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j0057/github-release | github_release.py | _recursive_gh_get | def _recursive_gh_get(href, items):
"""Recursively get list of GitHub objects.
See https://developer.github.com/v3/guides/traversing-with-pagination/
"""
response = _request('GET', href)
response.raise_for_status()
items.extend(response.json())
if "link" not in response.headers:
ret... | python | def _recursive_gh_get(href, items):
"""Recursively get list of GitHub objects.
See https://developer.github.com/v3/guides/traversing-with-pagination/
"""
response = _request('GET', href)
response.raise_for_status()
items.extend(response.json())
if "link" not in response.headers:
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j0057/github-release | github_release.py | main | def main(github_token, github_api_url, progress):
"""A CLI to easily manage GitHub releases, assets and references."""
global progress_reporter_cls
progress_reporter_cls.reportProgress = sys.stdout.isatty() and progress
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"""A CLI to easily manage GitHub releases, assets and references."""
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j0057/github-release | github_release.py | _update_release_sha | def _update_release_sha(repo_name, tag_name, new_release_sha, dry_run):
"""Update the commit associated with a given release tag.
Since updating a tag commit is not directly possible, this function
does the following steps:
* set the release tag to ``<tag_name>-tmp`` and associate it
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* set the release tag to ``<tag_name>-tmp`` and associate it
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lappis-unb/salic-ml | src/salicml/metrics/finance/approved_funds.py | approved_funds | def approved_funds(pronac, dt):
"""
Verifica se o valor total de um projeto é um
outlier em relação
aos projetos do mesmo seguimento cultural
Dataframes: planilha_orcamentaria
"""
funds_df = data.approved_funds_by_projects
project = (
funds_df
.loc[funds_df['PRONAC'] == ... | python | def approved_funds(pronac, dt):
"""
Verifica se o valor total de um projeto é um
outlier em relação
aos projetos do mesmo seguimento cultural
Dataframes: planilha_orcamentaria
"""
funds_df = data.approved_funds_by_projects
project = (
funds_df
.loc[funds_df['PRONAC'] == ... | [
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lappis-unb/salic-ml | src/salicml_api/analysis/api.py | complexidade | def complexidade(obj):
"""
Returns a value that indicates project health, currently FinancialIndicator
is used as this value, but it can be a result of calculation with other
indicators in future
"""
indicators = obj.indicator_set.all()
if not indicators:
value = 0.0
else:
... | python | def complexidade(obj):
"""
Returns a value that indicates project health, currently FinancialIndicator
is used as this value, but it can be a result of calculation with other
indicators in future
"""
indicators = obj.indicator_set.all()
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lappis-unb/salic-ml | src/salicml_api/analysis/api.py | details | def details(project):
"""
Project detail endpoint,
Returns project pronac, name,
and indicators with details
"""
indicators = project.indicator_set.all()
indicators_detail = [(indicator_details(i)
for i in indicators)][0]
if not indicators:
indicators_det... | python | def details(project):
"""
Project detail endpoint,
Returns project pronac, name,
and indicators with details
"""
indicators = project.indicator_set.all()
indicators_detail = [(indicator_details(i)
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lappis-unb/salic-ml | src/salicml_api/analysis/api.py | indicator_details | def indicator_details(indicator):
"""
Return a dictionary with all metrics in FinancialIndicator,
if there aren't values for that Indicator, it is filled with default values
"""
metrics = format_metrics_json(indicator)
metrics_list = set(indicator.metrics
.filter(name__in... | python | def indicator_details(indicator):
"""
Return a dictionary with all metrics in FinancialIndicator,
if there aren't values for that Indicator, it is filled with default values
"""
metrics = format_metrics_json(indicator)
metrics_list = set(indicator.metrics
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lappis-unb/salic-ml | src/salicml/data/query.py | Metrics.get_metric | def get_metric(self, pronac, metric):
"""
Get metric for the project with the given pronac number.
Usage:
>>> metrics.get_metric(pronac_id, 'finance.approved_funds')
"""
assert isinstance(metric, str)
assert '.' in metric, 'metric must declare a namespace'
... | python | def get_metric(self, pronac, metric):
"""
Get metric for the project with the given pronac number.
Usage:
>>> metrics.get_metric(pronac_id, 'finance.approved_funds')
"""
assert isinstance(metric, str)
assert '.' in metric, 'metric must declare a namespace'
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lappis-unb/salic-ml | src/salicml/data/query.py | Metrics.register | def register(self, category):
"""
Usage:
@metrics.register('finance')
def approved_funds(pronac, data):
return metric_from_data_and_pronac_number(data, pronac)
"""
def decorator(func):
name = func.__name__
key = f'{category}... | python | def register(self, category):
"""
Usage:
@metrics.register('finance')
def approved_funds(pronac, data):
return metric_from_data_and_pronac_number(data, pronac)
"""
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lappis-unb/salic-ml | src/salicml_api/analysis/models/utils.py | execute_project_models_sql_scripts | def execute_project_models_sql_scripts(force_update=False):
"""
Used to get project information from MinC database
and convert to this application Project models.
Uses bulk_create if database is clean
"""
# TODO: Remove except and use ignore_conflicts
# on bulk_create when django... | python | def execute_project_models_sql_scripts(force_update=False):
"""
Used to get project information from MinC database
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lappis-unb/salic-ml | src/salicml_api/analysis/models/utils.py | create_finance_metrics | def create_finance_metrics(metrics: list, pronacs: list):
"""
Creates metrics, creating an Indicator if it doesn't already exists
Metrics are created for projects that are in pronacs and saved in
database.
args:
metrics: list of names of metrics that will be calculated
p... | python | def create_finance_metrics(metrics: list, pronacs: list):
"""
Creates metrics, creating an Indicator if it doesn't already exists
Metrics are created for projects that are in pronacs and saved in
database.
args:
metrics: list of names of metrics that will be calculated
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lappis-unb/salic-ml | src/salicml/metrics/finance/total_receipts.py | total_receipts | def total_receipts(pronac, dt):
"""
This metric calculates the project total of receipts
and compare it to projects in the same segment
output:
is_outlier: True if projects receipts is not compatible
to others projects in the same segment
total_receipts: a... | python | def total_receipts(pronac, dt):
"""
This metric calculates the project total of receipts
and compare it to projects in the same segment
output:
is_outlier: True if projects receipts is not compatible
to others projects in the same segment
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lappis-unb/salic-ml | src/salicml_api/analysis/preload_data.py | load_project_metrics | def load_project_metrics():
"""
Create project metrics for financial indicator
Updates them if already exists
"""
all_metrics = FinancialIndicator.METRICS
for key in all_metrics:
df = getattr(data, key)
pronac = 'PRONAC'
if key == 'planilha_captacao':
pronac =... | python | def load_project_metrics():
"""
Create project metrics for financial indicator
Updates them if already exists
"""
all_metrics = FinancialIndicator.METRICS
for key in all_metrics:
df = getattr(data, key)
pronac = 'PRONAC'
if key == 'planilha_captacao':
pronac =... | [
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lappis-unb/salic-ml | src/salicml/metrics/finance/new_providers.py | new_providers | def new_providers(pronac, dt):
"""
Return the percentage of providers of a project
that are new to the providers database.
