until_complete(an.rpc.close())
except AttributeError:
pass
sys.exit(an._shutdown_mode.value)
if __name__ == "__main__":
main() | PypiClean |
/Charty-0.1.0.tar.gz/Charty-0.1.0/charty/example.py | from charty import Column, Line, Pie
g = Column( 600, 300,
[
[('aaaaaaaaaa', 'Subsidy Spending Unknown'),
('bbbbbbbbbb',800)
],
[('aaaaaaaaaa',230),
('bbbbbbbbbb',260),
('cccc', 300)
]
],
"css/barchart.css",
label_rotate=-45,
y_padding=30
)
g.output("svg/bar.svg")
h = Column( 600, 300,
[
[(2000, 10),
(2001, 30),
(2002, 40),
(2003, 50)
],
[(1990, 30),
(1992, 40),
(2004, 50)
]
],
'css/barchart.css',
label_intervals=2,
x_padding=15
)
h.output("svg/line.svg")
h = Pie( 500, 500,
[
[(2000, 1230),
(2001, 3230),
(2002, 4000),
(2003, 1250),
(2004, 1000),
(2005, 1200),
(2006, 800),
(2007, 100),
(22, 2332),
(30, 3234)
]
],
'css/piechart.css',
y_padding=70,
x_padding=70
)
h.output("svg/pie.svg")
#risk transfers
risk_transfers = Column( 370, 185,
[
[('Outstanding Credit', 7445983679),
('Subsidy', 114141251)
]
],
"css/barchart.css",
padding=10,
currency=True
)
risk_transfers.output("svg/risk_transfers.svg")
#contracts
contracts = Line( 515, 330,
[
[(2000, 12972951342),
(2001, 14109441817),
(2002, 15780150198),
(2003, 20911608531),
(2004, 21064466760),
(2005, 15275901189)
],
[(2005, 15275901189),
(2006, 15939230914),
(2007, 19124684255),
(2008, 18239197959),
(2009, 16226290107)
]
],
'css/linechart.css',
label_intervals=3,
x_padding=40,
units=True,
currency=True
)
contracts.output("svg/contracts.svg") | PypiClean |
/Electrum-Zcash-Random-Fork-3.1.3b5.tar.gz/Electrum-Zcash-Random-Fork-3.1.3b5/gui/kivy/uix/dialogs/password_dialog.py | from kivy.app import App
from kivy.factory import Factory
from kivy.properties import ObjectProperty
from kivy.lang import Builder
from decimal import Decimal
from kivy.clock import Clock
from electrum_zcash.util import InvalidPassword
from electrum_zcash_gui.kivy.i18n import _
Builder.load_string('''
<PasswordDialog@Popup>
id: popup
title: 'Electrum-Zcash'
message: ''
BoxLayout:
size_hint: 1, 1
orientation: 'vertical'
Widget:
size_hint: 1, 0.05
Label:
font_size: '20dp'
text: root.message
text_size: self.width, None
size: self.texture_size
Widget:
size_hint: 1, 0.05
Label:
id: a
font_size: '50dp'
text: '*'*len(kb.password) + '-'*(6-len(kb.password))
size: self.texture_size
Widget:
size_hint: 1, 0.05
GridLayout:
id: kb
size_hint: 1, None
height: self.minimum_height
update_amount: popup.update_password
password: ''
on_password: popup.on_password(self.password)
spacing: '2dp'
cols: 3
KButton:
text: '1'
KButton:
text: '2'
KButton:
text: '3'
KButton:
text: '4'
KButton:
text: '5'
KButton:
text: '6'
KButton:
text: '7'
KButton:
text: '8'
KButton:
text: '9'
KButton:
text: 'Clear'
KButton:
text: '0'
KButton:
text: '<'
''')
class PasswordDialog(Factory.Popup):
def init(self, app, wallet, message, on_success, on_failure, is_change=0):
self.app = app
self.wallet = wallet
self.message = message
self.on_success = on_success
self.on_failure = on_failure
self.ids.kb.password = ''
self.success = False
self.is_change = is_change
self.pw = None
self.new_password = None
self.title = 'Electrum-Zcash' + (' - ' + self.wallet.basename() if self.wallet else '')
def check_password(self, password):
if self.is_change > 1:
return True
try:
self.wallet.check_password(password)
return True
except InvalidPassword as e:
return False
def on_dismiss(self):
if not self.success:
if self.on_failure:
self.on_failure()
else:
# keep dialog open
return True
else:
if self.on_success:
args = (self.pw, self.new_password) if self.is_change else (self.pw,)
Clock.schedule_once(lambda dt: self.on_success(*args), 0.1)
def update_password(self, c):
kb = self.ids.kb
text = kb.password
if c == '<':
text = text[:-1]
elif c == 'Clear':
text = ''
else:
text += c
kb.password = text
def on_password(self, pw):
if len(pw) == 6:
if self.check_password(pw):
if self.is_change == 0:
self.success = True
self.pw = pw
self.message = _('Please wait...')
self.dismiss()
elif self.is_change == 1:
self.pw = pw
self.message = _('Enter new PIN')
self.ids.kb.password = ''
self.is_change = 2
elif self.is_change == 2:
self.new_password = pw
self.message = _('Confirm new PIN')
self.ids.kb.password = ''
self.is_change = 3
elif self.is_change == 3:
self.success = pw == self.new_password
self.dismiss()
else:
self.app.show_error(_('Wrong PIN'))
self.ids.kb.password = '' | PypiClean |
/DynEnv-2.0.tar.gz/DynEnv-2.0/README.md | # DynEnv
Dynamic Simulation Environments for Reinforcement Learning
This project contains two reinforcement learning environments based on 2D physics simulation via [pymunk](https://www.pymunk.org). The environments support different observation modalities and also noisy observations. The current environments are the following:
- **Robot Soccer SPL League (RoboCupEnvironment):** Here, two teams of robots are competing to play soccer.
- **Autonomous driving environment (DrivingEnvironment):** Here, two teams of cars try to get to their unique destinations as quickly as possible without crashing or hitting pedestrians. The teams are not competing here, but only cars on the same team are allowed to share information (to model human drivers).
## Table of contents
* [Requirements](#requirements)
* [Installation](#installation)
* [Usage](#usage)
* [Model structure](#model-structure)
* [Parameters](#parameters)
* [Important functions and members](#important-functions-and-members)
* [So, what are the actions?](#so-what-are-the-actions)
* [What is returned?](#what-is-returned)
* [Coding conventions](#coding-conventions)
## Requirements
- Python 3.6+
- PyMunk
- OpenCV
- PyGame
- PyTorch (optional)
## Installation
You can install simply using pip:
`pip install DynEnv`
Or build from source:
```
git clone https://github.com/szemenyeim/DynEnv.git
cd DynEnv
pip install -e .
```
## Usage
You can simply use the environments the following way:
```python
from DynEnv import *
myEnv = RoboCupEnvironment(nPlayers)
myEnv = DrivingEnvironment(nPlayers)
ret = myEnv.step(actions)
```
Or create vectorized environments by using:
```python
env, env_name = make_dyn_env(env, num_envs, num_players, render, observationType, noiseType, noiseMagnitude, use_continuous_actions)
```
More complex examples including
- neural networks tailored for the special output format (i.e. the number of observations can vary through time),
- logging and
- plotting the results.
For the above, confer the `DynEnv/examples` directory. The `main.py` file consists a full example, while if you would like to try out how the environments work by hand, `play.py` is there for you as well.
### Model structure
The most important part from the point of view of the neural network is the `DynEnv/models` directory, which exposes you the following classes:
- _ICMAgent_: the top-level agent consisting of an A2C and an Intrinsic Curiosity Module (and its variant, [Rational Curiosity Module](https://github.com/rpatrik96/AttA2C))
- _InOutArranger_: helper class to rearrange observations for simple NN forwarding
- _EmbedBlock_: the embedding network used for an object
- _InputLayer_: a complex network which convert all observations into a unified feature space
- _ActorBlock_: a neural network predicting actions for a given action type
- _ActorLayer_: an ensemble of _ActorBlock_ to predict every action
- _AttentionLayer_:
- _DynEnvFeatureExtractor_: a wrapper for the input transform by _InputLayer_, collapsing the time dimension with Recurrent Temporal Attention and running an LSTM
### Parameters
Here are some of the important settings of the environments
- **nPlayers [1-5/10]**: Number of total players in the environment (in the RoboCup env this is per team). The limit is 10 in the Driving, 5 in the RoboCup env.
