Reformatting main.py
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main.py
188
main.py
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@ -7,35 +7,45 @@ Aurélien VALENTIN - from 06/11/2022 to 29/12/2022
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************************"""
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# Default parameters, feel free to change them as you want.
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NB_SPECIES = 100 # Number of species wanted by the user. Can't exceed 100 with the GBIF method.
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NB_SPECIES = (
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50 # Number of species wanted by the user. Can't exceed 100 with the GBIF method.
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)
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LANGUAGE = "fr" # Please choose "fr" or "en" to get respectively French or English vernacular names.
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LANGUAGE = "fr" # Please choose "fr" or "en" to get respectively French or English vernacular names.
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SPECIE_LIST_PATH_IF_GBIF_METHOD = "" # A csv file from https://identify.plantnet.org/prediction. Only if you've chosen the GBIF method.
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SPECIE_LIST_PATH_IF_GBIF_METHOD = "" # A csv file from https://identify.plantnet.org/prediction. Only if you've chosen the GBIF method.
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MY_OWN_LIST_PATH = "" # A txt file with one specie by line. Be careful to write the scientific name used in Pl@ntNet and change NB_SPECIES if needed.
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MY_OWN_LIST_PATH = "" # A txt file with one specie by line. Be careful to write the scientific name used in Pl@ntNet and change NB_SPECIES if needed.
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MAX_NB_OF_LINKS_BY_TYPE_AND_BY_SPECIES = 100 # The code will accumulate links of pictures of leaves, flower, fruits and barks of eache species.
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# The most photos you want, the most diversified your learning will be, but the longer it will take to load...
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# Importation and other initialisations
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import json, sys
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import genanki #https://github.com/kerrickstaley/genanki.git
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import genanki # https://github.com/kerrickstaley/genanki.git
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from random import shuffle
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dict_common_plants = {}
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with open("_dict_species.json", "r") as fpi : dict_common_names = json.load(fpi) # From the 3-1 and 3-2 supplementary codes
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with open("_dict_species.json", "r") as fpi:
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dict_common_names = json.load(fpi) # From the 3-1 and 3-2 supplementary codes
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# Definition of the progressbar function, from https://gist.github.com/ChesterChowWOV/2b35c551b339adbf459363322aac5b4b
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def progressbar(it, prefix = "", size = 60, file = sys.stdout):
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def progressbar(it, prefix="", size=60, file=sys.stdout):
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count = len(it)
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def show(j):
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x = int(size*j/count)
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file.write("{}[{}{}] {}/{} {}%\r".format(prefix, "█"*x, "."*(size-x), j, count, round(j / count * 100, 2)))
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x = int(size * j / count)
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file.write(
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"{}[{}{}] {}/{} {}%\r".format(
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prefix, "█" * x, "." * (size - x), j, count, round(j / count * 100, 2)
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)
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)
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file.flush()
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show(0)
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for i, item in enumerate(it):
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yield item
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@ -51,7 +61,8 @@ Step 1 : Listing the most common species (if without a manual list or a GBIF fil
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if SPECIE_LIST_PATH_IF_GBIF_METHOD == MY_OWN_LIST_PATH:
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print("Listing the most common species")
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# Loading of the whole list
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with open("_dict_species_by_rarety.json") as fpi : dict_plants_sorted = json.load(fpi) # From the first supplementary code
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with open("_dict_species_by_rarety.json") as fpi:
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dict_plants_sorted = json.load(fpi) # From the first supplementary code
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# Writing of the user's list
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with open("Selected_species.txt", "w") as fpo:
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@ -65,35 +76,69 @@ Step 2 : Parsing data for each species.
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# Initialisation of the dictionary (and addition of the family) from a file from the step 1...
