def summary_html(results, output_dir, template_dir):
"""
生成自定義的聚合報告
:param results: 執行結果
:param output_dir: html輸出目錄
:param template_parent: jinja2模板所在目錄
"""
env = jinja2.Environment(
loader=jinja2.FileSystemLoader(template_dir),
extensions=(),
autoescape=True,
)
owner_ch_name = Exe_Cfg.OWNERNAME_DICT
template = env.get_template("summary_template.html", template_dir)
script_count = len(results)
True_count = len(py_.filter_(results, {'result': True}))
False_count = len(py_.filter_(results, {'result': False}))
html = template.render({
"results": results,
'project': owner_ch_name[exe_owner]
})
report_html = "%s_%s_%s_test%s_pass%s_fail%s.html" % (
exe_owner, exe_time, exe_min, script_count, True_count, False_count)
output_file = Path(output_dir, report_html) # 聚合報告路徑
with open(output_file, 'w', encoding="utf-8") as f:
f.write(html)
print(output_file)
def get_switch_alias_tower_id(xls_path, sheet_name, ftu_fault):
book = xlrd.open_workbook(xls_path)
startrowidx = 1
alist = []
ret = []
for sheet in book.sheets():
if sheet.name.lower() == sheet_name.lower():
sim_col = -1
id_col = -1
switch_alias_col = -1
line_py_col = -1
for i in range(100):
if sheet.cell_value(0, i).lower() == 'sim':
sim_col = i
if sheet.cell_value(0, i).lower() == '_id':
id_col = i
if sheet.cell_value(0, i).lower() == 'switch_alias':
switch_alias_col = i
if sheet.cell_value(0, i).lower() == 'line_py':
line_py_col = i
if sim_col > -1 and id_col > -1 and switch_alias_col > -1 and line_py_col > -1:
break
for row in range(startrowidx, sheet.nrows):
alist.append({
'sim':str(int(sheet.cell_value(row, sim_col))),
'_id':str(sheet.cell_value(row, id_col)),
'switch_alias': int(sheet.cell_value(row, switch_alias_col)),
'line_py': str(sheet.cell_value(row, line_py_col)),
})
def filt(x):
return _.find_index(ftu_fault, {'sim':x['sim']}) > -1
ret = _.filter_(alist, filt)
def filt_gtz(x):
return x['switch_alias'] > 0
ret = _.filter_(ret, filt_gtz)
return ret
def create_xls(filepath, line_py, data):
if os.path.exists(filepath):
print('File exist, removing...')
os.remove(filepath)
wb = xlwt.Workbook()
ws = wb.add_sheet('Sheet1')
alist = _.filter_(data, lambda x:x['line_py'] == line_py)
ftu_count = 0
if line_py == 'jfyk':
ftu_count = 8
if line_py == 'pzz':
ftu_count = 10
for i in range(1, ftu_count+1):
if _.find_index(alist, {'switch_alias':i}) > -1:
ws.write(0, i - 1, 1)
else:
ws.write(0, i - 1, 0)
wb.save(filepath)
def _try_place(acc: MatrixInt, desired_length: int) -> MatrixInt:
available_cells = get_available_cells(acc, FIELD_DIMENSIONS)
segments = find_straight_segments(available_cells, True) + \
find_straight_segments(available_cells, False)
available_segments = py_.filter_(
segments, lambda segment: len(segment) >= desired_length)
chosen_segment = choice(available_segments)
len_diff = len(chosen_segment) - desired_length
available_subsegments = py_.map_(
list(range(len_diff + 1)),
lambda x: chosen_segment[x:x + desired_length])
chosen_subsegment = choice(available_subsegments)
new_field = py_.clone_deep(acc)
for c in chosen_subsegment:
new_field[c.i][c.j] = CellState.CELL_DECK.value
return new_field
from pydash import py_
from directory_utilities import get_json_from_file, write_json_to_file
trades_file_directory = "../database/trades.json"
trades = get_json_from_file(trades_file_directory)
archived_trades_file_directory = "../database/archive/archived-trades.json"
archived_trades = get_json_from_file(archived_trades_file_directory, [])
new_archived_trades = py_.filter_(
trades["trades"],
lambda trade: "sell" in trade and trade not in archived_trades)
if len(new_archived_trades) > 0:
archived_trades += new_archived_trades
write_json_to_file(archived_trades_file_directory, archived_trades)
print("Archived {} closed trades.".format(len(new_archived_trades)))
else:
print("No closed trades to archive.")