- **render [bool]**: Whether to visualize the environment.
- **observationType [Full, Partial, Image]**: Image observation only supported for the RoboCup environment.
- **noiseType [Random, Realistic]**: Realistic noise: noise magnitude and false negative rate depends on distance, proximity of other objects and sighting type. False positives and misclassifications are more likely to occur in certain situations.
- **noiseMagnitude [0-5]**: Variable to control noise
- **continuousActions [bool]**: Whether the driving env actions are understood as categorical or continuous. (Driving env only)
- **allowHeadturn [bool]**: Enables head turining actions. (RoboCup env only)
Here are some examples of different noise and observation types
#### Random Noise
Full Observation | Partial Observation
:-------------------------:|:-------------------------:
 | 
Top Camera | Bottom Camera
:-------------------------:|:-------------------------:
 | 
#### Realistic Noise
Full Observation | Partial Observation
:-------------------------:|:-------------------------:
 | 
Top Camera | Bottom Camera
:-------------------------:|:-------------------------:
 | 
#### Large, Realistic Noise
Full Observation | Partial Observation
:-------------------------:|:-------------------------:
 | 
Top Camera | Bottom Camera
:-------------------------:|:-------------------------:
 | 
#### Driving, Realistic Noise
Full Observation | Partial Observation
:-------------------------:|:-------------------------:
 | 
### Important functions and members
- `reset()` Resets the environment to a new game and returns initial observations.
- `setRandomSeed(seed)` Sets the environment seed, resets the environment and returns initial observations.
- `observation_space` Returns information about the observations returned by the environrment. For the exact meaning please refer to [The Observation Space](#the-observation-space) section.
- `action_space` Returns information about the actions the environment expects.
- `step(actions)` Performs one step. This consists of several simulation steps (10 for the Driving and 50 for the RoboCup environments). It returns observations for every 10 simulation steps and full state for the last step.
- `renderMode` Whether to render to a display (`'human'`) or to a memory array (`'memory'`).
- `agentVisID` With this, you can visualize the observation of an agent during rendering.
- `render()` Returns rendered images if the render mode is `'memory'`. Does nothing otherwise, as the rendering is done by the step function due to the multi-timestep feature.
### So, what are the actions?
The environments expect an iterable object containing the actions for every player. Each player action must contain the following:
#### RoboCup:
- **Movement direction:** Categorical (5)
- **Turn:** Categorical (3)
- **Turn head:** Continuous [-6 +6]
- **Kick:** Categorical (3) (this is exclusive with moving or turning)
#### Driving:
- **Gas/break:** Continuous [-3 +3] or Categorical (3)
- **Turn:** Continuous [-3 +3] or Categorical (3)
### What is returned?
Both environments return the following variables in the step function:
- **Observations:** Observations for every agent. What this is exactly depends on the observationType variable.
- **Rewards:** Rewards for each agent.
- **Team rewards:** Shared rewards for every team. These are added to the agent reward variables, and are not returned.
- **Finished:** Game over flag
- **Info:** Other important data
- **Full State:** The full state of the env
- **episode_r**: Cumulative rewards for the episode (Returned only at the end of an episode)
- **episode_p_r**: Cumulative positive-only rewards for the episode (Returned only at the end of an episode)
- **episode_g**: Goals in these episode. For RoboCup this is goals per team, for the Driving env the first value is the number of cars that reached their destination without crashing, the second is the number of crashed cars. (Returned only at the end of an episode)
Position information is normalized in both the observations and the full state.
#### The Observation Space
Due to limitations in the OpenAI gym, this part of the environment is not fully compatible. The `observation_space` variable is an instance of `gym.space.Space`, however, the meaning is slightly different.
The main differences are:
- the observation space only gives you a placeholder for each object type to be observed (as dynamic length observation spaces are not supported in OpenAI gym)
- the `.sample()` method will not work without a slight modification (see example below) - following the example, you will get a valid observation format.
Unfortunately, to provide an interface as close to gym as possible, we were forced to break some methods in our observation space (mainly to be able to use the `SubprocVecEnv` method from `stable-baselines`), while providing as much information about the observation space as possible.
We needed to upcast the observation space to `gym.space.Space` from `gym.space.Tuple` to be able to vectorize the environments (we could have implemented a custom environment, but the goal was to avoid writing custom code to maintain a clean API for the users). This step did not result in any loss of information, but if you would like to use methods not implemented in the base class (i.e. `gym.space.Space`), you should downcast the environment.
```python
env, env_name = make_dyn_env(...)
# raises NotImplementedError
env.sample()
# downcast observation space and it works !
env.observation_space.__class__ = gym.spaces.Tuple
env.sample()
```
I.e. querying the `observation_space` variable after the trick and calling `.sample()` on it will get you a fully valid observation format, it does not cover every form of observations an environment can produce. Let us elaborate on that!
##### Gym-like observation space descriptor
Due to the fact that in every time step each agent can see different number of objects (such as cars in the _Driving_ environment), including 0 as a valid number for each object type (not to mention false positive sightings or misclassifications), we cannot give an observation space format which covers all possibilities. However, what we can do is to _assume_ that each object type is present in the observation with a single instance, thus including every necessary information about the object space (but be aware that multiple observations from the same object type can be in the list of observations).
Here is an example for the Driving environment how the observation space looks like (we use extensively the `Dict` gym space, as it enables to describe what is contained):
```python
...
# subspace for cars
car_space = Dict({
"position": Box(-self.mean * 2, +self.mean * 2, shape=(2,)),
"orientation": Box(-1, 1, shape=(2,)),
"width_height": Box(-10, 10, shape=(2,)),
"finished": MultiBinary(1)
})
...
# assemble observation space
self.observation_space = Tuple([
self_space,
car_space,
obstacle_space,
pedestrian_space,
lane_space
])
```
##### List of observations
The observations returned are arranged as follows:
`[nParallelEnvs x nTimeSteps x nAgents x nObjectType]`
Each element of the above list is a NumPy array containing all the observations by a single agent in a single timestep. To help contructing input layers a custom class `DynEnv.models.InOutArranger` is provided with the following two functions:
- `inputs, counts = rearrange_inputs(x)`: Creates a single list of NumPy arrays. Each element of this list contains a single numpy array of all the observations for a given object type. (Warning: in some cases this might be an empty list!)
- `outputs, masks = rearrange_outputs(inputs, counts, device)`: Takes a list of Torch Tensors and the counts output by the previous function, and creates a single tensor shaped [TimeSteps x maxObjCnt x nPlayers x featureCnt] by padding the second dimension to the largest number of objects seen for every robot. The masks variable is binary array shaped [TimeSteps x maxObjCnt x nPlayers], which is True for padded elements (this is in line with PyTorch's MultiHeadedAttention layer). (Warning: This assumes that the featureCnt is the same for every object time.)
Here is a more comprehensive example:
```python
from DynEnv.models import *
from torch import nn
# setup environment, query all required variables
myEnv = ...
obsSpace = myEnv.observation_space
nTime = 5 if env is DynEnvType.ROBO_CUP else 1
nPlayers = ...
featuresPerObject = [flatdim(s) for s in obsSpace.spaces]
nObjectTypes = len(featuresPerObject)
# create neural network and rearrange inputs
device = <CUDA or CPU>
myNeuralNets = [nn.Linear(objfeat,128).to(device) for objFeat in featuresPerObject]
myArranger = models.InOutArranger(nObjectTypes,nPlayers,nTime)
...