"""
info = data.providers_info
df = info[info['PRONAC'] == pronac]
providers_count = data.providers_count.to_dict()[0]
new_providers = []
segment_id = None
... | python | def new_providers(pronac, dt):
"""
Return the percentage of providers of a project
that are new to the providers database.
"""
info = data.providers_info
df = info[info['PRONAC'] == pronac]
providers_count = data.providers_count.to_dict()[0]
new_providers = []
segment_id = None
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lappis-unb/salic-ml | src/salicml/metrics/finance/new_providers.py | average_percentage_of_new_providers | def average_percentage_of_new_providers(providers_info, providers_count):
"""
Return the average percentage of new providers
per segment and the average percentage of all projects.
"""
segments_percentages = {}
all_projects_percentages = []
providers_count = providers_count.to_dict()[0]
... | python | def average_percentage_of_new_providers(providers_info, providers_count):
"""
Return the average percentage of new providers
per segment and the average percentage of all projects.
"""
segments_percentages = {}
all_projects_percentages = []
providers_count = providers_count.to_dict()[0]
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lappis-unb/salic-ml | src/salicml/metrics/finance/new_providers.py | providers_count | def providers_count(df):
"""
Returns total occurrences of each provider
in the database.
"""
providers_count = {}
cnpj_array = df.values
for a in cnpj_array:
cnpj = a[0]
occurrences = providers_count.get(cnpj, 0)
providers_count[cnpj] = occurrences + 1
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"""
Returns total occurrences of each provider
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"""
providers_count = {}
cnpj_array = df.values
for a in cnpj_array:
cnpj = a[0]
occurrences = providers_count.get(cnpj, 0)
providers_count[cnpj] = occurrences + 1
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lappis-unb/salic-ml | src/salicml/metrics/finance/new_providers.py | all_providers_cnpj | def all_providers_cnpj(df):
"""
Return CPF/CNPJ of all providers
in database.
"""
cnpj_list = []
for _, items in df.groupby('PRONAC'):
unique_cnpjs = items['nrCNPJCPF'].unique()
cnpj_list += list(unique_cnpjs)
return pd.DataFrame(cnpj_list) | python | def all_providers_cnpj(df):
"""
Return CPF/CNPJ of all providers
in database.
"""
cnpj_list = []
for _, items in df.groupby('PRONAC'):
unique_cnpjs = items['nrCNPJCPF'].unique()
cnpj_list += list(unique_cnpjs)
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lappis-unb/salic-ml | src/salicml/metrics/finance/new_providers.py | get_providers_info | def get_providers_info(pronac):
"""
Return all info about providers of a
project with the given pronac.
"""
df = data.providers_info
grouped = df.groupby('PRONAC')
return grouped.get_group(pronac) | python | def get_providers_info(pronac):
"""
Return all info about providers of a
project with the given pronac.
"""
df = data.providers_info
grouped = df.groupby('PRONAC')
return grouped.get_group(pronac) | [
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lappis-unb/salic-ml | src/salicml/metrics/base.py | get_info | def get_info(df, group, info=['mean', 'std']):
"""
Aggregate mean and std with the given group.
"""
agg = df.groupby(group).agg(info)
agg.columns = agg.columns.droplevel(0)
return agg | python | def get_info(df, group, info=['mean', 'std']):
"""
Aggregate mean and std with the given group.
"""
agg = df.groupby(group).agg(info)
agg.columns = agg.columns.droplevel(0)
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lappis-unb/salic-ml | src/salicml/metrics/base.py | get_salic_url | def get_salic_url(item, prefix, df_values=None):
"""
Mount a salic url for the given item.
"""
url_keys = {
'pronac': 'idPronac',
'uf': 'uf',
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'county': 'idmunicipio',
'item_id': 'idPlanilhaItem',
'stage': 'etapa',
}
if df_val... | python | def get_salic_url(item, prefix, df_values=None):
"""
Mount a salic url for the given item.
"""
url_keys = {
'pronac': 'idPronac',
'uf': 'uf',
'product': 'produto',
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lappis-unb/salic-ml | src/salicml/metrics/base.py | get_cpf_cnpj_by_pronac | def get_cpf_cnpj_by_pronac(pronac):
"""
Return the CNPF/CNPJ of the proponent
of the project with the given pronac.
"""
df = data.planilha_projetos
cpf_cnpj = None
row_df = df[df['PRONAC'].astype(str) == str(pronac)]
if not row_df.empty:
cpf_cnpj = row_df.iloc[0]['CgcCpf']
... | python | def get_cpf_cnpj_by_pronac(pronac):
"""
Return the CNPF/CNPJ of the proponent
of the project with the given pronac.
"""
df = data.planilha_projetos
cpf_cnpj = None
row_df = df[df['PRONAC'].astype(str) == str(pronac)]
if not row_df.empty:
cpf_cnpj = row_df.iloc[0]['CgcCpf']
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lappis-unb/salic-ml | src/salicml/metrics/base.py | has_receipt | def has_receipt(item):
"""
Verify if a item has a receipt.
"""
pronac_id = str(item['idPronac'])
item_id = str(item["idPlanilhaItens"])
combined_id = f'{pronac_id}/{item_id}'
return combined_id in data.receipt.index | python | def has_receipt(item):
"""
Verify if a item has a receipt.
"""
pronac_id = str(item['idPronac'])
item_id = str(item["idPlanilhaItens"])
combined_id = f'{pronac_id}/{item_id}'
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lappis-unb/salic-ml | src/salicml/metrics/base.py | get_segment_projects | def get_segment_projects(segment_id):
"""
Returns all projects from a segment.
"""
df = data.all_items
return (
df[df['idSegmento'] == str(segment_id)]
.drop_duplicates(["PRONAC"])
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) | python | def get_segment_projects(segment_id):
"""
Returns all projects from a segment.
"""
df = data.all_items
return (
df[df['idSegmento'] == str(segment_id)]
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lappis-unb/salic-ml | src/salicml/metrics/base.py | receipt | def receipt(df):
"""
Return a dataframe to verify if a item has a receipt.