num_of_initial_trades = len(trades["trades"])
trades["trades"] = py_.filter_(trades["trades"],
lambda trade: "sell" not in trade)
if len(trades["trades"]) < num_of_initial_trades:
write_json_to_file(trades_file_directory, trades)
print("Removed {} closed trades from active trades.".format(
num_of_initial_trades - len(trades["trades"])))
else:
print("No closed trades to remove from active trades.")
from pydash import py_
from directory_utilities import get_json_from_file, write_json_to_file
trades_file_directory = "../database/trades.json"
trades = get_json_from_file(trades_file_directory)
archived_trades_file_directory = "../database/archive/archived-trades.json"
archived_trades = get_json_from_file(archived_trades_file_directory, [])
new_archived_trades = py_.filter_(trades["trades"], lambda trade: "sell" in trade and trade not in archived_trades)
if len(new_archived_trades) > 0:
archived_trades += new_archived_trades
write_json_to_file(archived_trades_file_directory, archived_trades)
print("Archived {} closed trades.".format(len(new_archived_trades)))
else:
print("No closed trades to archive.")
num_of_initial_trades = len(trades["trades"])
trades["trades"] = py_.filter_(trades["trades"], lambda trade: "sell" not in trade)
if len(trades["trades"]) < num_of_initial_trades:
write_json_to_file(trades_file_directory, trades)
print("Removed {} closed trades from active trades.".format(num_of_initial_trades - len(trades["trades"])))
else:
print("No closed trades to remove from active trades.")
from pydash import py_
from directory_utilities import get_json_from_file
archived_trades_file_directory = "../database/archive/archived-trades.json"
archived_trades = get_json_from_file(archived_trades_file_directory, [])
completed_archived_trades = py_.filter_(
archived_trades, lambda trade: trade["sell"]["dateClosed"] is not None)
profit_btc = round(
py_.sum_by(
completed_archived_trades, lambda trade:
(trade["sell"]["price"] - trade["buy"]["price"] - trade["buy"][
"commissionPaid"] - trade["sell"]["commissionPaid"])), 8)
avg_profit_btc = round(profit_btc / len(completed_archived_trades), 8)
total_buy_btc = py_.sum_by(
completed_archived_trades, lambda trade: (trade["buy"]["price"] + trade[
"buy"]["commissionPaid"] + trade["sell"]["commissionPaid"]))
total_sell_btc = py_.sum_by(completed_archived_trades,
lambda trade: trade["sell"]["price"])
profit_margin = round(100 * total_sell_btc / total_buy_btc - 100, 2)
print("Total completed trades: {}\n".format(len(completed_archived_trades)))
print("Total profit: {} BTC".format(profit_btc))
print("Average profit: {} BTC per trade\n".format(avg_profit_btc))
print("Total profit margin: {}%".format(profit_margin))
from pydash import py_
from directory_utilities import get_json_from_file
archived_trades_file_directory = "../database/archive/archived-trades.json"
archived_trades = get_json_from_file(archived_trades_file_directory, [])
completed_archived_trades = py_.filter_(archived_trades, lambda trade: trade["sell"]["dateClosed"] is not None)
profit_btc = round(
py_.sum_by(
completed_archived_trades,
lambda trade: (
trade["sell"]["price"] -
trade["buy"]["price"] -
trade["buy"]["commissionPaid"] -
trade["sell"]["commissionPaid"]
)
),
8
)
avg_profit_btc = round(profit_btc / len(completed_archived_trades), 8)
total_buy_btc = py_.sum_by(
completed_archived_trades,
lambda trade: (
trade["buy"]["price"] +
trade["buy"]["commissionPaid"] +
trade["sell"]["commissionPaid"]
)