# create sample action and step
actions = torch.stack([action_space.sample() for _ in range(nPlayers)]
obs, _ = myEnv.step(actions)
# summary
# rearrange inputs - forward - rearrange outputs
netInputs, counts = myArranger.rearrange_inputs(obs)
netOutputs = [myNet(torch.tensor(netInput).to(device)) for myNet,netInput in zip(myNeuralNets,netInputs)]
outputs,masks = myArranger.rearrange_outputs(netOutputs,counts,device)
```
#### RoboCup
The full state contains the following:
- Robots **[x, y, cos(angle), sin(angle), team ID, fallen or penalized]**
- Balls **[x, y, ball owned by team ID, closest robot status]**
'Team ID' is +/-1. 'Fallen or penalized' and 'closest robot status' are binary numbers. The latter is 1 for the robot closest to the ball from each team.
If the observation is full state, the robot's own position is returned in a separate list, and both axes are flipped and angles rotated 180 degrees for team -1. Moreover, in this case the ball owned flag indicates whether the ball is owned by the robot's team, or the opponent.
The partial observation contains the following for each robot:
- Balls: **[x, y, radius, ball owned status, closest robot status]**
- Robots (self not included): **[x, y, cos(angle), sin(angle), team, fallen or penalized]**
- Goalposts: **[x, y, radius]**
- Crosses: **[x, y, radius]**
- Lines: **[x1, y1, x2, y2]**
- Center circle: **[x, y, radius]**
Ball owned status is 0 if the ball is not owned, +1 if the ball is owned by the robot's team and -1 if owned by the opposite team.
In the partial sighting case, the positions and angles are returned relative to the robot's position and head angle.
The image observations contain 2D images of semantic labels. The images have 4 binary channels:
- 0: Ball
- 1: Robot
- 2: Goalpost
- 3: Line
#### Driving
The full state contains the following:
- Cars: **[x, y, cos(angle), sin(angle), width, height, finished]**
- Obstacles: **[x, y, cos(angle), sin(angle), width, height]**
- Pedestrians: **[x, y]**
- Lanes: **[x1, y1, x2, y2, type]**
Lane type is 0 for standard lanes, 1 for the middle lane and -1 for the edge of the road.
If the observation is full state, the car's own position is returned in a separate list, identical to the Self entry below.
The partial observation contains the following for each car:
- Self: **[x, y, cos(angle), sin(angle), width, height, goal_x, goal_y, finished]**
- Cars: **[x, y, cos(angle), sin(angle), width, height]**
- Obstacles: **[x, y, cos(angle), sin(angle), width, height]**
- Pedestrians: **[x, y]**
- Lanes: **[signed distance, cos(angle), sin(angle), type]**
Widths and heights are also normalized.
## Coding conventions
- Functions:
- lower case names, usually verbs
- `__function`: private function in base class, children cannot use it
- `_function`: private function, children can use it
- `function`: everyone can use it
- Variables:
- camelCase: with **lowercase** initial
- usually nouns
- Classes:
- CamelCase: with **uppercase** initial
- usually nouns
| PypiClean |
/Nevow-0.14.5.tar.gz/Nevow-0.14.5/examples/pastebin/pastebin/web/pages.py | from cStringIO import StringIO
import time
from zope.interface import implements
from twisted.python import htmlizer
from twisted.web import static
from nevow import loaders
from nevow import rend
from nevow import tags
from nevow import url
from formless import annotate
from formless import iformless
from formless import webform
ANONYMOUS = 'anonymous'
##
# Text colourisers (aka syntax highlighting)
##
def _python_colouriser(text):
out = StringIO()
try:
htmlizer.filter(StringIO(text), out)
except AttributeError:
out = StringIO("""Starting after Nevow 0.4.1 Twisted
2.0 is a required dependency. Please install it""")
return out.getvalue()
_colourisers = {
'python': _python_colouriser
}
##
# Formless
##
class IAddPasting(annotate.TypedInterface):
def addPasting(
request=annotate.Request(),
author=annotate.String(strip=True),
text=annotate.Text(strip=True, required=True)):
pass
addPasting = annotate.autocallable(addPasting)
class IEditPasting(annotate.TypedInterface):
def editPasting(
request=annotate.Request(),
postedBy=annotate.String(immutable=1),
author=annotate.String(strip=True),
text=annotate.Text(strip=True, required=True)):
pass
editPasting = annotate.autocallable(editPasting)
##
# "Standard" renderers
##
def render_time(theTime):
def _(context, data):
return time.strftime('%Y-%m-%d %H:%M:%S %Z', theTime)
return _
def render_pastingText(text):
def _(context, data):
colouriser = _colourisers.get('python')
if colouriser:
return tags.xml(colouriser(text))
return tags.pre[tags.xml(text)]
return _
def render_pasting(version):
def _(context, data):
context.fillSlots('author', version.getAuthor() or ANONYMOUS)
time = context.fillSlots('time', render_time(version.getTime()))
text = context.fillSlots('text', render_pastingText(version.getText()))
return context.tag
return _
class BasePage(rend.Page):
docFactory = loaders.htmlfile(templateDir='templates', template='site.html')
child_css = static.File('static/css')
child_images = static.File('static/images')
def data_pastings(self, context, data):
return self.pastebin.getListOfPastings(20)
def render_pasting(self, context, data):
oid, author, time = data
context.tag.fillSlots('url', url.root.child(str(oid)))
context.tag.fillSlots('id', oid)
context.tag.fillSlots('author', author or ANONYMOUS)
return context.tag
def render_content(self, context, data):
tag = context.tag.clear()
tag[loaders.htmlfile(templateDir='templates', template=self.contentTemplateFile)]
return tag
class RootPage(BasePage):
implements(IAddPasting)
addSlash = True
def __init__(self, pastebin):
BasePage.__init__(self)
self.pastebin = pastebin
def locateChild(self, context, segments):
try:
return Pasting(self.pastebin, int(segments[0])), segments[1:]
except ValueError:
pass
return BasePage.locateChild(self, context, segments)
def render_content(self, context, data):
tag = context.tag.clear()
return tag[webform.renderForms()]
def addPasting(self, request, author, text):
oid = self.pastebin.addPasting(author, text)
request.setComponent(iformless.IRedirectAfterPost, '/'+str(oid))
class Pasting(BasePage):
implements(IEditPasting)
contentTemplateFile = 'pasting.html'
def __init__(self, pastebin, pastingOid, version=-1):
BasePage.__init__(self)
self.pastebin = pastebin
self.pastingOid = pastingOid
self.version = version
self.pasting = self.pastebin.getPasting(self.pastingOid)
def locateChild(self, context, segments):
try:
return Pasting(self.pastebin, self.pastingOid, int(segments[0])), segments[1:]
except:
pass
return BasePage.locateChild(self, context, segments)
def data_history(self, context, data):
return self.pasting.getHistory()
def render_aPasting(self, context, data):
return render_pasting(self.pasting.getVersion(self.version))
def render_form(self, context, data):
if self.version != -1:
return ''
version = self.pasting.getVersion(self.version)
formDefaults = context.locate(iformless.IFormDefaults)
formDefaults.setDefault('editPasting.text', version.getText())
formDefaults.setDefault('editPasting.postedBy', version.getAuthor())
return webform.renderForms()
def render_version(self, context, data):
version, author, theTime = data
if self.version == -1:
u = url.here.child
else:
u = url.here.sibling
context.tag.fillSlots('url', u(version))
context.tag.fillSlots('time', render_time(theTime))
context.tag.fillSlots('author', author or ANONYMOUS)
## context.fillSlots('link', a(href=[u(version)])[
## render_time(theTime), ' (',author or ANONYMOUS,')'
## ])
return context.tag
def editPasting(self, request, postedBy, author, text):
self.pastebin.updatePasting(self.pastingOid, author, text)
request.setComponent(iformless.IRedirectAfterPost, '/%s'%self.pastingOid)
class Version(BasePage):
contentTemplateFile = "pasting.html"
child_ = rend.FourOhFour()
def __init__(self, pastebin, pasting, version):
BasePage.__init__(self)
self.pastebin = pastebin
self.pasting = pasting
self.version = version
def data_history(self, context, data):
return self.pasting.getHistory()
def render_aPasting(self, context, data):
return render_pasting(self.pasting.getVersion(self.version))
def render_version(self, context, data):
version, author, theTime = data
context.fillSlots('link', tags.a(href=[url.here.sibling(str(version))])[
render_time(theTime), ' (',author,')'
])
return context.tag | PypiClean |
/Font-Awesome-Flask-0.1.1.tar.gz/Font-Awesome-Flask-0.1.1/src/flask_font_awesome/__init__.py | import re
import sys
import urllib.request
from pathlib import Path
from typing import Optional, Union
from flask import Blueprint, Flask, Markup, current_app, url_for
__version__ = "0.1.1"
STATIC_FOLDER = Path(__file__).parent / "static"
CDN_URL_TEMPLATE = "https://cdnjs.cloudflare.com/ajax/libs/font-awesome/{version}/{type}/{style}{possibly_min}.{ext}"
VERSION_PATTERN = re.compile(r"Font Awesome (?:Free\s)?(\d+.\d+.\d+)")
def _remove_prefix(s: str, prefix: str) -> str:
if sys.version_info < (3, 9):
return s[len(prefix) :] if s.startswith(prefix) else s
return s.removeprefix(prefix)
class FontAwesome:
"""Font Awesome icons for Flask."""