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if SPECIE_LIST_PATH_IF_GBIF_METHOD == "":
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with open("_dict_classification.json", "r") as fpi : dict_classification = json.load(fpi) # From the second supplementary code
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with open("_dict_classification.json", "r") as fpi:
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dict_classification = json.load(fpi) # From the second supplementary code
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try: fpi = open(MY_OWN_LIST_PATH)
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except : fpi = open("Selected_species.txt")
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try:
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fpi = open(MY_OWN_LIST_PATH)
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except:
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fpi = open("Selected_species.txt")
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for line in progressbar(fpi.readlines(), "Adding families", 40):
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specie = line.split(" ")[0] + " " + line.split(" ")[1].lower().strip()
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dict_common_plants[specie] = {"Occurrence": {"leaf": 0, "flower": 0, "fruit": 0, "bark": 0}}
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try: dict_common_plants[specie]["Family"] = dict_classification[specie]
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except: dict_common_plants[specie]["Family"] = "Family_not_found"
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dict_common_plants[specie]["Links"] = {"leaf": "", "flower": "", "fruit": "", "bark": ""}
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dict_common_plants[specie]["Authors"] = {"leaf": "", "flower": "", "fruit": "", "bark": ""}
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specie = line.split(" ")[0] + " " + line.split(" ")[1].lower().strip()
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dict_common_plants[specie] = {
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"Occurrence": {"leaf": 0, "flower": 0, "fruit": 0, "bark": 0}
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}
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try:
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dict_common_plants[specie]["Family"] = dict_classification[specie]
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except:
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dict_common_plants[specie]["Family"] = "Family not found"
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dict_common_plants[specie]["Links"] = {
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"leaf": "",
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"flower": "",
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"fruit": "",
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"bark": "",
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}
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dict_common_plants[specie]["Authors"] = {
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"leaf": "",
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"flower": "",
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"fruit": "",
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"bark": "",
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}
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# ...or from a GBIF file from here : https://identify.plantnet.org/prediction
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else:
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with open(SPECIE_LIST_PATH_IF_GBIF_METHOD) as fpi:
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fpi.readline()
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for line in progressbar(fpi.readlines(), "Adding families", 40):
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specie = line.split(",")[1].split(" ")[0] + " " + line.split(",")[1].split(" ")[1]
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dict_common_plants[specie] = {"Occurrence": {"leaf": 0, "flower": 0, "fruit": 0, "bark": 0}}
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specie = (
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line.split(",")[1].split(" ")[0]
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+ " "
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+ line.split(",")[1].split(" ")[1]
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)
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dict_common_plants[specie] = {
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"Occurrence": {"leaf": 0, "flower": 0, "fruit": 0, "bark": 0}
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}
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dict_common_plants[specie]["Family"] = line.split(",")[2]
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dict_common_plants[specie]["Links"] = {"leaf": "", "flower": "", "fruit": "", "bark": ""}
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dict_common_plants[specie]["Authors"] = {"leaf": "", "flower": "", "fruit": "", "bark": ""}
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dict_common_plants[specie]["Links"] = {
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"leaf": "",
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"flower": "",
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"fruit": "",
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"bark": "",
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}
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dict_common_plants[specie]["Authors"] = {
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"leaf": "",
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"flower": "",
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"fruit": "",
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"bark": "",
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}
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# Addition of vernacular name(s)
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for specie in progressbar(dict_common_plants.keys(), "Adding common names", 40):
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try:
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dict_common_plants[specie]["Common names"] = dict_common_names[specie][LANGUAGE]
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except: dict_common_plants[specie]["Common names"] = "No common name found."
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except:
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dict_common_plants[specie]["Common names"] = "No common name found."
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# Addition of photo links and author names
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with open("multimedia.txt", encoding="utf-8") as fpi:
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@ -104,12 +149,20 @@ with open("multimedia.txt", encoding="utf-8") as fpi:
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link = line_split[3].strip(" ").split("o/")[1]
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type = line_split[5].split(":")[1].strip(" ")
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author = line_split[len(line_split) - 1].strip()
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if specie in dict_common_plants.keys() and type in ["leaf", "flower", "fruit", "bark"]:
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if specie in dict_common_plants.keys() and type in [
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"leaf",
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"flower",
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"fruit",
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"bark",
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]:
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if dict_common_plants[specie]["Occurrence"][type] == 0:
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dict_common_plants[specie]["Links"][type] += link
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dict_common_plants[specie]["Authors"][type] += author
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dict_common_plants[specie]["Occurrence"][type] += 1
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elif dict_common_plants[specie]["Occurrence"][type] < 101:
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elif (
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dict_common_plants[specie]["Occurrence"][type]
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< MAX_NB_OF_LINKS_BY_TYPE_AND_BY_SPECIES + 1
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):
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dict_common_plants[specie]["Links"][type] += "," + link
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dict_common_plants[specie]["Authors"][type] += "," + author
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dict_common_plants[specie]["Occurrence"][type] += 1
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@ -122,25 +175,25 @@ Step 3 : Generation of the Anki deck.