"""
mutated_df = df[['IdPRONAC', 'idPlanilhaItem']].astype(str)
mutated_df['pronac_planilha_itens'] = (
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return (
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"""
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mutated_df = df[['IdPRONAC', 'idPlanilhaItem']].astype(str)
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lappis-unb/salic-ml | tasks.py | update_data | def update_data(ctx, models=True, pickles=False, f=False):
"""
Updates local django db projects and pickle files using salic database from
MinC
Pickles are saved in /data/raw/ from sql queries in /data/scripts/
Models are created from /data/scripts/models/
"""
if pickles:
save_sql_to... | python | def update_data(ctx, models=True, pickles=False, f=False):
"""
Updates local django db projects and pickle files using salic database from
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Pickles are saved in /data/raw/ from sql queries in /data/scripts/
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else:
manage(ctx, 'create_models_from_sql', env={}) | python | def update_models(ctx, f=False):
"""
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lappis-unb/salic-ml | src/salicml_api/analysis/models/financial.py | FinancialIndicatorManager.create_indicator | def create_indicator(self, project, is_valid, metrics_list):
"""
Creates FinancialIndicator object for a project, calculating
metrics and indicator value
"""
project = Project.objects.get(pronac=project)
indicator, _ = (FinancialIndicator
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"""
Creates FinancialIndicator object for a project, calculating
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"""
project = Project.objects.get(pronac=project)
indicator, _ = (FinancialIndicator
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lappis-unb/salic-ml | src/salicml/data/db_operations.py | save_sql_to_files | def save_sql_to_files(overwrite=False):
"""
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"""
ext_size = len(SQL_EXTENSION)
path = DATA_PATH / 'scripts'
save_dir = DATA_PATH / "raw"
for file in os.listdir(path):
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"""
Executes every .sql files in /data/scripts/ using salic db vpn and
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lappis-unb/salic-ml | src/salicml_api/analysis/models/base.py | Indicator.fetch_weighted_complexity | def fetch_weighted_complexity(self, recalculate_metrics=False):
"""
Calculates indicator value according to metrics weights
Uses metrics in database
args:
recalculate_metrics: If true metrics values are updated before
using weights
"""... | python | def fetch_weighted_complexity(self, recalculate_metrics=False):
"""
Calculates indicator value according to metrics weights
Uses metrics in database
args:
recalculate_metrics: If true metrics values are updated before
using weights
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lappis-unb/salic-ml | src/salicml/metrics/finance/item_prices.py | item_prices | def item_prices(pronac, data):
"""
Verify if a project is an outlier compared
to the other projects in his segment, based
on the price of bought items.
"""
threshold = 0.1
outlier_info = get_outliers_percentage(pronac)
outlier_info['is_outlier'] = outlier_info['percentage'] > threshold
... | python | def item_prices(pronac, data):
"""
Verify if a project is an outlier compared
to the other projects in his segment, based
on the price of bought items.
"""
threshold = 0.1
outlier_info = get_outliers_percentage(pronac)
outlier_info['is_outlier'] = outlier_info['percentage'] > threshold
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lappis-unb/salic-ml | src/salicml/metrics/finance/item_prices.py | is_outlier | def is_outlier(df, item_id, segment_id, price):
"""
Verify if a item is an outlier compared to the
other occurrences of the same item, based on his price.
Args:
item_id: idPlanilhaItens
segment_id: idSegmento
price: VlUnitarioAprovado
"""
if (segment_id, item_id) not in... | python | def is_outlier(df, item_id, segment_id, price):
"""
Verify if a item is an outlier compared to the
other occurrences of the same item, based on his price.
Args:
item_id: idPlanilhaItens
segment_id: idSegmento
price: VlUnitarioAprovado
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lappis-unb/salic-ml | src/salicml/metrics/finance/item_prices.py | aggregated_relevant_items | def aggregated_relevant_items(raw_df):
"""
Aggragation for calculate mean and std.
"""
df = (
raw_df[['idSegmento', 'idPlanilhaItens', 'VlUnitarioAprovado']]
.groupby(by=['idSegmento', 'idPlanilhaItens'])
.agg([np.mean, lambda x: np.std(x, ddof=0)])
)
df.columns = df.colu... | python | def aggregated_relevant_items(raw_df):
"""
Aggragation for calculate mean and std.
"""
df = (
raw_df[['idSegmento', 'idPlanilhaItens', 'VlUnitarioAprovado']]
.groupby(by=['idSegmento', 'idPlanilhaItens'])
.agg([np.mean, lambda x: np.std(x, ddof=0)])
)
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lappis-unb/salic-ml | src/salicml/metrics/finance/item_prices.py | relevant_items | def relevant_items(df):
"""
Dataframe with items used by cultural projects,
filtered by date and price.
"""
start_date = datetime(2013, 1, 1)
df['DataProjeto'] = pd.to_datetime(df['DataProjeto'])
# get only projects newer than start_date
# and items with price > 0
df = df[df.DataPr... | python | def relevant_items(df):
"""
Dataframe with items used by cultural projects,
filtered by date and price.
"""
start_date = datetime(2013, 1, 1)
df['DataProjeto'] = pd.to_datetime(df['DataProjeto'])
# get only projects newer than start_date
# and items with price > 0
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lappis-unb/salic-ml | src/salicml/metrics/finance/item_prices.py | items_with_price | def items_with_price(raw_df):
"""
Dataframe with price as number.
"""
df = (
raw_df
[['PRONAC', 'idPlanilhaAprovacao', 'Item',
'idPlanilhaItens', 'VlUnitarioAprovado',
'idSegmento', 'DataProjeto', 'idPronac',
'UfItem', 'idProduto', 'cdCidade', 'cdEtapa... | python | def items_with_price(raw_df):
"""
Dataframe with price as number.
"""
df = (
raw_df
[['PRONAC', 'idPlanilhaAprovacao', 'Item',
'idPlanilhaItens', 'VlUnitarioAprovado',
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lappis-unb/salic-ml | src/salicml/metrics/finance/item_prices.py | get_outliers_percentage | def get_outliers_percentage(pronac):
"""
Returns the percentage of items
of the project that are outliers.
"""
items = (
data.items_with_price
.groupby(['PRONAC'])
.get_group(pronac)
)
df = data.aggregated_relevant_items
outlier_items = {}
url_prefix = '/pre... | python | def get_outliers_percentage(pronac):
"""
Returns the percentage of items
of the project that are outliers.
"""
items = (
data.items_with_price
.groupby(['PRONAC'])
.get_group(pronac)
)
df = data.aggregated_relevant_items
outlier_items = {}
url_prefix = '/pre... | [
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lappis-unb/salic-ml | src/salicml/metrics/finance/number_of_items.py | number_of_items | def number_of_items(pronac, dt):
"""
This metric calculates the project number of declared number of items
and compare it to projects in the same segment
output:
is_outlier: True if projects number of items is not compatible
to others projects in the same segment
... | python | def number_of_items(pronac, dt):
"""
This metric calculates the project number of declared number of items
and compare it to projects in the same segment
output:
is_outlier: True if projects number of items is not compatible
to others projects in the same segment
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lappis-unb/salic-ml | src/salicml/metrics/finance/common_items_ratio.py | common_items | def common_items(df):
"""
Returns the itens that are common in all the segments,
in the format | idSegmento | id planilhaItens |.
"""
percentage = 0.1
return (
df
.groupby(['idSegmento', 'idPlanilhaItens'])
.count()
.rename(columns={'PRONAC': 'itemOccurrences'})
... | python | def common_items(df):
"""
Returns the itens that are common in all the segments,
in the format | idSegmento | id planilhaItens |.
"""
percentage = 0.1
return (
df
.groupby(['idSegmento', 'idPlanilhaItens'])
.count()
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lappis-unb/salic-ml | src/salicml/metrics/finance/common_items_ratio.py | common_items_percentage | def common_items_percentage(pronac, seg_common_items):
"""
Returns the percentage of items in a project that are
common in the cultural segment.
"""
if len(seg_common_items) == 0:
return 0
project_items = get_project_items(pronac).values[:, 0]
project_items_amount = len(project_item... | python | def common_items_percentage(pronac, seg_common_items):
"""
Returns the percentage of items in a project that are
common in the cultural segment.