style = "all"
style_choices = ("all", "regular", "solid", "brands")
core_style = "fontawesome"
use_min = True
use_css = False
version = "6.2.0"
css_sri_map = {
"all": "sha512-xh6O/CkQoPOWDdYTDqeRdPCVd1SpvCA9XXcUnZS2FmJNp1coAFzvtCN9BmamE+4aHK8yyUHUSCcJHgXloTyT2A==",
"regular": "sha512-aNH2ILn88yXgp/1dcFPt2/EkSNc03f9HBFX0rqX3Kw37+vjipi1pK3L9W08TZLhMg4Slk810sPLdJlNIjwygFw==",
"solid": "sha512-uj2QCZdpo8PSbRGL/g5mXek6HM/APd7k/B5Hx/rkVFPNOxAQMXD+t+bG4Zv8OAdUpydZTU3UHmyjjiHv2Ww0PA==",
"brands": "sha512-+oRH6u1nDGSm3hH8poU85YFIVTdSnS2f+texdPGrURaJh8hzmhMiZrQth6l56P4ZQmxeZzd2DqVEMqQoJ8J89A==",
"fontawesome": "sha512-uj2QCZdpo8PSbRGL/g5mXek6HM/APd7k/B5Hx/rkVFPNOxAQMXD+t+bG4Zv8OAdUpydZTU3UHmyjjiHv2Ww0PA==",
}
js_sri_map = {
"all": "sha512-naukR7I+Nk6gp7p5TMA4ycgfxaZBJ7MO5iC3Fp6ySQyKFHOGfpkSZkYVWV5R7u7cfAicxanwYQ5D1e17EfJcMA==",
"regular": "sha512-Kcbb5bDGCQQwo67YHS9uDvRmyrNEqHLPA1Kmn0eqrritqGDp3OpkBGvHk36GNEH44MtWM1L5k3i9MSQPMkNIuA==",
"solid": "sha512-dcTe66qF6q/NW1X64tKXnDDcaVyRowrsVQ9wX6u7KSQpYuAl5COzdMIYDg+HqAXhPpIz1LO9ilUCL4qCbHN5Ng==",
"brands": "sha512-1e+6G7fuQ5RdPcZcRTnR3++VY2mjeh0+zFdrD580Ell/XcUw/DQLgad5XSCX+y2p/dmJwboZYBPoiNn77YAL5A==",
"fontawesome": "sha512-j3gF1rYV2kvAKJ0Jo5CdgLgSYS7QYmBVVUjduXdoeBkc4NFV4aSRTi+Rodkiy9ht7ZYEwF+s09S43Z1Y+ujUkA==",
}
webfonts_map = {
"regular": "fa-regular-400",
"solid": "fa-solid-900",
"brands": "fa-brands-400",
}
def __init__(self, app: Optional[Flask] = None) -> None:
if app is not None:
self.init_app(app)
def init_app(self, app: Flask) -> None:
"""Initialize the Flask application for use with this extension instance."""
# register extension instance with the Flask application
if not hasattr(app, "extensions"):
app.extensions = {}
app.extensions["font_awesome"] = self
# create and register blueprint for this extension instance
blueprint = Blueprint(
"font_awesome",
__name__,
static_folder=STATIC_FOLDER.name,
static_url_path=f"/font_awesome{app.static_url_path}",
template_folder="templates",
)
app.register_blueprint(blueprint)
# register extension instance with the Jinja2 environment (for use in templates)
app.jinja_env.globals["font_awesome"] = self
# set default configuration values for this extension instance
app.config.setdefault("FONT_AWESOME_SERVE_LOCAL", False)
@staticmethod
def _get_file(
style: str, use_min: bool, ext: str, type: Optional[str] = None
) -> Path:
"""Get the file path for the given style, extension, and possibly-minified suffix."""
possibly_min = ".min" if use_min else ""
return (
STATIC_FOLDER
/ (type if type is not None else ext)
/ f"{style}{possibly_min}.{ext}"
)
@staticmethod
def _get_url(
version: str,
style: str,
use_min: bool,
ext: str,
serve_local: bool,
type: Optional[str] = None,
) -> str:
"""Get the URL for the given version, style, extension, and possibly-minified suffix."""
possibly_min = ".min" if use_min else ""
if serve_local:
return url_for(
"font_awesome.static", filename=f"{ext}/{style}{possibly_min}.{ext}"
)
return CDN_URL_TEMPLATE.format(
version=version,
type=type if type is not None else ext,
style=style,
possibly_min=possibly_min,
ext=ext,
)
@staticmethod
def _get_version(file: Path) -> Optional[str]:
"""Get the version from the given file."""
match = VERSION_PATTERN.search(file.read_text())
return match.group(1) if match is not None else None
@classmethod
def _request_file(
cls,
version: str,
style: str,
use_min: bool,
ext: str,
file: Path,
type: Optional[str] = None,
) -> None:
"""Request the file for serving locally."""
file.parent.mkdir(parents=True, exist_ok=True)
with urllib.request.urlopen(
cls._get_url(version, style, use_min, ext, False, type)
) as response:
file.write_bytes(response.read())
@classmethod
def _request_webfont_files(
cls,
version: str,
webfont_style: str,
) -> None:
"""Request the webfont files (ttf and woff2) for serving locally."""
_type = "webfonts"
for ext in ("ttf", "woff2"):
file = cls._get_file(webfont_style, False, ext, _type)
cls._request_file(version, webfont_style, False, ext, file, _type)
@classmethod
def _possibly_request_file(
cls, version: str, style: str, use_min: bool, ext: str
) -> None:
"""Possibly request the file for serving locally."""
file = cls._get_file(style, use_min, ext)
if not file.exists() or cls._get_version(file) != version:
cls._request_file(version, style, use_min, ext, file)
if ext == "css": # also request webfonts
if style == "all":
for _style in cls.style_choices[1:]:
webfont_style = cls.webfonts_map[_style]
cls._request_webfont_files(version, webfont_style)
else:
webfont_style = cls.webfonts_map[style]
cls._request_webfont_files(version, webfont_style)
def load(
self,
version: str = version,
style: str = style,
css_sri: str = css_sri_map[style],
core_css_sri: str = css_sri_map[core_style],
js_sri: str = js_sri_map[style],
core_js_sri: str = js_sri_map[core_style],
use_min: bool = use_min,
use_css: bool = use_css,
) -> Markup:
"""Load Font Awesome's `WebFonts + CSS <https://fontawesome.com/docs/web/setup/host-yourself/webfonts>`_ / `SVG + JS <https://fontawesome.com/docs/web/setup/host-yourself/svg-js>`_ resources for the given version. Defaults to `SVG + JS`.