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print("Preparing the Anki deck")
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# Definition of the Anki card model
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my_model = genanki.Model(
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1091735104,
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'Model for AnkIdentification',
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fields=[
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{'name': 'Name'},
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{'name': 'Common names'},
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{'name': 'Family'},
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{'name': 'Leaf'},
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{'name': 'Flower'},
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{'name': 'Fruit'},
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{'name': 'Bark'},
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{'name': 'Leaf authors'},
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{'name': 'Flower authors'},
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{'name': 'Fruit authors'},
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{'name': 'Bark authors'}
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],
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templates=[
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{
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'name': 'Card 1',
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'qfmt': """<style>
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1091735104,
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"Model for AnkIdentification",
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fields=[
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{"name": "Name"},
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{"name": "Common names"},
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{"name": "Family"},
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{"name": "Leaf"},
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{"name": "Flower"},
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{"name": "Fruit"},
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{"name": "Bark"},
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{"name": "Leaf authors"},
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{"name": "Flower authors"},
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{"name": "Fruit authors"},
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{"name": "Bark authors"},
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],
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templates=[
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{
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"name": "Card 1",
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"qfmt": """<style>
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.card {
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font-family: arial;
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font-size: 20px;
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@ -316,7 +369,7 @@ prepImg("{{Flower}}","{{Flower authors}}",'Flower');
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prepImg("{{Fruit}}","{{Fruit authors}}",'Fruit');
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prepImg("{{Bark}}","{{Bark authors}}",'Bark');
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</script>""",
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'afmt': """<div class="half">
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"afmt": """<div class="half">
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<h1><i>{{Name}}</i></h1>
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<br>
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<b><i>{{Family}}</i></b>
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@ -324,17 +377,15 @@ prepImg("{{Bark}}","{{Bark authors}}",'Bark');
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{{Common names}}
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</div>
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{{FrontSide}}""",
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'bfont': 'Arial'
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#'Styles': ".card {\n font-family: arial;\n font-size: 20px;\n text-align: center;\n color: black;\n background-color: white;\n}"
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},
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],
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css='.card {\n font-family: arial;\n font-size: 20px;\n text-align: center;\n color: black;\n background-color: white;\n}\n',
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"bfont": "Arial"
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#'Styles': ".card {\n font-family: arial;\n font-size: 20px;\n text-align: center;\n color: black;\n background-color: white;\n}"
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},
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],
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css=".card {\n font-family: arial;\n font-size: 20px;\n text-align: center;\n color: black;\n background-color: white;\n}\n",
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)
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# Creation of the deck
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my_deck = genanki.Deck(
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2059400110,
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'AnkIdentifaction')
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my_deck = genanki.Deck(2059400110, "AnkIdentifaction")
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# Randomization of the species order
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species_shuffled = list(dict_common_plants.keys())
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@ -342,14 +393,27 @@ shuffle(species_shuffled)
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# Generation of all notes
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for specie in progressbar(species_shuffled, "Creating notes", 40):
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dict_specie = dict_common_plants[specie]
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my_note = genanki.Note(
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model = my_model,
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fields = [specie, dict_specie["Common names"], dict_specie["Family"], dict_specie["Links"]["leaf"], dict_specie["Links"]["flower"], dict_specie["Links"]["fruit"], dict_specie["Links"]["bark"], dict_specie["Authors"]["leaf"], dict_specie["Authors"]["flower"], dict_specie["Authors"]["fruit"], dict_specie["Authors"]["bark"]],
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tags = ["AnkIdentification::" + dict_specie["Family"]])
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my_deck.add_note(my_note)
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dict_specie = dict_common_plants[specie]
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my_note = genanki.Note(
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model=my_model,
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fields=[
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specie,
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dict_specie["Common names"],
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dict_specie["Family"],
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dict_specie["Links"]["leaf"],
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dict_specie["Links"]["flower"],
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dict_specie["Links"]["fruit"],
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dict_specie["Links"]["bark"],
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dict_specie["Authors"]["leaf"],
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dict_specie["Authors"]["flower"],
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dict_specie["Authors"]["fruit"],
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dict_specie["Authors"]["bark"],
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],
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tags=["AnkIdentification::" + dict_specie["Family"]],
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)
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my_deck.add_note(my_note)
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# Creation of the final file
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print("Almost done!")
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genanki.Package(my_deck).write_to_file('AnkIdentification.apkg')
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genanki.Package(my_deck).write_to_file("AnkIdentification.apkg")
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print("Enjoy ^^")
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