"""
if len(seg_common_items) == 0:
return 0
project_items = get_project_items(pronac).values[:, 0]
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lappis-unb/salic-ml | src/salicml/metrics/finance/common_items_ratio.py | common_items_metrics | def common_items_metrics(all_items, common_items):
"""
Calculates the percentage of common items for each project
in each segment and calculates the mean and std of this percentage
for each segment.
"""
segments = common_items.index.unique()
metrics = {}
for seg in segments:
seg_... | python | def common_items_metrics(all_items, common_items):
"""
Calculates the percentage of common items for each project
in each segment and calculates the mean and std of this percentage
for each segment.
"""
segments = common_items.index.unique()
metrics = {}
for seg in segments:
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lappis-unb/salic-ml | src/salicml/metrics/finance/common_items_ratio.py | get_project_items | def get_project_items(pronac):
"""
Returns all items from a project.
"""
df = data.all_items
return (
df[df['PRONAC'] == pronac]
.drop(columns=['PRONAC', 'idSegmento'])
) | python | def get_project_items(pronac):
"""
Returns all items from a project.
"""
df = data.all_items
return (
df[df['PRONAC'] == pronac]
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lappis-unb/salic-ml | src/salicml/metrics/finance/common_items_ratio.py | segment_common_items | def segment_common_items(segment_id):
"""
Returns all the common items in a segment.
"""
df = data.common_items
return (
df
.loc[str(segment_id)]
.reset_index(drop=1)
.drop(columns=["itemOccurrences"])
) | python | def segment_common_items(segment_id):
"""
Returns all the common items in a segment.
"""
df = data.common_items
return (
df
.loc[str(segment_id)]
.reset_index(drop=1)
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lappis-unb/salic-ml | src/salicml/metrics/finance/common_items_ratio.py | get_uncommon_items | def get_uncommon_items(pronac):
"""
Return all uncommon items of a project
(related to segment common items).
"""
segment_id = get_segment_id(str(pronac))
seg_common_items = (
segment_common_items(segment_id)
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.index
)
project_items = ... | python | def get_uncommon_items(pronac):
"""
Return all uncommon items of a project
(related to segment common items).
"""
segment_id = get_segment_id(str(pronac))
seg_common_items = (
segment_common_items(segment_id)
.set_index('idPlanilhaItens')
.index
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lappis-unb/salic-ml | src/salicml/metrics/finance/common_items_ratio.py | add_info_to_uncommon_items | def add_info_to_uncommon_items(filtered_items, uncommon_items):
"""
Add extra info to the uncommon items.
"""
result = uncommon_items
url_prefix = '/prestacao-contas/analisar/comprovante'
for _, item in filtered_items.iterrows():
item_id = item['idPlanilhaItens']
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"""
Add extra info to the uncommon items.
"""
result = uncommon_items
url_prefix = '/prestacao-contas/analisar/comprovante'
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item_id = item['idPlanilhaItens']
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lappis-unb/salic-ml | src/salicml/metrics/finance/common_items_ratio.py | common_items_ratio | def common_items_ratio(pronac, dt):
"""
Calculates the common items on projects in a cultural segment,
calculates the uncommon items on projects in a cultural segment and
verify if a project is an outlier compared to the other projects
in his segment.
"""
segment_id = get_segment_id(str(pron... | python | def common_items_ratio(pronac, dt):
"""
Calculates the common items on projects in a cultural segment,
calculates the uncommon items on projects in a cultural segment and
verify if a project is an outlier compared to the other projects
in his segment.
"""
segment_id = get_segment_id(str(pron... | [
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lappis-unb/salic-ml | src/salicml/metrics/finance/verified_funds.py | verified_funds | def verified_funds(pronac, dt):
"""
Responsable for detecting anomalies in projects total verified funds.
"""
dataframe = data.planilha_comprovacao
project = dataframe.loc[dataframe['PRONAC'] == pronac]
segment_id = project.iloc[0]["idSegmento"]
pronac_funds = project[
["idPlanilhaAp... | python | def verified_funds(pronac, dt):
"""
Responsable for detecting anomalies in projects total verified funds.
"""
dataframe = data.planilha_comprovacao
project = dataframe.loc[dataframe['PRONAC'] == pronac]
segment_id = project.iloc[0]["idSegmento"]
pronac_funds = project[
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lappis-unb/salic-ml | src/salicml/metrics/finance/to_verify_funds.py | raised_funds_by_project | def raised_funds_by_project(df):
"""
Raised funds organized by project.
"""
df['CaptacaoReal'] = df['CaptacaoReal'].apply(
pd.to_numeric
)
return (
df[['Pronac', 'CaptacaoReal']]
.groupby(['Pronac'])
.sum()
) | python | def raised_funds_by_project(df):
"""
Raised funds organized by project.
"""
df['CaptacaoReal'] = df['CaptacaoReal'].apply(
pd.to_numeric
)
return (
df[['Pronac', 'CaptacaoReal']]
.groupby(['Pronac'])
.sum()
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lappis-unb/salic-ml | src/salicml/metrics/finance/to_verify_funds.py | to_verify_funds | def to_verify_funds(pronac, dt):
"""
Checks how much money is left for the project to verify,
using raised_funds - verified_funds
This value can be negative (a project can verify more money than
the value approved)
"""
project_raised_funds = data.raised_funds_by_project.loc[pronac]['Captacao... | python | def to_verify_funds(pronac, dt):
"""
Checks how much money is left for the project to verify,
using raised_funds - verified_funds
This value can be negative (a project can verify more money than
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"""
project_raised_funds = data.raised_funds_by_project.loc[pronac]['Captacao... | [
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lappis-unb/salic-ml | src/salicml/metrics/finance/proponent_projects.py | proponent_projects | def proponent_projects(pronac, data):
"""
Checks the CNPJ/CPF of the proponent of project
with the given pronac and returns all the projects
that have been submitted by this proponent and all
projects that have already been analyzed.
"""
cpf_cnpj = get_cpf_cnpj_by_pronac(pronac)
propone... | python | def proponent_projects(pronac, data):
"""
Checks the CNPJ/CPF of the proponent of project
with the given pronac and returns all the projects
that have been submitted by this proponent and all
projects that have already been analyzed.
"""
cpf_cnpj = get_cpf_cnpj_by_pronac(pronac)
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lappis-unb/salic-ml | src/salicml/metrics/finance/proponent_projects.py | analyzed_projects | def analyzed_projects(raw_df):
"""
Return all projects that was analyzed.
"""
df = raw_df[['PRONAC', 'proponenteCgcCpf']]
analyzed_projects = df.groupby('proponenteCgcCpf')[
'PRONAC'
].agg(['unique', 'nunique'])
analyzed_projects.columns = ['pronac_list', 'num_pronacs']
return... | python | def analyzed_projects(raw_df):
"""
Return all projects that was analyzed.
"""
df = raw_df[['PRONAC', 'proponenteCgcCpf']]
analyzed_projects = df.groupby('proponenteCgcCpf')[
'PRONAC'
].agg(['unique', 'nunique'])
analyzed_projects.columns = ['pronac_list', 'num_pronacs']
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lappis-unb/salic-ml | src/salicml/metrics/finance/proponent_projects.py | submitted_projects | def submitted_projects(raw_df):
"""
Return all submitted projects.