Some examples:
>>> font_awesome.load()
>>> font_awesome.load(style="solid", use_css=True)
>>> font_awesome.load(
... version="5.9.0",
... js_sri="sha512-q3eWabyZPc1XTCmF+8/LuE1ozpg5xxn7iO89yfSOd5/oKvyqLngoNGsx8jq92Y8eXJ/IRxQbEC+FGSYxtk2oiw=="
... )
Args:
version (str): The version to load. Defaults to `6.2.0`.
style (str): The `icon style(s) <https://fontawesome.com/v6/docs/web/dig-deeper/styles>`_ to load. Defaults to `all`.
css_sri (str): The `Subresource Integrity (SRI) <https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity>`_ for the CSS resource file when not served locally. Defaults to `sha512-xh6O/CkQoPOWDdYTDqeRdPCVd1SpvCA9XXcUnZS2FmJNp1coAFzvtCN9BmamE+4aHK8yyUHUSCcJHgXloTyT2A==`.
core_css_sri (str): The `SRI <https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity>`_ for the core CSS resource file when not served locally. Defaults to `sha512-uj2QCZdpo8PSbRGL/g5mXek6HM/APd7k/B5Hx/rkVFPNOxAQMXD+t+bG4Zv8OAdUpydZTU3UHmyjjiHv2Ww0PA==`.
js_sri (str): The `SRI <https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity>`_ for the JS resource file when not served locally. Defaults to `sha512-naukR7I+Nk6gp7p5TMA4ycgfxaZBJ7MO5iC3Fp6ySQyKFHOGfpkSZkYVWV5R7u7cfAicxanwYQ5D1e17EfJcMA==`.
core_js_sri (str): The `SRI <https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity>`_ for the core JS resource file when not served locally. Defaults to `sha512-j3gF1rYV2kvAKJ0Jo5CdgLgSYS7QYmBVVUjduXdoeBkc4NFV4aSRTi+Rodkiy9ht7ZYEwF+s09S43Z1Y+ujUkA==`.
use_min (bool): Whether to use the minified resource or not. Defaults to `True`.
use_css (bool): Whether to use `WebFonts + CSS <https://fontawesome.com/docs/web/setup/host-yourself/webfonts>`_ over `SVG + JS <https://fontawesome.com/docs/web/setup/host-yourself/svg-js>`_. Defaults to `False`.
Raises:
ValueError: When trying to load a non-free icon style (i.e. not one of `all`, `regular`, `solid`, or `brands`)
Returns:
flask.Markup: The HTML markup for the WebFonts + CSS / SVG + JS resource(s).
"""
if use_css:
return self.load_css(style, version, css_sri, core_css_sri, use_min)
return self.load_js(style, version, js_sri, core_js_sri, use_min)
def load_css(
self,
version: str = version,
style: str = style,
sri: str = css_sri_map[style],
core_sri: str = css_sri_map[core_style],
use_min: bool = use_min,
) -> Markup:
"""Load Font Awesome's `WebFonts + CSS <https://fontawesome.com/docs/web/setup/host-yourself/webfonts>`_ resources for the given version.
Some examples:
>>> font_awesome.load_css()
>>> font_awesome.load_css(style="regular")
Args:
version (str): The version to load. Defaults to `6.2.0`.
style (str): The `icon style(s) <https://fontawesome.com/v6/docs/web/dig-deeper/styles>`_ to load. Defaults to `all`.
sri (str): The `Subresource Integrity (SRI) <https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity>`_ for the CSS resource file when not served locally. Defaults to `sha512-xh6O/CkQoPOWDdYTDqeRdPCVd1SpvCA9XXcUnZS2FmJNp1coAFzvtCN9BmamE+4aHK8yyUHUSCcJHgXloTyT2A==`.
core_sri (str): The `SRI <https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity>`_ for the core CSS resource file when not served locally. Defaults to `sha512-uj2QCZdpo8PSbRGL/g5mXek6HM/APd7k/B5Hx/rkVFPNOxAQMXD+t+bG4Zv8OAdUpydZTU3UHmyjjiHv2Ww0PA==`.
use_min (bool): Whether to use the minified resources or not. Defaults to `True`.
Raises:
ValueError: When trying to load a non-free icon style (i.e. not one of `all`, `regular`, `solid`, or `brands`)
Returns:
flask.Markup: The HTML markup for the WebFonts + CSS resources.
"""
if style not in self.style_choices:
raise ValueError(f"`style` must be one of {', '.join(self.style_choices)}")
serve_local = current_app.config["FONT_AWESOME_SERVE_LOCAL"]
ext = "css"
url = self._get_url(version, style, use_min, ext, serve_local)
if serve_local:
self._possibly_request_file(version, style, use_min, ext)
css = f'<link rel="stylesheet" href="{url}" />'
else:
css = f'<link rel="stylesheet" href="{url}" integrity="{sri}" crossorigin="anonymous" />'
if style != "all":
core_url = self._get_url(
version, self.core_style, use_min, ext, serve_local
)
if serve_local:
self._possibly_request_file(version, self.core_style, use_min, ext)
css += f'\n<link rel="stylesheet" href="{core_url}" />'
else:
css += f'\n<link rel="stylesheet" href="{core_url}" integrity="{core_sri}" crossorigin="anonymous" />'
return Markup(css)
def load_js(
self,
version: str = version,
style: str = style,
sri: str = js_sri_map[style],
core_sri: str = js_sri_map[core_style],
use_min: bool = use_min,
) -> Markup:
"""Load Font Awesome's `SVG + JS <https://fontawesome.com/docs/web/setup/host-yourself/svg-js>`_ resource for the given version.
Some examples:
>>> font_awesome.load_js()
>>> font_awesome.load_js(
... use_min=False,
... sri="sha512-8XtSBQOB+R4dpcpQBpYC5Q7ti7y/MjIF0l/1ZiSd4xM04Dr052S/Py981Pzmwo2HrXCR2JhYE1MYR15aZGMnig=="
... )
Args:
version (str): The version to load. Defaults to `6.2.0`.
style (str): The `icon style(s) <https://fontawesome.com/v6/docs/web/dig-deeper/styles>`_ to load. Defaults to `all`.
sri (str): The `SRI <https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity>`_ for the JS resource file when not served locally. Defaults to `sha512-naukR7I+Nk6gp7p5TMA4ycgfxaZBJ7MO5iC3Fp6ySQyKFHOGfpkSZkYVWV5R7u7cfAicxanwYQ5D1e17EfJcMA==`.
core_sri (str): The `SRI <https://developer.mozilla.org/en-US/docs/Web/Security/Subresource_Integrity>`_ for the core JS resource file when not served locally. Defaults to `sha512-j3gF1rYV2kvAKJ0Jo5CdgLgSYS7QYmBVVUjduXdoeBkc4NFV4aSRTi+Rodkiy9ht7ZYEwF+s09S43Z1Y+ujUkA==`.
use_min (bool): Whether to use the minified resource or not. Defaults to `True`.
Raises:
ValueError: When trying to load a non-free icon style (i.e. not one of `all`, `regular`, `solid`, or `brands`)
Returns:
flask.Markup: The HTML markup for the SVG + JS resource.
"""
if style not in self.style_choices:
raise ValueError(f"`style` must be one of {', '.join(self.style_choices)}")
serve_local = current_app.config["FONT_AWESOME_SERVE_LOCAL"]
ext = "js"
url = self._get_url(version, style, use_min, ext, serve_local)
if serve_local:
self._possibly_request_file(version, style, use_min, ext)
js = f'<script defer src="{url}"></script>'
else:
js = f'<script defer src="{url}" integrity="{sri}" crossorigin="anonymous"></script>'
if style != "all":
core_url = self._get_url(
version, self.core_style, use_min, ext, serve_local
)
if serve_local:
self._possibly_request_file(version, self.core_style, use_min, ext)
js += f'\n<script defer src="{core_url}"></script>'
else:
js += f'\n<script defer src="{core_url}" integrity="{core_sri}" crossorigin="anonymous"></script>'
return Markup(js)
def render_icon(
self,
name: str,
inverse: bool = False,
size: Optional[str] = None,
fixed_with: bool = False,
rotation: Optional[Union[str, int]] = None,
animation: Optional[str] = None,
border: bool = False,
pull: Optional[str] = None,
swap_opacity: bool = False,
aria_hidden: bool = True,
style: Optional[str] = None,
_stack_size: Optional[str] = None,
) -> Markup:
"""Render an icon.