"""
df = raw_df.astype({'PRONAC': str, 'CgcCpf': str})
submitted_projects = df.groupby('CgcCpf')[
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submitted_projects.columns = ['pronac_list', 'num_pronacs']
return submitte... | python | def submitted_projects(raw_df):
"""
Return all submitted projects.
"""
df = raw_df.astype({'PRONAC': str, 'CgcCpf': str})
submitted_projects = df.groupby('CgcCpf')[
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submitted_projects.columns = ['pronac_list', 'num_pronacs']
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lappis-unb/salic-ml | src/salicml/utils/read_csv.py | read_csv | def read_csv(csv_name, usecols=None):
"""Returns a DataFrame from a .csv file stored in /data/raw/"""
csv_path = os.path.join(DATA_FOLDER, csv_name)
csv = pd.read_csv(csv_path, low_memory=False,
usecols=usecols, encoding="utf-8")
return csv | python | def read_csv(csv_name, usecols=None):
"""Returns a DataFrame from a .csv file stored in /data/raw/"""
csv_path = os.path.join(DATA_FOLDER, csv_name)
csv = pd.read_csv(csv_path, low_memory=False,
usecols=usecols, encoding="utf-8")
return csv | [
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lappis-unb/salic-ml | src/salicml/utils/read_csv.py | read_csv_with_different_type | def read_csv_with_different_type(csv_name, column_types_dict, usecols=None):
"""Returns a DataFrame from a .csv file stored in /data/raw/.
Reads the CSV as string. """
csv_path = os.path.join(DATA_FOLDER, csv_name)
csv = pd.read_csv(
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... | python | def read_csv_with_different_type(csv_name, column_types_dict, usecols=None):
"""Returns a DataFrame from a .csv file stored in /data/raw/.
Reads the CSV as string. """
csv_path = os.path.join(DATA_FOLDER, csv_name)
csv = pd.read_csv(
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lappis-unb/salic-ml | src/salicml/utils/read_csv.py | read_csv_as_integer | def read_csv_as_integer(csv_name, integer_columns, usecols=None):
"""Returns a DataFrame from a .csv file stored in /data/raw/.
Converts columns specified by 'integer_columns' to integer.
"""
csv_path = os.path.join(DATA_FOLDER, csv_name)
csv = pd.read_csv(csv_path, low_memory=False, usecols=usecols... | python | def read_csv_as_integer(csv_name, integer_columns, usecols=None):
"""Returns a DataFrame from a .csv file stored in /data/raw/.
Converts columns specified by 'integer_columns' to integer.
"""
csv_path = os.path.join(DATA_FOLDER, csv_name)
csv = pd.read_csv(csv_path, low_memory=False, usecols=usecols... | [
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lappis-unb/salic-ml | src/salicml/metrics/finance/operation_code_receipts.py | check_receipts | def check_receipts(pronac, dt):
"""
Checks how many items are in a same receipt when payment type is check
- is_outlier: True if there are any receipts that have more than one
- itens_que_compartilham_comprovantes: List of items that share receipt
"""
df = verified_repeated_receipts_for_... | python | def check_receipts(pronac, dt):
"""
Checks how many items are in a same receipt when payment type is check
- is_outlier: True if there are any receipts that have more than one
- itens_que_compartilham_comprovantes: List of items that share receipt
"""
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lappis-unb/salic-ml | src/salicml/metrics/finance/operation_code_receipts.py | transfer_receipts | def transfer_receipts(pronac, dt):
"""
Checks how many items are in a same receipt when payment type is bank
transfer
- is_outlier: True if there are any receipts that have more than one
- itens_que_compartilham_comprovantes: List of items that share receipt
"""
df = verified_repeate... | python | def transfer_receipts(pronac, dt):
"""
Checks how many items are in a same receipt when payment type is bank
transfer
- is_outlier: True if there are any receipts that have more than one
- itens_que_compartilham_comprovantes: List of items that share receipt
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lappis-unb/salic-ml | src/salicml/metrics/finance/operation_code_receipts.py | money_receipts | def money_receipts(pronac, dt):
"""
Checks how many items are in a same receipt when payment type is
withdraw/money
- is_outlier: True if there are any receipts that have more than one
- itens_que_compartilham_comprovantes: List of items that share receipt
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df = verified_repeated_... | python | def money_receipts(pronac, dt):
"""
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lappis-unb/salic-ml | src/salicml/metrics/finance/raised_funds.py | raised_funds | def raised_funds(pronac, data):
"""
Returns the total raised funds of a project
with the given pronac and if this project is an
outlier based on this value.
"""
is_outlier, mean, std, total_raised_funds = get_outlier_info(pronac)
maximum_expected_funds = gaussian_outlier.maximum_expected_val... | python | def raised_funds(pronac, data):
"""
Returns the total raised funds of a project
with the given pronac and if this project is an
outlier based on this value.
"""
is_outlier, mean, std, total_raised_funds = get_outlier_info(pronac)
maximum_expected_funds = gaussian_outlier.maximum_expected_val... | [
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lappis-unb/salic-ml | src/salicml/metrics/finance/raised_funds.py | segment_raised_funds_average | def segment_raised_funds_average(df):
"""
Return some info about raised funds.
"""
grouped = df.groupby('Segmento')
aggregated = grouped.agg(['mean', 'std'])
aggregated.columns = aggregated.columns.droplevel(0)
return aggregated | python | def segment_raised_funds_average(df):
"""
Return some info about raised funds.
"""
grouped = df.groupby('Segmento')
aggregated = grouped.agg(['mean', 'std'])
aggregated.columns = aggregated.columns.droplevel(0)
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lappis-unb/salic-ml | src/salicml/metrics/finance/raised_funds.py | get_outlier_info | def get_outlier_info(pronac):
"""
Return if a project with the given
pronac is an outlier based on raised funds.
"""
df = data.planilha_captacao
raised_funds_averages = data.segment_raised_funds_average.to_dict('index')
segment_id = df[df['Pronac'] == pronac]['Segmento'].iloc[0]
mean =... | python | def get_outlier_info(pronac):
"""
Return if a project with the given
pronac is an outlier based on raised funds.
"""
df = data.planilha_captacao
raised_funds_averages = data.segment_raised_funds_average.to_dict('index')
segment_id = df[df['Pronac'] == pronac]['Segmento'].iloc[0]
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lappis-unb/salic-ml | src/salicml/metrics/finance/verified_approved.py | verified_approved | def verified_approved(pronac, dt):
"""
This metric compare budgetary items of SALIC projects in terms of
verified versus approved value
Items that have vlComprovacao > vlAprovacao * 1.5 are considered outliers
output:
is_outlier: True if any item is outlier
valor: Absolute nu... | python | def verified_approved(pronac, dt):
"""
This metric compare budgetary items of SALIC projects in terms of
verified versus approved value
Items that have vlComprovacao > vlAprovacao * 1.5 are considered outliers
output:
is_outlier: True if any item is outlier
valor: Absolute nu... | [
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lappis-unb/salic-ml | src/salicml/data/loader.py | csv_to_pickle | def csv_to_pickle(path=ROOT / "raw", clean=False):
"""Convert all CSV files in path to pickle."""
for file in os.listdir(path):
base, ext = os.path.splitext(file)
if ext != ".csv":
continue
LOG(f"converting {file} to pickle")
df = pd.read_csv(path / file, low_memory... | python | def csv_to_pickle(path=ROOT / "raw", clean=False):
"""Convert all CSV files in path to pickle."""
for file in os.listdir(path):
base, ext = os.path.splitext(file)
if ext != ".csv":
continue
LOG(f"converting {file} to pickle")
df = pd.read_csv(path / file, low_memory... | [
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lappis-unb/salic-ml | src/salicml/data/loader.py | Loader.store | def store(self, loc, df):
"""Store dataframe in the given location.
Store some arbitrary dataframe:
>>> data.store('my_data', df)
Now recover it from the global store.
>>> data.my_data
...
"""
path = "%s.%s" % (self._root / "processed" / loc, FILE_EXTE... | python | def store(self, loc, df):
"""Store dataframe in the given location.
Store some arbitrary dataframe:
>>> data.store('my_data', df)
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>>> data.my_data
...
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path = "%s.%s" % (self._root / "processed" / loc, FILE_EXTE... | [
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MisterY/asset-allocation | asset_allocation/stocks.py | StocksInfo.close_databases | def close_databases(self):
""" Close all database sessions """
if self.gc_book:
self.gc_book.close()
if self.pricedb_session:
self.pricedb_session.close() | python | def close_databases(self):
""" Close all database sessions """
if self.gc_book:
self.gc_book.close()
if self.pricedb_session:
self.pricedb_session.close() | [
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MisterY/asset-allocation | asset_allocation/stocks.py | StocksInfo.load_stock_quantity | def load_stock_quantity(self, symbol: str) -> Decimal(0):
""" retrieves stock quantity """
book = self.get_gc_book()
collection = SecuritiesAggregate(book)
sec = collection.get_aggregate_for_symbol(symbol)
quantity = sec.get_quantity()
return quantity | python | def load_stock_quantity(self, symbol: str) -> Decimal(0):
""" retrieves stock quantity """
book = self.get_gc_book()
collection = SecuritiesAggregate(book)
sec = collection.get_aggregate_for_symbol(symbol)
quantity = sec.get_quantity()
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MisterY/asset-allocation | asset_allocation/stocks.py | StocksInfo.get_gc_book | def get_gc_book(self):
""" Returns the GnuCash db session """
if not self.gc_book:
gc_db = self.config.get(ConfigKeys.gnucash_book_path)
if not gc_db:
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# check if this is the abs file exists
... | python | def get_gc_book(self):
""" Returns the GnuCash db session """
if not self.gc_book:
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# check if this is the abs file exists
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MisterY/asset-allocation | asset_allocation/stocks.py | StocksInfo.get_symbols_with_positive_balances | def get_symbols_with_positive_balances(self) -> List[str]:
""" Identifies all the securities with positive balances """
from gnucash_portfolio import BookAggregate
holdings = []
with BookAggregate() as book:
# query = book.securities.query.filter(Commodity.)
hol... | python | def get_symbols_with_positive_balances(self) -> List[str]:
""" Identifies all the securities with positive balances """
from gnucash_portfolio import BookAggregate
holdings = []
with BookAggregate() as book:
# query = book.securities.query.filter(Commodity.)
hol... | [
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MisterY/asset-allocation | asset_allocation/stocks.py | StocksInfo.__get_pricedb_session | def __get_pricedb_session(self):
""" Provides initialization and access to module-level session """
from pricedb import dal
if not self.pricedb_session:
self.pricedb_session = dal.get_default_session()
return self.pricedb_session | python | def __get_pricedb_session(self):
""" Provides initialization and access to module-level session """
from pricedb import dal
if not self.pricedb_session:
self.pricedb_session = dal.get_default_session()
return self.pricedb_session | [
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MisterY/asset-allocation | asset_allocation/stocklink_cli.py | add | def add(assetclass: int, symbol: str):
""" Add a stock to an asset class """
assert isinstance(symbol, str)
assert isinstance(assetclass, int)
symbol = symbol.upper()
app = AppAggregate()
new_item = app.add_stock_to_class(assetclass, symbol)
print(f"Record added: {new_item}.") | python | def add(assetclass: int, symbol: str):
""" Add a stock to an asset class """
assert isinstance(symbol, str)
assert isinstance(assetclass, int)
symbol = symbol.upper()
app = AppAggregate()
new_item = app.add_stock_to_class(assetclass, symbol)
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MisterY/asset-allocation | asset_allocation/stocklink_cli.py | unallocated | def unallocated():
""" Identify unallocated holdings """
app = AppAggregate()
app.logger = logger
unalloc = app.find_unallocated_holdings()
if not unalloc:
print(f"No unallocated holdings.")
for item in unalloc:
print(item) | python | def unallocated():
""" Identify unallocated holdings """
app = AppAggregate()
app.logger = logger
unalloc = app.find_unallocated_holdings()
if not unalloc:
print(f"No unallocated holdings.")
for item in unalloc:
print(item) | [
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MisterY/asset-allocation | asset_allocation/formatters.py | AsciiFormatter.format | def format(self, model: AssetAllocationModel, full: bool = False):
""" Returns the view-friendly output of the aa model """
self.full = full
# Header
output = f"Asset Allocation model, total: {model.currency} {model.total_amount:,.2f}\n"
# Column Headers
for column in s... | python | def format(self, model: AssetAllocationModel, full: bool = False):
""" Returns the view-friendly output of the aa model """
self.full = full
# Header
output = f"Asset Allocation model, total: {model.currency} {model.total_amount:,.2f}\n"
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MisterY/asset-allocation | asset_allocation/formatters.py | AsciiFormatter.__format_row | def __format_row(self, row: AssetAllocationViewModel):
""" display-format one row
Formats one Asset Class record """
output = ""
index = 0
# Name
value = row.name
# Indent according to depth.
for _ in range(0, row.depth):
value = f" {value}"... | python | def __format_row(self, row: AssetAllocationViewModel):
""" display-format one row
Formats one Asset Class record """
output = ""