See the `Font Awesome documentation <https://fontawesome.com/search?o=r&m=free>`_ for the complete list of available icons.
Some examples:
>>> font_awesome.render_icon('fas fa-house')
>>> font_awesome.render_icon('fa-regular fa-square', size='xl')
>>> font_awesome.render_icon('fab fa-github', inverse=True, rotation=90)
Args:
name (str): The name of the icon (e.g. `fa-solid fa-user`).
inverse (bool): Inverts the color of the icon to white. Defaults to `False`.
size (Optional[str]): The `relative or literal size <https://fontawesome.com/v6/docs/web/style/size>`_ of the icon. Defaults to `None`.
fixed_with (bool): Set the icon to a `fixed width <https://fontawesome.com/v6/docs/web/style/fixed-width>`_ for easy vertical alignment. Defaults to `False`.
rotation (Optional[Union[str, int]]): `Rotate or flip <https://fontawesome.com/v6/docs/web/style/rotate>`_ the icon. Defaults to `None`.
animation (Optional[str]): `Animate <https://fontawesome.com/v6/docs/web/style/animate>`_ the icon. Defaults to `None`.
border (bool): Add a `border <https://fontawesome.com/v6/docs/web/style/pull>`_ to the icon. Defaults to `False`.
pull (Optional[str]): `Pull <https://fontawesome.com/v6/docs/web/style/pull>`_ the icon left or right. Defaults to `None`.
swap_opacity (bool): Swap the default opacity of each layer in a `duotone <https://fontawesome.com/v6/docs/web/style/duotone>`_ icon. Defaults to `False`.
aria_hidden (bool): Add the `aria-hidden` attribute to the icon. Defaults to `True`.
style (Optional[str]): Customize the icon even further using `CSS styling <https://fontawesome.com/v6/docs/web/style/custom>`_. Defaults to `None`.
Returns:
flask.Markup: The HTML markup for the icon.
"""
icon = f'<i class="{name}'
if _stack_size:
icon += f" fa-stack-{_remove_prefix(_stack_size, 'fa-stack-')}"
if inverse:
icon += " fa-inverse"
if size is not None:
icon += f" fa-{_remove_prefix(size, 'fa-')}"
if fixed_with:
icon += " fa-fw"
if rotation is not None:
if isinstance(rotation, int):
rotation = f"rotate-{rotation}"
icon += f" fa-{_remove_prefix(rotation, 'fa-')}"
if animation is not None:
icon += f" fa-{_remove_prefix(animation, 'fa-')}"
if border:
icon += " fa-border"
if pull is not None:
icon += f" fa-pull-{_remove_prefix(pull, 'fa-pull-')}"
if swap_opacity:
icon += " fa-swap-opacity"
icon += '"'
if style is not None:
icon += f' style="{style}"'
if aria_hidden:
icon += ' aria-hidden="true"'
icon += "></i>"
return Markup(icon)
def render_stacked_icon(
self,
name_1: str,
name_2: str,
stack_size_1: str = "2x",
stack_size_2: str = "1x",
inverse: bool = False,
size: Optional[str] = None,
aria_hidden: bool = True,
style: Optional[str] = None,
style_1: Optional[str] = None,
style_2: Optional[str] = None,
) -> Markup:
"""Render a `stacked <https://fontawesome.com/v6/docs/web/style/stack>`_ icon.
Some examples:
>>> font_awesome.render_stacked_icon(
... "fa-solid fa-square",
... "fab fa-twitter",
... inverse=True,
... size="2x",
... )
>>> font_awesome.render_stacked_icon(
... "fa-solid fa-camera",
... "fa-solid fa-ban",
... stack_size_1="1x",
... stack_size_2="2x",
... size="2x",
... style_2="color:Tomato",
... )
Args:
name_1 (str): The name of the first icon (e.g. `fa-solid fa-square`).
name_2 (str): The name of the second icon (e.g. `fab fa-twitter`).
stack_size_1 (str): The relative size of the first icon. One of `1x` or `2x`. Defaults to `2x`.
stack_size_2 (str): The relative size of the second icon. One of `1x` or `2x`. Defaults to `1x`.
inverse (bool): Inverts the color of the icon to white. Defaults to `False`.
size (Optional[str]): The `relative or literal size <https://fontawesome.com/v6/docs/web/style/size>`_ of the stacked icon. Defaults to `None`.
aria_hidden (bool): Add the `aria-hidden` attribute to the icon. Defaults to `True`.
style (Optional[str]): Customize the stacked icon even further using `CSS styling <https://fontawesome.com/v6/docs/web/style/custom>`_. Defaults to `None`.
style_1 (Optional[str]): Customize the first icon even further using `CSS styling <https://fontawesome.com/v6/docs/web/style/custom>`_. Defaults to `None`.
style_2 (Optional[str]): Customize the second icon even further using `CSS styling <https://fontawesome.com/v6/docs/web/style/custom>`_. Defaults to `None`.
Returns:
flask.Markup: The HTML markup for the icon.
"""
span = '<span class="fa-stack'
if size is not None:
span += f" fa-{_remove_prefix(size, 'fa-')}"
span += '"'
if style is not None:
span += f' style="{style}"'
if aria_hidden:
span += ' aria-hidden="true"'
span += ">"
span += f"\n {self.render_icon(name_1, inverse if stack_size_1 == '1x' else False, aria_hidden=False, style=style_1, _stack_size=stack_size_1)}"
span += f"\n {self.render_icon(name_2, inverse if stack_size_2 == '1x' else False, aria_hidden=False, style=style_2, _stack_size=stack_size_2)}"
span += "\n</span>"
return Markup(span) | PypiClean |
/BuildStream-2.0.1-cp39-cp39-manylinux_2_28_x86_64.whl/buildstream/plugins/sources/tar.py | import os
import tarfile
from contextlib import contextmanager
from tempfile import TemporaryFile
from buildstream import DownloadableFileSource, SourceError
from buildstream import utils
class ReadableTarInfo(tarfile.TarInfo):
"""
The goal is to override `TarFile`'s `extractall` semantics by ensuring that on extraction, the
files are readable by the owner of the file. This is done by overriding the accessor for the
`mode` attribute in `TarInfo`, the class that encapsulates the internal meta-data of the tarball,
so that the owner-read bit is always set.
"""
# https://github.com/python/mypy/issues/4125
@property # type: ignore
def mode(self):
# Respect umask instead of the file mode stored in the archive.
# The only bit used from the embedded mode is the executable bit for files.
umask = utils.get_umask()
if self.isdir() or bool(self.__permission & 0o100):
return 0o777 & ~umask
else:
return 0o666 & ~umask
@mode.setter
def mode(self, permission):
self.__permission = permission # pylint: disable=attribute-defined-outside-init
class TarSource(DownloadableFileSource):
# pylint: disable=attribute-defined-outside-init
BST_MIN_VERSION = "2.0"
def configure(self, node):
super().configure(node)
self.base_dir = node.get_str("base-dir", "*")
node.validate_keys(DownloadableFileSource.COMMON_CONFIG_KEYS + ["base-dir"])
def preflight(self):
self.host_lzip = None
if self.url.endswith(".lz"):
self.host_lzip = utils.get_host_tool("lzip")
def get_unique_key(self):
return super().get_unique_key() + [self.base_dir]
@contextmanager
def _run_lzip(self):
assert self.host_lzip
with TemporaryFile() as lzip_stdout:
with open(self._get_mirror_file(), "r") as lzip_file:
self.call([self.host_lzip, "-d"], stdin=lzip_file, stdout=lzip_stdout)
lzip_stdout.seek(0, 0)
yield lzip_stdout
@contextmanager
def _get_tar(self):
if self.url.endswith(".lz"):
with self._run_lzip() as lzip_dec:
with tarfile.open(fileobj=lzip_dec, mode="r:", tarinfo=ReadableTarInfo) as tar:
yield tar
else:
with tarfile.open(self._get_mirror_file(), tarinfo=ReadableTarInfo) as tar:
yield tar
def stage(self, directory):
try:
with self._get_tar() as tar:
base_dir = None
if self.base_dir:
base_dir = self._find_base_dir(tar, self.base_dir)
def filter_non_dev(tarfiles):
for file in tarfiles:
if not file.isdev():
yield file
if base_dir:
tar.extractall(
path=directory, members=filter_non_dev(self._extract_members(tar, base_dir, directory))
)
else:
tar.extractall(path=directory, members=filter_non_dev(tar.getmembers()))
except (tarfile.TarError, OSError) as e:
raise SourceError("{}: Error staging source: {}".format(self, e)) from e
# Override and translate which filenames to extract
def _extract_members(self, tar, base_dir, target_dir):
# Assert that a tarfile is safe to extract; specifically, make
# sure that we don't do anything outside of the target
# directory (this is possible, if, say, someone engineered a
# tarfile to contain paths that start with ..).
def assert_safe(member):
final_path = os.path.abspath(os.path.join(target_dir, member.path))
if not final_path.startswith(target_dir):
raise SourceError(
"{}: Tarfile attempts to extract outside the staging area: "
"{} -> {}".format(self, member.path, final_path)
)
if member.islnk():
linked_path = os.path.abspath(os.path.join(target_dir, member.linkname))
if not linked_path.startswith(target_dir):
raise SourceError(
"{}: Tarfile attempts to hardlink outside the staging area: "
"{} -> {}".format(self, member.path, final_path)
)
# Don't need to worry about symlinks because they're just
# files here and won't be able to do much harm once we are
# in a sandbox.
if not base_dir.endswith(os.sep):
base_dir = base_dir + os.sep
L = len(base_dir)
for member in tar.getmembers():
# First, ensure that a member never starts with `./`
if member.path.startswith("./"):
member.path = member.path[2:]
if member.islnk() and member.linkname.startswith("./"):
member.linkname = member.linkname[2:]
# Now extract only the paths which match the normalized path
if member.path.startswith(base_dir):
# Hardlinks are smart and collapse into the "original"
# when their counterpart doesn't exist. This means we
# only need to modify links to files whose location we
# change.
#
# Since we assert that we're not linking to anything
# outside the target directory, this should only ever
# be able to link to things inside the target
# directory, so we should cover all bases doing this.
#
if member.islnk() and member.linkname.startswith(base_dir):
member.linkname = member.linkname[L:]
member.path = member.path[L:]
assert_safe(member)
yield member
# We want to iterate over all paths of a tarball, but getmembers()
# is not enough because some tarballs simply do not contain the leading
# directory paths for the archived files.
def _list_tar_paths(self, tar):
visited = set()
for member in tar.getmembers():
# Remove any possible leading './', offer more consistent behavior
# across tarballs encoded with or without a leading '.'
member_name = member.name.lstrip("./")
if not member.isdir():
# Loop over the components of a path, for a path of a/b/c/d
# we will first visit 'a', then 'a/b' and then 'a/b/c', excluding
# the final component
components = member_name.split("/")
for i in range(len(components) - 1):
dir_component = "/".join([components[j] for j in range(i + 1)])
if dir_component not in visited:
visited.add(dir_component)
try:
# Dont yield directory members which actually do
# exist in the archive
_ = tar.getmember(dir_component)
except KeyError:
if dir_component != ".":
yield dir_component
continue
# Avoid considering the '.' directory, if any is included in the archive
# this is to avoid the default 'base-dir: *' value behaving differently
# depending on whether the tarball was encoded with a leading '.' or not
if member_name == ".":
continue
yield member_name
def _find_base_dir(self, tar, pattern):
paths = self._list_tar_paths(tar)
matches = sorted(list(utils.glob(paths, pattern)))
if not matches:
raise SourceError("{}: Could not find base directory matching pattern: {}".format(self, pattern))
return matches[0]
def setup():
return TarSource | PypiClean |
/FreePyBX-1.0-RC1.tar.gz/FreePyBX-1.0-RC1/freepybx/public/js/dojox/xmpp/UserService.js | define(["dijit","dojo","dojox"],function(_1,_2,_3){
_2.provide("dojox.xmpp.UserService");
_2.declare("dojox.xmpp.UserService",null,{constructor:function(_4){
this.session=_4;
},getPersonalProfile:function(){
var _5={id:this.session.getNextIqId(),type:"get"};
var _6=new _3.string.Builder(_3.xmpp.util.createElement("iq",_5,false));
_6.append(_3.xmpp.util.createElement("query",{xmlns:"jabber:iq:private"},false));
_6.append(_3.xmpp.util.createElement("sunmsgr",{xmlsns:"sun:xmpp:properties"},true));
_6.append("</query></iq>");
var _7=this.session.dispatchPacket(_6.toString(),"iq",_5.id);
_7.addCallback(this,"_onGetPersonalProfile");
},setPersonalProfile:function(_8){
var _9={id:this.session.getNextIqId(),type:"set"};
var _a=new _3.string.Builder(_3.xmpp.util.createElement("iq",_9,false));
_a.append(_3.xmpp.util.createElement("query",{xmlns:"jabber:iq:private"},false));
_a.append(_3.xmpp.util.createElement("sunmsgr",{xmlsns:"sun:xmpp:properties"},false));
for(var _b in _8){
_a.append(_3.xmpp.util.createElement("property",{name:_b},false));
_a.append(_3.xmpp.util.createElement("value",{},false));
_a.append(_8[_b]);
_a.append("</value></props>");
}
_a.append("</sunmsgr></query></iq>");
var _c=this.session.dispatchPacket(_a.toString(),"iq",_9.id);
_c.addCallback(this,"_onSetPersonalProfile");
},_onSetPersonalProfile:function(_d){
if(_d.getAttribute("type")=="result"){
this.onSetPersonalProfile(_d.getAttribute("id"));
}else{
if(_d.getAttribute("type")=="error"){
var _e=this.session.processXmppError(_d);
this.onSetPersonalProfileFailure(_e);
}
}
},onSetPersonalProfile:function(id){
},onSetPersonalProfileFailure:function(_f){
},_onGetPersonalProfile:function(_10){
if(_10.getAttribute("type")=="result"){
var _11={};
if(_10.hasChildNodes()){
var _12=_10.firstChild;
if((_12.nodeName=="query")&&(_12.getAttribute("xmlns")=="jabber:iq:private")){
var _13=_12.firstChild;
if((_13.nodeName=="query")&&(_13.getAttributes("xmlns")=="sun:xmpp:properties")){
for(var i=0;i<_13.childNodes.length;i++){
var n=_13.childNodes[i];
if(n.nodeName=="property"){
var _14=n.getAttribute("name");
var val=n.firstChild||"";
_11[_14]=val;
}
}
}
}
this.onGetPersonalProfile(_11);
}
}else{
if(_10.getAttribute("type")=="error"){
var err=this.session.processXmppError(_10);
this.onGetPersonalProfileFailure(err);
}
}
return _10;
},onGetPersonalProfile:function(_15){
},onGetPersonalProfileFailure:function(err){
}});
}); | PypiClean |
/Comet-3.1.0.tar.gz/Comet-3.1.0/comet/protocol/subscriber.py |
# Twisted protocol definition
from twisted.internet import reactor
from twisted.protocols.policies import TimeoutMixin
from twisted.internet.protocol import ReconnectingClientFactory
# Base protocol definitions
from comet.protocol.base import EventHandler, VOEVENT_ROLES
# Constructors for transport protocol messages
from comet.protocol.messages import iamaliveresponse, authenticateresponse
# Comet utility routines
import comet.log as log
from comet.utility import xml_document, ParseError
__all__ = ["VOEventSubscriberFactory"]
class VOEventSubscriber(EventHandler, TimeoutMixin):
ALIVE_INTERVAL = 120 # If we get no traffic for ALIVE_INTERVAL seconds,
# assume our peer forgot us.
def __init__(self, filters=[]):
self.filters = filters
def connectionMade(self, *args):
self.setTimeout(self.ALIVE_INTERVAL)
return EventHandler.connectionMade(self, *args)
def connectionLost(self, *args):
# Don't leave the reactor in an unclean state when we exit.
self.setTimeout(None)
return EventHandler.connectionLost(self, *args)
def timeoutConnection(self):
log.info(
"No iamalive received from %s for %d seconds; disconecting" %
(self.transport.getPeer(), self.ALIVE_INTERVAL),
system="VOEventSubscriber"
)
return TimeoutMixin.timeoutConnection(self)
def stringReceived(self, data):
"""
Called when a complete new message is received.