index = 0
# Name
value = row.name
# Indent according to depth.
for _ in range(0, row.depth):
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MisterY/asset-allocation | asset_allocation/formatters.py | AsciiFormatter.append_num_column | def append_num_column(self, text: str, index: int):
""" Add value to the output row, width based on index """
width = self.columns[index]["width"]
return f"{text:>{width}}" | python | def append_num_column(self, text: str, index: int):
""" Add value to the output row, width based on index """
width = self.columns[index]["width"]
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MisterY/asset-allocation | asset_allocation/formatters.py | AsciiFormatter.append_text_column | def append_text_column(self, text: str, index: int):
""" Add value to the output row, width based on index """
width = self.columns[index]["width"]
return f"{text:<{width}}" | python | def append_text_column(self, text: str, index: int):
""" Add value to the output row, width based on index """
width = self.columns[index]["width"]
return f"{text:<{width}}" | [
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MisterY/asset-allocation | asset_allocation/maps.py | AssetClassMapper.map_entity | def map_entity(self, entity: dal.AssetClass):
""" maps data from entity -> object """
obj = model.AssetClass()
obj.id = entity.id
obj.parent_id = entity.parentid
obj.name = entity.name
obj.allocation = entity.allocation
obj.sort_order = entity.sortorder
#... | python | def map_entity(self, entity: dal.AssetClass):
""" maps data from entity -> object """
obj = model.AssetClass()
obj.id = entity.id
obj.parent_id = entity.parentid
obj.name = entity.name
obj.allocation = entity.allocation
obj.sort_order = entity.sortorder
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MisterY/asset-allocation | asset_allocation/maps.py | ModelMapper.map_to_linear | def map_to_linear(self, with_stocks: bool=False):
""" Maps the tree to a linear representation suitable for display """
result = []
for ac in self.model.classes:
rows = self.__get_ac_tree(ac, with_stocks)
result += rows
return result | python | def map_to_linear(self, with_stocks: bool=False):
""" Maps the tree to a linear representation suitable for display """
result = []
for ac in self.model.classes:
rows = self.__get_ac_tree(ac, with_stocks)
result += rows
return result | [
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MisterY/asset-allocation | asset_allocation/maps.py | ModelMapper.__get_ac_tree | def __get_ac_tree(self, ac: model.AssetClass, with_stocks: bool):
""" formats the ac tree - entity with child elements """
output = []
output.append(self.__get_ac_row(ac))
for child in ac.classes:
output += self.__get_ac_tree(child, with_stocks)
if with_stocks:
... | python | def __get_ac_tree(self, ac: model.AssetClass, with_stocks: bool):
""" formats the ac tree - entity with child elements """
output = []
output.append(self.__get_ac_row(ac))
for child in ac.classes:
output += self.__get_ac_tree(child, with_stocks)
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... | [
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MisterY/asset-allocation | asset_allocation/maps.py | ModelMapper.__get_ac_row | def __get_ac_row(self, ac: model.AssetClass) -> AssetAllocationViewModel:
""" Formats one Asset Class record """
view_model = AssetAllocationViewModel()
view_model.depth = ac.depth
# Name
view_model.name = ac.name
view_model.set_allocation = ac.allocation
... | python | def __get_ac_row(self, ac: model.AssetClass) -> AssetAllocationViewModel:
""" Formats one Asset Class record """
view_model = AssetAllocationViewModel()
view_model.depth = ac.depth
# Name
view_model.name = ac.name
view_model.set_allocation = ac.allocation
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MisterY/asset-allocation | asset_allocation/maps.py | ModelMapper.__get_stock_row | def __get_stock_row(self, stock: Stock, depth: int) -> str:
""" formats stock row """
assert isinstance(stock, Stock)
view_model = AssetAllocationViewModel()
view_model.depth = depth
# Symbol
view_model.name = stock.symbol
# Current allocation
view_mod... | python | def __get_stock_row(self, stock: Stock, depth: int) -> str:
""" formats stock row """
assert isinstance(stock, Stock)
view_model = AssetAllocationViewModel()
view_model.depth = depth
# Symbol
view_model.name = stock.symbol
# Current allocation
view_mod... | [
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MisterY/asset-allocation | asset_allocation/maps.py | ModelMapper.__get_cash_row | def __get_cash_row(self, item: CashBalance, depth: int) -> str:
""" formats stock row """
assert isinstance(item, CashBalance)
view_model = AssetAllocationViewModel()
view_model.depth = depth
# Symbol
view_model.name = item.symbol
# Value in base currency
... | python | def __get_cash_row(self, item: CashBalance, depth: int) -> str:
""" formats stock row """
assert isinstance(item, CashBalance)
view_model = AssetAllocationViewModel()
view_model.depth = depth
# Symbol
view_model.name = item.symbol
# Value in base currency
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.create_asset_class | def create_asset_class(self, item: AssetClass):
""" Inserts the record """
session = self.open_session()
session.add(item)
session.commit() | python | def create_asset_class(self, item: AssetClass):
""" Inserts the record """
session = self.open_session()
session.add(item)
session.commit() | [
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.add_stock_to_class | def add_stock_to_class(self, assetclass_id: int, symbol: str):
""" Add a stock link to an asset class """
assert isinstance(symbol, str)
assert isinstance(assetclass_id, int)
item = AssetClassStock()
item.assetclassid = assetclass_id
item.symbol = symbol
session... | python | def add_stock_to_class(self, assetclass_id: int, symbol: str):
""" Add a stock link to an asset class """
assert isinstance(symbol, str)
assert isinstance(assetclass_id, int)
item = AssetClassStock()
item.assetclassid = assetclass_id
item.symbol = symbol
session... | [
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.delete | def delete(self, id: int):
""" Delete asset class """
assert isinstance(id, int)
self.open_session()
to_delete = self.get(id)
self.session.delete(to_delete)
self.save() | python | def delete(self, id: int):
""" Delete asset class """
assert isinstance(id, int)
self.open_session()
to_delete = self.get(id)
self.session.delete(to_delete)
self.save() | [
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.find_unallocated_holdings | def find_unallocated_holdings(self):
""" Identifies any holdings that are not included in asset allocation """
# Get linked securities
session = self.open_session()
linked_entities = session.query(AssetClassStock).all()
linked = []
# linked = map(lambda x: f"{x.symbol}", ... | python | def find_unallocated_holdings(self):
""" Identifies any holdings that are not included in asset allocation """
# Get linked securities
session = self.open_session()
linked_entities = session.query(AssetClassStock).all()
linked = []
# linked = map(lambda x: f"{x.symbol}", ... | [
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.get | def get(self, id: int) -> AssetClass:
""" Loads Asset Class """
self.open_session()
item = self.session.query(AssetClass).filter(
AssetClass.id == id).first()
return item | python | def get(self, id: int) -> AssetClass:
""" Loads Asset Class """
self.open_session()
item = self.session.query(AssetClass).filter(
AssetClass.id == id).first()
return item | [
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.open_session | def open_session(self):
""" Opens a db session and returns it """
from .dal import get_session
cfg = Config()
cfg.logger = self.logger
db_path = cfg.get(ConfigKeys.asset_allocation_database_path)
self.session = get_session(db_path)
return self.session | python | def open_session(self):
""" Opens a db session and returns it """
from .dal import get_session
cfg = Config()
cfg.logger = self.logger
db_path = cfg.get(ConfigKeys.asset_allocation_database_path)
self.session = get_session(db_path)
return self.session | [
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.get_asset_allocation | def get_asset_allocation(self):
""" Creates and populates the Asset Allocation model. The main function of the app. """
# load from db
# TODO set the base currency
base_currency = "EUR"
loader = AssetAllocationLoader(base_currency=base_currency)
loader.logger = self.logg... | python | def get_asset_allocation(self):
""" Creates and populates the Asset Allocation model. The main function of the app. """
# load from db
# TODO set the base currency
base_currency = "EUR"