"""
try:
incoming = xml_document(data)
except ParseError:
log.warn("Unparsable message received")
return
# Reset the timeout counter and wait another 120 seconds before
# disconnecting due to inactivity.
self.resetTimeout()
# The root element of both VOEvent and Transport packets has a
# "role" element which we use to identify the type of message we
# have received.
if incoming.element.get('role') == "iamalive":
log.debug("IAmAlive received from %s" % str(self.transport.getPeer()))
self.send_xml(
iamaliveresponse(self.factory.local_ivo,
incoming.element.find('Origin').text)
)
elif incoming.element.get('role') == "authenticate":
log.debug("Authenticate received from %s" % str(self.transport.getPeer()))
self.send_xml(
authenticateresponse(
self.factory.local_ivo,
incoming.element.find('Origin').text,
self.filters
)
)
elif incoming.element.get('role') in VOEVENT_ROLES:
log.info(
"VOEvent %s received from %s" % (
incoming.element.attrib['ivorn'],
str(self.transport.getPeer())
)
)
# We don't send a NAK even if the event is invalid since we don't
# want to be removed from upstream's distribution list.
self.process_event(incoming, can_nak=False)
else:
log.warn(
"Incomprehensible data received from %s (role=%s)" %
(self.transport.getPeer(), incoming.element.get("role"))
)
class VOEventSubscriberFactory(ReconnectingClientFactory):
RESET_DELAY = 5 # Reset exponential backoff after connection survives for
# at least RESET_DELAY seconds
protocol = VOEventSubscriber
callLater = reactor.callLater # Can be replaced in test cases
def __init__(self,
local_ivo=None, validators=None, handlers=None, filters=None,
):
self.local_ivo = local_ivo
self.handlers = handlers or []
self.validators = validators or []
self.filters = filters or []
# Calling resetDelay() now is not necessary, but we want
# self.reset_call always to exist when we use it later
self.reset_call = self.callLater(0, self.resetDelay)
def buildProtocol(self, addr):
self.reset_call = self.callLater(self.RESET_DELAY, self.resetDelay)
p = self.protocol(self.filters)
p.factory = self
return p
def stopFactory(self):
if self.reset_call.active():
self.reset_call.cancel()
def clientConnectionFailed(self, connector, reason):
log.info(
"Connection to %s failed; will retry in %d second%s" %
(connector.getDestination(), self.delay, "" if self.delay == 1 else "s"),
system="VOEventSubscriberFactory"
)
ReconnectingClientFactory.clientConnectionFailed(self, connector, reason)
def clientConnectionLost(self, connector, reason):
log.info(
"Connection to %s lost; will retry in %d second%s" %
(connector.getDestination(), self.delay, "" if self.delay == 1 else "s"),
system="VOEventSubscriberFactory"
)
if self.reset_call.active():
self.reset_call.cancel()
ReconnectingClientFactory.clientConnectionFailed(self, connector, reason) | PypiClean |
/FastSent-0.2.0.tar.gz/FastSent-0.2.0/README.rst | FastSent is Sentiment Classification python library. It uses Sequential model for Sentiment classfication. FastSent is developed using GRU(Gated Recurrent Unit) model.
Requirement
------------
FastSent support Python 3.6 or newer.
Installation
------------
pip install FastSent
Example
-------------
This package is being developed for sentiment classfication using Sequential model GRU(Gated Recurrent Unit).
data = 'Sample.csv'
labels = 'sentiment'
text = 'content'
f = FastSent()
X_train, X_test, y_train, y_test = f.train_test_split(data, labels, text)
trained_model = f.fit_train(X_train, y_train, 500, 50, 7789, 5, 4)
prediction = f.predict(trained_model, X_test, y_train, 4)
where ``sample`` is a training file containing labels and text.
References
----------
DataSet Information
~~~~~~~~~~~~~~~~~~~
[1] Sample DataSet is being used for research purpose from `*data.world* <https://data.world/crowdflower/sentiment-analysis-in-text>`. | PypiClean |
/GhTrack-1.1.1.tar.gz/GhTrack-1.1.1/docs/introduction.rst | Introduction
============
github-track is a Python library to use the `Github API v3 <http://developer.github.com/v3>`__.
With it, you can pull any public repositories pull requests from Python scripts.
**Sending email currently work only with sendGrid**
Download and install
--------------------
First of all make sure you have install python in your machine and the version is higher than `3.6`. If not please process as follow to install it.
.. code-block:: bash
>> brew install python@3.9
**Installation using pip**
The easiest way to install is to use [Python Package Index](https://pypi.org/project/GhTrack/),
so, a pip install should be enough.
.. code-block:: bash
>> pip3 install GhTrack
**Installation by cloning the source code**
If you have done the installation using pip, you can ignore this part.
To use it please clone the [github-track](https://github.com/zinaLacina/github-track) repository.
.. code-block:: bash
>> git clone https://github.com/zinaLacina/github-track
Once it clone please cd into the directory
.. code-block:: bash
>> cd github-track
Once inside the direction check that you have the latest up to date of the setuptools.
.. code-block:: bash
python3 -m pip install --upgrade setuptools
And lastly install the *module*
.. code-block:: bash
python3 setup.py install
And you are all set for to run the application.
Short tutorial
---------------------
Let's test the base features of the module, that consist to pull the last
7 days pull requests of a public repo.
By default the module has default value in the settings located in the data folder.
The default repo is ``kubernetes``.
So to get the list of the last 7 days pull requests of the ``kubernetes`` repo.
Open a terminal, and in the console please type >>``python3``
After that, import the ``GhTrack`` module
.. code-block:: python
>> from GhTrack import GhTrack
# create GhTrack object without any params(first of all the default params)
>> g = GhTrack()
#That will print on the console the html of the last 7 days pull requests
>> g.sendEmailOrPrintConsole(emailNotConsole=False)
You can also get the json format of the last 7 days pull requests
.. code-block:: python
>> from GhTrack import GhTrack
>> g = GhTrack()
>> pulls = g.getPulls()
#json format
>> pulls
Then play with your Github objects::
for pull in pulls:
print(pull["title"])
Licensing
---------
This is free and unencumbered software released into the public domain.
Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.
In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit
of the public at large and to the detriment of our heirs and
successors. We intend this dedication to be an overt act of
relinquishment in perpetuity of all present and future rights to this
software under copyright law.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.
For more information, please refer to <https://unlicense.org>
| PypiClean |
/FutureLog-0.1.1.tar.gz/FutureLog-0.1.1/README.md | [](https://github.com/psf/black)
# Installation
```pip install futurelog```
# Usage
## Introduction
The goal of this library is to provide a way to defer logs and consume (print) them when needed, in an async application.
For instance, it would perfectly fit a config deployer in async. It would help to keep messages grouped by servers.
Usage should be limited to reporting and not error/exception logging.
Also you should ensure you catch all possible exception in your program in your entrypoint, in order to consume all logs before exiting your application.
## Create a logger
```python
from futurelog import FutureLogger
future_logger = FutureLogger(__name__)
```
## Register logs
The methods supported are: `.debug()`, `.info()`, `.warning()`, `.error()`, `.critical()`
```python
future_logger.debug(topic, msg)
```
Example:
```python
future_logger.debug("server1", "deploying stuff 1")
future_logger.error("server1", "failed")
future_logger.debug("server2", "deploying stuff 1")
future_logger.warning("server2", "success")
```
## Consume logs
### One specific logger
```python
logger.consume(topic)
```
Example:
```python
future_logger.consume("server1")
future_logger.consume("server2")
```
### All loggers for a topic (one for each module)
```python
FutureLogger.consume_all_logger_for(topic)
```
```python
FutureLogger.consume_all_logger_for("server1")
FutureLogger.consume_all_logger_for("server2")
```
### All unconsumed logger
```python
FutureLogger.consume_all_logger()
```
| PypiClean |
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