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.get_asset_classes_for_security | def get_asset_classes_for_security(self, namespace: str, symbol: str) -> List[AssetClass]:
""" Find all asset classes (should be only one at the moment, though!) to which the symbol belongs """
full_symbol = symbol
if namespace:
full_symbol = f"{namespace}:{symbol}"
result =... | python | def get_asset_classes_for_security(self, namespace: str, symbol: str) -> List[AssetClass]:
""" Find all asset classes (should be only one at the moment, though!) to which the symbol belongs """
full_symbol = symbol
if namespace:
full_symbol = f"{namespace}:{symbol}"
result =... | [
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.validate_model | def validate_model(self):
""" Validate the model """
model: AssetAllocationModel = self.get_asset_allocation_model()
model.logger = self.logger
valid = model.validate()
if valid:
print(f"The model is valid. Congratulations")
else:
print(f"The mode... | python | def validate_model(self):
""" Validate the model """
model: AssetAllocationModel = self.get_asset_allocation_model()
model.logger = self.logger
valid = model.validate()
if valid:
print(f"The model is valid. Congratulations")
else:
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MisterY/asset-allocation | asset_allocation/app.py | AppAggregate.export_symbols | def export_symbols(self):
""" Exports all used symbols """
session = self.open_session()
links = session.query(AssetClassStock).order_by(
AssetClassStock.symbol).all()
output = []
for link in links:
output.append(link.symbol + '\n')
# Save output ... | python | def export_symbols(self):
""" Exports all used symbols """
session = self.open_session()
links = session.query(AssetClassStock).order_by(
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output = []
for link in links:
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# Save output ... | [
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MisterY/asset-allocation | asset_allocation/config.py | Config.__read_config | def __read_config(self, file_path: str):
""" Read the config file """
if not os.path.exists(file_path):
raise FileNotFoundError("File path not found: %s", file_path)
# check if file exists
if not os.path.isfile(file_path):
log(ERROR, "file not found: %s", file_pat... | python | def __read_config(self, file_path: str):
""" Read the config file """
if not os.path.exists(file_path):
raise FileNotFoundError("File path not found: %s", file_path)
# check if file exists
if not os.path.isfile(file_path):
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MisterY/asset-allocation | asset_allocation/config.py | Config.__create_user_config | def __create_user_config(self):
""" Copy the config template into user's directory """
src_path = self.__get_config_template_path()
src = os.path.abspath(src_path)
if not os.path.exists(src):
log(ERROR, "Config template not found %s", src)
raise FileNotFoundError(... | python | def __create_user_config(self):
""" Copy the config template into user's directory """
src_path = self.__get_config_template_path()
src = os.path.abspath(src_path)
if not os.path.exists(src):
log(ERROR, "Config template not found %s", src)
raise FileNotFoundError(... | [
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MisterY/asset-allocation | asset_allocation/config_cli.py | set | def set(aadb, cur):
""" Sets the values in the config file """
cfg = Config()
edited = False
if aadb:
cfg.set(ConfigKeys.asset_allocation_database_path, aadb)
print(f"The database has been set to {aadb}.")
edited = True
if cur:
cfg.set(ConfigKeys.default_currenc... | python | def set(aadb, cur):
""" Sets the values in the config file """
cfg = Config()
edited = False
if aadb:
cfg.set(ConfigKeys.asset_allocation_database_path, aadb)
print(f"The database has been set to {aadb}.")
edited = True
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MisterY/asset-allocation | asset_allocation/config_cli.py | get | def get(aadb: str):
""" Retrieves a value from config """
if (aadb):
cfg = Config()
value = cfg.get(ConfigKeys.asset_allocation_database_path)
click.echo(value)
if not aadb:
click.echo("Use --help for more information.") | python | def get(aadb: str):
""" Retrieves a value from config """
if (aadb):
cfg = Config()
value = cfg.get(ConfigKeys.asset_allocation_database_path)
click.echo(value)
if not aadb:
click.echo("Use --help for more information.") | [
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MisterY/asset-allocation | asset_allocation/model.py | _AssetBase.fullname | def fullname(self):
""" includes the full path with parent names """
prefix = ""
if self.parent:
if self.parent.fullname:
prefix = self.parent.fullname + ":"
else:
# Only the root does not have a parent. In that case we also don't need a name.
... | python | def fullname(self):
""" includes the full path with parent names """
prefix = ""
if self.parent:
if self.parent.fullname:
prefix = self.parent.fullname + ":"
else:
# Only the root does not have a parent. In that case we also don't need a name.
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MisterY/asset-allocation | asset_allocation/model.py | Stock.value | def value(self) -> Decimal:
"""
Value of the holdings in exchange currency.
Value = Quantity * Price
"""
assert isinstance(self.price, Decimal)
return self.quantity * self.price | python | def value(self) -> Decimal:
"""
Value of the holdings in exchange currency.
Value = Quantity * Price
"""
assert isinstance(self.price, Decimal)
return self.quantity * self.price | [
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MisterY/asset-allocation | asset_allocation/model.py | Stock.asset_class | def asset_class(self) -> str:
""" Returns the full asset class path for this stock """
result = self.parent.name if self.parent else ""
# Iterate to the top asset class and add names.
cursor = self.parent
while cursor:
result = cursor.name + ":" + result
c... | python | def asset_class(self) -> str:
""" Returns the full asset class path for this stock """
result = self.parent.name if self.parent else ""
# Iterate to the top asset class and add names.
cursor = self.parent
while cursor:
result = cursor.name + ":" + result
c... | [
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MisterY/asset-allocation | asset_allocation/model.py | AssetClass.child_allocation | def child_allocation(self):
""" The sum of all child asset classes' allocations """
sum = Decimal(0)
if self.classes:
for child in self.classes:
sum += child.child_allocation
else:
# This is not a branch but a leaf. Return own allocation.
... | python | def child_allocation(self):
""" The sum of all child asset classes' allocations """
sum = Decimal(0)
if self.classes:
for child in self.classes:
sum += child.child_allocation
else:
# This is not a branch but a leaf. Return own allocation.
... | [
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MisterY/asset-allocation | asset_allocation/model.py | AssetAllocationModel.get_class_by_id | def get_class_by_id(self, ac_id: int) -> AssetClass:
""" Finds the asset class by id """
assert isinstance(ac_id, int)
# iterate recursively
for ac in self.asset_classes:
if ac.id == ac_id:
return ac
# if nothing returned so far.
return None | python | def get_class_by_id(self, ac_id: int) -> AssetClass:
""" Finds the asset class by id """
assert isinstance(ac_id, int)
# iterate recursively
for ac in self.asset_classes:
if ac.id == ac_id:
return ac
# if nothing returned so far.
return None | [
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MisterY/asset-allocation | asset_allocation/model.py | AssetAllocationModel.get_cash_asset_class | def get_cash_asset_class(self) -> AssetClass:
""" Find the cash asset class by name. """
for ac in self.asset_classes:
if ac.name.lower() == "cash":
return ac
return None | python | def get_cash_asset_class(self) -> AssetClass:
""" Find the cash asset class by name. """
for ac in self.asset_classes:
if ac.name.lower() == "cash":
return ac
return None | [
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MisterY/asset-allocation | asset_allocation/model.py | AssetAllocationModel.validate | def validate(self) -> bool:
""" Validate that the values match. Incomplete! """
# Asset class allocation should match the sum of children's allocations.
# Each group should be compared.
sum = Decimal(0)
# Go through each asset class, not just the top level.
for ac in sel... | python | def validate(self) -> bool:
""" Validate that the values match. Incomplete! """
# Asset class allocation should match the sum of children's allocations.
# Each group should be compared.
sum = Decimal(0)
# Go through each asset class, not just the top level.
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